Geophysical study of the crust in the
central Red Sea
A thesis submitted to The University of Manchester for
the degree of Doctor of Philosophy in the Faculty of
Science & Engineering
2019
Wen Shi
School of Natural Sciences
Department of Earth and Environmental Sciences
2
Table of Contents
Table of Contents ........................................................................................................... 2
List of Figures ................................................................................................................. 6
Abstract ........................................................................................................................ 11
Declaration ................................................................................................................... 12
Copyright Statement .................................................................................................... 13
Acknowledgements ...................................................................................................... 14
The Author ................................................................................................................... 15
List of publications ....................................................................................................... 16
1. Introduction ............................................................................................................. 18
1.1 Research background and motivations .............................................................. 18
1.2 Aim of thesis ....................................................................................................... 19
1.3 Thesis content and layout .................................................................................. 19
1.4 References .......................................................................................................... 23
2. Review of literature on the Red Sea and how it prompts the present work .......... 27
2.1 Study area ........................................................................................................... 27
2.2 Geological and tectonic setting .......................................................................... 29
2.2.1 Seafloor spreading and continental rifting in the Red Sea .......................... 30
2.2.2 Seismic tomographic studies encompassing the Red Sea ........................... 34
2.3 How the previous studies prompt the present work ......................................... 36
2.4 References .......................................................................................................... 37
3. Data and methods .................................................................................................... 48
3.1 Multichannel seismic reflection data ................................................................. 48
3.2 Magnetic anomalies ........................................................................................... 51
3.2.1 Shipboard magnetic data ............................................................................ 51
3.2.2 Aeromagnetic data ...................................................................................... 54
3.2.3 2D Werner deconvolution ........................................................................... 56
3.2.4 Statistical analysis of the Werner solutions ................................................ 62
3.2.5 Reduction to the pole (RTP) ........................................................................ 62
3.3 Gravity anomalies ............................................................................................... 64
3.3.1 Free-air gravity data .................................................................................... 64
3
3.3.2 Bouguer gravity anomalies .......................................................................... 65
3.3.3 Mantle Bouguer anomalies (MBAs)............................................................. 67
3.3.4 Bouguer slab formula .................................................................................. 67
3.3.5 2D gravity forward modelling ...................................................................... 69
3.4 Isostatic loading corrections .............................................................................. 70
3.5 Bathymetry data ................................................................................................. 71
3.5.1 Smith and Sandwell (1997) global topography dataset (Version 18.1)....... 71
3.5.2 Multibeam sonar data ................................................................................. 72
3.6 References .......................................................................................................... 72
4. Paper 1: Oceanic-like axial crustal high in the central Red Sea ............................... 79
4.1 Introduction ........................................................................................................ 81
4.2 Tectonic setting .................................................................................................. 85
4.2.1 Continental rifting and seafloor spreading in the northern and southern
Red Sea ................................................................................................................. 85
4.2.2 Seismic tomographic studies encompassing the Red Sea ........................... 86
4.3 Data and methods .............................................................................................. 87
4.3.1 Seismic reflection ........................................................................................ 87
4.3.2 Magnetic anomalies .................................................................................... 88
4.3.3 Bathymetry data .......................................................................................... 92
4.3.4 Isostatic loading corrections ........................................................................ 92
4.3.5 Bouguer gravity anomalies .......................................................................... 93
4.4 Results ................................................................................................................ 94
4.4.1 Character of basement and seabed derived from seismic reflection profiles
.............................................................................................................................. 94
4.4.2 Oceanic-like axial crustal highs in isostatically corrected basement depths
.............................................................................................................................. 96
4.4.3 Correlation between Bouguer gravity anomalies and basement reflection
depths ................................................................................................................... 99
4.5 Discussion ......................................................................................................... 105
4.5.1 How does the Red Sea axial high compare with axial highs at other
spreading centres near hotspots? ...................................................................... 105
4.5.2 How thick is crust beneath the axial high and how does it relate to mantle
tomographic results? .......................................................................................... 107
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4.5.3 What are its implications? ......................................................................... 111
4.6 Conclusions ....................................................................................................... 111
4.7 Acknowledgments ............................................................................................ 112
4.8 References ........................................................................................................ 113
5. Paper 2: Central Red Sea basement depths from Werner deconvolution of
aeromagnetic data ..................................................................................................... 128
5.1 Introduction ...................................................................................................... 130
5.2 Geological setting ............................................................................................. 132
5.3 Data and methods ............................................................................................ 135
5.3.1 Multichannel seismic reflection ................................................................ 135
5.3.2 Magnetic anomalies .................................................................................. 135
5.3.3 Bouguer gravity anomalies ........................................................................ 142
5.3.4 Bathymetry data ........................................................................................ 143
5.4 Results .............................................................................................................. 143
5.4.1 Basement depth derived from aeromagnetic data ................................... 143
5.4.2 Correlation between Bouguer gravity anomalies and magnetic basement
elevations ............................................................................................................ 145
5.4.3 Number of magnetic source solutions ...................................................... 148
5.5 Discussion ......................................................................................................... 149
5.5.1 How well do the magnetic basement topography and source solution
numbers correspond with other data? .............................................................. 150
5.5.2 The potential utility of magnetic source depth determination in the Red
Sea ...................................................................................................................... 154
5.6 Conclusions ....................................................................................................... 154
5.7 Acknowledgments ............................................................................................ 155
5.8 References ........................................................................................................ 156
6. Paper 3: Oceanic basement roughness in the central Red Sea ............................. 164
6.1 Introduction ...................................................................................................... 166
6.2 Tectonic setting ................................................................................................ 167
6.3 Data and methods ............................................................................................ 169
6.3.1 Multichannel seismic reflection ................................................................ 169
6.3.2 Gravity anomalies ...................................................................................... 172
6.3.3 Bathymetry data ........................................................................................ 179
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6.4 Results .............................................................................................................. 179
6.4.1 Basement roughness along across-ridge seismic profiles ......................... 179
6.4.2 Basement roughness along the ridge-parallel gravity profiles ................. 182
6.5 Discussion ......................................................................................................... 183
6.5.1 Reduced-to-pole magnetic anomalies ....................................................... 184
6.5.2 Along-axis gradients in mantle Bouguer anomalies .................................. 185
6.6 Conclusion ........................................................................................................ 187
6.7 Acknowledgments ............................................................................................ 188
6.8 References ........................................................................................................ 188
7. Synthesis ................................................................................................................ 198
7.1 Crust types in the central Red Sea ................................................................... 198
7.1.1 Classifications ............................................................................................ 198
7.1.2 Character of the axial high......................................................................... 203
7.1.3 Distinct domains from north to south ....................................................... 204
7.2 Moho depth and crustal thickness ................................................................... 204
7.3 Uncertainty in the seismically derived basement depth ................................. 207
7.4 Acknowledgments ............................................................................................ 207
7.5 References ........................................................................................................ 208
8. Conclusion and future work ................................................................................... 213
8.1 Conclusions ....................................................................................................... 213
8.2 Future work suggestions .................................................................................. 215
8.2.1 Future work in the Red Sea ....................................................................... 215
8.2.2 Apply Werner deconvolution in other areas ............................................. 216
8.3 References ........................................................................................................ 217
Appendices ................................................................................................................. 221
Appendix 1 .............................................................................................................. 221
Appendix 2 .............................................................................................................. 227
References .............................................................................................................. 235
Word Count: 54,698 words
6
List of Figures
Figure 2.1 Map of Red Sea bathymetry showing the location of study area……………28
Figure 2.2 Simplified stratigraphic sections of the Red Sea and Gulf of Suez………….29
Figure 2.3 Seafloor spreading magnetic anomalies in the southern Red Sea……………31
Figure 2.4 Shear wave velocity map at a depth of 150 km………………………..……….35
Figure 3.1 Map of free-air gravity anomalies showing the locations of multichannel
seismic reflection profiles……………………………………………………………………………………….48
Figure 3.2 Depths derived from the seismic reflection profiles………………………………49
Figure 3.3 Confidence map showing the ability to image the basement reflection....51
Figure 3.4 (a): Tracks of shipboard magnetic surveys. (b): Residual magnetic
anomalies……………………………………………………………………………………………………………….52
Figure 3.5 (a): Extents of shipboard magnetic lines contributing to the evaluation of
seismic profiles using Werner source depths. (b): A sketch showing how the source
depths and apparent susceptibilities were projected onto the seismic profiles……53
Figure 3.6 (a): Locations of aeromagnetic survey flight lines. (b): Residual
aeromagnetic anomalies. (c): Locations of the long survey lines used in Chapter 5. (d):
Residual aeromagnetic anomalies…………………………………………………………………….55
Figure 3.7 Parameters of a vertical thin dike resolved using 2D Werner
deconvolution………………………………………………………………………………………………58
Figure 3.8 Aeromagnetic anomalies reduced to pole…………………………………………….63
Figure 3.9 (a): Free-air gravity anomalies and locations of multichannel seismic
reflection profiles. (b): Locations of gravity profiles G1-32………………………………………65
Figure 3.10 Bouguer gravity anomalies …………….………….……………………………..………..66
Figure 3.11 Bathymetry of the central Red Sea……………………………………..…………………71
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Figure 4.1 Bathymetry of the Red Sea showing the location of study area……………..81
Figure 4.2 Free-air gravity anomalies and locations of multichannel seismic reflection
profiles……………………………………………………………………………………………………………………83
Figure 4.3 (a): Tracks of shipboard magnetic surveys. (b): Extents of magnetic lines
contributing to the seismic profiles of Werner source depths. (c): Residual magnetic
anomalies. (d): Bouguer gravity anomalies……………………………………………………………..89
Figure 4.4 Depths derived from the seismic reflection profiles and Werner
deconvolution of marine magnetic data………………………………………………………………….95
Figure 4.5 (a): Basement depths along the Red Sea seismic lines corrected for
evaporite and other sediment loading. (b): Basement depths around the Reykjanes
Ridge. (c): Locations of Reykjanes Ridge profiles. (d): Red Sea crustal deepening with
distance from the ridge-axis……………………………………………………………………………………99
Figure 4.6 Graphs showing correlation between basement reflection depths and
Bouguer gravity anomalies…………………………………………………………………………………….100
Figure 4.7 Apparent density contrasts deduced from Bouguer-basement depth
gradients…………………………………………………………………………………………………………101
Figure 4.8 Simulation using basement depth profile 21 illustrating how apparent
density contrasts inferred using the gravity slab formula are reduced by upward
continuation…………………………………………………………………………………………………………102
Figure 4.9 (a): Density structure along line PIII. (b): Free-air gravity anomaly calculated
from (a) compared with observations from the Sandwell et al. (2014) gravity field
(version 23.1). (c): Total mass anomaly per unit area along PIII……………………………..104
Figure 4.10 (a): Sodium oxide contents of axial lavas. (b): Seismically determined
estimates of crustal thickness versus average Na8.0 ……………………………………………….107
Figure 4.11 Examples of locally elevated topography at ridges located near mantle
hotspots…………………………………………………………………………………………………………110
Figure 5.1 Bathymetry of the Red Sea showing the location of study area……………131
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Figure 5.2 Seafloor spreading magnetic anomalies in the southern Red Sea………134
Figure 5.3 (a): Locations of aeromagnetic survey flight lines and multichannel seismic
reflection profiles. (b): Residual aeromagnetic anomalies. (c): Locations of the survey
lines used for the Werner deconvolution. (d): Residual aeromagnetic anomalies along
the long survey lines plotted as profiles………………………………………………………………..136
Figure 5.4 Depths derived from the seismic reflection profiles and Werner
deconvolution of the aeromagnetic data………………………………………………………………140
Figure 5.5 Histograms and cumulative distribution functions (CDF) of differences
between the Werner source depths and the seismically derived basement depths
(ΔZ)……………………………………………………………………………………………………………………….142
Figure 5.6 Basement topography map derived from the aeromagnetic data Werner
source solutions……………………………………………………………………………………………………144
Figure 5.7 Magnetic basement depths along the spreading axis…………………………..145
Figure 5.8 (a): Bouguer gravity anomalies. (b): Map of aeromagnetic-derived
basement depths with shading from the Bouguer gravity grid………………………………146
Figure 5.9 (a): Correlation between Bouguer gravity anomalies and aeromagnetic-
derived basement depths within 60 km of the axis. (b): Differences between
aeromagnetic-derived basement depths and those predicted from Bouguer gravity
anomalies using the regression in (a).………………………………………………………………..147
Figure 5.10 The numbers of magnetic sources……………………………………………………..149
Figure 5.11 (a): Map locating the fracture zones over the basement topography map.
(b): Map locating the interpreted extent of evaporite and other sedimentary cover of
overlain on the magnetic basement depths………………………………………………………….151
Figure 5.12 (a): Map locating the fracture zones over the map of Figure 5.10. (b):
Comparison of the data in (a) with the distribution of evaporites and other
sediments……………………………………………………………………………………………………………..153
Figure 6.1 Bathymetry of the Red Sea showing the location of study area…………..167
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Figure 6.2 (a): Free-air gravity anomalies and locations of multichannel seismic
reflection. (b): Locations of gravity profiles G1 -32 and seismic reflection
profiles…………………………………………………………………………………………………………………170
Figure 6.3 Depths derived from the seismic reflection profiles…………………………….171
Figure 6.4 Histograms of differences between the SSv23 and free-air anomaly data
collected on (a): RRS Shackleton and (b): RV Robert Conrad…………………………………173
Figure 6.5 Differences between the SSv23 gravity field and the shipboard gravity data
after the shipboard data were fi ltered with a 4 km along -track median
filter………………………………………………………………………………………………………………………174
Figure 6.6 Forward modelling of gravity profile G21…………………………………………… 178
Figure 6.7 (a): Basement depths along the Red Sea seismic lines corrected for the
isostatic loading of evaporites and other sediments. (b): Regional crustal subsidence
trend. (c): Residual basement reliefs. (d): The relationship between the mean
basement roughness value and filter width…………………………………………………………..180
Figure 6.8 The relationship between the basement roughness and spreading rate for
ultraslow and slow spreading ridges……………………………………………………………………181
Figure 6.9 Basement roughness values computed with a modified Bouguer slab
formula along axis-parallel gravity profiles G1-32………………………………………………….183
Figure 6.10 Aeromagnetic anomalies and reduced to pole…………………………………..185
Figure 6.11 Comparison of along-axis gradients in mantle Bouguer anomalies in the
central Red Sea with those at other mid-ocean ridges………………………………………….186
Figure 7.1 (a): Geological map of the central Red Sea interpreted in this study. (b): A
comparison of crust type classification in (a) with that of Izzeldin (1987)……………….199
Figure 7.2 Interpretations of crust types along seismic lines 17 and 21…………………200
Figure 7.3 Comparisons of crust type classification in Figure 7.1a with (a): Free-air
gravity anomalies, (b): Bouguer gravity anomalies, and (c): RTP aeromagnetic
10
anomalies (d): A comparison of Bouguer gravity anomalies in (b) with RTP
aeromagnetic anomalies in (c)……………………………………………….……………………………..202
Figure 7.4 (a): Free-air gravity anomalies and locations of multichannel seismic
reflection profiles, seismic refraction profile SO53-PIII, and profile A-B. (b): A
composite profile produced by projecting the seafloor and basement reflections along
profile 25 on onto profile PIII. (c): Graph showing basement reflection along profile
25 and Moho along profiles PIII and A-B………………………………….……………………….…...205
Figure 7.5 A sketch showing across-ridge crustal structures in the central Red Sea…207
Figure A1.1 Depths derived from the seismic reflection profiles and Werner
deconvolution of marine magnetic data……………………………………………………………… 226
11
Abstract
The Red Sea is an important example a continental rift proceeding to an
oceanic basin, but whether the crust in the central Red Sea is continental or oceanic
has been controversial. Contributing to this debate, the basement geometry and
roughness are assessed using seismic reflection and potential field data.
An axial crustal high with a width of 70-100 km and a height of 0.8-1.6 km is
found after correcting the seismically derived basement depths for evaporite and
other sediment isostatic loading. Basement axial highs are commonly found at mid-
ocean ridges affected by hotspots, where enhanced mantle melting results in
thickened crust. Therefore, it is suggested that the central Red Sea is underlain by
oceanic crust typical of a mid-ocean ridge near to a mantle hotspot, like the Reykjanes
Ridge. Bouguer gravity anomalies are found strongly correlated with basement
depths from seismic reflection data. The low average basement densities deduced
from Bouguer-basement depth gradients imply thickened crust and/or low mantle
densities beneath the ridge axis. Normal axial crust thickness predicted from
fractionation-corrected sodium contents (Na8.0) implies that the earliest seafloor
spreading in the central Red Sea began with thinner than average crust.
To further assess the basement geometry, the inverse method of Werner
deconvolution is improved and used to invert aeromagnetic anomalies for magnetic
basement depths. The improved Werner deconvolution effectively maps out the axial
plateau and valleys in the crustal basement. The results confirm that the basement
topography in the region away from the seismic lines also has an axial plateau within
~60 km of the axis. Magnetic basement depth near the spreading axis generally co-
varies with Bouguer gravity anomalies. Valleys in the derived depths coincide with
fracture zones interpreted previously from shipboard gravity, aeromagnetic,
bathymetric and seismic reflection data. Those valleys also correspond with areas
where the evaporites have extended into the axial valley floor, as suggested by earlier
researchers.
Basement roughness values are computed in profiles both across and parallel
to the axis. The values from axis-crossing seismic data are ~230 m, similar to those
observed at other ultraslow and slow spreading ridges. The roughness values derived
from axis-parallel profiles of the gravity field (200-550 m) are comparable with those
of the Mid-Atlantic Ridge where it has similar along-axis segmentation. Although
these basement roughness values by themselves do not exclude an extended
continental crust interpretation in the central Red Sea, they are supportive of an
oceanic crustal interpretation when considered along with other evidence.
Finally, our new produced geological map suggests that seafloor spreading and
continental rifting in the central Red Sea have been symmetric.
12
Declaration
I declare that no portion of the work referred to in the thesis has been
submitted in support of an application for another degree or qualification,
of this, or any other university or other institute of learning.
Signed: Date:
13
Copyright Statement
i. The author of this thesis (including any appendices and/or schedules to this thesis)
owns certain copyright or related rights in it (the “Copyright”) and s/he has given The
University of Manchester certain rights to use such Copyright, including for
administrative purposes.
ii. Copies of this thesis, either in full or in extracts and whether in hard or electronic
copy, may be made only in accordance with the Copyright, Designs and Patents Act
1988 (as amended) and regulations issued under it or, where appropriate, in
accordance with licensing agreements which the University has from time to time. This
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iii. The ownership of certain Copyright, patents, designs, trademarks and other
intellectual property (the “Intellectual Property”) and any reproductions of copyright
works in the thesis, for example graphs and tables (“Reproductions”), which may be
described in this thesis, may not be owned by the author and may be owned by third
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f), in any relevant Thesis restriction declarations deposited in the University Library,
The University Library’s regulations:
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University’s policy on presentation of Theses.
14
Acknowledgements
Foremost, I would like to thank my supervisor Neil Mitchell for his guidance, support,
patience, encouragement, and great enthusiasm over the last four years.
I would like to thank my co-supervisor Lara Kalnins at the University of Edinburgh for
her helpful comments, support, and enthusiasm during my PhD research.
I would like to thank A.Y. Izzeldin in Sudan and Ian C.F. Stewart in Australia for their
constructive comments and support.
I would like to thank British Geological Survey (BGS) for providing us the software of
GRAVMAG, which is used to check some results computed using my own program.
I would like to thank the staff in School of Earth and Environmental Sciences for their
help throughout the course of this PhD.
I would like to thank my parents for their support and encouragement.
I would like to thank Lin Ma and Jianpeng Wang for their help throughout the four
years.
I would like to thank all my friends for their support and company throughout the four
years.
15
The Author
Wen Shi graduated from the China University of Mining and Technology with
a bachelor’s degree in Geophysics in 2009. He graduated from the Graduate
University of Chinese Academy of Sciences with a degree of Master of Natural Science
in Solid Earth Physics in 2012. During his master’s course, he worked with his master's
supervisor in the Institute of Geology and Geophysics, Chinese Academy of Sciences
from July 2010 to July 2012. Then he worked as a research assistant in the Shanghai
Institute of Microsystem and Information Technology, Chinese Academy of Sciences
from July 2012 to July 2014.
Wen Shi started PhD studies in Basin Studies and Petroleum Geoscience,
School of Earth and Environmental Sciences in the University of Manchester since
January 2015. His research interest is focusing on the structure of the central Red Sea
from potential field and seismic data.
16
List of publications
1. Shi, W., N. C. Mitchell, L. M. Kalnins, and A. Y. Izzeldin, 2018, Oceanic-like axial
crustal high in the central Red Sea: Tectonophysics, v. 747-748, p. 327-342.
2. Shi, W., N. C. Mitchell, L. M. Kalnins, and I. AY, 2017, Assessing the Nature of Crust
in the Central Red Sea Using Potential Fields and Seismic Reflection Data: AGU Fall
Meeting Abstracts.
3. Shi, W., N. Mitchell, and L. Kalnins, 2017, Assessing the nature of crust in the central
Red Sea using potential field methods: EGU General Assembly Conference Abstracts,
p. 542.
4. Hui Dong, Longqing Qiu, Wen Shi, Baolin Chang, Yang Qiu et al., Ultra-low field
magnetic resonance imaging detection with gradient tensor compensation in urban
unshielded environment. Appl. Phys. Lett., 2013, 102, 102602.
5. Xu P F, Shi W, Ling S Q, et al., Mapping spherically weathered “Boulders” using 2D
microtremor profiling method: a case study along subway line 7 in Shenzhen. Chinese
J. Geophysics. (in Chinese), 2012, 55(6) : 2120-2128.
17
Chapter 1.
Introduction
18
1. Introduction
1.1 Research background and motivations
Wilson (1966) noted that the Earth has been undergoing a cyclical process of
supercontinent assemblage and breakup. In these cycles, continents have repeatedly
assembled into a supercontinent and then broken apart again (e.g., Rogers and
Santosh, 2004; Santosh et al., 2009). At present, we are in a stage when continental
blocks are scattered on the surface of the Earth (Bonatti et al., 2015; Rogers and
Santosh, 2004). Geological reconstructions suggested that the most recently
assembled supercontinent (Pangea) existed roughly between ~250 Ma and ~160 Ma
(e.g., Anderson, 1982; Condie, 1998). A key step in this Wilson's cycle is ocean
formation, during which a continent rifts and proceeds to seafloor spreading.
Understanding the processes that occur during the transition from continental
rifting to seafloor spreading is important in exploring how our planet works and has
been a big challenge of Plate Tectonics for decades (e.g., Bonatti et al., 2015; Taylor et
al., 1995). On the modern Earth, there are few young ocean basins where this
transition can be observed. Those basins are in comparable ocean basin stages of
transition from continental rifting to oceanic spreading, but differ in spreading rate
and opening direction. The Woodlark Basin is small, opening relatively quickly (~60
mm yr-1) and in a complicated tectonic setting (e.g., its spreading center is highly offset
and the basin is still evolving rapidly after the Ontong Java collision with the West
Melanesian Trench) (Martinez et al., 1999; Weissel et al., 1982). The Gulf of California
rift is opening highly obliquely (e.g., Atwater and Stock, 1998; Lonsdale, 1989;
Withjack and Jamison, 1986) with a spreading rate of ~45–47 mm yr-1 (Plattner et al.,
2007). In contrast, the Red Sea is opening slowly (~10-~16 mm yr-1) and nearly
orthogonally (e.g., Chu and Gordon, 1998), so it provides an important example of
transition from nearly orthogonal slow continental rifting to seafloor spreading.
However, how far the central Red Sea is through this transition to full seafloor
spreading has been controversial (e.g., Augustin et al., 2016; Bonatti, 1985; Davies and
Tramontini, 1970; Izzeldin, 1982, 1987; Ligi et al., 2012; Mitchell and Park, 2014; Shi
19
et al., 2018; Sultan et al., 1992, 1993; Tramontini and Davies, 1969). Contributing to
this debate, the study assessed the crustal type (whether the crust is continental or
oceanic) in the central Red Sea by evaluating the basement geometry and roughness.
Moreover, the nature of transitions from oceanic to continental crusts were also
addressed in this study.
1.2 Aim of thesis
The work presented in this thesis is based primarily on the analysis and
interpretation of multichannel seismic reflection, satellite free-air gravity, shipboard
magnetic, aeromagnetic, Smith and Sandwell (1997) global topography and
bathymetry, and multibeam sonar data. Its overall objective is to address whether the
crust in the central Red Sea is continental or oceanic, and where those types extend,
with the aim of improving the understanding of how the transition from continental
rifting to seafloor spreading is evolving along the Red Sea rift. For example, Bonatti
(1985) and Ligi et al. (2011,2012) suggested that the inception of seafloor spreading
is not synchronous along the central Red Sea since the stretched continental crusts
still exist in the inter-trough zones and separate the oceanic-like ‘deeps’, while this
study suggests that this oceanic spreading inception is synchronous in the central Red
Sea along the spreading ridge because the entire axial zone including inter-trough
zones is underlain by oceanic crust. The edges of that oceanic crust and thus
transitions to extended continental crust are located at distances of ~60 km on both
sides of the ridge axis.
1.3 Thesis content and layout
This thesis is presented in Journal Format. It is divided into seven chapters.
Three research papers containing original research are presented in Chapters 4, 5, and
6. The descriptions of each chapter, author contributions, and publication status are
listed as follows.
Chapter 1
This chapter presents a general introduction to research background and
motivations, aim of thesis, and thesis content and layout.
20
Chapter 2
This chapter presents the corresponding literature review on the Red Sea and
how they prompt the present work.
Chapter 3
This chapter summarizes the data and methods applied in this study. The basic
and derived data include multichannel seismic reflection data, shipboard magnetic
data, aeromagnetic anomalies, reduction to the pole magnetic anomalies, satellite
free-air gravity anomalies, Bouguer gravity anomalies, Smith and Sandwell (1997)
global topography and bathymetry, and multibeam sonar data. The methods include
Werner deconvolution, isostatic loading corrections, Bouguer slab formula, and
gravity forward modeling.
Chapter 4
This chapter presents the first research paper: “Oceanic-like axial crustal high
in the central Red Sea”.
In this paper, we found an axial crustal high after correcting the seismically
derived basement depths for evaporite and other sediment isostatic loading, and
interpreted it as suggesting the central Red Sea is underlain by oceanic crust typical of
a mid-ocean ridge near to a mantle hotspot, like the Reykjanes Ridge. We then
discussed what our results imply about the evolution of the Red Sea rift in this area
and broader implications.
Author contributions: as first and corresponding author, I processed and
interpreted the data and produced all the figures. All the codes used in this study
were written by me. Codes were written to work in Matlab. Figures and calculations
were also performed with Generic Mapping Tools (Wessel et al., 2013). I produced
the first draft manuscript of this paper and modified it under the guidance of my main
supervisor Neil Mitchell. Co-authors Neil Mitchell, Lara Kalnins, and A.Y. Izzeldin
provided helpful comments on the draft manuscript.
Publication status: this chapter is published in the journal Tectonophysics.
21
Chapter 5
This chapter presents the second research paper: “Central Red Sea basement
depths from Werner deconvolution of aeromagnetic data”.
In this paper, we improved the inverse method of Werner deconvolution and
used it to invert aeromagnetic anomalies for magnetic basement depths in the central
Red Sea. The results confirmed that the basement topography in the region away
from the seismic lines also has an axial plateau within ~60 km of the axis. Moreover,
this exercise illustrated the potential feasibility and applicability of magnetic source
depth determination in the central Red Sea and elsewhere where there is a
magnetized basement overlain by sediments lacking magnetization.
Author contributions: as first and corresponding author, I processed and
interpreted the data and produced all the figures. All the codes used in this study
were written by me. I produced the first draft manuscript of this paper and modified
it under the guidance of my main supervisor Neil Mitchell. Co-authors Neil Mitchell,
Lara Kalnins, Ian C.F. Stewart, and A.Y. Izzeldin provided helpful comments on the draft
manuscript.
Publication status: this chapter is ready for submission to the journal Marine
Geophysical Researches.
Chapter 6
This chapter presents the third research paper: “Oceanic basement roughness
in the central Red Sea”.
In this paper, we computed basement roughness values in the central Red Sea
along lines both parallel to the axis and across it in order to assess if basement
roughness is compatible with those of other mid-ocean ridges. These roughness
values in the central Red Sea are similar to the values observed at other ultraslow and
slow spreading ridges. A change in those roughness values roughly mid-way between
the coast and the axis may mark the transition in crustal type from stretched
continental to predominantly oceanic. Although these basement roughness values by
22
themselves do not exclude an extended continental crust interpretation in the central
Red Sea, they are supportive of an oceanic crustal interpretation when considered
along with other evidence.
Author contributions: as first and corresponding author, I processed and
interpreted the data and produced all the figures. All the codes except those for the
‘reduction-to-the pole’ technique were written by me. I produced the first draft
manuscript of this paper and modified it under the guidance of my main supervisor
Neil Mitchell. Co- supervisor Lara Kalnins provided helpful comments on the draft
manuscript.
Publication status: this chapter is in preparation to be submitted to the journal
Marine Geophysical Researches.
Chapter 7
This chapter synthesizes the interpretations presented in Chapters 4, 5 and 6.
The spatial geometry of crustal type classifications and variations in crustal thickness
are discussed.
Chapter 8
This chapter summarizes the results of the earlier chapters, tries to take a
broader view in discussing them and makes suggestions for future work.
The results Chapters 4, 5, and 6 are interconnected here. To address the thesis
objective of whether the crust in the central Red Sea is continental or oceanic, the
basement geometry was assessed in Chapters 4 and 5, while the basement roughness
was assessed in Chapter 6. The results in Chapter 4 are mainly based on seismic
reflection data, whilst those in Chapter 5 are mainly based on aeromagnetic data. The
axial highs found in Chapters 4 and 5 from different data can confirm each other. The
basement roughness values computed in Chapter 6 are compatible with those of other
mid-ocean ridges, supporting the oceanic crustal interpretation proposed in Chapters
4 and 5.
23
1.4 References
Anderson, D. L., 1982, Hotspots, polar wander, Mesozoic convection and the geoid:
Nature, v. 297, p. 391.
Atwater, T., and J. Stock, 1998, Pacific-North America plate tectonics of the Neogene
southwestern United States: an update: International Geology Review, v. 40,
p. 375-402.
Augustin, N., F. M. van der Zwan, C. W. Devey, M. Ligi, T. Kwasnitschka, P. Feldens, R.
A. Bantan, and A. S. Basaham, 2016, Geomorphology of the central Red Sea
Rift: Determining spreading processes: Geomorphology, v. 274, p. 162-179.
Bonatti, E., 1985, Punctiform initiation of seafloor spreading in the Red Sea during
transition from a continental to an oceanic rift: Nature, v. 316, p. 33-37.
Bonatti, E., A. Cipriani, and L. Lupi, 2015, The Red Sea: Birth of an Ocean, The Red Sea,
Springer, p. 29-44.
Chu, D., and R. G. Gordon, 1998, Current plate motions across the Red Sea:
Geophysical Journal International, v. 135, p. 313-328.
Condie, K. C., 1998, Episodic continental growth and supercontinents: a mantle
avalanche connection?: Earth and Planetary Science Letters, v. 163, p. 97-108.
Davies, D., and C. Tramontini, 1970, The deep structure of the Red Sea: Philosophical
Transactions of the Royal Society of London A: Mathematical, Physical and
Engineering Sciences, v. 267, p. 181-189.
Izzeldin, A., 1982, On the structure and evolution of the Red Sea: PhD Diss. Univ.
Strasbourg.
Izzeldin, A., 1987, Seismic, gravity and magnetic surveys in the central part of the Red
Sea: their interpretation and implications for the structure and evolution of the
Red Sea: Tectonophysics, v. 143, p. 269-306.
Ligi, M., E. Bonatti, G. Bortoluzzi, A. Cipriani, L. Cocchi, F. Caratori Tontini, E. Carminati,
L. Ottolini, and A. Schettino, 2012, Birth of an ocean in the Red Sea: initial pangs:
Geochemistry, Geophysics, Geosystems, v. 13 (Paper Q08009,
doi:10.1029/2012GC004155).
Ligi, M., E. Bonatti, F. C. Tontini, A. Cipriani, L. Cocchi, A. Schettino, G. Bortoluzzi, V.
Ferrante, S. Khalil, and N. C. Mitchell, 2011, Initial burst of oceanic crust
24
accretion in the Red Sea due to edge-driven mantle convection: Geology, v. 39,
p. 1019-1022.
Lonsdale, P., 1989, Geology and tectonic history of the Gulf of California: The eastern
Pacific Ocean and Hawaii: Boulder, Colorado, Geological Society of America,
Geology of North America, v. N, p. 499-521.
Martinez, F., B. Taylor, and A. M. Goodliffe, 1999, Contrasting styles of seafloor
spreading in the Woodlark Basin: Indications of rift‐induced secondary mantle
convection: Journal of Geophysical Research: Solid Earth, v. 104, p. 12909-
12926.
Mitchell, N. C., and Y. Park, 2014, Nature of crust in the central Red Sea:
Tectonophysics, v. 628, p. 123-139.
Plattner, C., R. Malservisi, T. H. Dixon, P. LaFemina, G. Sella, J. Fletcher, and F. Suarez-
Vidal, 2007, New constraints on relative motion between the Pacific plate and
Baja California microplate (Mexico) from GPS measurements: Geophysical
Journal International, v. 170, p. 1373-1380.
Rogers, J. J., and M. Santosh, 2004, Continents and supercontinents, Oxford University
Press, 289 p.
Sandwell, D. T., R. D. Muller, W. H. F. Smith, E. Garcia, and R. Francis, 2014, New global
marine gravity model from CryoSat-2 and Jason-1 reveals buried tectonic
structure: Science, v. 346, p. 65-67.
Santosh, M., S. Maruyama, and S. Yamamoto, 2009, The making and breaking of
supercontinents: some speculations based on superplumes, super
downwelling and the role of tectosphere: Gondwana Research, v. 15, p. 324-
341.
Shi, W., N. C. Mitchell, L. M. Kalnins, and A. Y. Izzeldin, 2018, Oceanic-like axial crustal
high in the central Red Sea: Tectonophysics, v. 747-748, p. 327-342.
Smith, W. H. F., and Sandwell, D. T., 1997, Global sea floor topography from satellite
altimetry and ship soundings: Science, v. 277, p. 1956-1962.
Sultan, M., R. Becker, R. E. Arvidson, P. Shore, R. J. Stern, Z. Elalfy, and E. A. Guinness,
1992, Nature of the Red Sea crust: A controversy revisited: Geology, v. 20, p.
593-596.
25
Sultan, M., R. J. Stern, R. E. Arvidson, P. Shore, and R. Becker, 1993, Nature Of the Red-
Sea Crust - a Controversy Revisited - Reply: Geology, v. 21, p. 575-576.
Taylor, B., A. Goodliffe, F. Martinez, and R. Hey, 1995, Continental rifting and initial
sea-floor spreading in the Woodlark Basin: Nature, v. 374, p. 534.
Tramontini, C., and D. Davies, 1969, A Seismic Refraction Survey in The Red Sea:
Geophysical Journal International, v. 17, p. 225-241.
Weissel, J. K., B. Taylor, and G. D. Karner, 1982, The opening of the Woodlark Basin,
subduction of the Woodlark spreading system, and the evolution of northern
Melanesia since mid-Pliocene time: Tectonophysics, v. 87, p. 253-277.
Wessel, P., W. H. Smith, R. Scharroo, J. Luis, and F. Wobbe, 2013, Generic mapping
tools: improved version released: Eos, Transactions American Geophysical
Union, v. 94, p. 409-410.
Wilson, J. T., 1966, Did the Atlantic close and then re-open?: Nature, v. 211, p. 676-
681.
Withjack, M. O., and W. R. Jamison, 1986, Deformation produced by oblique rifting:
Tectonophysics, v. 126, p. 99-124.
26
Chapter 2.
Review of literature on the Red Sea and how
it prompts the present work
27
2. Review of literature on the Red Sea and how it
prompts the present work
2.1 Study area
The Red Sea is located between Africa and Arabia, with a length of ~2,000 km,
a maximum width of 355 km, and a surface area of ~458,620 km2 (Head, 1987). A
bathymetric map of the Red Sea is presented in Figure 2.1. In the north, the Red Sea
is bifurcated by the Sinai Peninsula into the Gulf of Suez and the Gulf of Aqaba (Figure
2.1). In the south, it is connected to the Indian Ocean through the Strait of Bab-el-
Mandeb and the Gulf of Aden (Figure 2.1). The Afar hotspot region (Figure 2.1) is
located near the southern end of the Red Sea (e.g., Nyblade et al., 2000; Sicilia et al.,
2008).
The study area in the central Red Sea is located between 19°N and 23°N (Figure
2.1). The central Red Sea is characterized by a complex pattern of axial deeps floored
with volcanic rocks and shallower inter-trough zones between them floored with
evaporites (e.g., Augustin et al., 2014; Bonatti, 1985; Izzeldin, 1982, 1987). The
magnetic anomalies found in this region are poorly lineated and seafloor spreading
anomalies can only be identified up to Chron 3 (e.g., Izzeldin, 1982, 1987; Ligi et al.,
2012; Phillips, 1970; Roeser, 1975; Searle and Ross, 1975). The southern Red Sea has
a comparatively straight and continuous axis with lineated magnetic anomalies (e.g.,
Augustin et al., 2014; Phillips, 1970; Roeser, 1975; Vine, 1966), whilst the northern
Red Sea has few lineated magnetic anomalies (Cochran, 2005) though a few isolated
deeps (e.g., Bonatti, 1985; Cochran and Karner, 2007; Ehrhardt and Hübscher, 2015;
Guennoc et al., 1988; Ligi et al., 2018; Martinez and Cochran, 1988; Pautot et al., 1984).
28
Figure 2.1 Map of Red Sea bathymetry (Smith and Sandwell, 1997, version 18.1) showing the
location of the central Red Sea study area. Red dots locate the prominent deeps in the central
Red Sea from Augustin et al. (2014) and Karbe (1987). From north to south, these are (1)
Nereus, (2) Thetis, (3) Hadarba, (4) Hatiba, (5) Atlantis II, (6) Erba, (7) Port Sudan, (8) Suakin,
and (9) Pelagia deeps. The relative plate motion vectors were calculated from the pole of Chu
and Gordon (1998).
Thick evaporites were deposited from Middle to Late Miocene (15–5 Ma)
(Figure 2.2) in the Red Sea basin, complicating the seismic imaging of underlying crust
structure and preventing direct sampling of basement except in isolated locations (e.g.,
Augustin et al., 2014; Bosworth et al., 2005; Girdler and Whitmarsh, 1974; Mitchell
and Park, 2014; Stoffers and Kühn, 1974; Tramontini and Davies, 1969; Whitmarsh et
al., 1974). These evaporites exceed 3 km in thickness in places (e.g., Izzeldin, 1987;
Tramontini and Davies, 1969). The seismic S-reflection from the top of the Miocene
29
evaporites is found throughout most of the Red Sea (e.g., Izzeldin, 1987; Knott et al.,
1966; Phillips and Ross, 1970; Ross and Schlee, 1973). The Plio-Pleistocene (PP)
sediments overlying the S-reflection are thin (only 0.2–0.3 km thick) and tend to be
uniform (e.g., Izzeldin, 1987; Phillips and Ross, 1970; Ross and Schlee, 1973). In deep
waters away from the coasts, they have a similar density to halite (Wheildon et al.,
1974), hence diapirism is muted, whereas diapirism occurs under the thicker and
denser PP sediments along the coasts (Mitchell et al., 2017).
Figure 2.2 Simplified stratigraphic sections of the Red Sea and Gulf of Suez (Bosworth, 2015).
2.2 Geological and tectonic setting
The Red Sea is a young ocean basin that is at various stages in the transition
from continental rifting to seafloor spreading, though the exact stage that some areas
are at have been controversial (e.g., Bonatti et al., 1981; Cochran and Martinez, 1988;
30
Hall, 1989; Rihm and Henke, 1998). How this transition is evolving along the Red Sea
rift is therefore still open to vigorous debate.
2.2.1 Seafloor spreading and continental rifting in the Red Sea
The Red Sea was formed as the African-Arabian shield rifted, allowing the
distinct Arabian and Nubian plates to separate (e.g., Ghebreab, 1998; McKenzie et al.,
1970). The extension of the Red Sea may have begun in the Eocene but developed
more greatly in the Oligocene associated with massive and rapidly erupted basalts in
Ethiopia and southern Yemen at ~30 Ma (Bosworth and McClay, 2001; Hofmann et al.,
1997; Mohr, 1983; Omar and Steckler, 1995). These rapid eruptions have been
attributed to the Afar plume penetrating the lithosphere (Furman et al., 2006; George
et al., 1998; Richards et al., 1989). The present Red Sea opening rate increases
southward from ~10 mm yr−1 at 25.5°N to ~16 mm yr−1 near 18°N away from the
Nubia/Africa spreading pole located in the Mediterranean (e.g., Chu and Gordon, 1998;
DeMets et al., 1990; DeMets et al., 2010; Reilinger et al., 2015).
2.2.1.1 Southern Red Sea
The southern Red Sea (south of 19°N; Figure 2.1) has a continuous axial zone
with extensive volcanism and seafloor spreading magnetic anomalies (e.g., Augustin
et al., 2014; Phillips, 1970; Roeser, 1975). These lineated seafloor spreading magnetic
anomalies are clearly identifiable up to anomaly Chron 3 (5 Ma, Figure 2.3) near the
axial trough between 16°N and 19°N, suggesting that recognizable seafloor spreading
began at least by 5 Ma (e.g., Cochran, 1983; Girdler and Styles, 1974; Phillips, 1970;
Roeser, 1975; Vine, 1966). Augustin et al. (2014, 2016) suggested that seafloor
spreading likely began somewhat earlier, 8-12 Ma, based on spreading rates of Chu
and Gordon (1998) and locations of volcanic ridges interpreted from multibeam sonar
and vertical gravity gradient data. In addition to the clear anomalies in the centre of
the basin, Girdler and Styles (1974) interpreted the low amplitude magnetic anomalies
over the southern Red Sea shelves as additional seafloor spreading magnetic stripes,
suggesting the Red Sea was formed by two stages of seafloor spreading. In contrast,
Cochran (1983) argued that these magnetic anomalies result from a wide region of
mafic diking and intrusions rather than a continuous oceanic crust of dykes and
31
extrusives, because the anomalies have low amplitudes (less than 200 nT) and long
wavelengths (20-50 km). However, Hall (1989) supported the interpretation of
seafloor spreading, because he found the reduced-to-pole magnetic anomalies are
linear and symmetrical about the axis. Based on magnetic and gravity modelling
constrained by the seismic refraction data of Gettings et al. (1986) and Mooney et al.
(1985), Almalki et al. (2014) recently suggested that about 75 km of oceanic crust
formed before Middle to Late Miocene (15–5 Ma) under the Farasan Bank (Figure 2.1),
which supports a two-stage spreading evolution of the Red Sea. A seismic refraction
line shot across the Yemen margin by Egloff et al. (1991) was interpreted as showing
that oceanic crust adjacent to the axis terminates southward of 16°N and that
continental-type crust lies farther south as far as 14˚N.
Figure 2.3 Seafloor spreading magnetic anomalies in the southern Red Sea (Phillips, 1970).
The bottom curve represents synthetic magnetic anomalies generated by the seafloor
spreading model beneath it using a spreading rate of 10 mm yr-1. The black blocks indicate
normal magnetization, whereas open blocks represent reversed magnetization.
Going south of 18°N, increasing influence of the Afar melting anomaly is
indicated by basalt Sr-Nd-Pb isotopes and higher 3He/4He ratios, in both major and
trace elements (Altherr et al., 1988; Moreira et al., 1996; Volker et al., 1997).
32
2.2.1.2 Central Red Sea
In the central Red Sea, the topographic structure of the axial zone becomes
less lineated, consisting of a series of ‘deeps’, which are separated by inter-trough
zones. The inter-trough zones are shallower, lack strong magnetic anomalies
compared to the ‘deeps’, and are covered by evaporites that have flowed laterally
along with overlying sediments across the axis (e.g., Augustin et al., 2014; Izzeldin,
1982, 1987).
How far the central Red Sea is through the transition from continental rifting
to full seafloor spreading has been controversial.
Bonatti (1985) suggested the central Red Sea is just at the point of transitioning
from continental rifting to oceanic spreading. He proposed that the ‘deeps’ found in
the central Red Sea are discrete seafloor spreading cells based on the presence of
normal mid-ocean ridge basalt (MORB) sampled from them and their high amplitude
magnetic anomalies. This contrasts with low amplitude anomalies outside the deeps,
which were therefore assumed to overlie stretched continental crust (Ligi et al., 2011,
2012).
However, other evidence indicates more established seafloor spreading in the
central Red Sea. An extensive aeromagnetic survey revealed that there are low
amplitude magnetic anomalies outside the ‘deeps’ that are lineated and aligned
parallel to the ridge axis (Izzeldin, 1987; Rasul et al., 2015). LaBrecque and Zitellini
(1985) showed with numerical modelling that such subdued anomalies could be
produced by widely distributed dykes, lava flows, and sills, as occur in modern-day
Afar. Low amplitudes may also have arisen from the slow spreading rate, the greater
depth of basement and alteration under the evaporites (Augustin et al., 2014; Dyment
et al., 2013; Izzeldin, 1987, 1989; Mitchell and Park, 2014). Based on seismic reflection,
gravity and magnetic data, Izzeldin (1982, 1987) suggested the inter-trough zones are
manifestations of less organized seafloor spreading and underlain by oceanic crust.
Using multibeam sonar data, Augustin et al. (2014, 2016) also interpreted these inter-
trough zones as merely areas where the off-axis evaporites have flowed into the axis,
obscuring the volcanic geomorphology. Seismic refraction data show the velocity of
33
basement under the inter-trough zone between Nereus and Thetis deeps (Figure 2.1)
is 6.86 km s-1 (Davies and Tramontini, 1970; Tramontini and Davies, 1969) which
overlaps with velocities of oceanic crust elsewhere (6.7-6.9 km s-1; Carlson, 2001,
2010). Further seismic refraction data collected by Egloff et al. (1991) along their line
PIII (near 19.5°N) also suggested the basement around the ridge axis is oceanic, which
transitions to stretched continental crustal velocities towards the coast of Sudan.
Finally, free-air gravity anomalies derived from satellite altimeter data (Sandwell et al.,
2014; Sandwell and Smith, 2009) reveal that anomalies along the spreading centre are
segmented. Mitchell and Park (2014) and Augustin et al. (2016) suggested that this
segmented pattern is similar to the segmentation observed at slow-spreading mid-
ocean ridges elsewhere (e.g., the northern Mid-Atlantic Ridge) (Schouten et al., 1987;
Sempéré et al., 1990).
Based on seismic reflection and potential field data, Izzeldin (1982, 1987)
suggested that intermediate crust separates crust that is continental near the coasts
from that which is oceanic around the axis. This area lies ~65-160 km from the ridge
axis.
2.2.1.3 Northern Red Sea
The northern Red Sea (North of 23°N; Figure 2.1), which is closer to the Euler
pole of rotation of the relative motion of the African plate with respect to the Arabian
plate (e.g., Chu and Gordon, 1998; DeMets et al., 1990; DeMets et al., 2010) and has
experienced less extension than our study area, has been thought to be underlain by
continental crust with a series of large crustal fault blocks interpreted from seismic
velocity data and from magnetic and gravity anomalies (Cochran and Karner, 2007;
Gaulier et al., 1986; Martinez and Cochran, 1988). Cochran and Karner (2007)
suggested that the strong lithosphere resulting from low mantle temperature in the
northern Red Sea is preventing the transition to oceanic spreading. If correct, this area
may still be in late stage continental rifting (e.g., Cochran, 1983; Gaulier et al., 1988;
Martinez and Cochran, 1988). In contrast, others have interpreted this region as
underlain by oceanic crust on the basis of unpublished seismic and magnetic data (e.g.,
Dyment et al., 2013; Tapponnier et al., 2013). Using remote sensing, geochemical, and
34
geochronological data, Sultan et al. (1992) carried out a plate reconstruction for the
opening of the Red Sea and found a best match of pre-existing African and Arabian
geologic features by juxtaposing present Red Sea coastlines. This has been interpreted
as indicating that the entire Red Sea basin is underlain by oceanic crust (Bosworth et
al., 1993). In addition, a few ‘deeps’ containing basalts are revealed in the northern
Red Sea (e.g., Bonatti, 1985; Ehrhardt and Hübscher, 2015; Guennoc et al., 1988; Ligi
et al., 2018; Pautot et al., 1984).
2.2.2 Seismic tomographic studies encompassing the Red Sea
Seismic tomographic studies have found that upper mantle S- and P-wave
seismic velocities of the adjacent to the Red Sea increase by up to a few percent from
south to north with increasing distance from the Afar plume. Using body wave travel
time tomography, Park et al. (2007) found a -1.5% S-wave velocity anomaly at 200 km
depth beneath the coast of the southern Red Sea, rising to ~-1% in the central Red Sea
and to 0% or more in the northern Red Sea. A similar structure was found by Park et
al. (2008) from Rayleigh wave tomography although with a more subdued northwards
increase in S-wave velocity. They suggested this structure is caused by an upwelling
of warm mantle beneath the southern Arabian shield, originating from the Afar
hotspot. They proposed that this hot plume material flows from Afar underneath the
southern and central Red Sea, and then extends northwards beneath Arabia, whereas
the northern Red Sea (north of ~23°N) is without underlying hot mantle. The upper
mantle under the Red Sea is poorly resolved in such models as they are mainly based
on teleseismic recordings along the coast of Saudi Arabia (no offshore recordings).
Nevertheless, this general pattern of upper mantle structure is corroborated by Na8.0
analyses of axial lavas (sodium oxide concentrations corrected for fractionation (Klein
and Langmuir, 1987)), which indicate the upper mantle temperature in the Red Sea
generally decreases by about 60°C from 18°N to 26°N (Haase et al., 2000).
35
Figure 2.4 Shear wave velocity map at a depth of 150 km (Chang et al., 2011). Shear wave
splitting data (blue lines) were derived from Gashawbeza et al. (2004) and Hansen et al. (2006).
More recently, Chang et al. (2011) have carried out an inversion of seismic
travel times and waveforms that provides a more complete coverage of the area
under the Red Sea (Figure 2.4). They found low velocity (hot) material is located
beneath the southern Red Sea and Gulf of Aden, where there is active seafloor
spreading. They also suggested that the hot material at a depth of ~150 km does not
extend north-westwards below the central and northern Red Sea areas, but forms a
channel extending northward beneath Arabia. The higher velocities under the central
Red Sea prompt the question of whether we should expect a non-volcanic margin in
this area and whether any seafloor spreading should be unlike at a hotspot.
36
The Afar mantle plume is located at the Afar Triangle, with hot mantle plume
material expected to spread out in a star-like pattern into the soft asthenosphere
(Courtillot et al., 1999; Ebinger and Sleep, 1998; Schilling, 1973). Recently, the
existence of another separate mantle hotspot beneath the northern Arabia and
Jordan was suggested by Chang and Van der Lee (2011), based on their tomographic
results. They suggested that this separate mantle plume could be the reason for
simultaneous northward and southward migration of the Neogene volcanism
between Afar and Jordan (Bosworth et al., 2005; Camp and Roobol, 1992). As a result
of this volcanism migration, significant upwelling mantle occurs in western Arabia
(Figure 2.4).
Cenozoic volcanism on the continental flanks of the Red Sea are asymmetric,
being more common in Arabia (e.g., Dixon et al., 1989; Makris and Rihm, 1991).
Abundant basaltic lava fields characterize the eastern flank (Saudi Arabia), while the
volcanisms are absent on the western flank (Egypt and Sudan). Besides the
explanation of double mantle plume model proposed by Chang and Van der Lee (2011),
some studies (Voggenreiter et al., 1988; Wernicke, 1985) explained this asymmetry by
suggesting that the Red Sea is opening on an east-dipping low-angle detachment fault
(the Wernicke Model). However, Camp and Roobol (1991) argued that this low-angle
detachment model does not accord with field and age data delineating the timing of
magmatism and uplift on the Arabian plate. Bosworth (2015) suggested that this
simple shear low-angle detachment geometry cannot reproduce the value or
distribution of heat flow, which is more nearly symmetric (Girdler, 1970; Girdler and
Evans, 1977; Scheuch, 1976).
2.3 How the previous studies prompt the present work
Although there are strong indications that much of the central Red Sea is
underlain by oceanic crust (Augustin et al., 2014; Izzeldin, 1982, 1987; Mitchell and
Park, 2014), there is still some doubt, given that the off-axis magnetic anomalies are
not identifiable as seafloor spreading anomalies and the seismic refraction data are
limited. Augustin et al. (2014, 2016) and Mitchell and Park (2014) have suggested that
evaporites are flowing into the axis at areas where the basement is deeper (oceanic
37
fracture zones), although this has remained to be proven given the previously
available deep-seismic data able to penetrate the evaporites. Furthermore, the more
recent mantle seismic tomography results (Chang et al., 2011) also prompt the
question of whether any underlying crust, if it is oceanic, is likely to be similar to ridges
away from hotspots rather than those proximal to hotspots.
This research has been enabled by accessing to the Izzeldin (1982, 1987)
multichannel seismic reflection data, which penetrate the evaporites, as well as the
newly released satellite gravity data (Sandwell et al., 2014) (version 23), and the
aeromagnetic anomalies (Izzeldin, 1982, 1987). This combination allows us to address
the above problems. In this study, those multichannel seismic reflection seismic,
satellite gravity, and aeromagnetic data are used to evaluate the basement geometry
and roughness in the central Red Sea. We then compare our findings with other mid-
ocean ridges and discuss what these results imply about the evolution of the Red Sea
rift in the central Red Sea.
2.4 References
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southern Red Sea: Tectonophysics, v. 617, p. 140-149.
Altherr, R., F. Henjes-Kunst, H. Puchelt, and A. Baumann, 1988, Volcanic activity in the
Red Sea axial trough—evidence for a large mantle diapir?: Tectonophysics, v.
150, p. 121-133.
Augustin, N., C. W. Devey, F. M. van der Zwan, P. Feldens, M. Tominaga, R. A. Bantan,
and T. Kwasnitschka, 2014, The rifting to spreading transition in the Red Sea:
Earth and Planetary Science Letters, v. 395, p. 217-230.
Augustin, N., F. M. van der Zwan, C. W. Devey, M. Ligi, T. Kwasnitschka, P. Feldens, R.
A. Bantan, and A. S. Basaham, 2016, Geomorphology of the central Red Sea
Rift: Determining spreading processes: Geomorphology, v. 274, p. 162-179.
Bonatti, E., 1985, Punctiform initiation of seafloor spreading in the Red Sea during
transition from a continental to an oceanic rift: Nature, v. 316, p. 33-37.
38
Bonatti, E., P. Hamlyn, and G. Ottonello, 1981, Upper mantle beneath a young oceanic
rift: peridotites from the island of Zabargad (Red Sea): Geology, v. 9, p. 474-
479.
Bosworth, W., 2015, Geological evolution of the Red Sea: historical background,
review, and synthesis, The Red Sea, Springer, p. 45-78.
Bosworth, W., P. Huchon, and K. McClay, 2005, The Red Sea and Gulf of Aden basins:
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Bosworth, W., and K. McClay, 2001, Structural and stratigraphic evolution of the Gulf
of Suez rift, Egypt: a synthesis: Mémoires du Muséum national d'histoire
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Bosworth, W., M. Sultan, R. Stern, R. Arvidson, P. Shore, and R. Becker, 1993, Nature
of the Red Sea crust: A controversy revisited: Comment and Reply: Geology, v.
21, p. 574-576.
Camp, V. E., and M. J. Roobol, 1991, Comment on “Topographic and volcanic
asymmetry around the Red Sea: Constraints on rift models” by TH Dixon, ER
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Carlson, R., 2001, The effects of temperature, pressure, and alteration on seismic
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oceanic crust: Modeling downhole logs from Holes 504B and 1256D:
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47
Chapter 3.
Data and methods
48
3. Data and methods
3.1 Multichannel seismic reflection data
Multichannel seismic reflection data used in this study were collected in 1976
(Izzeldin, 1982, 1987), using a Vaporchoc source with a 2.4 km streamer consisting of
48 channels (50 m spacing) in deep-water survey, and with a 1.2 km streamer
consisting of 24 channels (50 m spacing) in shallow-water survey. The data were
moveout-corrected by others as described by Izzeldin (1982, 1987). Unfortunately,
we do not have access to the digital data, but we have paper copies of the seismic
reflection profiles from Izzeldin (1982, 1987). The locations of seismic reflection
profiles 7, 9, 11, 15, 17, 19, 21, 25, 27, 29, and 31 are shown in Figures 3.1.
Figure 3.1 Map of free-air gravity anomalies (Sandwell et al., 2014, version 23.1) showing
the locations of multichannel seismic reflection profiles 7, 9, 11, 15, 17, 19, 21, 25, 27, 29, 31
of Izzeldin (1982, 1987). The data were gridded using the GMT software (Wessel et al., 2013).
Two-way travel times of the basement and seabed reflections were converted
to depths below sea level (Figure 3.2) as follows. A P-wave velocity (Vp) of 1.538 km
s-1 was used for the water according to the empirical equations of Mackenzie (1981),
49
with typical Red Sea salinity of 40 ppt and temperature of 21°C. A 1.9 km s-1 Vp for
the Plio-Pleistocene sediments was chosen, based on the measurements made on
samples recovered from DSDP Leg 23 (Whitmarsh et al., 1974) and the results of
seismic reflection and refraction surveys of Egloff et al. (1991) and Gaulier et al. (1988).
A Vp of 4.21 km s-1 was used for the evaporites, based on seismic refraction data from
Tramontini and Davies (1969), Girdler and Whitmarsh (1974), and Egloff et al. (1991).
Figure 3.2 Depths derived from the seismic reflection profiles of Izzeldin (1982, 1987). Line
numbers are shown in the lower right corner of each panel. Black lines denote bathymetry
(Smith and Sandwell, 1997, version 18.1). Dark green and cyan lines are the depths of the
seabed and the S-reflection at the top of the Miocene evaporites, respectively. Red and blue
lines are the basement reflection depths computed using the P-wave velocities of 4.21 km s-1
and 3 km s-1 for the evaporites, respectively.
Depths of the basement computed using a P-wave velocity of 4.21 km s-1 for
the evaporites and seabed derived from the seismic reflection profiles are used in
Chapters 4, 5, and 6.
50
Although they were collected 43 years ago, the seismic data quality is high.
Due to the thick evaporite layer and data noise, there is no Moho reflection obtained
from those data. On the western flank of profile 15, the basement reflection is not
clear enough to be identified. About 15% of the seismic data cannot be used to
compute the basement depth, because the basement reflection is in places absent or
un-interpretable.
The main uncertainty in the seismically derived basement depth originates
from the P-wave velocity used for the evaporites. During the seismic depth conversion,
the Vp of 4.21 km s-1 for the evaporites was chosen based on laboratory sample and
field refraction measurements of the upper evaporites, which are dominated by halite
(Girdler and Whitmarsh, 1974; Tramontini and Davies, 1969). However, the seismic
data show that there are many laminations in the lower evaporites also. Those
laminations are probably due to the laminated evaporites (halite, anhydrite, limestone
and shale), which would have a different velocity. Izzeldin (1982) suggested the
average seismic velocity of the lower evaporites ranges between 3 and 3.5 km s-1. To
address how the velocity affects the basement depths found, a Vp of 3 km s-1 for the
evaporites was used to compute another set of basement depths (in Figure 3.2). We
consider the models derived using the P-wave velocities of 3 km s-1 and 4.21 km s-1 for
evaporites as the minimum and maximum salt thickness models, respectively. In
Figure 3.2, the difference between the basement depths of these two models
increases with the basement two-way time. The difference increases from ~0.2 km to
~1.8 km as the basement depth derived using 4.21 km s-1 (red lines in Figure 3.2)
increases from 2 km to 6.7 km. The average difference is 1.5 km. Due to the
uncertainty in seismically derived basement depth, the height of the found axial
plateau is potentially overestimated.
Figure 3.3 is a depth to basement confidence map. In Figure 3.3, red indicates
where the basement reflections can be imaged with a high confidence, while those in
the areas away from the seismic lines have to be estimated using other geophysical
methods (e.g., Werner deconvolution of magnetic data).
51
Figure 3.3 Confidence map showing the ability to image the basement reflection.
3.2 Magnetic anomalies
3.2.1 Shipboard magnetic data
Marine magnetic field measurements from towed magnetometers were
obtained from the National Centers for Environmental Information (NCEI)
(www.ngdc.noaa.gov/mgg). The data comprise residual magnetic anomalies after
removal of the international geomagnetic reference field (IGRF) from the total field
measurements. Figure 3.4 shows the survey locations and contoured anomalies after
further adjustments to correct IGRF errors of the individual surveys (see figure
caption).
52
Figure 3.4 (a): Tracks of shipboard magnetic surveys of RVs Jean Charcot (78005111,
83008011), Atlantis (A2093L19), Chain (CH043L01, CH043L03, CH061L02, CH100L03),
Discovery (DI103B), Glomar Challenger (DSDP23GC), Melville (INMD09MV), Robert Conrad
(RC0911A), Shackleton (SHA1079) and Vema (V1413). (b): Residual magnetic anomalies of the
surveys in (a) obtained from the National Centers for Environmental Information (NCEI)
(www.ngdc.noaa.gov/mgg) gridded and contoured every 50 nT. To reduce effects of
reference field errors, the residual anomalies of each survey were adjusted by subtracting
their mean value before gridding and contouring. (Anomalies are not reduced to the pole.)
The data were gridded and contoured using the GMT software (Wessel et al., 2013).
Major causes of magnetic anomalies are expected to be susceptibility and
remanent magnetization variations within the basement produced by intrusive or
extrusive volcanic bodies. To investigate possible magnetic sources, Werner
deconvolution was applied to calculate the magnetic source depths and apparent
susceptibilities. They were calculated along individual segments of the magnetic lines
(ungridded magnetic data) where they cross the seismic reflection profiles of Izzeldin
(1987) (Figure 3.5a), and then were projected to the seismic profiles (Figure 3.5b).
53
Figure 3.5 (a): Extents of shipboard magnetic lines (blue) contributing to the evaluation of
seismic profiles (red) using Werner source depths. (b): A sketch showing how the source
depths and apparent susceptibilities were projected onto the seismic profiles. A source
located at point M was assigned position SM along the seismic line.
In Chapter 4, the projected magnetic source solutions are used to verify the
basement depths derived from the seismic reflection data.
The data quality of shipboard residual magnetic data is generally high. Those
data can roughly reflect the fracture zones in the central Red Sea (Figure 3.4b). More
than 95% of the data have reasonable values (between -1000 nT and 1000 nT). Less
54
than 10% of the data are distorted due to the shake and course changes of the ship.
The mean value of each survey ranges from to 10-700 nT.
3.2.2 Aeromagnetic data
The aeromagnetic survey was carried out in 1976 by the Arabian Geophysical
and Surveying Company (ARGAS) as described by Saudi-Sudanese Red Sea
Commission (1976) and Izzeldin (1982, 1987). This survey covered the central Red Sea
between 18.5 °N and 23 °N with flight lines oriented N60°E (Figure 3.6a). Sixty-four
survey lines were run from coast to coast and spaced at a distance of 10 km. 464
shorter lines were added over the axial zone and some coastal zones for detailed
investigation with the lines spaced 2.5 km apart. The total length of the main survey
lines is 23,011 km, while that of additional lines is 28,210 km. The survey was flown
at an altitude of 305 m above mean sea level. Measurements of total magnetic field
were obtained using a caesium vapour magnetometer with a resolution of 0.01 nT at
a sample frequency of 1 Hz.
Diurnal variations were corrected using data from a magnetometer station in
Jeddah and the results verified by analysis of data at crossing lines. Minor line levelling
errors in the data were minimised. Residual magnetic anomalies derived from the
total field data were used in this study. Figure 3.6b shows the contoured anomalies
after further adjustments made here to correct minor remaining data offsets of the
individual lines (see figure caption). The length of survey line tends to affect the
number of magnetic sources found by the Werner deconvolution (a longer length of
data is needed to resolve deeper magnetic bodies), so we used the longer lines for our
analysis (Figure 3.6c).
In Chapter 5, aeromagnetic data are used to compute magnetic basement
depth throughout the central Red Sea.
In Chapter 6, aeromagnetic anomalies were adjusted using reduction to the
pole technique by Ian C.F. Stewart. The reduced-to-pole aeromagnetic anomalies are
symmetric and lack of correlation with basement topography, indicating they are likely
seafloor spreading anomalies, explained by Hall (1989).
55
Figure 3.6 (a): Locations of aeromagnetic survey flight lines (blue) and multichannel seismic
reflection profiles 7, 9, 11, 15, 17, 19, 21, 25, 27, 29, 31 of Izzeldin (1987) (red). Black line
locates the spreading axis. (b): Residual aeromagnetic anomalies from data collected by
Arabian Geophysical and Surveying Company (ARGAS) in 1976. The data have been gridded
and contoured every 75 nT. In order to reduce effects of remaining reference field errors, the
residual aeromagnetic anomalies of each survey line were adjusted by subtracting their mean
anomaly value before gridding and contouring. The data were gridded and contoured using
the GMT software (Wessel et al., 2013). (c): Locations of the long survey lines used to derive
magnetic basement depth in Chapter 5 (blue). (d): Residual aeromagnetic anomalies along
the long survey lines in (c).
56
The aeromagnetic data quality is high. More than 95% of the data are
continuous and smooth (Figure 3.6d). All the observed aeromagnetic values range
from -600 nT to 600 nT, which are reasonable values. The variation between the mean
values of each survey line is less than 100 nT. Those data can roughly reveal the
fracture zones in the central Red Sea (Figure 3.6b). The residual aeromagnetic
anomalies are generally consistent with the magnetic anomalies reported in other
studies, for example, Roeser (1975) and Hall et al. (1977).
3.2.3 2D Werner deconvolution
2D Werner deconvolution has been widely used in the assessment of magnetic
basement structure by estimating the magnetic source depth and susceptibility (e.g.
Karner et al., 1991; Ku and Sharp, 1983; Thakur et al., 2000).
This method was originally designed to solve the thin-dike problem (Ku and
Sharp, 1983; Werner, 1953). The edges of a thick body can also be recognized by 2D
Werner deconvolution, because the horizontal gradient of the total magnetic field
caused by the edge of a thick body is equal to the total field from a thin-dike body (Ku
and Sharp, 1983; Werner, 1953). The 2D Werner deconvolution does not require any
initial model parameter values (Subrahmanyam and Gebissa, 2017). This method has
been tested in a large number of studies with synthetic and real magnetic data. Some
typical examples are as follows.
Based on synthetic studies, Jain (1976) suggested that the 2D Werner
deconvolution can locate the tops of thin sheets and the edges of thick bodies with
high accuracy. To test the validity of the 2D Werner deconvolution, Ku and Sharp
(1983) used it to resolve real magnetic anomalies and synthetic anomalies of various
geometric models, which include thin dikes (alternatively, bodies with a large ratio of
length to thickness), thick body edges, dike-like bodies with tapering edge from thin
to thick, and high/low basement topographic relief. They suggested that the 2D
Werner deconvolution can provide reliable estimates of magnetic source bodies.
Moreover, they also suggested that iteration, statistic decision, and seven-point
Werner operator are necessary for obtaining accurate estimates. The synthetic
studies of Subrahmanyam and Gebissa (2017) confirmed that the 2D Werner
57
deconvolution can yield reliable source parameter estimates for the sources of thin,
thick, wide, and faulted bodies.
Hartman et al. (1971) extended 2D Werner deconvolution in estimating the
basement depth around Rainbow Lake and Peace River in Canada by considering the
thin-dike body as an approximation. Because each Werner solution in their study is
associated to a single magnetic anomaly, the resolution of their results is low. Stagg
et al. (1989) mapped the magnetic basement in the Great Australian Bight based on
Werner solutions. Davy and Wood (1994) simply delineated the basement top using
visual identification of Werner source clusters. Thakur et al. (2000) revealed the
basement configuration in Bay of Bengal using 2D Werner deconvolution, although
short wavelength features were absent in the magnetic derived basement. Martelet
et al. (2013) used this method to extract magnetic sources at the basement interface
in the south-western part of the Paris Basin. During the extraction, they kept the
significant clusters of solutions and rejected the disseminated solutions.
Hansen and Simmonds (1993) extended the 2D Werner deconvolution to
interpret anomalies of multiple magnetic bodies and applied it to investigate the top
and bottom of the spreading center basalts in the Cobb Offset area of the Juan de Fuca
Ridge. Hansen (2005) developed 3D multiple-source Werner deconvolution based on
the algorithm of Hansen and Simmonds (1993). Hansen (2005) suggested that 3D
multiple-source Werner deconvolution can provide useful depth estimates and
locations of the sources, but it cannot provide useful dip angle and susceptibility
information.
Although individual depth values derived using the method have large
uncertainties and the method can produce some erroneous solutions due to non-
uniqueness and calculation window sizes poorly matching those needed for the
solutions, their depths have been shown generally to cluster within basement
(Cochran and Karner, 2007; Karner et al., 1991).
58
Following Werner (1953) and Ku and Sharp (1983), the magnetic anomaly due
to a dike or other tabular body can be written as:
𝑇𝑚𝑎𝑔(𝑥, 0) =𝐴(𝑥−𝑥0)+𝐵𝐷
(𝑥−𝑥0)2+𝐷2 (3.1)
where 𝑥 is distance along a profile, 𝐴 and 𝐵 are functions of orientation and
magnetization of the dike, 𝑥0 is horizontal position of the point immediately above
the dike, and 𝐷 is depth to the top of the dike (Figure 3.7).
Figure 3.7 Parameters of a vertical thin dike resolved using 2D Werner deconvolution (Ku
and Sharp, 1983).
The interferences from neighbouring anomalies, regional trends, and
measured magnetic noise are addressed by the addition of an interference polynomial
(𝑃) to the right side of equation (3.1) (Ku and Sharp, 1983; Werner, 1953):
𝑃 = 𝐶0 + 𝐶1𝑥 + 𝐶2𝑥2 + ⋯ + 𝐶𝑛𝑥𝑛 (3.2)
where 𝑛 is the order of the interference polynomial, and 𝐶0, 𝐶1, 𝐶2, ⋯ , 𝐶𝑛 are the
coefficients.
In practice, a polynomial of order two is adequate for obtaining stable and
reliable solutions (Hartman et al., 1971; Ku and Sharp, 1983; Werner, 1953):
59
𝑇𝑚𝑎𝑔(𝑥, 0) =𝐴(𝑥−𝑥0)+𝐵𝐷
(𝑥−𝑥0)2+𝐷2+ 𝐶0 + 𝐶1𝑥 + 𝐶2𝑥2 (3.3)
Equation (3.3) can be expressed as:
𝑎0 + 𝑎1𝑥 + 𝑎2𝑥2 + 𝑎3𝑥3 + 𝑎4𝑥4 + 𝑏0𝑇𝑚𝑎𝑔 + 𝑏1𝑥𝑇𝑚𝑎𝑔 = 𝑥2𝑇𝑚𝑎𝑔 (3.4)
where
𝑎0 = −𝐴𝑥0 + 𝐵𝐷 + 𝐶0𝐷2 + 𝑥02𝐶0,
𝑎1 = 𝐴 − 2𝐶0𝑥0 + 𝐶1𝐷2 + 𝐶1𝑥02,
𝑎2 = 𝐶0 − 2𝐶1𝑥0 + 𝐶2𝐷2 + 𝐶2𝑥02,
𝑎3 = 𝐶1 − 2𝐶2𝑥0,
𝑎4 = 𝐶2,
𝑏0 = −𝑥0 − 𝐷2,
and
𝑏1 = 2𝑥0
Marquardt’s (1963) inverse modelling method was used to solve the
simultaneous equations constructed from equation (3.4) by a seven-point Werner
operator (Ku and Sharp, 1983). If the sample spacing is ∆𝑥, we have the following
results for the thin dike (Ku and Sharp, 1983):
Horizontal position:
𝑋 = 0.5𝑏1∆𝑥 + 𝑥 (3.5a)
Depth:
𝑌 = √−𝑏0 − 0.25𝑏12∆𝑥
(3.5b)
Magnetic susceptibility: 𝜒𝑚 =√𝐽𝑥
2+𝐽𝑧2
|𝑭|∆𝑥 (3.5c)
where
𝐽𝑥 =−𝐵 cos 𝐼 sin 𝛼−𝐴 sin 𝐼
2∆𝑇[(cos 𝐼 sin 𝛼)2+(sin 𝐼)2] (3.6a)
and
60
𝐽𝑧 =−𝐴 cos 𝐼 sin 𝛼+𝐵 sin 𝐼
2∆𝑇[(cos 𝐼 sin 𝛼)2+(sin 𝐼)2] (3.6b)
where 𝑱𝒔 = ( 𝐽𝑥, 𝐽𝑧 ) is the vector sum of the induced and remanent magnetization,
2∆𝑇 is thickness of the dike (∆𝑇 ≪ 𝐷), 𝐼 is magnetic inclination of the main field 𝑭,
and 𝛼 is the strike of the tabular body measured counterclockwise from magnetic
north (Figure 3.7).
Matlab codes for 2D Werner deconvolution and Marquardt’s (1963) inverse
modelling method are provided in Appendix 2.
In Chapter 4, magnetic source solutions from Werner deconvolution of
shipboard magnetic data are used to verify the seismically derived basement depths.
In Chapter 5, Werner deconvolution is used to invert aeromagnetic anomalies for
magnetic basement depths.
Although 2D Werner deconvolution can be carried out quickly and can be
easily implemented (Hassan et al., 2007; Martelet et al., 2013), it can be limited by the
following seven issues:
(1): This method is limited to the analysis of simple 2D models (Kilty, 1983).
Magnetic source parameters derived from the 2D analysis tend to be less accurate
than those from the 3D analysis, because in reality the observed magnetic field are
produced by 3D objects.
(2): This method cannot work out the shape of magnetic bodies. Due to the
thin-dike assumption, the 2D Werner deconvolution can provide just the source
clusters around the tops of thin dikes and the edges of thick bodies (Ku and Sharp,
1983; Werner, 1953). The shape of magnetic bodies instead needs to be estimated
using magnetic forward modelling.
(3): Shallow bodies mask deeper sources (Jain, 1976). The high frequency
anomalies produced by shallow bodies tend to mask the interpretation of anomalies
caused by the deeper bodies (Jain, 1976; Ku and Sharp, 1983). Nevertheless, if the
deep source is displaced from the shallow body edges horizontally by a distance
greater than the depth to the top of deep body, the deeper bodies can still be
61
recognized (Jain, 1976; Radhakrishna Murthy et al., 2000). Moreover, if the anomalies
produced by deeper bodies are much stronger than those caused by the shallow
bodies, the top of the deeper bodies can also be located (Jain, 1976).
(4): This method can produce some erroneous solutions, due to noise, non-
uniqueness, and calculation window sizes poorly matching those needed for the
solutions (Cochran and Karner, 2007; Karner et al., 1991; Kilty, 1983; Ku and Sharp,
1983).
(5): If the horizontal distance between neighbouring magnetic bodies is less
than the depth to the top of the bodies, 2D Werner deconvolution has difficulty in
separating them (Hartman et al., 1971; Jain, 1976).
(6): This method produces unacceptable errors when applied to data collected
over varied altitudes (Ostrowski et al., 1993).
(7): This method of depth estimation is easily affected by the magnetized
minerals in the materials above the target basement.
There are many other magnetic interpretation techniques based on source
depth determination that could be used in the central Red Sea, for example, Euler
deconvolution (Thompson, 1982), source parameter imaging method (Thurston and
Smith, 1997), and analytical signal method (MacLeod et al., 1993). Li (2003) assessed
those methods. He suggested that no single method is best overall and an optimum
method should be selected according to the data quality and nature of the geological
problems. Compared to traditional magnetic forward and inverse modelling methods,
those methods are quick and have strong anti-noise properties, as they can well
isolate the magnetic anomaly from the noise (Li, 2003).
There are three reasons why we prefer to apply 2D Werner deconvolution in
this study. First, this method can be easily carried out on our high-quality magnetic
data. Second, it does not require any initial source model parameter values. Third,
comparisons of the Werner solutions with the results from other studies (see 5.5.1)
show the acceptable accuracy of this method.
62
3.2.4 Statistical analysis of the Werner solutions
Although the Werner method produced stable clusters of solutions, the results
are nevertheless noisy and cannot uniquely indicate the top of basement. To obtain
reliable magnetic basement depths, the Werner deconvolution was improved by
including the seismic reflection data as constraints.
Differences between the individual Werner source depths and the seismically
derived basement depths (ΔZ) (i.e., Werner source depth minus seismically derived
basement depth) were computed. Cumulative distribution functions (CDFs) of those
differences (ΔZ) were then derived. Since the primary magnetic source around the
spreading centre is expected to lie within the shallow basement from the
magnetizations of the extrusive basalts and sheeted dykes (Tivey and Dyment, 2010;
Tivey and Johnson, 1987), we first recorded the CDF level corresponding with ΔZ=0
(i.e., magnetic sources within the seismic basement) for the axial data. We then use
this CDF level to estimate depth to basement throughout the central Red Sea,
assuming that the whole region consists of similarly magnetized basement, with none
of the magnetic field originating in the overlying sediments. CDFs were computed
from magnetic sources within rectangular cells 20 km × 10 km along the survey lines.
This statistical method needs a large sample size (greater than 200 in this study)
to compute reliable CDF levels. Hence, the calculation cell sizes are large, resulting in
the low resolution of derived basement topography maps.
In Chapter 5, statistical analysis of the Werner solutions is used to derive
magnetic basement depths from the Werner source solutions.
3.2.5 Reduction to the pole (RTP)
Due to the geomagnetic inclination, magnetic anomalies observed anywhere
other than magnetic poles are asymmetric even when the distribution of causative
bodies is symmetric (Ansari and Alamdar, 2009). To remove the skewness of the
anomalies caused by inclination, reduction to the pole was used to adjust the
aeromagnetic data. The RTP magnetic anomalies is shown in Figure 3.8.
63
Figure 3.8 Aeromagnetic anomalies of Izzeldin (1982, 1987) reduced to pole. Red lines locate
the seismic reflection profiles 7, 9, 11, 15, 17, 19, 21, 25, 27, 29, 31 from Izzeldin (1982, 1987).
The data are contoured every 80 nT. The data were gridded and contoured using the GMT
software (Wessel et al., 2013).
The magnetic anomaly due to a localized spherical source can be expressed as
(Ravat, 2007):
∆T𝑚(r) = −∂
∂β∆Vφ(r) =
∂2
∂β ∂φ
∆J
r (3.7)
where r is distance between source and observation point, ∆Vφ is anomalous
potential due to the magnetization direction φ , ∆J is the intensity of anomalous
magnetization, β is the direction of the Earth’s main field, and ∆J
r is the anomalous
source function.
The RTP magnetic anomaly ∆Tz(r) is the vertical intensity anomaly due to
vertical magnetization, which can be computed by twice differentiating the
anomalous source function ∆J
r in the vertical direction (to obtain first the anomalous
64
potential due to the vertically magnetized source, and then its anomaly in the vertical
direction) as (Ravat, 2007):
∆Tz(r) =∂2
∂z2
∆J
r =
∂2
∂z2 ∫ ∫ ∆T𝑚(r) ∂β ∂φ+∞
−∞
+∞
−∞ (3.8)
where z represents the vertical direction.
At low latitudes, the magnetic RTP becomes unstable, resulting in severe
linear artefacts along the magnetic declination direction (Arkani-Hamed, 2006;
Keating and Zerbo, 1996). Additionally, this technique is seriously affected by high-
frequency noise, which can cause distortion of the RTP result (Zhang et al., 2018).
The reduced-to-pole aeromagnetic anomaly grid used in Chapter 6 (Figure 3.8)
was provided by Ian C.F. Stewart.
3.3 Gravity anomalies
3.3.1 Free-air gravity data
Version 23.1 of the marine gravity field (referred to as “SSv23”) used in this
study were derived from satellite altimetry measurements by Sandwell et al. (2014).
The data are shown in Figures 3.1 and 3.9a.
The SSv23 data are evaluated in Chapter 6, using shipboard gravity data
collected on the RRS Shackleton (Girdler and Southren, 1987) and on RV Robert
Conrad (Cochran and Martinez, 1988). The differences between the SSv23 and the
RRS Shackleton and RV Robert Conrad data have standard deviations of 5.5 and 3.7
mGal. Sandwell (pers. comm. 2013) suggested that these biases could be due to edge
effects from when the vertical offshore altimetry deflections were converting to
gravity anomalies (Mitchell, 2015). Nevertheless, the biases are small compared to
the >100 mGal full range of the SSv23 gravity anomalies.
65
Figure 3.9 (a): Free-air gravity anomalies (Sandwell et al., 2014, version 23.1) and locations
of multichannel seismic reflection profiles 7, 9, 11, 15, 17, 19, 21, 25, 27, 29, 31 from Izzeldin
(1982, 1987). The data were gridded using the GMT software (Wessel et al., 2013). (b):
Locations of gravity profiles G1-32 and seismic reflection profiles as in (a). Cyan line
approximately locates the spreading axis. Green line locates gravity profile G21, along which
the gravity forward modelling results are shown in Figure 6.9. In Chapter 6, the study area is
divided into two areas: north of 20.25°N and south of 20.25°N, as the free-air gravity field
north of 20.25°N has cross-axis lineaments suggested to be due to oceanic spreading
segments (Mitchell, 2015).
In Chapter 6, free-air gravity anomalies are sampled from SSv23 along the
ridge-parallel gravity profiles G1-32 shown in Figure 3.9. Because the free-air gravity
field has lineations crossing the Red Sea north of 20.25°N but not south of there
(Mitchell, 2015), the profiles are each divided into two segments either side of 20.25°N.
Those segmented gravity profiles are then inverted for basement depth variations,
which are used to estimate basement roughness.
3.3.2 Bouguer gravity anomalies
Gravity anomalies arise from density variations within the crust and upper
mantle, topography of the Moho and crust-evaporite interfaces, as well as seabed
topography. Mitchell et al. (2017) computed marine Bouguer anomalies of the central
Red Sea to remove the component of the gravity field due to the seabed topography
(Figure 3.10).
66
The minor errors in Bouguer gravity anomalies are likely to arise from the
thickness variations of Plio-Pleistocene sediments (Cowie and Karner, 1990; Mitchell
et al., 2017).
Figure 3.10 Bouguer gravity anomalies from Mitchell et al. (2017) computed by removing
the component of the free-air gravity field (Sandwell et al., 2014, version 23.1) due to the
seabed topography. The data are contoured every 50 mGal. The data were gridded and
contoured using the GMT software (Wessel et al., 2013).
In Chapter 4, the correlation between the marine Bouguer anomalies and the
basement depths is examined for evidence of variations in crustal thickness or density
or in mantle density. In regions of high correlation, we solve for the apparent density
contrast that best explains the observed gravity anomaly to see if it is consistent with
the expected density contrast between the mantle and the evaporites, assuming a
constant thickness crust.
In Chapter 5, the covariation between the marine Bouguer anomalies and
magnetic basement depths is used as a test of the magnetically derived depths.
67
3.3.3 Mantle Bouguer anomalies (MBAs)
The mantle Bouguer anomaly (MBA) is a gravity anomaly, obtained by
subtracting the gravitational attraction of a reference crust and sediments from the
free-air gravity anomaly, with a correction made for cooling of the lithosphere with
age (Grindlay et al., 1998; Lin et al., 1990; Rommevaux et al., 1994).
The MBAs vary with varied crustal thickness and/or upper mantle densities,
therefore, they can be used to investigate the upwelling structure of mantle beneath
spreading ridges (Magde and Sparks, 1997).
MBAs along 11 seismic profiles were computed by removing gravity effects of
evaporite-crust and crust-mantle interfaces from the marine Bouguer gravity
anomalies of Mitchell et al. (2017) (Figure 3.10), assuming a uniform 7 km thick crust.
Densities of 2,148 kg m-3 (Wheildon et al., 1974), 2,957 kg m-3 (Hyndman and Drury,
1977), and 3,220 kg m-3 (Crough, 1983; Gvirtzman et al., 2016) were used for
evaporites, oceanic crust, and hot mantle, respectively.
Because MBAs are derived from Bouguer gravity anomalies of Mitchell et al.
(2017), MBAs can also be affected by the thickness variations of Plio-Pleistocene
sediments.
In Chapter 6, the along-axis gradients in MBAs in the central Red Sea were
compared with those at other mid-ocean ridges. As the gradients were calculated for
the spreading axis, with zero age crust, no gravity anomaly correction for lithospheric
cooling component was needed.
3.3.4 Bouguer slab formula
The gravity anomaly caused by a layer of infinite lateral extent and constant
thickness ℎ and density contrast ∆𝜌 can be computed using the Bouguer slab formula:
𝛿𝑔 = 2𝜋𝐺ℎ∆𝜌 (3.9)
Equation (3.9) can be written as:
𝜕𝛿𝑔
𝜕ℎ= 2𝜋𝐺∆𝜌 (3.10)
68
In Chapter 4, equation (3.10) is used to compute apparent density contrast
from Bouguer-basement depth gradients.
In Chapter 6, equation (3.9) is modified as:
𝑔𝑓𝑎𝑎 = 2𝜋𝐺[ℎ𝑤(𝜌𝑤 − 𝜌𝑐) + 𝑡𝑒𝑠(𝜌𝑒 − 𝜌𝑐)] + 𝑐 (3.11)
where 𝑔𝑓𝑎𝑎 is free-air anomaly along the axis-parallel profiles, ℎ𝑤 is water depth, 𝑡𝑒𝑠
is total thickness of the evaporites and other sediments, 𝜌𝑤 and 𝜌𝑐 are water and
crustal densities, 𝜌𝑒 is the mean density of the evaporite and sediment layers, and 𝑐
is a constant along each ridge-parallel gravity profile.
The physical significance of 𝑐 is to derive 𝑡𝑒𝑠 along the gravity profile from
𝑔𝑓𝑎𝑎 , when other data (e.g., seismic reflection data) can provide 𝑡𝑒𝑠 at some measure
points as constraints.
A mean density of 2,148 kg m-3 is used for the evaporite and sediment layers
based on DSDP sample measurements of Wheildon et al. (1974). The crust was
assumed to have a density typical of oceanic crust dominated by gabbro. A density of
2,957 kg m-3 was used for the oceanic crust based on DSDP sample measurements of
Hyndman and Drury (1977). A 1,020 kg m-3 density was used for the seawater.
By rearranging equation (3.11), we obtain:
𝑡𝑒𝑠 =𝑔𝑓𝑎𝑎−𝑐
2𝜋𝐺(𝜌𝑒−𝜌𝑐)− ℎ𝑤
𝜌𝑤−𝜌𝑐
𝜌𝑒−𝜌𝑐 (3.12)
Hence, the basement depth is:
ℎ𝑏 = ℎ𝑤 + 𝑡𝑒𝑠 =𝑔𝑓𝑎𝑎−𝑐
2𝜋𝐺(𝜌𝑒−𝜌𝑐)+ ℎ𝑤
𝜌𝑒−𝜌𝑤
𝜌𝑒−𝜌𝑐 (3.13)
Although absolute basement depths cannot be calculated merely from gravity
anomalies using equation (3.13) because 𝑐 is unknown, the basement depths derived
from seismic data are used to determine c for each profile.
The basement depths computed from equation (3.13) are then used to
estimate basement roughness along ridge-parallel gravity profiles.
69
Basement relief derived using this technique will be underestimated, because
the assumption of an infinite slab is not fully met. Therefore, gravity forward
modelling is needed for assessing the bias magnitude.
3.3.5 2D gravity forward modelling
In Chapter 6, we have used 2D gravity forward modelling to assess the above-
mentioned bias magnitude, which can be used to correct the roughness values.
Forward models of free-air gravity anomalies were computed along profiles G1-32 by
summing the gravitational effects of elementary mass rectangular cells.
The vertical gravitational attraction of a small rectangular cell is (Shengye and
Yuling, 2004):
∆𝑔 = 𝐺𝜌[(𝑥 + 𝑎)𝑙𝑛(𝑥+𝑎)2+𝐻2
(𝑥+𝑎)2+ℎ2 − (𝑥 − 𝑎)𝑙𝑛(𝑥−𝑎)2+𝐻2
(𝑥−𝑎)2+ℎ2 + 2𝐻 (𝑡𝑔−1 𝑥+𝑎
𝐻− 𝑡𝑔−1 𝑥−𝑎
𝐻) −
2ℎ(𝑡𝑔−1 𝑥+𝑎
ℎ− 𝑡𝑔−1 𝑥−𝑎
ℎ)] (3.14)
where 2𝑎 is plate width, ℎ is depth to upper boundary, and 𝐻 is depth to lower
boundary.
Based on the principle of superposition, the vertical gravitational attraction of
a geological body can be reproduced by the sum of the attractions of many small
individual rectangular cells constituting the body (Blakely, 1996). To forward model
the gravity anomalies, the structure derived from the along-axis profiles were
subdivided into 𝑛 small cells and equation (3.13) was applied to compute the sum of
their gravitational attractions:
𝑔𝑘 = ∑(∆𝑔)𝑖
𝑛
𝑖=1
(3.15)
where 𝑔𝑘 is the vertical gravitational attraction measured at the 𝑘𝑡ℎ measurement
point, (∆𝑔)𝑖 is the vertical gravitational attraction produced for the 𝑘𝑡ℎ measurement
point by the 𝑖𝑡ℎ small rectangular cell, (∆𝑔)𝑖 is computed from equation (3.14).
MATLAB software was used to carry out the 2D gravity forward modelling,
based on equations (3.14) and (3.15).
70
The major uncertainty of the 2D gravity forward modelling originates from its
assumption of simple 2D models. The results derived from 2D analysis is less accurate
than those from the 3D analysis, since the observed gravity field are produced by 3D
objects. Moreover, the uncertainty in the gravity anomalies derived from the 2D
forward modelling can originate from the assumptions of flat Moho. Egloff et al. (1991)
suggested that Moho is not flat in the central Red Sea. Their seismic refraction profiles
shown the Moho varies in depth from 5 km to 10 km near the ridge axis.
We reproduced the seismic profile SO53-PIII of Egloff et al. (1991) using this
2D gravity forward modelling (Figure 4.9), although we did not perform this modelling
along the seismic lines from Izzeldin (1982, 1987).
3.4 Isostatic loading corrections
When assessing whether the geometry of crustal basement is typical of
oceanic crust, it is necessary to correct the observed basement depth for the effect of
loading by the overlying evaporites and sediment.
In Chapter 4, we have used a simple 1-D Airy isostatic model (Airy, 1855; Watts,
2001) in which the isostatic depression, ∆𝑧, is:
∆𝑧 =(𝜌𝑒𝑠−𝜌𝑤)
(𝜌𝑚−𝜌𝑤)𝑡𝑒𝑠 (3.16)
where 𝜌𝑒𝑠 is the mean density of the evaporite and sediment layers, 𝜌𝑚 and 𝜌𝑤 are
the densities of mantle and seawater, and 𝑡𝑒𝑠 is the total thickness of the evaporites
and other sediments.
A mean density of 2,148 kg m-3 is used for the evaporite and sediment layers
(Wheildon et al., 1974). A density of 3,220 kg m-3 was chosen for the hot mantle
(Crough, 1983; Gvirtzman et al., 2016). A 1,020 kg m-3 density was used for the
seawater.
Because the assumption of Airy isostasy ignores lithospheric rigidity, the deep
basement will be overcorrected and the shallow basement will be undercorrected,
compared with flexural isostasy (e.g., Watts, 2001). Thus, unloaded basement relief
71
will also be underestimated. For the relatively weak Red Sea, this difference should
be moderate.
3.5 Bathymetry data
3.5.1 Smith and Sandwell (1997) global topography dataset (Version 18.1)
Version 18.1 of the Smith and Sandwell (1997) bathymetry data (referred to as
“V18.1”) used in this study is shown in Figure 3.11. These data were derived by
combining shipboard depth measurements with depths inferred from satellite
altimetry of the sea surface.
In the region away from the coasts, the differences between the seabed
reflection and the bathymetry of V18.1 are less than 200 m (Figure 3.2). In the region
near to the coasts, these differences become larger than 800 m (Figure 3.2), indicating
a decrease in the accuracy of V18.1 data.
Figure 3.11 Bathymetry of the central Red Sea (Smith and Sandwell, 1997, version 18.1). Red
lines locate the seismic reflection profiles 7, 9, 11, 15, 17, 19, 21, 25, 27, 29, 31 from Izzeldin
(1982, 1987). The data are contoured every 500 m. The data were gridded and contoured
using the GMT software (Wessel et al., 2013).
72
In Chapters 4, 5, and 6, comparisons of the bathymetry sampled along the
seismic lines with depths derived from the seabed reflection are used to verify the
positions of the seismic profiles.
3.5.2 Multibeam sonar data
Augustin et al. (2014) interpreted multibeam sonar data from the central Red
Sea to reveal the pattern of evaporite flow.
These data only cover the region around the spreading centre.
In Chapter 6, we overlay their interpreted extents of evaporite and exposed
volcanic basement on the map of magnetic source depths to help assess how well the
more extensive flow corresponds with basement valleys and indirectly assess the
deconvolution results for geological consistency.
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78
Chapter 4.
Paper 1: Oceanic-like axial crustal high in the
central Red Sea
79
4. Paper 1: Oceanic-like axial crustal high in the central
Red Sea
Wen Shi1*, Neil C. Mitchell1, Lara M. Kalnins2, A.Y. Izzeldin3
1School of Earth and Environmental Sciences, The University of Manchester,
Manchester M13 9PL, UK.
2School of GeoSciences, The University of Edinburgh, The King’s Buildings, Edinburgh,
EH9 3FE, UK.
3Awasconrc, Gereif W, H4, Bld 376, Khartoum, POB 410, Khartoum, Sudan.
* Corresponding author.
E-mail address: [email protected] (Wen Shi)
This paper is published in the journal Tectonophysics.
Shi, W., N. C. Mitchell, L. M. Kalnins, and A. Y. Izzeldin, 2018, Oceanic-like axial crustal
high in the central Red Sea: Tectonophysics, v. 747-748, p. 327-342.
80
Abstract
The Red Sea is an important example of a rifted continental shield proceeding
to seafloor spreading. However, whether the crust in the central Red Sea is
continental or oceanic has been controversial. Contributing to this debate, we assess
the basement geometry using seismic reflection and potential field data. We find
that the basement topography from seismically derived structure corrected for
evaporite and other sediment loading has an axial high with a width of 70-100 km and
a height of 0.8-1.6 km. Basement axial highs are commonly found at mid-ocean ridges
affected by hotspots, where enhanced mantle melting results in thickened crust. We
therefore interpret this axial high as oceanic-like, potentially produced by recently
enhanced melting associated with the broader Afar mantle anomaly. We also find the
Bouguer gravity anomalies are strongly correlated with basement reflection depths.
The apparent density contrast necessary to explain the Bouguer anomaly varies from
220 kg m-3 to 580 kg m-3 with no trend with latitude. These values are too small to be
caused primarily by the density contrast between evaporites and mantle across a crust
of uniform thickness and density structure, further supporting a thickened crustal
origin for the axial high. Complicating interpretation, only a normal to modestly
thickened axial crust is predicted from fractionation-corrected sodium contents (Na8.0),
and the basement reflection is rugged, more typical of ultra-slow spreading ridges that
are not close to hotspots. We try to reconcile these observations with recent results
from seismic tomography, which show modest mantle S-wave velocity anomalies
under this part of the Red Sea.
Keywords: Red Sea, Ocean–continent transition, Oceanic crust, Seismic reflection,
Potential field, Subsalt
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4.1 Introduction
The Red Sea is a young ocean basin transitioning from continental extension
to seafloor spreading (e.g., Bonatti et al., 1981; Cochran and Martinez, 1988; Rihm and
Henke, 1998). However, how far the central Red Sea (Figure 4.1) is through this
transition to full seafloor spreading has been debated.
Figure 4.1 Bathymetry of the Red Sea (Smith and Sandwell, 1997, version 18.1). Red dots
locate the prominent deeps in the central Red Sea from Augustin et al. (2014) and Karbe
(1987). From north to south, these are (1) Nereus, (2) Thetis, (3) Hadarba, (4) Hatiba, (5)
Atlantis II, (6) Erba, (7) Port Sudan, (8) Suakin, and (9) Pelagia deeps. Green dot marks the
Farasan Islands. The relative plate motion vectors were predicted using the Chu and Gordon
(1998) plate rotation pole.
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Bonatti (1985) suggested the central Red Sea is just at the point of transitioning
from continental rifting to oceanic spreading. He proposed that the ‘deeps’ found in
the central Red Sea are discrete seafloor spreading cells based on the presence of
normal mid-ocean ridge basalt (MORB) sampled from them and their high amplitude
magnetic anomalies. This contrasts with low amplitude anomalies outside the deeps,
which were therefore assumed to overlie stretched continental crust (Ligi et al., 2011,
2012).
However, other evidence could support the interpretation of more established
seafloor spreading in the central Red Sea. An extensive aeromagnetic survey revealed
that there are low amplitude magnetic anomalies outside the ‘deeps’ aligned parallel
to the ridge axis (Izzeldin, 1987; Rasul et al., 2015). LaBrecque and Zitellini (1985)
showed with numerical modelling that such subdued anomalies could be produced by
widely distributed dykes, lava flows, and sills, as occur in modern-day Afar. Low
amplitudes may also have arisen from the slow spreading rate, the greater depth of
basement and alteration under the evaporites (Augustin et al., 2014; Dyment et al.,
2013; Izzeldin, 1987, 1989; Levi and Riddihough, 1986; Mitchell and Park, 2014). The
‘deeps’ are separated by inter-trough zones, which are shallower, lacking in strong
magnetic anomalies compared to the ‘deeps’, and covered by evaporites that have
flowed laterally and sediments across the axis. Based on seismic reflection, gravity
and magnetic data, Izzeldin (1982, 1987) suggested the inter-trough zones are
manifestations of less organized seafloor spreading and underlain by oceanic crust.
Using multibeam sonar data, Augustin et al. (2014, 2016) also interpreted these zones
as merely areas where the off-axis evaporites have flowed into the axis, obscuring the
volcanic geomorphology. Seismic refraction data show the velocity of basement
under the inter-trough zone between Nereus and Thetis deeps (Figure 4.1) is 6.86 km
s-1 (Davies and Tramontini, 1970; Tramontini and Davies, 1969), which overlaps with
velocities of oceanic crust elsewhere (6.7-6.9 km s-1; Carlson, 2001, 2010). Further
seismic refraction data collected by Egloff et al. (1991) along line PIII (Figure 4.2) also
suggested the basement around the ridge axis is oceanic, which transitions to
stretched continental crustal velocities towards the coast of Sudan. Finally, free-air
gravity anomalies derived from satellite altimeter data (Sandwell et al., 2014; Sandwell
83
and Smith, 2009) reveal that anomalies along the spreading centre are segmented
(Figure 4.2). Mitchell and Park (2014) and Augustin et al. (2016) suggested that this
segmented pattern is similar to the segmentation observed at slow-spreading mid-
ocean ridges elsewhere (e.g., the northern Mid-Atlantic Ridge) (Schouten et al., 1987;
Sempéré et al., 1990). The rugosity of basement computed from these anomalies is
similar to that of the similarly slow-spreading Mid-Atlantic Ridge (Shi et al., 2017).
Figure 4.2 Free-air gravity anomalies (Sandwell et al., 2014, version 23.1) and locations of
multichannel seismic reflection profiles 7, 9, 11, 15, 17, 19, 21, 25, 27, 29, 31 of Izzeldin (1987)
and seismic refraction profile SO53-PIII of Egloff et al. (1991). Purple curves show the
segmentation of gravity anomalies in the centre of the basin.
Based on seismic reflection and potential field data, Izzeldin (1982, 1987)
suggested that intermediate crust separates crust that is clearly continental near the
coasts from that which is clearly oceanic around the axis. This area lies ~65-160 km
from the ridge axis.
84
Young ocean basins such as the Red Sea offer opportunities to explore mantle
and crustal processes at the transition from rifting to seafloor spreading. In particular,
the rate and geometry of deformation may be important for how rapidly the rising
mantle cools during this phase. This in turn affects the flux of melt produced by mantle
decompression and where oceanic crust is first emplaced. Buck (1986) suggested that
lateral temperature gradients in the asthenosphere produced by rifting could lead to
more rapid upwelling, implying a greater initial melt flux. Alternatively, the surface
rifting and lithospheric mantle thinning could be laterally offset (Hopper and Roger
Buck, 1998), implying a different location of initial magma emplacement. Some of
these and other issues affecting the initial melting are illustrated in the recent
numerical geodynamic models of Harry and Bowling (1999), Corti et al. (2003),
Fletcher et al. (2009), Jeanniot et al. (2016), Ros et al. (2017), and Armitage et al.
(2018). However, the evidence needed to investigate these ideas from basins
presently transitioning to seafloor spreading is limited as examples are rare and often
complicated. For example, the Woodlark Basin is small, opening relatively fast (~60
mm yr-1) and in a complicated tectonic setting that is still evolving rapidly after the
Ontong Java collision with the West Melanesian Trench (Martinez et al., 1999; Weissel
et al., 1982). The Gulf of California rift is opening highly obliquely (e.g., Atwater and
Stock, 1998; Lonsdale, 1989; Withjack and Jamison, 1986). The Red Sea, in contrast,
is opening slowly (~10-~16 mm yr-1) and more nearly orthogonally (e.g., Chu and
Gordon, 1998), so it provides an important example of mantle and crustal dynamics
of slow orthogonal rifting.
In the present study, we use 11 lines of industrial seismic reflection data from
the central Red Sea reported in Izzeldin (1982, 1987). We verify interpreted basement
depths using Werner deconvolution applied to magnetic anomalies and then correct
those depths for isostatic loading by the evaporites and other sediments. The
basement geometry is found to reveal axial highs similar in gross morphology to,
though larger than, those of the Reykjanes Ridge, with more rapid deepening with
distance from the axis that cannot be explained by simple subsidence. This leads us
to favour an oceanic interpretation for the crust here, in which melt production has
recently increased, creating thicker crust which forms the axial high. We then discuss
85
what these results imply about the evolution of this section of the Red Sea rift and
broader implications.
4.2 Tectonic setting
4.2.1 Continental rifting and seafloor spreading in the northern and southern Red
Sea
The Red Sea opening rate increases southward from ~10 mm yr−1 at 25.5°N to
~16 mm yr−1 near 18°N with increasing distance from the Nubia/Africa spreading pole,
which lies in the Mediterranean (e.g., Chu and Gordon, 1998; DeMets et al., 1990;
DeMets et al., 2010). The extension of the Red Sea may have begun in the Eocene but
became more established in the Oligocene, associated with massive and rapidly
erupted basalts in Ethiopia and southern Yemen at approximately 30 Ma (Bosworth
and McClay, 2001; Hofmann et al., 1997; Mohr, 1983; Omar and Steckler, 1995).
These rapid eruptions have been attributed to the Afar plume penetrating the
lithosphere (Furman et al., 2006; George et al., 1998; Richards et al., 1989).
The northern Red Sea, which is closer to the pole of opening and has
experienced less extension than our study area (Figure 4.1), has been thought to be
underlain by continental crust with a series of large crustal fault blocks interpreted
from seismic velocity data and from magnetic and gravity anomalies (Cochran and
Karner, 2007; Gaulier et al., 1986; Martinez and Cochran, 1988). If correct, this area
may still be in late stage continental rifting (e.g., Cochran, 1983; Gaulier et al., 1988;
Martinez and Cochran, 1988). In contrast, others have interpreted this region as
underlain by oceanic crust on the basis of unpublished seismic and magnetic data (e.g.,
Dyment et al., 2013; Tapponnier et al., 2013). Using remote sensing, geochemical, and
geochronological data, Sultan et al. (1992) carried out a plate reconstruction for the
opening of the Red Sea and found a best match of pre-existing African and Arabian
geologic features by juxtaposing present Red Sea coastlines. This has been interpreted
as indicating that the entire Red Sea basin is underlain by oceanic crust (Bosworth et
al., 1993). In addition, a few ‘deeps’ containing basalts are revealed in the northern
Red Sea (e.g., Bonatti, 1985; Guennoc et al., 1988; Ligi et al., 2018; Pautot et al., 1984).
86
In the southern Red Sea, farther from the pole than our study area (Figure 4.1),
seafloor spreading magnetic anomalies are clearly identifiable up to Chron 3 near the
axial trough between 16°N and 19°N, suggesting that recognizable seafloor spreading
began at least by 5 Ma (e.g., Cochran, 1983; Girdler and Styles, 1974; Phillips, 1970;
Vine, 1966). Augustin et al. (2016) suggested that oceanic spreading likely began
somewhat earlier, 8-12 Ma, based on spreading rates of Chu and Gordon (1998) and
locations of volcanic ridges interpreted from multibeam sonar and vertical gravity
gradient data. These are consistent with the spreading ages (8–12 Ma) discussed by
Izzeldin (1987) and Augustin et al. (2014). In addition to the clear anomalies in the
centre of the basin, Girdler and Styles (1974) and Hall (1989) also interpreted the low
magnetic anomalies over the southern Red Sea shelves as seafloor spreading magnetic
stripes, suggesting the Red Sea was formed by two stages of seafloor spreading. Based
on magnetic and gravity modelling constrained by the seismic refraction data of
Gettings et al. (1986) and Mooney et al. (1985), Almalki et al. (2014) recently
suggested that about 75 km of oceanic crust formed before Middle to Late Miocene
(15–5 Ma) under the Farasan Bank (Figure 4.1), which supports a two-stage spreading
evolution of the Red Sea. In contrast, Cochran (1983) argued that these magnetic
anomalies result from a wide region of mafic diking and intrusions rather than a
continuous oceanic crust of dykes and extrusives, because the anomalies have low
amplitudes (less than 200 nT) and long wavelengths (20-50 km). A seismic refraction
line shot across the Yemen margin by Egloff et al. (1991) was interpreted as showing
that oceanic crust adjacent to the axis terminates southward of 16°N and that
continental-type crust lies farther south as far as 14˚N.
4.2.2 Seismic tomographic studies encompassing the Red Sea
Seismic tomographic studies have found that S- and P-wave seismic velocities
of the upper mantle adjacent to the Red Sea increase by up to a few percent from
south to north with increasing distance from the Afar plume. Using body wave travel
time tomography, Park et al. (2007) found a -1.5% S-wave velocity anomaly at 200 km
depth beneath the coast of the southern Red Sea, rising to ~-1% in the central Red Sea
and to 0% or more in the northern Red Sea. A similar structure was found by Park et
al. (2008) from Rayleigh wave tomography although with a more subdued northwards
87
increase in S-wave velocity. They suggested this structure is caused by an upwelling
of warm mantle beneath the southern Arabian shield, originating from the Afar
hotspot. They proposed that this hot plume material flows from Afar underneath the
southern and central Red Sea, and then extends northwards beneath Arabia, whereas
the northern Red Sea (north of ~23°N) is without underlying hot mantle. Shear wave
splitting directions from Hansen et al. (2006) indicate that the hot mantle flow moves
northwards rather than parallel to the Red Sea. This is supported by the azimuthal
anisotropy analysis of Sebai et al. (2006). The upper mantle under the Red Sea is
poorly resolved in such models as they are mainly based on teleseismic recordings
along the coast of Saudi Arabia (no offshore recordings). Nevertheless, this general
pattern of upper mantle structure is corroborated by Na8.0 analyses of axial lavas
(sodium oxide concentrations corrected for fractionation (Klein and Langmuir, 1987)),
which indicate the upper mantle temperature in the Red Sea generally decreases by
about 60°C from 18°N to 26°N (Haase et al., 2000).
More recently, Chang et al. (2011) have carried out an inversion of seismic
travel times and waveforms that provides a more complete coverage of the area
under the Red Sea. They found low velocity (hot) material is located beneath the
southern Red Sea and Gulf of Aden, consistent with active seafloor spreading. They
also suggested that the hot material at a depth of ~150 km does not extend north-
westwards below the central and northern Red Sea areas, but forms a channel
extending northward beneath Arabia. The comparative high velocities under the
central Red Sea coincide with our data and, as we show later, this could be important
for interpretation of our results.
4.3 Data and methods
4.3.1 Seismic reflection
The multi-channel seismic reflection survey was carried out by a geophysical
services company in 1976 (Izzeldin, 1982). The data were collected using a Vaporchoc
source with a streamer consisting of 48 channels 50 m apart for the deep-water survey
(2.4 km streamer), and of 24 channels 50 m apart for the shallow-water survey (1.2
km streamer), positioned using a local radio navigation system. The data were
88
processed (24-fold), with semblance analysis providing interval velocity every 3.6 km
along-track, and moveout corrected. The locations of seismic reflection profiles 7, 9,
11, 15, 17, 19, 21, 25, 27, 29, and 31 used in this study are shown in Figure 4.2.
Two-way travel times for the basement and seabed reflections were converted
to depths below sea level (Figure 4.4) as follows. A P-wave velocity (Vp) of 1.538 km s-
1 was used for the water according to the empirical equations of Mackenzie (1981),
with typical Red Sea salinity of 40 ppt and temperature of 21°C. A 1.9 km/s Vp for the
Plio-Pleistocene sediments was chosen based on the measurements of DSDP Leg 23
samples (Whitmarsh et al., 1974) and the results of seismic reflection and refraction
surveys by Egloff et al. (1991) and Gaulier et al. (1988). A Vp of 4.21 km/s was used for
the evaporites, based on seismic refraction data from Tramontini and Davies (1969),
Girdler and Whitmarsh (1974), and Egloff et al. (1991).
4.3.2 Magnetic anomalies
4.3.2.1 Sources of magnetic data
Marine magnetic field measurements from towed magnetometers were
obtained from the National Centers for Environmental Information (NCEI)
(www.ngdc.noaa.gov/mgg). The data comprise residual magnetic anomalies after
removal of the international geomagnetic reference field (IGRF) from the total field
measurements. Figures 4.3a and 4.3c show the survey locations and contoured
anomalies after further adjustments to correct IGRF errors of the individual surveys
(see figure caption).
Major causes of magnetic anomalies are expected to be susceptibility and
remanent magnetization variations within the basement produced by intrusive or
extrusive volcanic bodies. To investigate possible magnetic sources, Werner
deconvolution was applied to derive the magnetic source depths and apparent
susceptibilities, which were calculated along individual segments of the magnetic lines
(ungridded magnetic data) where they cross the seismic reflection profiles of Izzeldin
(1987) (Figure 4.3b), and then were projected to the seismic profiles.
89
Figure 4.3 (a): Tracks of shipboard magnetic surveys of RVs Jean Charcot (78005111,
83008011), Atlantis (A2093L19), Chain (CH043L01, CH043L03, CH061L02, CH100L03),
Discovery (DI103B), Glomar Challenger (DSDP23GC), Melville (INMD09MV), Robert Conrad
(RC0911A), Shackleton (SHA1079) and Vema (V1413). (b): Extents of magnetic lines (blue)
contributing to the seismic profiles (red) of Werner source depths. (c): Residual magnetic
anomalies of the surveys in (a) obtained from the National Centers for Environmental
Information (NCEI) (www.ngdc.noaa.gov/mgg) gridded and contoured every 50 nT. To reduce
effects of reference field errors, the residual anomalies of each survey were adjusted by
subtracting their mean value before gridding and contouring. (Anomalies are not reduced to
the pole.) (d): Bouguer gravity anomalies from Mitchell et al. (2017) computed by removing
the component of the free-air gravity field (Sandwell et al., 2014, version 23.1) due to the
seabed topography.
90
4.3.2.2 Werner deconvolution
Werner deconvolution is an inverse method that is used to solve for magnetic
source parameters (e.g., depth and susceptibility) from the observed magnetic field
assuming that the sources comprise thin sheet-like bodies of semi-infinite extent
(Werner, 1953). The total field from a thin sheet-like body is equal to the horizontal
gradient of the total field caused by the edge of a thick body. Werner deconvolution
exploits this idea to estimate likely parameters of dykes and other layered structures
(Ku and Sharp, 1983). Although individual depth values derived using the method
have large uncertainties and the method can produce some erroneous solutions, their
depths have been shown generally to cluster within basement (Cochran and Karner,
2007; Karner et al., 1991).
The total magnetic anomaly caused by a dike or other tabular body is given as
(Ku and Sharp, 1983):
(4.1)
where , , is
horizontal position of the top centre of the dike, is depth to the top of the dike,
is thickness of the dike ( ), is the vector sum of induced and
remanent magnetization, is magnetic inclination of the main field , and is
strike of the body measured counterclockwise from magnetic north.
Interference from neighbour anomalies or regional trends is incorporated in the form
of a polynomial (Ku and Sharp, 1983):
(4.2)
where are interference terms.
By rearranging equation (4.2), an inversion equation is obtained (Ku and
Sharp, 1983; Rao, 1984):
0
2 2
0
( )( ,0)=
( )mag
A x x BDT x
x x D
− +
− +
=-2 ( sin cos sin )x zA T J I J + =2 ( - cos sin sin )x zB T J I J + 0x
D
2 T T D =( , )x zJ JJs
I F
200 1 22 2
0
( )( ,0)=
( )mag
A x x BDT x C C x C x
x x D
− ++ + +
− +
2
0 1 2C C x C x+ +
91
(4.3)
where
and
A seven-point Werner operator was applied to construct seven simultaneous
equations for inversion equation (4.3), with a sample spacing of . Then, we obtain
the following results for the thin dike (Ku and Sharp, 1983):
Horizontal position:
(4.4a)
Depth:
(4.4b)
Magnetic susceptibility: (4.4c)
Marquardt’s (1963) non-linear least-squares best-fit method was used to solve
the simultaneous equations, producing the estimates of magnetic source depth and
susceptibility shown in Figure 4.4.
Magnetic source depths were estimated from the magnetic anomalies where
the sources lay less than 5 km from the seismic lines. If the magnetic bodies
recognized by Werner deconvolution are real, the depth estimates should define
either the upper boundaries of dykes or the edges of other causative bodies, so
magnetic source solutions tend to be tightly grouped vertically beneath the true
locations of the causative bodies (Cochran and Karner, 2007; Karner et al., 1991; Ku
2 3 4 2
0 1 2 3 4 0 1mag mag maga a x a x a x a x b T b xT x T+ + + + + + =
2 2
0 0 0 0 0
2 2
1 0 0 1 1 0
2 2
2 0 1 0 2 2 0
3 1 2 0
4 2
2 2
0 0
2 ,
2 ,
2 ,
,
,
a Ax BD C D x C
a A C x C D C x
a C C x C D C x
a C C x
a C
b x D
= − + + +
= − + +
= − + +
= −
=
= − −
1 02b x=
x
1X=0.5 b x x +
2
0 1= 0.25 Y b b x− −
2 2
=x z
m
J Jx
+
F
92
and Sharp, 1983). Therefore, the upper clusters of Werner solutions were interpreted
as the top of the magnetic basement.
4.3.3 Bathymetry data
We have used version 18.1 of the Smith and Sandwell (1997) bathymetry grid,
which combines shipboard depth measurements with depths inferred from satellite
altimetry of the sea surface. These data are shown in Figure 4.1. Comparisons of the
bathymetry sampled along the seismic lines with depths derived from the seabed
reflection were used to verify the positions of the seismic profiles.
4.3.4 Isostatic loading corrections
When assessing whether the geometry of crustal basement is typical of
oceanic crust, it is necessary to correct the observed basement depth for the effect of
loading by the overlying evaporites and sediment. We have used a simple 1-D Airy
isostatic model (Airy, 1855; Watts, 2001) in which the isostatic depression, ∆z, is:
(4.5)
where ρes is the mean density of the evaporite and sediment layers, ρm and ρw are the
densities of mantle and seawater, and tes is the total thickness of the evaporites and
other sediments. A mean density of 2,148 kg m-3 was used for the evaporite and
sediment layers based on DSDP sample measurements of Wheildon et al. (1974). A
density of 3,220 kg m-3 was chosen for the hot mantle (Crough, 1983; Gvirtzman et al.,
2016). A 1,020 kg m-3 density was used for the seawater. Reversing isostatic
depression, which was typically 1-2 km, produced the profiles shown in Figure 4.5a.
It was not possible to backstrip fully these sediments due to lack of detailed
stratigraphic data, but industry well data show the evaporites were deposited from
~15 Ma, at the start of the Middle Miocene (Hughes and Beydoun, 1992) to ~5.3 Ma,
at the end of the Miocene. This corresponds to times of active rifting, and continental
rifts are typically weak, with a low effective elastic thickness (Te) of 5-15 km (Watts
and Burov, 2003). Young, slow-spreading oceanic lithosphere is also typically weak,
with Te < 13 km and commonly Te < 5 km (Cochran, 1979; Kalnins, 2011). The
( )es wes
m w
z t
− =
−
93
assumption of Airy isostasy, ignoring lithospheric rigidity, will lead to overcorrected
deep basement and undercorrected shallow basement compared with flexural
isostasy (e.g., Watts, 2001); unloaded basement relief will thus also be
underestimated. For the relatively weak Red Sea, this difference should be moderate.
For a basin of comparable scale, Davison et al. (2012) estimated 0.5 km of isostatic
overcorrection of their deepest basement for a Te of 5 km.
To reveal the systematic trend of basement deepening with distance away
from the axis, both western and eastern sides of the unloaded basement depth
profiles were plotted together by offsetting each segment to their average axial depth
of 1.69 km (Figure 4.5d). To help assess whether the crust is oceanic, we compare the
observed subsidence with the global average oceanic crust subsidence curve (blue
solid line in Figure 4.5d) from Crosby and McKenzie (2009) using the Chron 2A to
present spreading rates of Chu and Gordon (1998). In doing so, we assume that Red
Sea opening prior to Chron 2A occurred with a similar opening pole and rate. Besides
some offsets of dated features along the Dead Sea transform fault (e.g., Barjous and
Mikbel, 1990; Garfunkel, 1981; Garfunkel et al., 1974) there are unfortunately no
independent measures of Nubia-Arabia motion to confirm this unequivocally.
However, other data from the Gulf of Aden at 14°N, 52°E show continuous spreading,
with opening rate decreasing from ~30 mm year-1 at 15-17.5 Ma to ~20 mm year-1 at
10 Ma and then remaining constant to the present (Fournier et al., 2010).
4.3.5 Bouguer gravity anomalies
Gravity anomalies arise from density variations within the crust and upper
mantle, as well as topography on the seabed, crust-evaporite, and Moho interfaces.
Mitchell et al. (2017) computed marine Bouguer anomalies of the central Red Sea to
remove the component of the gravity field due to the seabed topography.
We examine the correlation between the marine Bouguer anomalies and the
basement depths for evidence of variations in crustal thickness or density or in mantle
density. In regions of high correlation, we solve for the apparent density contrast (Δρ)
that best explains the observed gravity anomaly (Figure 4.7) to see if it is consistent
94
with the expected density contrast between the mantle and the evaporites, assuming
a constant thickness crust.
Apparent densities were derived from Bouguer-basement depth gradients
by inverting the equation derived from the gravity slab formula:
(4.6)
where is the universal constant of gravitation. The gradients were obtained
by least-squares regression for data within 60 km of the axis (regions of high
correlation). Using equation (4.6) ignores effects of upward continuation; we explore
these potential inaccuracies in section 4.4.3.
4.4 Results
4.4.1 Character of basement and seabed derived from seismic reflection profiles
In Figure 4.4, the seabed in all the seismic profiles forms an axial trough within
~20 km of the axis. The average depth of the axial trough shallows southwards from
~1.8 km in profile 7 to ~1.4 km in profile 29. The seismically derived seabed depths
are generally consistent with Smith and Sandwell (1997, version 18.1) bathymetry,
except in the axial trough of profile 9, where within 4 km of the axis, the seismically
derived depth is 0.5 km shallower. Below the seabed, the S-reflection marking the top
of the Miocene evaporites (Ross and Schlee, 1973) is found everywhere other than
over the axial trough. The Plio-Pleistocene (PP) sediments overlying the S-reflection
are thin (0.2-0.3 km thick) and tend to be uniform, as found in shallow seismic surveys
(e.g., Phillips and Ross, 1970; Ross and Schlee, 1973).
Bg
h
2BgG
h
− =
G Bg
h
95
Figure 4.4 Depths derived from the seismic reflection profiles of Izzeldin (1987) and Werner
deconvolution of marine magnetic data. Line numbers are shown in the lower right corner of
each panel. Magnetic anomalies (purple lines) along the seismic profiles were sampled from
the EMAG2 v3 grid (Meyer et al., 2017). Black lines denote bathymetry (Smith and Sandwell,
1997, version 18.1). Dark green, cyan, and red lines are the depths of the seabed, the S-
reflection at the top of the Miocene evaporites, and the basement, respectively, derived from
the seismic reflection data. Grey circles are Werner source depth solutions, with circle size
96
proportional to 𝑙𝑜𝑔2(𝜒𝑚 + 2). Depth estimates tend to cluster vertically beneath the true
location of the causative body, with magnetic basement being interpreted around the top of
the vertical clusters of solution depths. The Werner solutions generally confirm the
seismically derived basement depths.
The basement is considerably more rugged. The basement reflection is
discontinuous, probably because of faulting, and in places completely absent or un-
interpretable, a result of varied data quality. Basement outcrops directly on the
seafloor in the axial trough and deepens progressively towards the coasts from an
average depth of 1.69 km near the axis to ~6 km depth at a distance of ~60 km on both
sides of the axial trough. Further landward, this trend changes: the basement rises
steeply towards the coasts by up to 4 km in ~60 km distance, before becoming harder
to identify in the seismic data near the coasts. On the western flank of profile 15, the
reflection basement is not clear. Across the central Red Sea, the magnetic basement
tops derived from Werner deconvolution are generally consistent with the seismic
basement reflection depths. Additionally, only a minority of magnetic sources are
found by the deconvolution within the evaporites or PP sediments.
4.4.2 Oceanic-like axial crustal highs in isostatically corrected basement depths
After correcting for evaporite and sediment loading, the data reveal axial highs
in all profiles (Figure 4.5a and 4.5d). They have plateaux 70-100 km wide with adjacent
steep slopes deepening by 0.8-1.6 km over a distance of 30-40 km (Figure 4.5a).
Within the plateaux are axial troughs, where basement typically outcrops over 14 km,
forming a valley of varied size but on average 0.43 km deep (Figure 4.5d). Three
profiles marked in green in Figure 4.5d differ from the others; these lines lie furthest
to the north and furthest from the Afar plume. The other basement depth profiles
have a broadly similar morphology. The basement deepens between ~35 km from the
axis (at the axial plateau edge) and ~60-100 km, with the average profile reaching a
minimum at ~80 km. Beyond there, the basement commonly ascends towards the
coasts. Axial crustal highs are not found in active magmatic rifts, which instead contain
basement depressions (Corti et al., 2004; Mohr, 1982; Rosendahl, 1987; Thybo and
Nielsen, 2009). However, an axial high is commonly found at spreading ridges located
near mantle hotspots where excess melting generates thicker and more elevated axial
97
crust, such as the slow-spreading Reykjanes Ridge near the Iceland hotspot (Searle
and Laughton, 1981), the ultra-slow spreading Spiess Ridge near the Bouvet hotspot
(Mitchell and Livermore, 1998), and the intermediate rate Galápagos Spreading
Centre near the Galápagos hotspot (Blacic et al., 2008).
Based on the seismic profiles of Johansen et al. (1984), the Reykjanes Ridge
axial crustal high is ~40-60 km wide and rises 0.6-1.0 km above the surrounding
topography (Figure 4.5b). Although more pronounced than the Reykjanes Ridge, the
Red Sea axial basement high may imply that the central Red Sea has similarly
experienced increased melt supply and enhanced crustal thickness in the recent
geological past. As shown in Figure 4.5a and 4.5b, the relief of the Red Sea axial high
does not vary systematically with distance from the Afar region, in contrast with the
axial relief of the Reykjanes Ridge, which increases systematically towards Iceland
(Jones et al., 2002; Vogt, 1971; White et al., 1995). Moreover, with a short-wavelength
(<10 km) relief exceeding 150 m, the basement surface around the Red Sea axis is
rougher than that near the Reykjanes Ridge.
98
Figure 4.5 to be continued on next page.
99
Figure 4.5 (a): Basement depths along the Red Sea seismic lines (Figure 4.4) corrected for
evaporite and other sediment loading. (b): Basement depths around the Reykjanes Ridge from
Johansen et al. (1984), also corrected for sediment loading. (c): Locations of Reykjanes Ridge
profiles shown over the bathymetry of Smith and Sandwell (1997, version 18.1). (d): Red Sea
crustal deepening with distance from the ridge‐axis. All profiles are shown offset to their
average axial depth of 1.69 km (depth at zero distance). The solid blue line is the global normal
oceanic lithosphere subsidence curve from Crosby and McKenzie (2009). Green lines are
profiles 7 (both western and eastern flanks) and 9 (western flank) lying farthest from the Afar
plume. Global normal oceanic lithosphere subsidence (blue line) was predicted from the
Crosby and McKenzie (2009) rate with seafloor spreading rates from Chu and Gordon (1998).
Normal oceanic subsidence curves allowing for different subsidence rates were predicted
using the axial depths and the subsidence rates of Marty and Cazenave (1989). Red subsidence
curves have been offset to common 1.69 km axial depth while blue subsidence curve is shown
without offset.
4.4.3 Correlation between Bouguer gravity anomalies and basement reflection
depths
There is a strong correlation between the Bouguer anomalies and the
basement depths, although this correlation breaks down at distances greater than ~60
km from the ridge axis, where the basement shallows while the Bouguer anomaly
stays subdued (Figure 4.6). This strong correlation suggests that the density interface
between the evaporites and basement is a prominent contributor to the Bouguer
anomaly, although other density contributions (crustal thickness, and mantle and
crustal density) may also vary coherently with the deepening of basement. The
changes near the coasts suggest a reduction in the average density of the materials
100
within and beneath basement. This may reflect a change from oceanic crust around
the axis to continental or transitional crust near the coasts.
Figure 4.6 Graphs showing correlation between basement reflection depths (red) and
Bouguer gravity anomalies (blue) (Mitchell et al., 2017) derived by correcting free-air
anomalies for seabed relief using a halite density (2,160 kg m-3). Line numbers are shown in
lower right of each panel.
If the mantle density and crustal thickness are both assumed for the sake of
argument to be uniform, the correlation would be mainly due to the density contrast
between mantle rocks and evaporites acting on the topography of the basement (a
uniform crustal thickness would contribute a uniform amount to the gravity field,
aside from upward continuation effects). The derived apparent density contrasts in
Figure 4.7 vary from 220 to 580 kg m-3, with no obvious trend with latitude. These
contrasts are rather low compared with 1,070 kg m-3 if hot mantle rocks of 3,220 kg
m-3 density (Crough, 1983; Gvirtzman et al., 2016) were contrasting with evaporite
and other sediments of 2,148 kg m-3 (Wheildon et al., 1974). The difference between
101
the 1,070 kg m-3 expected value and the 220-580 kg m-3 apparent density contrasts
could arise from a combination of upward continuation effects, thickened crust, and
hotter mantle beneath the axis.
Figure 4.7 Apparent density contrasts deduced from Bouguer‐basement depth gradients.
The red and blue symbols represent western and eastern flanks, while black symbols represent
contrasts derived from data of both flanks combined. On the western flank of profile 7, the
basement reflection was too indistinct to calculate an apparent density contrast.
The apparent density contrasts were computed based on the gravity slab
formula, so it ignores contributions to the gravity field arising from topographic
changes on the basement and Moho interfaces away from the points of observations.
We carried out a simulation in which crust with a uniform thickness of 7 km and
uniform gabbroic density of 2,900 kg m-3 (Hyndman and Drury, 1977) overlies mantle
with a uniform density of 3,220 kg m-3 (Crough, 1983; Gvirtzman et al., 2016). Figure
4.8 shows two simulations using basement relief from profile 21 (Figure 4.2). To
quantify the effect of upward continuation, theoretical Bouguer gravity anomalies
(Figure 4.8c) computed from the models with and without the interface between
basement and mantle (Figures 4.8a and 4.8b) were used to derive graphs of Bouguer
gravity anomaly versus basement reflection depth and regression lines (Figure 4.8d)
whose gradients were used to calculate apparent density contrasts. Figure 4.8d shows
that if only the topography on the evaporite-basement interface were taken into
account, the apparent density contrast between evaporite and mantle would be 1,006
102
kg m-3. It also shows that if the topography on both evaporite-basement interface and
Moho were taken into account, the apparent density contrast would be reduced by
~97 kg m-3 to 909 kg m-3. We have also run the simulation with varying basement
depths, and found that upward continuation can reduce the apparent density
contrasts we infer using the gravity slab formula by up to ~160 kg m-3.
Figure 4.8 Simulation using basement depth profile 21 illustrating how apparent density
contrasts inferred using the gravity slab formula are reduced by upward continuation. (a):
Model with evaporites (2,148 kg m‐3), 7 km thick crust (2,900 kg m‐3) and mantle (3,220 kg m‐
3). (b): Model with evaporites directly overlying mantle. (c): Theoretical Bouguer gravity
anomalies computed using 2D gravity forward modelling for the two density models. (d):
Scatterplots with regression lines of Bouguer gravity anomaly versus basement reflection
depth. The slight difference in slope translates to a ~97 kg m‐3 difference in apparent density
contrast.
Alternatively, the axial topography could reflect thickened crust. If the
basement topography is uncompensated, with a near-flat Moho, the gravity anomaly
reflects the ~730 kg m-3 density contrast between evaporite and oceanic crust, much
closer to the values observed. This further supports the view that the axial high is at
least partly due to thickened crust. For a model with 7 km of crust beneath the axis
using Airy isostasy, so the topography on the Moho compensates for the basement
103
topography, our simulations suggest that an apparent density contrast of ~575 kg m-3
would be observed. However, this is an extreme model, as it ignores lateral variations
in mantle density due to temperature variations.
Addressing those mantle temperature variations, upper mantle velocities
varying from 7.4 to 7.8 km s-1 were reported for seismic refraction profile PIII of Egloff
et al. (1991), which is located in Figure 4.2. In Figure 4.9a, we show a density structure
derived from their velocities using density‐velocity relations of Christensen and Shaw
(1970). The model in Figure 4.9a is generally isostatically balanced, though there are
small imbalances at the oceanic-continental boundary and around Suakin Deep
(Figure 4.9c). The free-air anomalies predicted using 2D gravity forward modelling
successfully reproduce the observed free-air anomalies. It implies a lateral mantle
density variation of ~300 kg m-3 (Figure 4.9a). Using the basement topography and
Bouguer anomaly from 45 km to 85 km along profile PIII (outside the axial valley and
east of the ocean-continent transition), we derived an apparent density contrast of
880 kg m-3. The difference of 190 kg m-3 between 880 kg m-3 and 1,070 kg m-3 could
be due to mantle density variation and upward continuation, since the line shows no
variation in crustal thickness, but does imply a variation in mantle density. More
generally, we conclude that a combination of crustal thickness variations, upward
continuation, and mantle density variations can potentially explain the low apparent
density contrasts in Figure 4.7.
104
Figure 4.9 (a): Density structure (kg m‐3) along line PIII located in Figure 4.2 based on the
seismic refraction velocity (Vp) model of Egloff et al. (1991, their profile SO53‐PIII) and the
density‐velocity relations of Christensen and Shaw (1970). (“Pre‐evaporites” are pre‐evaporite
sedimentary rocks.) OCT: Oceanic–continental transition. (b): Free‐air gravity anomaly
calculated from (a) compared with observations from the Sandwell et al. (2014) gravity field
105
(version 23.1). (c): Total mass anomaly per unit area along PIII, computed by integrating
density over depth to the base of the model in (a).
4.5 Discussion
As mentioned above, the axial highs with basement deepening with distance
to 60 km from the spreading axis (Figure 4.5) are more like those of oceanic crust than
continental rifts, which typically host depressions (Corti et al., 2004; Mohr, 1982;
Rosendahl, 1987; Thybo and Nielsen, 2009). Prominent axial highs are common
features of oceanic spreading ridges near mantle hotspots (Blacic et al., 2008; Cochran
and Sempéré, 1997; Hooft and Detrick, 1995; Searle and Laughton, 1981). In the
central Red Sea, the boundary of the oceanic crust to transitional or continental crust
likely occurs where the correlations between basement reflection depths and Bouguer
gravity anomalies break down, coinciding roughly with the transitions identified by
Izzeldin (1987). This boundary also coincides with a transition at ~60 km from the axis
that was interpreted by Egloff et al. (1991) from their velocity data near Suakin Deep
(Figure 4.9). We here compare the axial high to those of other spreading centres,
examine its origin in more detail and explore implications.
4.5.1 How does the Red Sea axial high compare with axial highs at other spreading
centres near hotspots?
Axial highs are usually associated with “magmatically robust” spreading
centres, where the crust is unusually thick (e.g., Blacic et al., 2008). For Reykjanes
Ridge, it has been suggested that the axial high is due to thickened crust resulting from
enhanced mantle decompression melting near to the Iceland hotspot (White et al.,
1995). Using seismic reflection and refraction data, Smallwood and White (1998)
suggested that at ~62°N the Reykjanes Ridge crust thins from 10 km on the ridge axis
to 7.8 km on 5 Ma crust ~45 km from axis.
Figure 4.11 shows a compilation of bathymetry from other spreading centres
near hotspots. It includes an area south of the Azores, where a pair of ridges
surrounding the Mid-Atlantic Ridge (MAR) form a giant V-shape in plan-view, believed
to have resulted from a pulse of magmatism from the plume that has now ended,
106
leaving the previous high rifted (Cannat et al., 1999; Escartin et al., 2001). The
Reykjanes Ridge is surrounded by more than one V-shaped ridge, suggesting multiple
pulses of magmatism (e.g., Parnell‐Turner et al., 2017; Vogt, 1971). Ridges
surrounding the Galápagos Spreading Centre have been interpreted as arising from
magmatic pulses (Kappel and Ryan, 1986). Full spreading rates in these examples vary
from ~16 mm yr−1 to ~64 mm yr−1 (Chu and Gordon, 1998; DeMets et al., 1990; DeMets
et al., 2010).
The axial relief in the central Red Sea (0.8-1.6 km) is similar to that at Spiess
Ridge, more pronounced than those at Reykjanes Ridge and Galápagos Spreading
Centre, and lower than those at the Mid-Atlantic Ridge near the Azores. The crustal
thickness beneath the Spiess Ridge was estimated to be ~11-15 km (Mitchell and
Livermore, 1998), while the Galápagos Spreading Centre axis near the Galápagos
hotspot has a crustal thickness of only ~5.6-7.5 km (Canales et al., 2002).
Unlike the Reykjanes Ridge near Iceland and the Mid-Atlantic Ridge near the
Azores, the central Red Sea axial high is not obviously surrounded by V-shaped ridges
in either the gravity field (Figure 4.2) or from the seismic data (Figure 4.5a), suggesting
that the influence of Afar hotspot on the opening of central Red Sea is not that strong.
Whether this implies a lack of fluctuations in melt supply from the plume is unclear,
as any such effect might be complicated by the fracture zones apparent from the
cross-axis trends in the gravity field (Figure 4.2). Possible V-shaped ridges appear in
the free-air gravity anomalies at 17˚-18˚N, closer to the Afar plume (Mitchell and Park,
2014).
107
Figure 4.10 (a): Sodium oxide contents of axial lavas from Haase et al. (2000) (solid circles)
and Ligi et al. (2012) (plus symbols) corrected for fractionation to 8 wt% MgO. Diamond
symbols indicate the average Na8.0 values expected at the axial locations of the eleven seismic
reflection profiles based on the dashed regression line shown. (b): Seismically determined
estimates of crustal thickness versus average Na8.0 from Klein and Langmuir (1987). The Na8.0
values at the seismic lines (orange shading) suggest that the axial crustal thickness of the
central Red Sea is ~5-10 km (orange dashed lines).
4.5.2 How thick is crust beneath the axial high and how does it relate to mantle
tomographic results?
In the central Red Sea, there is only one seismic refraction dataset capable of
revealing crustal thickness (Egloff et al., 1991), and it did not reveal thickened crust
under the spreading axis (Figure 4.9a). Alternative estimates of crustal thickness are
available from geochemistry of the axial lavas. Sodium oxide concentrations in mid-
ocean ridge basalt samples corrected for magma-chamber fractionation to 8% MgO
(Na8.0) have been interpreted by Klein and Langmuir (1987) as a measure of the depth-
extent of mantle melting and shown to correlate with the thickness of oceanic crust
derived from seismic refraction experiments. The Na8.0 values from the Red Sea
108
shown in Figure 4.10a (Haase et al., 2000; Ligi et al., 2012) increase systematically
northwards implying decreasing crustal thickness, as expected from decreasing
extents of melting and decreasing mantle temperature away from the Afar plume. We
use the regression trend in Figure 4.10a to estimate the average Na8.0 at the points
where the seismic reflection lines cross the spreading axis. From the range of Na8.0
and a regression of the Klein and Langmuir (1987) Na8.0 data on crustal thickness, the
central Red Sea axial crust thickness is estimated to be ~5-10 km. This is similar to the
mean of 7.1±0.8 km for normal oceanic crust (White et al., 1992), so the geochemical
data do not indicate particularly thick crust. Furthermore, the basement is noticeably
more rugged than the Reykjanes Ridge (Figure 4.5). This may be explained by a
combination of (1) the slower spreading rate in the Red Sea, which leads to stronger,
colder lithosphere closer to the ridge and larger abyssal hills (e.g., Malinverno, 1991;
Sauter et al., 2011; Whittaker et al., 2008) and (2) potentially thinner crust in the Red
Sea, which shows some correlation with greater roughness in slow to ultraslow
spreading systems (Sauter et al., 2018).
To reconcile these observations, we speculate that the earliest seafloor
spreading in the central Red Sea began with lower melt fluxes and thinner than
average crust. Melt production then increased, increasing the crustal thickness to near
average and creating the axial high. Based on current spreading rates of Chu and
Gordon (1998) and the basement depths of Figure 4.5d, we suggest the axial high has
developed since ~9 Ma. In Figure 4.5d, the basement is most elevated relative to the
subsidence curve from 10 to 35 km off-axis, and returns to it by ~60 km. The rate of
deepening from 10 to 35 km is too fast to be caused by normal thermal subsidence. If
we interpret these variations in basement topography as solely due to thickened crust,
the crust would be thickest 10 to 35 km from the axis and would thin to ~60 km, while
the increasing elevation with distance within 10 km of the axis is most likely due to
dynamic effects within the active rift (e.g., Buck et al., 2005; Schmalholz and
Mancktelow, 2016; Tapponnier and Francheteau, 1978). This view of near normal
crustal thickness is compatible with the recent mantle seismic velocity model of Chang
et al. (2011), who showed low S-wave velocities associated with hotter mantle from
the Afar plume extending beneath Arabia rather than beneath the central Red Sea (S-
109
wave velocity beneath the southern Red Sea and Arabia is ~0.25 km s-1 lower than that
beneath the central Red Sea). This extent of hot plume material could also explain
why the influence of Afar hotspot on the opening of central Red Sea is not that strong
(although the increased melt production could have been affected by the Afar) and
there is no relation to the distance from the Afar in the apparent density contrast
(Figure 4.7).
In the Afar region, there have been pulses of volcanism (Audin et al., 2004;
Barberi et al., 1975), so the variations in basement gradient in Figure 4.5d may have
arisen from temporal changes in composition or temperature of the upwelling mantle.
Others have remarked on the possibility of pulsating mantle plumes leaving V-shaped
ridges south of Iceland and similar V-shaped ridges have been found elsewhere (e.g.,
Parnell‐Turner et al., 2017; Vogt, 1971). However, no V-shaped ridges are observed
in the central Red Sea; the crustal thickness variations appear to be consistent along
the ridge.
Alternatively, a low initial melt supply may be a result of the mechanics of
rifting mentioned in the introduction, if early melting was suppressed at the slow
rifting rates due to conductive cooling or locally infertile mantle (Bonath, 1990; Zhou
and Dick, 2013). Such a low melt supply would not be expected if there were
enhanced mantle circulation at this stage as proposed by Buck (1986). We note that
seaward thickening of oceanic crust is not always observed in seismic refraction
datasets from other rifted margins (Peron-Pinvidic et al., 2013). However, seismic
reflection and refraction data do show the crust thickens seaward at the oceanic–
continental transition (OCT) on the Angolan margin (Contrucci et al., 2004; Moulin et
al., 2005), indicating the South Atlantic Ocean basin there may have experienced an
increase of melt production during early seafloor spreading as we suggest for the
central Red Sea.
110
Figure 4.11 Examples of locally elevated topography at ridges located near mantle hotspots.
Panels (a), (c), (e) and (g) locate profiles at the Reykjanes Ridge near the Iceland hotspot, the
Spiess Ridge near the Bouvet hotspot, the northern Mid-Atlantic Ridge near Azores hotspot,
111
and the Galápagos Spreading Centre near Galápagos hotspot, respectively. Panels (b), (d), (f),
and (h) show the profiles located in (a), (c), (e) and (g), respectively. Bathymetry data from
Smith and Sandwell (1997, version 18.1).
4.5.3 What are its implications?
If the axial high in the central Red Sea represents an increasingly thick crust
but approaching only normal crustal thickness, the earlier spreading centre would
have been deeper. The earlier evaporites may have therefore been deposited
continuously across the ridge and not only on the flanks (as might otherwise have
been the case in the south). This would in turn imply that volcanic eruption occurred
beneath or through the evaporites. Magma can heat adjacent evaporite and cause it
to flow (Schofield et al., 2014). Augustin et al. (2016) proposed that the salt craters
with raised rims found in the inter-trough zones were likely created by such eruptions,
marking locations where volcanism continued after the area was covered by
evaporites. Also, such eruptions ought to have geochemical consequences. For
example, the evaporites affected could be rich in KCl and CaCl2 but poor in MgSO4 due
to hydrothermal alteration of host basalts (e.g., Jackson et al., 2000), and sulfur
isotope compositions of marine sulphates should be negatively shifted (e.g., Mills et
al., 2017). Thus, if suitable samples could be recovered, the geochemistry of the
evaporites could help to confirm the existence of a ridge buried by evaporites and map
out its transition to exposed ridge.
4.6 Conclusions
To understand what type of crust underlies the central Red Sea, we carefully
corrected for effects of overlying evaporite and other sediments to reconstruct
basement geometry from 11 deep seismic reflection lines. The seismically derived
basement depths corrected for evaporite and other sediment loading reveal an axial
high typical of mid-ocean ridges affected by hotspots such as Reykjanes Ridge, where
enhanced mantle melting results in thickened crust. In contrast, basement axial highs
are not commonly observed at active amagmatic continental rifts. Its relief of ~1 km
relative to a background subsidence trend is within the observed range. It is similar
to that at Spiess Ridge, larger than that at Reykjanes Ridge, but smaller than that of
112
the Mid-Atlantic Ridge near the Azores. We suggest the central Red Sea is underlain
by oceanic crust and the central part of the Red Sea rift is an (ultra) slow spreading
ridge influenced by the Afar hotspot, although our data do not reveal V-shaped ridges
in this part of the Red Sea like those associated with plume pulses on the Reykjanes
Ridge near Iceland or the Mid-Atlantic Ridge near the Azores.
Bouguer gravity anomalies calculated by correcting for the seabed topography
are strongly correlated with basement reflection depths with ~60 km of the axis. The
apparent density contrast implied by the correlation (220 to 580 kg m-3) is too small
for a uniform thickness crust overlying a mantle of uniform density, which would lead
to mantle rocks contrasting with evaporites and a 1,070 kg m-3 apparent density
contrast. Around 160 kg m-3 of this difference could be caused by an upward
continuation effect (our method ignores topography of interfaces). We suggest that
the remaining discrepancy is caused by lower density mantle and/or thicker crust
towards the spreading axis, although variations in crustal density may also contribute.
Geochemical data (Na8.0) suggest that the crust has normal thickness beneath
the present axis, while the rugged basement topography is consistent with a slow to
ultra-slow spreading ridge with cold, rigid lithosphere and thin crust. To reconcile the
axial high and gravity inversion results, which suggest thickening crust towards the
present day, with these other observations, we speculate that the crust was unusually
thin earlier in the evolution of the basin and has recently thickened to a more normal
thickness for a slow-spreading ridge.
4.7 Acknowledgments
We thank David Sandwell and Walter Smith for leading the gravity and
bathymetry mapping initiatives, and for the group involved in producing the grids used
in our study. Figures were prepared using the GMT software (Wessel et al., 2013).
LMK is supported by a Royal Society of Edinburgh Personal Research Fellowship
funded by the Scottish Government. We also thank Nico Augustin and an anonymous
reviewer for helpful comments that significantly improved the article.
113
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Chapter 5.
Paper 2: Central Red Sea basement depths
from Werner deconvolution of aeromagnetic
data
128
5. Paper 2: Central Red Sea basement depths from
Werner deconvolution of aeromagnetic data
Wen Shi1*, Neil C. Mitchell1, Lara M. Kalnins2, Ian C.F. Stewart3, A.Y. Izzeldin4
1School of Earth and Environmental Sciences, The University of Manchester,
Manchester M13 9PL, UK.
2School of GeoSciences, The University of Edinburgh, The King’s Buildings, Edinburgh,
EH9 3FE, UK.
3Stewart Geophysical Consultants Pty. Ltd., Adelaide, South Australia.
4Awasconrc, Gereif W, H4, Bld 376, Khartoum, POB 410, Khartoum, Sudan.
* Corresponding author.
E-mail address: [email protected] (Wen Shi)
This paper is ready for submission to the journal Marine Geophysical Researches.
129
Abstract
The Red Sea is an important example of a rifting continent transitioning to
oceanic basin. The geometry of its basement is central to questions concerning the
nature of the crust (whether it is oceanic or highly stretched continental crust) and to
whether the relief of the basement affects the flow of evaporites, questions that may
also apply to some more ancient rifted margins. To reconstruct basement geometry,
Werner deconvolution was used to invert a grid of aeromagnetic anomalies (with
survey lines spaced 2-10 km apart) for magnetic source depths. At any location, the
deconvolution typically yields many solutions over a wide range of depths, though
usually clustered below the depth of magnetic basement. Comparing magnetic source
depths with basement depths interpreted from eleven seismic reflection profiles, we
computed cumulative density functions (CDFs) of differences between them (ΔZ). For
the near-axis data, where we know the basement is igneous, we recorded the CDF
level corresponding with ΔZ=0 and then mapped out the depth corresponding with
that CDF level elsewhere throughout the central Red Sea. The derived magnetic
basement along the ridge axis tends to deepen by ~0.25 km from 18.5°N to 23°N,
consistent with declining influence of the Afar plume. Magnetic basement depth near
the spreading axis generally co-varies with Bouguer gravity anomalies, as expected
from the latter reflecting a strong density contrast between basement and the
overlying evaporites and other sediments. Valleys in the derived depths mostly
coincide with fracture zones interpreted previously from gravity, magnetic,
bathymetric and seismic reflection data. Those valleys also correspond with areas
where the evaporites have extended into the axial valley floor, as suggested by earlier
researchers. Nearer to the coasts, the resolved magnetic basement depth is shallower
than seismic basement, possibly because of magnetized minerals in the sedimentary
section. This suggests a second utility of the method in mapping out sedimentary
sources where seismic data are available but lithological information is poor. Overall,
our work illustrates the potential utility of magnetic source depth determination in
areas with few seismic data but where the basement has a strong magnetization
contrast with overlying sediments.
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Keywords: Central Red Sea, Magnetic basement depth, Werner deconvolution,
Cumulative density function
5.1 Introduction
Depth of basement from magnetic anomalies can be useful in regions where
basement is not well resolved in seismic reflection or refraction data, or where seismic
data are sparse. This is the case in the Red Sea, where the geometry of the basement
is an important constraint on the type of crust (whether it is oceanic or continental),
which is important for models of the continental rift to spreading transition, a key
stage of Wilson's (1966) cycle. In the central Red Sea, which some have argued is
currently undergoing a transition to seafloor spreading (Bonatti et al., 1981; Ligi et al.,
2011, 2012), seismic reflection and refraction data able to image basement
continuously along lines and thus resolve basement geometry are sparse (Egloff et al.,
1991; Izzeldin, 1982, 1987, 1989), and otherwise only refraction data from single
hydrophones are available (Drake and Girdler, 1964; Tramontini and Davies, 1969).
The crust of the central Red Sea has also been interpreted as mainly oceanic (Izzeldin,
1987; Mitchell and Park, 2014; Shi et al., 2018). The morphology of the seabed
comprises a series of closed-contour deeps (Figure 5.1) separated by shallower areas
underlain by evaporites (Inter-Trough Zones or ITSs; Bonatti, 1985). The ITZs have
been suggested to arise from flowage of the evaporites on the flanks of the ridge
underlying the central Red Sea along fracture zones (Augustin et al., 2014, 2016;
Mitchell et al., 2017), where the basement is depressed and the evaporites likely
warmer, thus the geometry of basement is important for understanding the flowage
also. Although basement depths derived from magnetic anomalies are not usually as
reliable as those from seismic datasets, their calculation is nevertheless potentially
useful given the importance of the region and lack of publicly available seismic data.
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Figure 5.1 Bathymetry of the Red Sea (Smith and Sandwell, 1997, version 18.1). Red dots
locate the prominent deeps in the central Red Sea (from Augustin et al. (2014) and Karbe
(1987)). From north to south, these are (1) Nereus, (2) Thetis, (3) Hadarba, (4) Hatiba, (5)
Atlantis II, (6) Erba, (7) Port Sudan, (8) Suakin, and (9) Pelagia deeps. Yellow dot marks the
city of Jeddah. Purple dot marks the Tokar Delta. Green dot marks the Farasan Islands.
Relative plate motion vectors (blue) were predicted using the Chu and Gordon (1998) plate
rotation pole.
In regions where seismic coverage is sufficiently extensive to allow basement
structure to be mapped out continuously, magnetic methods can also be useful to
determine if magnetic sources exist within the sediments. For example, in the Red
Sea, we would not expect much induced or remanent magnetism to originate from
the evaporites if they were wholly formed by seawater evaporation. On the other
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hand, the presence of some magnetic sources within them could suggest the presence
of terrigenous sediments containing magnetic minerals and that may have
implications for the supply of sediment derived by erosion of the adjacent land.
Terrigenous sediments within impermeable evaporite bodies may also suggest
potential petroleum reserves if suitable organic sources and thermal histories are
present.
Werner deconvolution of magnetic data has been used to investigate
basement geometry and geological structure for decades (e.g., Ku and Sharp, 1983;
Martelet et al., 2013; Stagg et al., 1989; Thakur et al., 2000; Tsokas and Hansen, 1995).
In the present study, we invert 64 lines of aeromagnetic anomalies for magnetic
source depths in the central Red Sea using Werner deconvolution. To obtain more
reliable magnetic basement depths, seismic reflection data are used as constraints.
We overlay the fracture zones interpreted previously from gravity, magnetic,
bathymetric and seismic reflection data on the map of magnetic basement depths to
assess how well these fracture zones coincide with basement valleys. We use a
correlation between basement depth and Bouguer anomalies found previously (Shi et
al., 2018), along with geological consistency, to test of the method results. We also
overlay the extents of evaporite and exposed volcanic basement suggested by earlier
researchers on the derived depth map to help assess how well the more extensive
flows correspond with those valleys. We then discuss the potential utility of magnetic
source depth determination in the central Red Sea.
5.2 Geological setting
The Red Sea has formed by the extension of the Afro-Arabian shield, creating
the separate Arabian and Nubian plates (e.g., Ghebreab, 1998; McKenzie et al., 1970).
The extension may have begun in the Eocene and developed substantially in the
Oligocene at ~30 Ma (Bosworth and McClay, 2001; Hofmann et al., 1997; Mohr, 1983;
Omar and Steckler, 1995). The 3.2-Ma-to-present Red Sea opening rate increases
southward from ~10 mm yr−1 at 25.5°N to ~16 mm yr−1 near 18°N with increasing
distance from the Nubia/ Arabia pole located in the Mediterranean (e.g., Chu and
Gordon, 1998; DeMets et al., 1990). Southward of 18°N, the Red Sea is affected by
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the Afar plume, revealed in 3He/4He ratios and both major and trace elements of axial
lava samples (Altherr et al., 1988; Moreira et al., 1996; Volker et al., 1997). Haase et
al. (2000) provided geochemical data of axial lavas (Na8.0, sodium oxide concentrations
corrected for fractionation (Klein and Langmuir, 1987)) suggesting that the upper
mantle temperature in the Red Sea generally decreases by about 60°C from 18°N to
26°N. (The source pressure of melting also declines (Haase et al., 2000), implying that
the temperature change at a given depth may not be so large.) Chang et al. (2011)
suggested that the hot plume material from Afar at a depth of ~150 km does not
extend north-westwards below the central and northern Red Sea areas, but forms a
channel extending northward beneath Arabia.
The transition from continental extension to seafloor spreading is a key stage
in Wilson's (1966) cycle, but there are few young ocean basins where this transition
can be observed. The Woodlark Basin is small and opening quickly (~60 mm yr-1;
Martinez et al., 1999; Weissel et al., 1982) and the Gulf of California rift is opening
highly obliquely (Atwater and Stock, 1998; Lonsdale, 1989; Withjack and Jamison,
1986) with a spreading rate of ~45–47 mm yr-1 (Plattner et al., 2007). The Red Sea is
the only example of a young transitioning rift opening slowly (~10-~16 mm yr-1) and
nearly orthogonally (e.g., Chu and Gordon, 1998), so it is an important example of
transitioning from nearly orthogonal slow continental rifting to seafloor spreading.
Unfortunately, the Miocene evaporites covering much of the Red Sea, which
reach up to 4 km in places (Shi et al., 2018), make imaging of the basement with
seismic methods difficult and magnetic anomalies are affected by the greater depth
of basement, which is depressed isostatically by the evaporites, and by potential
alteration of magnetic minerals by hydrothermal circulation under them (Augustin et
al., 2014; Izzeldin, 1987; Mitchell and Park, 2014). In the northern Red Sea, low seismic
velocities (Gaulier et al., 1986) and other data have been interpreted as indicating the
presence of continental crust (Cochran, 1983), although this has recently been
disputed (Dyment et al., 2013). In the southern Red Sea, a continuous axial zone with
extensive volcanism and linear magnetic anomalies identifiable up to Chron 3 (5 Ma,
Figure 5.2) indicate that spreading has been oceanic since at least 5 Ma (Augustin et
al., 2014; Phillips, 1970; Roeser, 1975; Vine, 1966). Although not attributable to
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individual chrons, parallel magnetic anomalies closer to the coasts may also indicate
oceanic crust, as they are symmetrical about the axis and not correlated with
basement geometry (Hall, 1989).
Figure 5.2 Seafloor spreading magnetic anomalies in the southern Red Sea (Phillips, 1970).
The bottom curve represents synthetic magnetic anomalies generated by the seafloor
spreading model beneath it using a spreading rate of 10 mm yr-1. The black blocks indicate
normal magnetization, whereas open blocks represent reversed magnetization.
In the central Red Sea (19°N to 23°N; Figure 5.1), the structure of the axial zone
is more complicated, consisting of a series of ‘deeps’ separated by inter-trough zones.
Normal mid-ocean ridge basalt (MORB) and high amplitude magnetic anomalies have
been found in these deeps (e.g., Bonatti, 1985; Pautot et al., 1984). There is still
debate concerning whether the deeps are discrete seafloor spreading cells, separated
by stretched continental lithosphere (Bonatti, 1985; Cochran, 1983; Ligi et al., 2011,
2012) or exposed parts of a continuous oceanic spreading axis, which is partly covered
by evaporites and other sediments (e.g., Augustin et al., 2014, 2016; Davies and
Tramontini, 1970; Dyment et al., 2013; Egloff et al., 1991; Izzeldin, 1982, 1987, 1989;
LaBrecque and Zitellini, 1985; Mitchell and Park, 2014; Searle and Ross, 1975; Shi et
al., 2018; Tramontini and Davies, 1969). Here, we favour the second interpretation,
135
as axial crustal highs typical of a spreading ridge are found in the entire central Red
Sea, based on seismic reflection data and Bouguer anomalies (Izzeldin, 1987; Shi et al.,
2018).
5.3 Data and methods
5.3.1 Multichannel seismic reflection
Multichannel seismic reflection data were collected by a geophysical services
company in 1976 as described by Izzeldin (1982). The deep-water survey used a 2.4
km, 48 channel streamer (50 m spacing), whilst a 1.2 km, 24 channel streamer (50 m
spacing) was used in shallow water. The data were moveout-corrected by others as
described by Izzeldin (1982, 1987). The locations of profiles 7, 9, 11, 15, 17, 19, 21, 25,
27, 29, and 31 used in this study are shown in Figures 5.3a and 5.3c.
Depths of basement were derived from these data as described by Shi et al.
(2018). Two-way travel times for the basement and seabed reflections were
converted to depths below sea level using P-wave velocities (Vp) of 1.538 km s-1
(Mackenzie, 1981), 1.9 km s-1 (Egloff et al., 1991; Gaulier et al., 1988; Whitmarsh et al.,
1974), and 4.21 km s-1 (Egloff et al., 1991; Girdler and Whitmarsh, 1974; Tramontini
and Davies, 1969) for water, Plio-Pleistocene sediments, and evaporites , respectively.
5.3.2 Magnetic anomalies
5.3.2.1 Sources of magnetic data
The aeromagnetic survey was also carried out in 1976 by the Arabian
Geophysical and Surveying Company (ARGAS) as described by Izzeldin (1982, 1987).
As shown in Figure 5.3a, this survey covered the central Red Sea between 18.5°N and
23°N with flight lines oriented N60°E. Sixty-four survey lines were run from coast to
coast and spaced 10 km apart. 464 shorter lines were added over the axial zone and
some coastal zones for detailed investigation with the lines spaced 2.5 km apart. The
total length of the main survey lines is 23,011 km, whereas that of the additional lines
is 28,210 km. The survey was flown at 305 m above sea level. Measurements of total
136
magnetic field were obtained using a caesium vapour magnetometer with a resolution
of 0.01 nT and sample frequency of 1Hz.
Figure 5.3 (a): Locations of aeromagnetic survey flight lines (blue) and multichannel seismic
reflection profiles 7, 9, 11, 15, 17, 19, 21, 25, 27, 29, 31 of Izzeldin (1987) (red). Black line
locates the spreading axis. (b): Residual aeromagnetic anomalies from data collected by
Arabian Geophysical and Surveying Company (ARGAS) in 1976. The data have been gridded
with a horizontal resolution of 1 arc-minute and contoured every 75 nT. In order to reduce
effects of remaining reference field errors, the residual aeromagnetic anomalies of each
survey line were adjusted by subtracting its mean anomaly value before gridding and
contouring. (c): Locations of the survey lines used for the Werner deconvolution (blue). (d):
Residual aeromagnetic anomalies along the long survey lines plotted as profiles.
137
Magnetic anomalies were corrected for Earth's main field variations. Diurnal
variations were corrected using data from a magnetometer stationed in Jeddah
(Figure 5.1) and the results verified by analysis of data at crossing flight lines. Minor
line levelling errors in the data were minimised. Figure 5.3b shows the contoured
anomalies after further adjustments made here to correct minor remaining data
offsets of the individual lines (see figure caption). The length of survey line affects the
number of magnetic sources found by Werner deconvolution (a longer length of data
is needed to resolve deeper magnetic bodies) so we used the longer lines for our
analysis (Figure 5.3c). Consequently, there are fewer deep sources revealed towards
the ends of each line.
5.3.2.2 Werner deconvolution
Werner deconvolution has been widely used to estimate depths and
susceptibilities of magnetic sources (e.g. Karner et al., 1991; Ku and Sharp, 1983;
Thakur et al., 2000). The method is valid for sources comprising thin sheet-like bodies
of semi-infinite extent (alternatively, bodies with a large ratio of length to thickness)
and the edges of thick bodies (Ku and Sharp, 1983). Although individual depth values
derived using the method have large uncertainties and the method can produce some
erroneous solutions due to non-uniqueness and calculation window sizes poorly
matching those needed for the solutions, their depths generally cluster within
basement (Cochran and Karner, 2007; Karner et al., 1991).
Following Werner (1953) and Ku and Sharp (1983), the total magnetic anomaly
due to a dike or other tabular body can be written as:
(5.1)
where is distance along a profile, and are functions of orientation and
magnetization of the dike, is horizontal position of the point immediately above the
dike, and is depth to the top of the dike.
0
2 2
0
( )( ,0)=
( )
A x x BDTmag x
x x D
− +
− +
x A B
0x
D
138
The interferences from neighbouring anomalies, regional trends, and
measured magnetic noise are addressed by the addition of an interference polynomial
( ) to the right side of equation (5.1) (Ku and Sharp, 1983; Werner, 1953):
(5.2)
where is the order of the interference polynomial, and are the
coefficients.
In practice, a polynomial of order two is adequate for obtaining stable and
reliable solutions (Hartman et al., 1971; Ku and Sharp, 1983; Werner, 1953):
(5.3)
Equation (5.3) can be expressed as:
(5.4)
where
and
Marquardt’s (1963) inverse modelling method was used to solve the
simultaneous equations constructed from equation (5.4) by a seven-point Werner
operator (Ku and Sharp, 1983). If the sample spacing is , we have the following
results for the thin dike (Ku and Sharp, 1983):
Horizontal position:
(5.5a)
P
2
0 1 2
n
nP C C x C x C x= + + + +
n 0 1 2, , , nC C C C
200 1 22 2
0
( )( ,0)=
( )
A x x BDTmag x C C x C x
x x D
− ++ + +
− +
2 3 4 2
0 1 2 3 4 0 1a a x a x a x a x b Tmag b xTmag x Tmag+ + + + + + =
2 2
0 0 0 0 0
2 2
1 0 0 1 1 0
2 2
2 0 1 0 2 2 0
3 1 2 0
4 2
2 2
0 0
,
2 ,
2 ,
2 ,
,
,
a Ax BD C D x C
a A C x C D C x
a C C x C D C x
a C C x
a C
b x D
= − + + +
= − + +
= − + +
= −
=
= − −
1 02b x=
x
1X=0.5 b x x +
139
Depth:
(5.5b)
Magnetic susceptibility: (5.5c)
where
(5.6a)
and
(5.6b)
where is the vector sum of the induced and remanent magnetization,
is thickness of the dike ( ), is magnetic inclination of the main field ,
and is the strike of the tabular body measured counterclockwise from magnetic
north.
Werner deconvolution was performed along the profiles using a moving
window with a minimum/maximum size of 0.5/60 km in 0.5 km increments and shifted
every 1 km. This returned a number of stable clusters of Werner solutions (Figure 5.4).
2
0 1= 0.25 Y b b x− −
2 2
=x z
m
J Jx
+
F
2 2
cos sin sin
2 (cos sin ) (sin )x
B A IJ
T I
− −=
+
2 2
cos sin sin
2 (cos sin ) (sin )z
A B IJ
T I
− +=
+
=( , )x zJ JJs
2 T T D I F
140
Figure 5.4 Depths derived from the seismic reflection profiles of Izzeldin (1987) and Werner
deconvolution of the aeromagnetic data. Line numbers are shown in the top left corner of
each panel. Black lines denote bathymetry (Smith and Sandwell, 1997, version 18.1). Dark
green, cyan, and red lines are the depths of the seabed, the S-reflection at the top of the
Miocene evaporites, and the basement, respectively, derived from the seismic reflection data.
Grey circles are Werner source depth solutions, with circle size proportional to 𝑙𝑜𝑔2(𝜒𝑚 + 2),
where 𝜒𝑚 is apparent susceptibility. Blue lines are the basement depths derived from
magnetic sources using the CDF level of 93.16% (corresponding with ΔZ =0 for the axial data
(Figure 5.5a)).
141
5.3.2.3 Statistical analysis of the Werner solutions
Although the Werner method produced stable clusters of solutions, the results
are nevertheless noisy and not centred on the top of basement. To obtain more
reliable magnetic basement depths, the seismic reflection data were used as
constraints. Differences between the individual Werner source depths and the
seismically derived basement depths (ΔZ) (i.e., Werner source depth minus seismically
derived basement depth) were computed and cumulative histograms (cumulative
density functions, CDFs) derived from those differences as shown in Figure 5.5. CDFs
of ΔZ were derived from the data around the spreading axis (distance from the
spreading axis ≤ 60 km) and close to the coasts (distance from the axis > 60 km)
separately (Figure 5.5a and 5.5b). Since the primary magnetic source around the
spreading centre is expected to lie within the shallow basement from the
magnetizations of extrusive basalts and sheeted dykes (Tivey and Dyment, 2010; Tivey
and Johnson, 1987), we first recorded the CDF level corresponding with ΔZ=0 (i.e.,
magnetic sources lying at the top of seismic basement) for the axial data (Figure 5.5a).
We then used this CDF level to estimate depth to basement throughout the central
Red Sea, assuming that the whole region consists of similarly magnetized basement,
with none of the magnetic field originating in the overlying sediments. CDFs were
computed from magnetic sources within rectangular cells 20 km × 10 km along the
survey lines. Figures 5.4, 5.6 and 5.7 show those magnetic basement depths.
142
Figure 5.5 Histograms and cumulative density functions (CDF) of differences between the
Werner source depths and the seismically derived basement depths (ΔZ) (i.e., Werner source
depth minus seismically derived basement depth). Left axes correspond with the histograms.
(a) and (b) are, respectively, calculated from the data over the areas around the axial trough
(distance from the ridge axis ≤ 60 km) and near the coasts (distance from the ridge axis > 60
km).
5.3.3 Bouguer gravity anomalies
Mitchell et al. (2017) produced a map of marine Bouguer gravity anomalies of
the central Red Sea, removing the seabed effect from free-air gravity anomalies
(Figure 5.8a). Short-wavelength variations in the Bouguer anomalies are affected by
topography of the basement underlying the evaporites, due to the strong density
contrast across the basement surface. Consequently, Bouguer anomalies and
basement depths are strongly correlated within 60 km of the axis (Shi et al., 2018).
Essentially, Bouguer anomalies can be used as a proxy for basement depths. We
143
therefore examined the covariation between Bouguer anomalies and magnetic
basement depths as an independent, albeit indirect, test of the magnetically derived
depths. Figure 5.8b shows the magnetic depths in colour shaded using the Bouguer
gravity anomalies of Mitchell et al. (2017), to help the reader locate features between
the two datasets. We also used the correlation between the two data types to invert
for a single apparent basement density using the slab formula.
5.3.4 Bathymetry data
Augustin et al. (2014) interpreted multibeam sonar data from the central Red
Sea to reveal the pattern of evaporite flowage. We overlaid their interpreted extents
of evaporite and exposed volcanic basement on the map of magnetic source depths
to help assess how well the more extensive flow corresponds with basement valleys
and indirectly assess the deconvolution results for geological consistency.
5.4 Results
5.4.1 Basement depth derived from aeromagnetic data
In Figure 5.4, magnetic source solutions produced by Werner deconvolution
occur over a wide range of depths. Some of those solutions are clearly erroneous, for
example, the solutions that lie in water. After carrying out the statistical analysis of
the solutions (section 5.3.2.3), the derived magnetic basement depths shown in Figure
5.4 show some local discrepancies. At the axis, the magnetic basement tends to be
deeper than the seismic basement by up to 2 km (Figure 5.4). At ~60 km off-axis, the
magnetic basement is commonly shallower than seismic basement by up to a few km
in places. Near the coasts, the magnetic basement depth is shallower than seismic
derived basement, representing the effects of magnetized minerals in the
sedimentary section. Nevertheless, ignoring the local differences and the
discrepancies nearer to the coasts, the derived magnetic basement depths seem to
reveal the main geomorphological features of the basement.
In Figure 5.6, the basement has an axial plateau ~120 km wide with adjacent
steep slopes deepening by 0.8-2.5 km over a distance of ~40 km. The axial plateau
shallows southward from ~1.8 km near 23°N to ~1.2 km near 18.5°N. It is
144
discontinuous, with three main valleys located around 20.2°N, 22°N, and 23°N. Due
to the low resolution of the magnetic basement grid, axial troughs revealed in the
seismic reflection data in Figure 5.4 are not shown within the axial plateau in Figure
5.6. On both sides of the axial plateau, the trend of basement deepening toward the
coasts changes at a distance of ~60 km from the ridge axis. The apparent basement
rises steeply landward from there to the coasts by up to 3 km, partly due to the
sedimentary sources mentioned earlier and partly due to a genuine rise in basement
(Shi et al., 2018). The shallow region next to the western coast is ~10 km wider than
that next to the eastern coast. Moreover, the basement along the ridge axis tends to
deepen by ~0.25 km from 18.5°N to 23°N (Figure 5.7).
Figure 5.6 Basement topography map derived from the aeromagnetic data Werner source
solutions. The map shows the elevation within each cell (with a size of 20 km × 10 km) at
which the CDF of magnetic source elevations within that cell equals 93.16% (Figure 5.5a).
Dashed cyan line locates the spreading axis. (The statistical method used here is described
and justified in section 3.2.4 and 5.3.2.3)
145
Figure 5.7 Magnetic basement depths along the spreading axis. Red dashed line is a least-
squares regression through the data. Magnetic basement tends to deepen by ~0.25 km from
18.5°N to 23°N.
5.4.2 Correlation between Bouguer gravity anomalies and magnetic basement
elevations
The Bouguer anomalies from Mitchell et al. (2017) are partly correlated with
the magnetic basement elevations (Figure 5.8). As there is a strong correlation
between Bouguer gravity anomalies (Mitchell et al., 2017) and basement seismic
reflection depths around the spreading axis (Shi et al., 2018), this indirectly suggests
that the magnetic basement elevations are reasonable. Both Bouguer anomalies and
the magnetic basement are elevated around the spreading centre (i.e., in the area
within ~ 60 km of the axis) and depressed in the region flanking the axial zone.
The apparent density contrast computed from the Bouguer-basement depth
correlation line (white dashed line in Figure 5.9a) based on the slab formula is 427 kg
m-3. This is a strong density contrast compared with values of 220-580 kg m-3 deduced
from similar gradients using seismic reflection depth by Shi et al. (2018). If a mean
density of 2,148 kg m-3 is used for the evaporite and sediment layers (Wheildon et al.,
1974), the apparent basement density is 2,575 kg m-3.
146
Figure 5.8 (a): Bouguer gravity anomalies from Mitchell et al. (2017) computed by removing
the component of the free-air gravity field (Sandwell et al., 2014, version 23.1) due to the
seabed topography. The data are contoured every 50 mGal. Black lines mark fracture zones
interpreted here from the gravity data. (b): Map of aeromagnetic-derived basement depths
(Figure 5.6) with shading from the Bouguer gravity grid of (a) with a light direction of N30°W
to highlight the fracture zones.
In Figure 5.9a, the diversity of magnetic source depths increases where the
Bouguer anomalies are small, particularly those below 30 mGal. These occur outside
the axial zone (Figure 5.8a). Although they could be erroneous, we speculate that this
could be caused by magnetic bodies (e.g., basaltic sills) in the evaporite and sediment
layers. Alternatively, they may be caused by crustal density or thickness variations, so
that, for example, basement of depths shallower than the regression line in Figure 5.
9a may overlie lower density or thicker crust.
Basement depths were predicted from the Bouguer gravity anomalies of
Mitchell et al. (2017) (Figure 5.8a) using the regression in Figure 5.9a. Figure 5.9b
shows the aeromagnetic-derived basement depths minus those predicted depths in
order to study the origins of deviations from the correlation in Figure 5.9a. Those
differences can be as large as 0.8 km and occur in coherent patches of a few cells
across outside the axial zone. They do not obviously relate to the fracture zones
147
(Figure 5.8a) suggesting that these large differences likely do not arise from varied
crustal thickness or density structure affecting the Bouguer anomalies.
Figure 5.9 (a): Correlation between Bouguer gravity anomalies from Mitchell et al. (2017)
(Figure 5.8a) and aeromagnetic-derived basement depths (in Figure 5.6) within 60 km of the
axis. Contours represent the number of points falling within each 0.02 km by 2 mGal block
148
(contour interval 150 counts). White dashed line is regression of the data. (b): Differences
between basement depths from Figure 5.6 and those predicted from Bouguer gravity
anomalies from Figure 5.8a using the regression in (a).
In areas that lie ~70–160 km from the ridge axis, the correlation between
Bouguer gravity anomalies and magnetic basement depths breaks down. The Bouguer
gravity anomaly stays subdued while the estimated magnetic basement shallows. We
suggest that this likely arises from magnetic minerals supplied from erosion of the
adjacent land areas. For example, magnetic basement is shallow offshore the Tokar
Delta, where the Plio-Pleistocene sediments in exploration wells reach 2 km in
thickness (Hughes and Beydoun, 1992). The westerly 10 km of seismic refraction
profile PIII of Egloff et al. (1991) closest to the delta revealed a 3-km thick lower
velocity body interpreted as terrigenous sediment. Arabian-African shield rocks on
the adjacent land contain ophiolites and, on the Arabian side, are overlain by volcanic
rocks (Stern and Johnson, 2010). Shallow magnetic basement around other parts of
the coasts therefore likely also represent the effects of terrigenous sediments
containing minerals with greater remanent and induced magnetization.
5.4.3 Number of magnetic source solutions
The derived number of magnetic source solutions should ideally reflect the
number of thin sheet-like bodies and edges of thick bodies, e.g., basaltic dykes and
edges between oceanic crust and continental or transitional crust. In Figure 5.10, the
number of source solutions per kilometre ranges from 9 to 15 near the spreading
centre and at a distance of ~60 km from the axis on both sides of the axial zone. In
other regions, the numbers are lower: 5 counts km-1 is common. The along-rift
continuity of high numbers around the axis and mid-way between axis and the coasts
ceases at ~21°N. This may be due to the fracture zone. Additionally, the numbers of
source solutions near the western coast are ~2 counts km-1 higher than numbers near
the eastern coast.
149
Figure 5.10 The numbers of magnetic sources revealed by the Werner deconvolution
normalized by the cumulative length of survey lines in each cell (cells as Figure 5.6).
5.5 Discussion
Shi et al. (2018) found an axial crustal high after correcting the seismically
derived basement depths for evaporite and other sediment isostatic loading, and
interpreted it as suggesting the central Red Sea is underlain by oceanic crust typical of
a mid-ocean ridge near to a mantle hotspot, like the Reykjanes Ridge. In this study,
we confirm that the basement topography in the region away from the seismic lines
also has an axial plateau within ~60 km of the axis. Shi et al. (2018) have discussed
how this axial high could have formed.
Along the ridge axis, the magnetic basement tends to be elevated from 23°N
to 18.5°N by ~0.25 km. Moreover, the plateau shallows on average southward from
~1.8 km around 23°N to ~1.2 km around 18.5°N (Figure 5.7). These variations are
consistent with declining influence of the Afar plume to the north.
150
5.5.1 How well do the magnetic basement topography and source solution numbers
correspond with other data?
Figure 5.11a shows the fracture zones interpreted from the Bouguer gravity
anomalies of Mitchell et al. (2017) and from magnetic, bathymetric, and seismic
reflection data by Izzeldin (1982, 1989) superimposed on the map of magnetic
basement topography. Fracture zones are usually characterised by valleys and
escarpments due to faulting and by thinner crust (e.g., Menard and Atwater, 1969;
Searle, 2013). In Figure 5.11a, although some discrepancies occur at 18.8°N and
20.5°N, the valleys found in the derived magnetic depths coincide with fracture zones
near the axis around 20.2°N, 22°N, and 23°N.
Figure 5.11 to be continued on next page.
151
Figure 5.11 (a): Map of the basement topography of Figure 5.6 overlain with fracture zones
interpreted by Izzeldin (1982) (blue and white lines from magnetic and bathymetric data,
respectively). Black lines locate the fracture zones identified here from the gravity data in
Figure 5.8a. Cyan line locates the spreading axis. Black box locates the area of (b). (b): Map
locating the interpreted extent of evaporite and other sedimentary cover of Augustin et al.
(2014) overlain on the magnetic basement depths. White lines mark the boundary of
multibeam bathymetry survey area. Heavy black lines indicate the front of evaporite flows.
The prominent deeps in this region are labeled.
Evaporites including halite were widely deposited during the Miocene in the
Red Sea (Girdler and Whitmarsh, 1974; Stoffers and Kühn, 1974). Because of the weak
rheology of halite, the evaporites tend to flow downslope toward the axial valleys, due
152
to subsidence and as their lateral constraints are lost (Feldens and Mitchell, 2015;
Mitchell et al., 2017). From multibeam sonar data, Augustin et al. (2014) interpreted
the extents of evaporite and exposed volcanic basement. Figure 5.11b shows those
extents overlain on the map of magnetic basement depths. It shows that the
evaporites have extended into the axial valleys around 21.7°N and 23°N, where the
derived magnetic basement depth has cross-axis valleys with depths of ~1.2 km and
~1 km, respectively. Those two valleys (fracture zones) also correspond with the
inter-trough zones separating the deeps. This is consistent with the basement in the
inter-trough zones being deeper than that in the deeps and with the inter-trough
zones being merely areas where evaporites blanket the axial valley and obscure the
volcanic geomorphology (Augustin et al., 2014, 2016). The volcanic basement is
generally exposed where it is elevated. There is nevertheless some disagreement
between these data, e.g., the evaporite flow around 20.5°N does not correspond with
an axial valley, although there are valleys nearby.
Figure 5.12 to be continued on next page.
153
Figure 5.12 The number of Werner sources from Figure 5.10 overlain with (a) the fracture
zones from Figure 5.11a and (b) the distribution of evaporites from Figure 5.11b.
We interpret the high numbers of magnetic source solutions near the axis
(Figures 5.10 and 5.12) as due to the dikes and lava flows, while those mid-way
between axis and the coasts are due to the edges between oceanic crust and
continental or transitional crust. The higher count in the axial zone could also be due
to the shallower and more exposed crust, hence a stronger signal than the other
regions. Seafloor spreading ridges are often offset by transform faults and fracture
zones (e.g., Schouten et al., 1985; Searle, 2013). In Figure 5.12a, the ends of short
axial zone segments generally coincide with the fracture zones interpreted previously
154
from other data. In Figure 5.12b, the presence of underlying cross-axis valleys
suggested by the evaporite flows at 20.5°N, 21.7°N, and 23°N coincide with low
numbers of magnetic sources. This may be because the Werner deconvolution
method missed some magnetic causative bodies in depressions, since high frequency
magnetic anomalies tend to be suppressed due to upward continuation effects.
5.5.2 The potential utility of magnetic source depth determination in the Red Sea
Although containing some noise of up to a few km in depth, as the Werner
deconvolution here reveals the main basement features seen in seismic, Bouguer
gravity, and bathymetry data, we suggest the derived magnetic basement has a
reasonable morphology about the axis.
Due to non-uniqueness effects and poorly matching of calculation window
sizes, some erroneous solutions are produced during the calculation.
There are many other magnetic interpretation techniques based on source
depth determination that could be used in the central Red Sea, e.g., Euler
deconvolution (Thompson, 1982), source parameter imaging method (Thurston and
Smith, 1997), and analytical signal method (MacLeod et al., 1993). Compared to
traditional magnetic forward and inverse modelling methods, those methods are
quick and have strong anti-noise properties, as they can well isolate the magnetic
anomaly from the noise.
5.6 Conclusions
To assess the basement geometry in the central Red Sea, we have inverted
aeromagnetic anomalies for source depths using Werner deconvolution. After
applying a statistical method to resolve the depths most likely to correspond with
seismic basement, the method effectively maps out the major topographic features
of the crustal basement near the axis.
The results confirm that the basement topography in the region has an axial
plateau within ~60 km of the axis, suggesting the entire axial zone including inter-
155
trough-zones in the central Red Sea is underlain by oceanic crust. The basement axial
plateau shallows southward, consistent with increasing influence of the Afar plume.
Magnetic basement elevation near the spreading axis generally co-varies with
Bouguer gravity anomalies. Their correlation implies a strong apparent density
contrast of 427 kg m-3 between basement and the overlying evaporites. The axial
valleys revealed in the basement coincide with fracture zones previously interpreted
from Bouguer gravity data of Mitchell et al. (2017) and from magnetic, bathymetry,
and seismic reflection data by Izzeldin (1982). Those valleys also correspond with
areas where the evaporites have invaded the axial valley, likely along fracture zones
(Augustin et al., 2014). Nearer to the coasts, the resolved magnetic basement is
shallower than seismic basement. We suggest this is due to the effects of magnetized
minerals in the sedimentary section. Additionally, we suggest the high numbers of
magnetic source solution near the axis are due to dikes and shallow and exposed crust,
whereas those located at a distance of ~60 km from the axis are due to the contact
between oceanic crust and continental or transitional crust. Overall, the exercise
illustrates the potential feasibility and applicability of magnetic source depth
determination in the central Red Sea and elsewhere where magnetized basement is
overlain by sediments lacking magnetization.
5.7 Acknowledgments
We thank the Arabian Geophysical and Surveying Company for the
aeromagnetic survey. We thank David Sandwell and Walter Smith for leading the
gravity and bathymetry mapping initiatives, and for the group involved in producing
the grids used in our study. Figures were prepared using GMT software (Wessel et al.,
2013). LMK was supported by a Royal Society of Edinburgh Personal Research
Fellowship funded by the Scottish Government. A Royal Society (International
Exchanges Scheme) grant to NCM enabled discussions with colleagues Nico Augustin
and Froukje van der Zwan that contributed to our conclusions.
156
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163
Chapter 6.
Paper 3: Oceanic basement roughness in the
central Red Sea
164
6. Paper 3: Oceanic basement roughness in the central
Red Sea
Wen Shi1*, Neil C. Mitchell1, Lara M. Kalnins2, Ian C.F. Stewart3, A.Y. Izzeldin4
1School of Earth and Environmental Sciences, The University of Manchester,
Manchester M13 9PL, UK.
2School of GeoSciences, The University of Edinburgh, The King’s Buildings, Edinburgh,
EH9 3FE, UK.
3Stewart Geophysical Consultants Pty. Ltd., Adelaide, South Australia.
4Awasconrc, Gereif W, H4, Bld 376, Khartoum, POB 410, Khartoum, Sudan.
* Corresponding author.
E-mail address: [email protected] (Wen Shi)
This paper is in preparation to be submitted to the journal Marine Geophysical
Researches.
165
Abstract
The Red Sea is a rare example of a continental rift proceeding to an oceanic
basin, but the nature of the crust underlying it (whether oceanic or highly extended
continental) has been controversial. We continue our investigation of crustal type
here by assessing the basement roughness (the root-mean-square variation of
basement relief) along profiles across and parallel to the spreading axis in the central
Red Sea. If the crust were oceanic, the across-axis roughness would be typical of
abyssal hill topography formed by faulting and volcanism, whereas the axis-parallel
roughness would mimic typical variations due to the ridge segmentation including
fracture zones. We estimated roughness values from depths of basement interpreted
from across-ridge seismic reflection profiles. The mean across-ridge roughness value
of 230 m is consistent with those observed over ultraslow and slow spreading ridges.
Basement roughness values along ridge-parallel profiles were computed from the
free-air gravity field using densities appropriate for oceanic crust and a modified
Bouguer slab formula, since suitable ridge-parallel seismic profiles are not available.
The derived roughness values around the axial trough are comparable with those of
slow spreading ridges such as the Mid-Atlantic Ridge. Systematic bias in the measured
roughness arising from the slab approximation was assessed using forward 2D
modelling and found to be ~30%. Correcting for this bias still leaves roughness values
within the range of values for oceanic crust. The axis-parallel roughness values change
mid-way between the coast and the rift axis, where a transition in crustal type from
stretched continental to predominantly oceanic has been suggested previously based
on the seismic reflection data. Although the basement roughness values by
themselves do not rule out extremely extended continental crust, combined with
other evidence they support an oceanic crustal interpretation.
Keywords: Central Red Sea, Basement roughness, Oceanic crust, Seismic reflection,
Potential field
166
6.1 Introduction
The Red Sea is currently transitioning from continental rifting to seafloor
spreading (Cochran and Martinez, 1988; Rihm and Henke, 1998). Identifiable ocean
floor magnetic anomalies suggest that seafloor spreading has been occurring in the
southern Red Sea since at least 5 Ma (Cochran, 1983; Girdler and Styles, 1974; Phillips,
1970; Vine, 1966). However, whether the crust in the central Red Sea (Figure 6.1) is
continental or oceanic has been debated (Bonatti, 1985; Ligi et al., 2012; Mitchell and
Park, 2014; Shi et al., 2018). Shi et al. (2018) found an oceanic-like axial crustal high
in the central Red Sea after correcting seismically derived basement depths for
isostatic loading by evaporites and other sediments. They suggested that the axis of
the central Red Sea rift is an ultra-slow spreading mid-ocean ridge affected by the Afar
hotspot, somewhat like the Reykjanes Ridge, an axial high affected by the Iceland
hotspot. If so, the entire central Red Sea is likely underlain by oceanic crust.
Basement roughness is defined as the root-mean-square deviation of residual
basement relief along a profile after removal of its systematic trend (Malinverno,
1991). The roughness can provide observational constraints on the nature of changes
in crustal thickness and tectonics (Ma and Cochran, 1997). Basement roughness has
been used in investigations of crustal structure, spreading rate, faulting models, and
ridge morphology at mid-ocean ridges (e.g., Bird and Pockalny, 1994; Malinverno and
Gilbert, 1989; Minshull, 1999; Sauter et al., 2018; Small, 1994). Sauter et al. (2011)
and Sauter et al. (2018) suggested that spreading rate, mantle temperature, and
lithosphere composition could affect the lithospheric strength and thus the basement
roughness.
In this study, we computed basement roughness values in the central Red Sea
along lines both parallel to the axis and across it in order to assess if those basement
roughness values compatible with those of other mid-ocean ridges. We then reassess
the other evidence supporting the oceanic crustal interpretation.
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Figure 6.1 Bathymetry of the Red Sea (Smith and Sandwell, 1997, version 18.1). Red dots
locate prominent deeps in the central Red Sea from Augustin et al. (2014) and Karbe (1987).
From north to south, these are (1) Nereus, (2) Thetis, (3) Hadarba, (4) Hatiba, (5) Atlantis II, (6)
Erba, (7) Port Sudan, (8) Suakin, and (9) Pelagia deeps. The relative plate motion vectors were
predicted based on the poles of Chu and Gordon (1998).
6.2 Tectonic setting
The Red Sea is a young ocean basin formed by the Arabian plate being split
from Nubian plate (Ghebreab, 1998; McKenzie et al., 1970). It is one of the few places
on Earth where a geologically recent or active transition from continental extension
to seafloor spreading can be observed (Cochran and Martinez, 1988; Rihm and Henke,
1998). The extension of the Red Sea may have first started in the Eocene and
developed substantially in the Oligocene at ~30 Ma (Bosworth and McClay, 2001;
168
Hofmann et al., 1997; Mohr, 1983; Omar and Steckler, 1995). The 0-3 Ma Red Sea
spreading rate increases southward from ~10 mm yr−1 at 25.5°N to ~16 mm yr−1 near
18°N (Chu and Gordon, 1998; DeMets et al., 1990; DeMets et al., 2010; Reilinger et al.,
2015).
The southern Red Sea (south of 19°N; Figure 6.1) has a well-developed
continuous axial zone typical of seafloor spreading, with volcanic geomorphology in
multibeam data, large amplitude magnetic anomalies and basaltic lavas recovered in
dredges as evidence of extensive volcanism (Augustin et al., 2014; Haase et al., 2000;
Phillips, 1970; Roeser, 1975). Ocean floor magnetic anomalies there are clearly
identifiable up to Chron 3, suggesting that full seafloor spreading started at least by 5
Ma (Cochran, 1983; Girdler and Styles, 1974; Phillips, 1970; Roeser, 1975; Vine, 1966).
Based on spreading rates of Chu and Gordon (1998) and locations of volcanic ridges,
Augustin et al. (2014, 2016) suggested that seafloor spreading began at 8–12 Ma, with
the oceanic crust created older than 5 Ma buried under the thick Miocene evaporites
(Girdler, 1984; Girdler and Whitmarsh, 1974).
A series of depressions described as ‘deeps’ occur in the central Red Sea
(between 19°N and 23°N; Figure 6.1) (Bonatti, 1985; Pautot et al., 1984). High
amplitude magnetic anomalies, volcanic geomorphology, and normal mid-ocean ridge
basalt (MORB) suggest that they are oceanic spreading centres (Augustin et al., 2014,
2016; Bonatti, 1985; Izzeldin, 1987; Pautot et al., 1984). However, the nature of crust
underlying the shallower inter-trough zones and crust off-axis covered by evaporites
and hemipelagic sediments has been more controversial. Some authors have
interpreted the low amplitude magnetic anomalies found in these areas as indicating
a highly extended continental crust (Bonatti, 1985; Cochran and Karner, 2007; Ligi et
al., 2011, 2012), whereas others have interpreted seismic velocity structures obtained
from limited seismic refraction data and segmented structure of the gravity field as
indicating oceanic crust while explaining the low amplitude magnetic anomalies by
various mechanisms (e.g., Augustin et al., 2014, 2016; Dyment et al., 2013; Egloff et
al., 1991; Girdler, 1985; LaBrecque and Zitellini, 1985; Mitchell and Park, 2014; Searle
and Ross, 1975; Shi et al., 2018; Tramontini and Davies, 1969).
169
In the northern Red Sea (north of 23°N; Figure 6.1), the ‘deeps’ are less
pronounced and become more widely spaced, although the basaltic intrusions lavas
have been recovered from them (Bonatti, 1985; Cochran, 2005; Guennoc et al., 1988;
Pautot et al., 1984). The presence of large fault blocks of continental crust has been
inferred from the gravity anomalies combined with seismic refraction data (Cochran
and Karner, 2007; Martinez and Cochran, 1988). In contrast, others have suggested
this region is also underlain by oceanic crust based on unpublished seismic reflection
and magnetic data (Dyment et al., 2013; Tapponnier et al., 2013). From
reconstructions of geological features across the Red Sea, Sultan et al. (1992, 1993)
suggested that the entire Red Sea basin is underlain by oceanic crust.
6.3 Data and methods
6.3.1 Multichannel seismic reflection
Multichannel seismic reflection data used in this study were collected in 1976
(Izzeldin, 1982, 1987), using a Vaporchoc source with a 2.4 km streamer consisting of
48 channels during deep-water surveying and with a 1.2 km streamer during shallow-
water surveying. The data were processed using a 24-fold stack, with stacking
velocities computed every 3.6 km along track. The locations of seismic reflection
profiles 7, 9, 11, 15, 17, 19, 21, 25, 27, 29, and 31 are shown in Figures 6.2a and 6.2b.
Basement depths were derived from these data as described by Shi et al.
(2018). They converted two-way travel times of the basement and seabed reflections
to depths below sea level using P-wave velocities (Vp) of 1.538 km s-1, 1.9 km s-1, and
4.21 km s-1 for water, Plio-Pleistocene sediments, and evaporites, respectively. These
velocities were chosen based on the earlier studies. The Vp of water was chosen
according to the empirical equations of Mackenzie (1981), with typical Red Sea salinity
of 40 ppt and temperature of 21 °C. The Vp of Plio-Pleistocene sediments was chosen
based on the measurements of DSDP Leg 23 samples (Whitmarsh et al., 1974) and the
results of seismic reflection and refraction surveys by Egloff et al. (1991) and Gaulier
et al. (1988). The Vp of evaporites was chosen based on seismic refraction data from
Tramontini and Davies (1969), Girdler and Whitmarsh (1974), and Egloff et al. (1991).
Figure 6.3 shows those depths derived from the seismic reflection data.
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Figure 6.2 (a): Free-air gravity anomalies (Sandwell et al., 2014, version 23.1) and locations
of multichannel seismic reflection profiles 7, 9, 11, 15, 17, 19, 21, 25, 27, 29, 31 from Izzeldin
(1982, 1987). (b): Locations of gravity profiles G1-32 and seismic reflection profiles as in (a).
Cyan line approximately locates the spreading axis. Green line locates gravity profile G21,
along which the gravity forward modelling results are shown in Figure 6.6. The study area was
divided into two areas: north of 20.25°N and south of 20.25°N, as the free-air gravity field
north of 20.25°N has cross-axis lineaments suggested to be due to oceanic spreading
segments (Mitchell, 2015).
171
Figure 6.3 Depths derived from the seismic reflection profiles of Izzeldin (1987). Line
numbers are shown in the lower right corner of each panel. Magnetic anomalies (purple lines)
along the seismic profiles are reduced-to-pole magnetic anomalies (Figure 6.10). Black lines
denote bathymetry (Smith and Sandwell, 1997, version 18.1). Dark green, cyan, and red lines
are the depths of the seabed, the S-reflection at the top of the Miocene evaporites, and the
basement, respectively. RTP: Reduced-to-pole.
172
The basement depths corrected for isostatic loading of the evaporites and
other sediments by Shi et al. (2018) were used here to estimate basement roughness
along the seismic profiles. To compute residual basement reliefs, we needed to
remove the systematic trend with basement age, but, in the central Red Sea, the crust
deepens too fast to be caused by normal thermal subsidence, likely an effect of varied
crustal thickness (Shi et al., 2018). Therefore, rather than use a theoretical subsidence
curve, we have removed a running median average. For example, the residual
basement reliefs in Figure 6.7c were obtained by removing the regional variation of
Figure 6.7b from the basement depths in Figure 6.7a.
The results are unfortunately non-unique; Figure 6.7d shows how the
basement roughness varies with filter width. However, after experimenting with
various filter widths, 60 km appears to do a good job of attenuating most of the abyssal
hill topography while still recording the regional variation (Figure 6.7b). Furthermore,
the roughness in Figure 6.7d varies gradually with filter width. In Figure 6.8, the value
obtained with the 60 km filter width is shown with the red star, whereas the error bar
represents the effect of filter width varying from 120 to 460 km.
6.3.2 Gravity anomalies
6.3.2.1 Free-air gravity data
We have used version 23 of the marine gravity field (referred to below as
“SSv23”) derived from satellite altimetry measurements by Sandwell et al. (2014). The
data are shown in Figure 6.2a.
Shipboard gravity data obtained from the National Centers for Environmental
Information (NCEI) (www.ngdc.noaa.gov/mgg) were used to evaluate the SSv23 data.
These data were collected on the RRS Shackleton in 1987 with a LaCoste and Romberg
gravity meter (Girdler and Southren, 1987) and on RV Robert Conrad during cruise
2507 in 1984 with a Bell BGM-3 gravity meter (Cochran and Martinez, 1988).
Some spikes occur in shipboard datasets, e.g., due to errors in Eötvös
correction and centripetal accelerations occurring with course changes (Mitchell, 2015;
Wessel and Watts, 1988). To reduce their effects, a 4-km running median average
173
filter was applied to the shipboard values before comparing the two datasets and
calculating the distribution of their differences shown in Figures 6.4 and 6.5.
Figure 6.4 Histograms of differences between the SSv23 and free-air anomaly data collected
on (a): RRS Shackleton and (b): RV Robert Conrad (SSv23 minus shipboard value). Vertical lines
show the means and standard deviations of the differences.
The differences between the SSv23 and the RRS Shackleton and RV Robert
Conrad data have standard deviations of 5.5 and 3.7 mGal (Figure 6.4). The RV Robert
Conrad data more closely follow SSv23 than the RRS Shackleton data, most likely
because of the superior Bell BGM-3 gravity meter used on the RV Conrad (Mitchell,
2015). Figure 6.5 shows a map of the differences. Blue areas indicate that SSv23 is -
10 mGal smaller than the shipboard values in the northernmost Red Sea, east side at
25-26 °N, centre at 24 °N, and centre at 20 °N. Their origins are difficult to identify.
Sandwell (pers. comm. 2013) suggested that these biases could be due to edge effects
from when the vertical offshore altimetry deflections were converting to gravity
anomalies (Mitchell, 2015). Nevertheless, the biases are small compared to the >100
mGal full range of the SSv23 gravity anomalies.
(a) (b)
174
Figure 6.5 Differences between the SSv23 gravity field and the shipboard (RRS Shackleton
and RV Conrad) gravity data (SSv23 minus shipboard) after the shipboard data were filtered
with a 4 km along-track median filter.
Free-air gravity anomalies were sampled from SSv23 along the ridge-parallel
gravity profiles G1-32 shown in Figure 6.2b. Because the free-air gravity field has
lineations crossing the Red Sea north of 20.25°N but not south of there (Mitchell,
2015), the profiles were each divided into two segments either side of 20.25°N. Those
segmented gravity profiles were then inverted for basement depth variations as
follows.
175
6.3.2.2 Bouguer slab formula
The gravity anomaly caused by a layer of infinite lateral extent and constant
thickness ℎ and density contrast ∆𝜌 can be computed using the Bouguer slab formula:
𝛿𝑔 = 2𝜋𝐺ℎ∆𝜌 (6.1)
where, 𝐺 is the gravitational constant.
To use equation (6.1) to invert the gravity data for basement relief, we
assumed a simplified structure of water underlain by evaporite and other sediments
of uniform density, in turn underlain by crust and mantle also each of uniform density.
As the lines are parallel to the axis, temperature in the upper mantle is expected to
vary only modestly along each line, and hence we can ignore its effect on the gravity
variations. In the central Red Sea, a 200-300 m thick layer of Plio-Pleistocene sediment
overlies the Miocene evaporites (Egloff et al., 1991; Izzeldin, 1987; Whitmarsh et al.,
1974). However, it is almost uniform in thickness (Mitchell et al., 2017; Ross and
Schlee, 1973) and has a similar density to the underlying evaporites (Mitchell et al.,
2010; Wheildon et al., 1974), so little error is introduced by using a single density for
both units. If the crust is oceanic, its upper layer (seismic layer 2) comprises low-
density lavas and dykes (Searle, 2013). We have chosen to ignore this layer in the
calculations and instead use a uniform gabbro density in the inversion because a
global study of seismic refraction data revealed that variations in crustal thickness
arise mainly from variations in the gabbro layer, while the lavas and dykes are more
uniform (Mutter and Mutter, 1993). Hence, its effect on the gravity variations should
be small. Similarly, the crust was also considered to be a layer of uniform density,
because seismic refraction data typically show little variation in seismic velocity
(Grevemeyer and Weigel, 1996), although this may be less true of some fracture zones
(White and Williams, 1986). The effect of topography of the Moho is ignored due to
its small density contrast and deep location. We return to some of these assumptions
later.
Using equation (6.1), the free-air anomaly variation along the axis-parallel
profiles can then be expressed in the following form:
176
𝑔𝑓𝑎𝑎 = 2𝜋𝐺[ℎ𝑤(𝜌𝑤 − 𝜌𝑐) + 𝑡𝑒𝑠(𝜌𝑒 − 𝜌𝑐)] + 𝑐 (6.2)
where 𝑔𝑓𝑎𝑎 is free-air anomaly, ℎ𝑤 is water depth, 𝑡𝑒𝑠 is total thickness of the
evaporites and other sediments, 𝜌𝑤 and 𝜌𝑐 are water and crustal densities, 𝜌𝑒 is the
mean density of the evaporite and sediment layers, and 𝑐 is a constant along each
ridge-parallel gravity profile.
A mean density of 2,148 kg m-3 was used for the evaporite and sediment layers
(Wheildon et al., 1974). The crust was assumed to have a density typical of oceanic
crust dominated by gabbro. A density of 2,957 kg m-3 was used for the oceanic crust
based on DSDP sample measurements of Hyndman and Drury (1977). A 1,020 kg m-3
density was used for the seawater.
By rearranging equation (6.2), we obtain:
𝑡𝑒𝑠 =𝑔𝑓𝑎𝑎−𝑐
2𝜋𝐺(𝜌𝑒−𝜌𝑐)− ℎ𝑤
𝜌𝑤−𝜌𝑐
𝜌𝑒−𝜌𝑐 (6.3)
Hence, the basement depth is:
ℎ𝑏 = ℎ𝑤 + 𝑡𝑒𝑠 =𝑔𝑓𝑎𝑎−𝑐
2𝜋𝐺(𝜌𝑒−𝜌𝑐)+ ℎ𝑤
𝜌𝑒−𝜌𝑤
𝜌𝑒−𝜌𝑐 (6.4)
Although absolute basement depths cannot be calculated merely from gravity
anomalies using equation (6.4) because 𝑐 is unknown, the basement depths in Figure
6.3 derived from seismic data were used to determine c for each profile.
The basement depths computed from equation (6.4) were then used to
estimate basement roughness along ridge-parallel gravity profiles, which are shown in
Figure 6.9a and 6.9b.
6.3.2.3 2D gravity forward modelling
Basement relief derived using the Bouguer slab formula will be
underestimated, because the assumption of an infinite slab is not fully met. We have
used gravity forward modelling to assess the bias magnitude, which can be used to
correct the roughness values. Forward models of free-air gravity anomalies were
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computed along profiles G1-32 (Figure 6.2b) by summing the gravitational effects of
elementary mass rectangular cells.
The vertical gravitational attraction of a small rectangular cell is (Shengye and
Yuling, 2004):
∆𝑔 = 𝐺𝜌[(𝑥 + 𝑎)𝑙𝑛(𝑥+𝑎)2+𝐻2
(𝑥+𝑎)2+ℎ2 − (𝑥 − 𝑎)𝑙𝑛(𝑥−𝑎)2+𝐻2
(𝑥−𝑎)2+ℎ2 + 2𝐻 (𝑡𝑔−1 𝑥+𝑎
𝐻− 𝑡𝑔−1 𝑥−𝑎
𝐻) −
2ℎ(𝑡𝑔−1 𝑥+𝑎
ℎ− 𝑡𝑔−1 𝑥−𝑎
ℎ)] (6.5)
where 2𝑎 is plate width, ℎ is depth to upper boundary, and 𝐻 is depth to lower
boundary.
Based on the principle of superposition, the vertical gravitational attraction of
a geological body can be reproduced by the sum of the attractions of many small
individual rectangular cells constituting the body (Blakely, 1996). To forward model
the gravity anomalies, density structure derived from the along-axis profiles were
subdivided into 𝑛 small cells and equation (6.6) was applied to compute the sum of
their gravitational attractions:
𝑔𝑘 = ∑(∆𝑔)𝑖
𝑛
𝑖=1
(6.6)
where 𝑔𝑘 is the vertical gravitational attraction measured at the 𝑘𝑡ℎ measurement
point, (∆𝑔)𝑖 is the vertical gravitational attraction produced for the 𝑘𝑡ℎ measurement
point by the 𝑖𝑡ℎ small rectangular cell, (∆𝑔)𝑖 is computed from equation (6.5).
The density model in Figure 6.6a for gravity profile G21 was obtained using the
modified Bouguer slab formula (equation (6.4) first to estimate the
evaporite/basement depth, with bathymetry data used to constrain the top two
interfaces assuming constant thickness of Plio-Pleistocene (PP) sediments (water-PP
sediments and PP sediments-evaporites)). The same densities of seawater, evaporites,
and oceanic crust were used as in section 6.3.2.2. The forward model in Figure 6.6b
derived from the density structure in Figure 6.6a using equations (6.5) and (6.6) tends
to underestimate the extreme gravity anomalies (peaks and troughs). After scaling
the basement relief by a factor of 1.3 (i.e., maintaining the same mean depth but
increasing the rugosity about that mean depth), the calculated forward model does a
178
better job of reproducing the observed free-air anomalies. We concluded that the
systematic calculation bias arising from the use of the gravity slab formula is ~30%,
which is uniform along the central Red Sea gravity profiles as density interfaces show
no systematic variation with latitude. In order to get more accurate basement
roughness values from the slab formula, the roughness values were therefore
multiplied by a factor of 1.3, as shown by the red symbols in Figure 6.9.
Figure 6.6 Forward modelling of gravity profile G21. (a): Density model obtained from the
slab-formula-based results. The structure was subdivided into n=3600 small cells, and the
number of measurement points m is 720. (b): Forward 2D model predictions of free-air
gravity anomalies based on the slab formula results (red) underestimate the gravity anomaly
variation (blue line is free air anomaly from satellite altimetry). After multiplying the
basement relief variation by a factor of 1.3, the forward model (black line) better predicts the
observations. Based on this result, the systematic bias in basement roughness derived from
axis-parallel gravity profiles is 30%.
(a)
(b)
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6.3.3 Bathymetry data
Version 18.1 of the Smith and Sandwell (1997) bathymetry data used in this
study is shown in Figure 6.1. These data were derived by combining shipboard depth
measurements with, in areas lacking shipboard depth measurements, variations
inferred from the effect of the seabed density contrast on free air anomalies, in turn
derived from satellite altimetry measurements. As the density of ship tracks along the
centre of the Red Sea is high, the high relief areas around the rift axis are mainly
constrained by survey data rather than gravity-based interpolation. Seabed depths
sampled along the gravity profiles were used in inverting basement depths with
equation (6.4).
6.4 Results
6.4.1 Basement roughness along across-ridge seismic profiles
The relationship between basement roughness and filter width is shown in
Figure 6.7d. The mean roughness value derived from data both north and south of
20.25°N increases from 120 m at the filter width of 10 km to 460 m at the filter width
of 240 km. For filter widths of less than 70 km, the mean roughness values in the
northern and southern regions are very close to each other. When the filter width is
greater than 70 km, the roughness value of the northern region is slightly higher than
that of the southern region. As the basement deepens to its deepest value at a 60 km
distance either side of the axis (Figure 6.7a), we suggest that 60 km is the most
appropriate filter width to use here and so the roughness value of 230 m is our best
estimate for the central Red Sea.
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Figure 6.7 (a): Basement depths along the Red Sea seismic lines (Figures 6.2a and 6.2b)
corrected for the isostatic loading of evaporites and other sediments. (b): Regional systematic
trend estimated from (a) using a 60 km running median average filter. (c): Residual basement
reliefs obtained by removing the systematic trend in (b) from the isostatically adjusted
basement depths in (a). Grey shadings (within ~60 km of the axis) in (a), (b), and (c) show the
area Shi et al. (2018) interpreted as underlain by oceanic crust. (d): The relationship between
181
the mean basement roughness value and filter width. Blue and black lines represent
roughness values in northern (north of 20.25°N) and southern (south of 20.25°N) regions,
while red line represents the values derived from data of both regions combined. The
roughness value of 230 m at the filter width of 60 km is considered to be the most appropriate
value for the central Red Sea (see main text).
Figure 6.8 The relationship between the basement roughness and spreading rate for
ultraslow and slow spreading ridges, modified from Sauter et al. (2018). The error bar for the
Red Sea value indicates the range of roughness value derived from various filter widths in
Figure 6.7d. The other error bars represent the standard deviations of the corresponding
roughness values. SWIR: Southwest Indian Ridge, MCSC: Mid-Cayman Spreading Center, MAR:
Mid-Atlantic Ridge, SPR: South Pandora Ridge. Data for the Red Sea are determined in this
study. Data for Arctic ridge are from Weigelt and Jokat (2001) and Ehlers and Jokat (2009).
Data for SWIR are from Sauter et al. (2011) and Sloan et al. (2012). Data for MCSC are from
Sauter et al. (2018). Data for MAR are from Goff (1991), Goff et al. (1995), Neumann and
Forsyth (1995), Minshull (1999), and Lizarralde et al. (2004). Data for Sheba ridge are from
d'Acremont et al. (2010). Data for SPR are from Lagabrielle et al. (1996). The continuous black
line is the power-law of Malinverno (1991). The dashed blue and red lines are power-laws
derived by Ehlers and Jokat (2009) from basement topography adjacent to ridges with axial
valleys and with axial highs, respectively.
Figure 6.8 shows the relationship between the basement roughness and
spreading rate for the central Red Sea together with other ultraslow and slow
spreading ridges from Sauter et al. (2018). The roughness values at ultraslow
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spreading ridges range from 100 to >500 m, while those at slow spreading ridges are
200-240 m. The Red Sea basement roughness value (230 m) is generally consistent
with these data. It lies near the curve of Malinverno’s (1991) global study of abyssal
hill roughness and near to the curve of Ehlers and Jokat (2009) of abyssal hills of near
hotspots. The 60 km filter width leaves some abyssal hill topography (Figure 6.7b),
suggesting it may be too small. Increasing the filter width would produce a higher
roughness value as shown by the error bar in Figure 6.8. This would still leave the
roughness within the range of values typical for an ultra-slow spreading ridge.
6.4.2 Basement roughness along the ridge-parallel gravity profiles
In Figure 6.9a and 6.9b, the basement roughness values in both areas range
from 200 m to 550 m and are comparable to those of the Mid-Atlantic Ridge
(horizontal pink lines in Figure 6.9a and 6.9b). The roughness values around the
spreading axis are higher than those near the coasts. Those values change about mid-
way between the coast and the spreading axis (40-80 km off-axis), coinciding with a
transition in crustal type from stretched continental to predominantly oceanic
interpreted by Izzeldin (1982, 1987) from varying character of the basement reflection
in regional seismic profiles and by Shi et al. (2018) from a change in Bouguer anomaly-
basement depth correlation.
183
Figure 6.9 Basement roughness values (green symbols) computed with a modified Bouguer
slab formula along axis-parallel gravity profiles G1-32 (Figure 6.2b) using a crustal density
(2,957 kg m-3) appropriate for oceanic crust dominated by gabbro. (a): North of 20.25°N. (b):
South of 20.25°N. Red symbols show the values corrected for bias arising from the slab
formula based on the results of gravity forward modelling (see section 3.2.3). Horizontal pink
lines represent basement roughness values calculated along lines parallel to the Mid-Atlantic
Ridge axis from bathymetry where the basement is only weakly sedimented (bathymetry data
derived from the Global Multi-Resolution Topography Synthesis (Ryan et al., 2009) over
latitudes 22°N to 32°N and 80 km off-axis, where the bathymetry has a similar segmentation
structure to the central Red Sea).
6.5 Discussion
In this study, we have shown that basement roughness values in the central
Red Sea are similar to those of the similarly ultraslow and slow spreading ridges,
although they by themselves do not rule out an extremely extended continental crust
184
interpretation. This is, however, consistent with the oceanic-like seismic velocity
structures in the central Red Sea (Davies and Tramontini, 1970; Egloff et al., 1991;
Tramontini and Davies, 1969) and an axial high similar to hotspot-affected ridges (Shi
et al., 2018) and supports the interpretation that rifting has proceeded to seafloor
spreading in the central Red Sea, as well as in the south.
After correcting seismically derived basement topography for isostatic loading
of evaporites and other sediments, Shi et al. (2018) revealed that the basement has
an axial high, as shown in Figure 6.7a. Such a high is not typically found at continental
rifts but is common for mid-ocean ridges near to mantle hotspots, such as the
Reykjanes Ridge near Iceland or Spiess Ridge on the similarly ultra-slow spreading
Southwest Indian Ridge near to the Bouvet hotspot.
Some other clues for assessing crust type in the central Red Sea are reassessed
as follows.
6.5.1 Reduced-to-pole magnetic anomalies
Figure 6.10 shows the aeromagnetic data originally presented by Izzeldin (1982,
1987, 1989) after reduction to pole. Izzeldin (1987) interpreted spreading anomalies
up to Chron 2A (3 Ma) north of 20˚N and up to Chron 3A (6 Ma) south of 20˚N from
these data. However, although less easily identified, linear anomalies also exist
further from the axis, and they lie parallel with and are symmetrical about the axis
(e.g., at 60 km from the axis in line 9). That symmetry and their lack of correlation
with basement topography (Figure 6.3) is a strong indication that they are seafloor-
spreading anomalies, as argued for similar anomalies in the southern Red Sea (Hall,
1989). The low magnetic amplitudes here could be due to the deeper basement,
alteration under the evaporites, overlapping flows and effects of crustal segmentation
(Augustin et al., 2014; Dyment et al., 2013; Izzeldin, 1987, 1989; LaBrecque and
Zitellini, 1985; Levi and Riddihough, 1986; Mitchell and Park, 2014; Searle and Ross,
1975).
185
Figure 6.10 Aeromagnetic anomalies of Izzeldin (1982, 1987) reduced to pole. Red lines
locate the seismic reflection profiles (Figure 6.2a). The data are contoured every 80 nT.
6.5.2 Along-axis gradients in mantle Bouguer anomalies
Mantle Bouguer anomalies (MBAs) are marine Bouguer anomalies in which the
gravitational effect of the cooling lithospheric plate is removed from free-air
anomalies as well as the effect of the seabed density contrast (Grindlay et al., 1998;
Lin and Morgan, 1992). As MBAs vary with varied crustal thickness and/or upper
mantle densities, they are commonly interpreted in terms of the three-dimensional
upwelling structure of mantle beneath ridges (Magde and Sparks, 1997). (As regions
of upwelling mantle are hot, and hence less dense, they reduce gravity anomalies. In
addition, crust is generally thicker above such regions because of greater melting,
which also reduces the MBA.) Wang and Cochran (1995) measured along-axis
gradients in MBA by dividing the peak to trough amplitude by distance and found them
to be ~0.1 mGal km-1 at mid-ocean ridges with axial highs including the slow-spreading
Reykjanes Ridge, while finding MBAs at slow spreading ridges that are not affected by
mantle hotspots to be higher (e.g., gradients along parts of the Mid-Atlantic Ridge
186
away from hotspots are 0.3-1.2 mGal km-1 and those along Southwest Indian Ridge
are 0.4– 0.7 mGal km-1) (Figure 6.11).
Figure 6.11 Comparison of along-axis gradients in mantle Bouguer anomalies (MBA) in the
central Red Sea with those at other mid-ocean ridges, modified from Wang and Cochran
(1993). RR: Reykjanes Ridge, CIR: Central Indian Ridge, SEIR: Southeast Indian Ridge, GSC:
Galápagos spreading center, EPR: East Pacific Rise.
We have computed differences in MBAs between the seismic reflection
profiles where they cross the spreading axis, using the depth of basement in those
profiles as a constraint, along with the seabed reflection where the axis is covered
with evaporites and other sediments. Mantle Bouguer anomalies along 11 seismic
profiles (Figure 6.3b) in the central Red Sea were computed by subtracting gravity
effects of evaporite-crust and crust-mantle interfaces from the marine Bouguer
gravity anomalies of Mitchell et al. (2017), assuming a uniform 7 km thick crust.
Densities of 2,148 kg m-3 (Wheildon et al., 1974), 2,957 kg m-3 (Hyndman and Drury,
1977), and 3,220 kg m-3 (Crough, 1983; Gvirtzman et al., 2016) were used for
evaporites, oceanic crust, and mantle, respectively. As the differences were
calculated for the spreading axis, with zero age crust, no lithospheric cooling
component was needed. Figure 6.11 shows those differences converted to along-axis
gradients in MBA, which range from 0.02 to 0.3 mGal km-1. Given that the seismic
lines are not optimally located for sampling the largest along-axis MBA gradients (the
187
seismic lines are spaced typically ~50 km (Figure 6.2), whereas peaks and troughs in
MBA profiles can be 20 km or less (Magde and Sparks, 1997), the 0.3 mGal km-1 value
may be the most representative of the steepest values.
This 0.3 mGal km-1 value is larger than the 0.1 mGal km-1 value of Wang and
Cochran (1995) for the Reykjanes Ridge, suggesting that crustal thickness is less
uniform along-axis in the central Red Sea (Bell and Buck, 1992). This may suggest the
axial crust is not as hot and/or thick as at the Reykjanes Ridge. The geochemistry of
basaltic lavas (Na8.0) also suggest that the present axis has a normal or only modestly
thick crust (Haase et al., 2000), and hence is less likely to have redistributed crustal
material by the mechanism of Bell and Buck (1992). Although these various lines of
evidence for a somewhat cold axial lithosphere would seem to be incompatible with
an axial high, Shi et al. (2018) suggested this could be explained by crustal thickening
from an early rifting stage which produced less magma and thinner than average
oceanic crust. Furthermore, seismic tomography results indicate that the hot material
from the Afar plume has mainly propagated under Arabia rather than the central Red
Sea (Chang et al., 2011).
6.6 Conclusion
To further assess the nature of crust in the central Red Sea, we computed
basement roughness values in profiles both across and parallel to the axis and
compared them with those observed at ultraslow and slow spreading ridges.
Basement roughness values from axis-crossing seismic data are ~230 m, similar to the
values observed at other ultraslow and slow spreading ridges (e.g., the Mid-Atlantic
Ridge, the Sheba Ridge, and the Southwest Indian Ridge). The roughness values
derived from axis-parallel profiles of the gravity field (200-550 m) are comparable with
those of the Mid-Atlantic Ridge where it has similar along-axis segmentation. A
change in those roughness values roughly mid-way between the coast and the axis
may mark the transition in crustal type from stretched continental to predominantly
oceanic. Although these basement roughness values by themselves do not exclude an
extended continental crust interpretation in the central Red Sea, they are supportive
of an oceanic crustal interpretation when considered along with other evidences,
188
including oceanic-like seismic velocity structures, crustal axial high, reduced-to-pole
magnetic anomalies, and along-axis gradients in mantle Bouguer anomalies.
6.7 Acknowledgments
We thank David Sandwell and Walter Smith for leading the gravity and
bathymetry mapping initiatives, and for the group involved in producing the grids used
in our study. Figures were prepared using GMT software (Wessel et al., 2013). LMK
was supported by a Royal Society of Edinburgh Personal Research Fellowship funded
by the Scottish Government. A Royal Society (International Exchanges Scheme) grant
to NCM enabled discussions with colleagues Nico Augustin and Froukje van der Zwan
that contributed to our conclusions.
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Chapter 7.
Synthesis
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7. Synthesis
7.1 Crust types in the central Red Sea
7.1.1 Classifications
In this study, we assessed crust types and their basement geometries in the
central Red Sea using multichannel seismic reflection data, ship-board magnetic data,
aeromagnetic data, and satellite gravity data.
Figure 7.1a shows our interpreted crust types. The presence of oceanic crust
was interpreted based on axial crustal high revealed in seismically derived basement
topography corrected for evaporite and other sediment loading in Chapter 4 (Figure
4.5), an axial high similarly in basement topography from Werner deconvolution of
aeromagnetic data in Chapter 5 (Figure 5.6), and basement roughness in Chapter 6
(Figure 6.9), which is comparable with roughness of ultra-slow spreading mid-ocean
ridges. Transitional crust lies between that oceanic crust and the extended
continental crust nearer to the two coasts of the Red Sea. Locating such transitional
crust is difficult and commonly is located differently by different researchers working
on the same margins (e.g., Eagles et al., 2015). We here locate uncertain transitional
crust where the Bouguer-basement depth correlations break (Chapter 4; Figure 4.6).
The loss of this correlation towards the coasts implies a lower net density underlying
the basement, hence more likely continental crust. Furthermore, we have found a
change in basement roughness implied by along-axis roughness of gravity anomalies
(Chapter 6; Figure 6.9), suggesting a decrease in relief due to oceanic fracture zones.
The narrow zones around the basement troughs where the trend changes from
decreasing to increasing towards the coast are interpreted as oceanic–continental
transitions (OCTs) (see also Figure 7.2). In Figure 7.1a, the lineaments interpreted by
Izzeldin (1987) from gravity, magnetic, and bathymetric data of Izzeldin (1987) are
probably fracture zones.
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Figure 7.1 (a): Geological map of the central Red Sea based on the interpretation principles
given in main text. Cross-axis lineaments are from Izzeldin (1987). (b): A comparison of crust
type classification in (a) with that of Izzeldin (1987).
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In Figure 7.1b, we compare our crust type classification with that of Izzeldin
(1987), who interpreted continental crust primarily from a change in the topographic
character of basement seismic reflections. In Figure 7.1b, the locations of oceanic and
uncertain transitional crust interpreted in our study are generally consistent with his.
Thus, the transitions we have identified also coincide with the reflection character
changes Izzeldin (1987) identified.
Figure 7.2 Interpretations of crust types along seismic lines 17 and 21. OCT: oceanic–
continental transition.
In Figures 7.1a and 7.2, the edges of oceanic crust tend to be symmetrical
about the axis, suggesting a symmetrical spreading in the central Red Sea.
In Figures 7.3a, 7.3b and 7.3c, Free-air gravity anomalies (Figures 3.1 and 3.9a),
Bouguer gravity anomalies (Figure 3.10) and RTP aeromagnetic anomalies (Figure 3.8)
are overlain on our crust type classification (Figure 7.1a). The high gravity anomalies
(Figures 7.3a and 7.3b) and high magnetic anomaly amplitudes (Figure 7.3c) near the
axis are in line with the basement axial high. Over our interpreted extended
continental crust towards the coasts, the gravity and magnetic anomies are generally
subdued (Figures 7.3a, 7.3b and 7.3c). Over the OCT areas (Figures 7.3a and 7.3b), the
Free-air and Bouguer gravity anomalies are generally also subdued. Within these OCT
areas, they can be observed some linear magnetic anomalies that are aligned with the
axis and occurring on both sides of the axis (Figure 7.3c). We interpret these as caused
201
by volcanic dyke swarms intruded parallel to the axis or extrusives associated with
them, possibly during the final breakup stage.
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Figure 7.3 Comparisons of crust type classification in Figure 7.1a with (a): Free-air gravity
anomalies (Sandwell et al., 2014, version 23.1) contoured every 20 mGal, (b): Bouguer gravity
anomalies from Mitchell et al. (2017) contoured every 50 mGal, and (c): RTP aeromagnetic
anomalies contoured every 80 nT. (d): A comparison of Bouguer gravity anomalies in (b) with
RTP aeromagnetic anomalies in (c).
203
In Figure 7.3d, RTP aeromagnetic anomalies (Figure 3.8) are overlain on the
Bouguer gravity anomalies (Figure 3.10). Figure 7.3d shows that the cross-axis
magnetic highs generally overlie the Bouguer gravity highs. At 21.5°N and 23°N, both
the cross-axis magnetic and Bouguer gravity highs are subdued (see also Figures 7.3b
and 7.3c), due to the fracture zones. There are some linear high magnetic anomalies
in the OCT areas, over which the Bouguer gravity anomalies are low. The low Bouguer
gravity anomalies reflect deep basements. The magnetic anomalies here lack of
correlation with basement topography. This could indicate that they are seafloor-
spreading magnetic anomalies, as argued for similar anomalies in the southern Red
Sea (Hall, 1989). Here, we suspect that these high magnetic anomalies may be
produced either by dykes intruding the last stretched continental crust of the OCT or
youngest oceanic crust.
7.1.2 Character of the axial high
We suggested that the axial high was created by the increased melt supply and
enhanced crustal thickness (Shi et al., 2018). The axial relief in the central Red Sea
(0.8-1.6 km) is similar to that at the ultra-slow spreading Spiess Ridge (full rate, ~12.8
mm yr−1 (DeMets et al., 1994)) near the Bouvet hotspot (Mitchell and Livermore, 1998),
but larger than those at the slow-spreading Reykjanes Ridge near Iceland (0.6–1.0 km)
(Figure 4.5) and the intermediate rate Galápagos Spreading Centre near the Galápagos
hotspot (Blacic et al.,2008). This could be explained by the colder, stronger lithosphere
close to the ridge in the Red Sea due to the greater distance from the hotspot and the
slower spreading rate. The distances between the spreading ridges and their
associated hotspots are ~1,000 km for the central Red Sea ridge, ~300 km for the
Reykjanes Ridge, and ~100 km for the Galápagos Spreading Centre. The full spreading
rates of the central Red Sea, the Reykjanes Ridge, and the Galápagos Spreading Centre
are ~14 mm yr−1 (Chu and Gordon, 1998; DeMets et al., 2010), ~20 mm yr−1 (DeMets
et al., 2010; Talwani et al., 1971), and 55 mm yr−1 (DeMets et al., 1990), respectively.
As shown in Figure 7.1a, the width of Red Sea oceanic crust decreases
northwards from ~140 km at 19°N to ~100 km at 21°N, and then it increases to ~120
km at 23°N. Although oceanic crust is a bit narrower in the north than in the south,
its width does not vary systematically with distance from the Afar region.
204
The axial high is found along the whole central Red Sea, a distance of ~725 km.
South of our study area, the axial high probably extends southwards to around 16°N
in the southern Red Sea, because the Bouguer anomalies are similarly elevated and
this region is also undergoing ultra-slow seafloor spreading (e.g., Cochran, 1983;
Girdler and Styles, 1974; Phillips, 1970; Vine, 1966) with underlying hot mantle (e.g.,
Chang et al., 2011; Park et al., 2007, 2008).
7.1.3 Distinct domains from north to south
Cross-axis gravity lineations crossing the Red Sea occur in the region north of
20.25°N but not south of there (Mitchell, 2015). Thus, the central Red Sea can be
divided into two distinct domains as shown in Figure 6.2. The basement roughness
measured along strike is larger north of 20.25°N (with a mean value of ~350 m) than
it is south of 20.25°N (with a mean value of ~ 290 m) (Figure 6.8). This implies that
fracture zones have only developed north of 20.25˚N.
7.2 Moho depth and crustal thickness
None of the data in the 11 seismic reflection profiles in this study reveal the
Moho. To investigate the crustal thickness, geometry and type across the Red Sea,
Moho depths along seismic refraction profile SO53-PIII of Egloff et al. (1991) and
profile A-B of Salem et al. (2013) were plotted together with the basement reflections
along seismic profile 25 (Figure 7.4).
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Figure 7.4 (a): Free-air gravity anomalies (Sandwell et al., 2014, version 23.1) and locations
of multichannel seismic reflection profiles 7, 9, 11, 15, 17, 19, 21, 25, 27, 29, 31 of Izzeldin
(1987), seismic refraction profile SO53-PIII of Egloff et al. (1991), and profile A-B of Salem et
al. (2013). (b): A composite profile produced by projecting the seafloor and basement
206
reflections along profile 25 of Izzeldin (1987) on onto profile PIII of Egloff et al. (1991). (“Pre-
evaporites” are pre-evaporite sedimentary rocks.) (c): Graph showing basement reflection
along profile 25 and Moho along profiles PIII and A-B. OBS: Ocean bottom seismographs.
Profile 25 is the only seismic profile near profiles PIII and A-B (Figure 7.4a). In
Figure 7.4b, the basement top from Egloff et al. (1991) (blue) is elevated above that
from seismic profile 25 (red) at distances -60– -45 km. This may be explained by the
interface between the two layers marking a velocity change within igneous basement
rather than the basement-evaporite interface exactly (Mitchell et al., 2010), since the
seismic velocity of evaporites (~4.2 km s-1) overlaps with seismic velocities of volcanic
extrusives (Hammer et al., 1994; Mitchell, 2001). The difference in the basement
depth within the distance of -20–20 km is probably due to the different locations of
profiles 25 and PIII.
In Figure 7.4c, necking zones are probably located around the distance of ~53
km on either side of the axis, where the crust is thinnest. This is consistent with the
seismic interpretations of Egloff et al. (1991), which also suggested that the
continental crust is thinned from the coast up until ~53 km from the axis (their OBS 9
position) (Figure 7.4b). As demonstrated by profiles 25 and A-B, the trend of crustal
thickening occurs on both sides of the axis, suggesting a symmetric crustal structure
in the central Red Sea. The symmetry of structures in the gravity and magnetic data
(Figure 7.3) also suggest that the rift was symmetric not asymmetric in this part of the
Red Sea.
Based on the above studies, across-ridge crustal structures in the central Red
Sea are sketched in Figure 7.5.
207
Figure 7.5 A sketch showing across-ridge crustal structures in the central Red Sea.
7.3 Uncertainty in the seismically derived basement depth
As discussed in Chapter 3 (3.1), the main uncertainty in the seismically derived
basement depth and the thickness of evaporates originates from the P-wave velocity
(Vp) used for the evaporites. In Chapter 3, P-wave velocities of 3 km s-1 and 4.21 km
s-1 for evaporites were used to compute the minimum and maximum salt thickness
models (Figure 3.2). If evaporite Vp is 3 km s-1 rather than 4.21 km s-1, the axial relief
reduces by about 40% (Figure 3.2), the axial relief (corrected for the isostatic loading)
would be 0.5-1.0 km rather than 0.8-1.6 km. However, even for the smaller axial relief
estimates, the axial high and the rising in basement towards the coasts are not
eliminated, so this uncertainty does not affect the interpretations of axial high and
ocean-continent boundaries. Lateral variations in evaporite Vp could distort the
seismically derived basement depth. However, we suggest this variation is minor,
since layering within the evaporites, which is an indicator of the presence of non-halite
components with lower velocities, does not vary along-axis (Izzeldin, 1987).
7.4 Acknowledgments
We thank David Sandwell and Walter Smith for leading the gravity and
bathymetry mapping initiatives, and for the group involved in producing the grids used
in our study. Figures were prepared using GMT software (Wessel et al., 2013). We
208
thank Ian C.F. Stewart for providing reduced-to-pole aeromagnetic anomaly grid. A
Royal Society (International Exchanges Scheme) grant to NCM enabled discussions
with colleagues Nico Augustin and Froukje van der Zwan that contributed to our
conclusions.
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giant: regional topography of the Red Sea Miocene evaporites: Basin Research,
v. 29, p. 352-369.
Mitchell, N. C., M. Ligi, V. Ferrante, E. Bonatti, and E. Rutter, 2010, Submarine salt
flows in the central Red Sea: Geological Society of America Bulletin, v. 122, p.
701-713.
Mitchell, N. C., and R. A. Livermore, 1998, Spiess Ridge: An axial high on the slow
spreading Southwest Indian Ridge: Journal of Geophysical Research: Solid
Earth, v. 103, p. 15457-15471.
Park, Y., A. A. Nyblade, A. J. Rodgers, and A. Al‐Amri, 2007, Upper mantle structure
beneath the Arabian Peninsula and northern Red Sea from teleseismic body
wave tomography: Implications for the origin of Cenozoic uplift and volcanism
in the Arabian Shield: Geochemistry, Geophysics, Geosystems, v. 8 (Paper
Q06021, doi:10.1029/2006GC001566).
Park, Y., A. A. Nyblade, A. J. Rodgers, and A. Al‐Amri, 2008, S wave velocity structure
of the Arabian Shield upper mantle from Rayleigh wave tomography:
Geochemistry, Geophysics, Geosystems, v. 9 (Paper Q07020,
doi:10.1029/2007GC001895).
Phillips, J. D., 1970, Magnetic anomalies in the Red Sea: Philosophical Transactions of
the Royal Society of London A: Mathematical, Physical and Engineering
Sciences, v. 267, p. 205-217.
Salem, A., C. Green, S. Campbell, J. D. Fairhead, L. Cascone, and L. Moorhead, 2013,
Moho depth and sediment thickness estimation beneath the Red Sea derived
from satellite and terrestrial gravity data: Geophysics, v. 78, p. G89-G101.
Sandwell, D. T., R. D. Muller, W. H. F. Smith, E. Garcia, and R. Francis, 2014, New global
marine gravity model from CryoSat-2 and Jason-1 reveals buried tectonic
structure: Science, v. 346, p. 65-67.
Shi, W., N. C. Mitchell, L. M. Kalnins, and A. Y. Izzeldin, 2018, Oceanic-like axial crustal
high in the central Red Sea: Tectonophysics, v. 747-748, p. 327-342.
211
Stoffers, P., and R. Kühn, 1974, Red Sea evaporites: a petrographic and geochemical
study: Init. Rep. DSDP, v. 23, p. 821-847.
Sultan, M., R. Becker, R. E. Arvidson, P. Shore, R. J. Stern, Z. Elalfy, and E. A. Guinness,
1992, Nature of the Red Sea crust: A controversy revisited: Geology, v. 20, p.
593-596.
Talwani, M., C. C. Windisch, and M. G. Langseth, 1971, Reykjanes ridge crest: A
detailed geophysical study: Journal of Geophysical Research, v. 76, p. 473-517.
Tapponnier, P., J. Dyment, M. Zinger, D. Franken, A. Afifi, A. Wyllie, H. Ali, and I. Hanbal,
2013, Revisiting Seafloor-Spreading in the Red Sea: Basement Nature,
Transforms and Ocean-Continent Boundary: AGU Fall Meeting Abstracts
(T12B-04).
Tramontini, C., and D. Davies, 1969, A seismic refraction survey in the Red Sea:
Geophysical Journal International, v. 17, p. 225-241.
Vine, F. J., 1966, Spreading of the ocean floor: new evidence: Science, v. 154, p. 1405-
1415.
Wessel, P., W. H. Smith, R. Scharroo, J. Luis, and F. Wobbe, 2013, Generic mapping
tools: improved version released: Eos, Transactions American Geophysical
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212
Chapter 8.
Conclusion and future work
213
8. Conclusion and future work
8.1 Conclusions
Understanding the processes that occur during the transition from continental
rifting to seafloor spreading is important in exploring how the Earth works and has
been a major challenge of Plate Tectonics. The Red Sea provides an important
example of transition from nearly orthogonal slow continental rifting to seafloor
spreading. Seafloor spreading in the southern Red Sea began at least by 5 Ma (e.g.,
Cochran, 1983; Girdler and Styles, 1974; Phillips, 1970; Roeser, 1975; Vine, 1966). But
how far the central Red Sea is through the transition to full seafloor spreading has
been controversial and is still open to debate. Contributing to this debate, this study
assessed the crustal type (whether the crust is continental or oceanic) in the central
Red Sea by evaluating the basement geometry and roughness.
We corrected for effects of overlying evaporite and other sediments to
reconstruct basement geometry from 11 seismic reflection lines. The seismically
derived basement depths corrected for evaporite and other sediment loading reveal
an axial high. Such a high is not typically found at continental rifts but is common for
mid-ocean ridges near to mantle hotspots, such as the Reykjanes Ridge near Iceland
or Spiess Ridge on the similarly ultra-slow spreading Southwest Indian Ridge near to
the Bouvet hotspot. Its relief of ~1 km relative to a background subsidence trend is
within the observed range. It is similar to that at Spiess Ridge, larger than that at
Reykjanes Ridge, but smaller than that of the Mid-Atlantic Ridge near the Azores.
To further assess the basement geometry, the inverse method of Werner
deconvolution is improved and used to invert aeromagnetic anomalies for magnetic
basement depths. The improved Werner deconvolution effectively maps out the axial
plateau and valleys in the crustal basement. The results confirm that the basement
topography in the region away from the seismic lines also has an axial plateau within
~60 km of the axis. The basement axial plateau shallows southward, consistent with
increasing influence of the Afar plume.
214
Basement roughness values are computed in profiles both across and parallel
to the axis. The values from axis-crossing seismic data are ~230 m, similar to those
observed at other ultraslow and slow spreading ridges. The roughness values derived
from axis-parallel profiles of the gravity field (200-550 m) are comparable with those
of the Mid-Atlantic Ridge where it has similar along-axis segmentations. Although
these basement roughness values by themselves do not exclude an extended
continental crust interpretation in the central Red Sea, they are supportive of an
oceanic crustal interpretation when considered along with other evidences including
basement axial high, reduced-to-pole magnetic anomalies, and along-axis gradients in
mantle Bouguer anomalies.
Therefore, this study suggests that the entire axial zone in the central Red Sea
is underlain by oceanic crust and the central part of the Red Sea rift is an ultra-slow
spreading ridge influenced by the Afar hotspot, further supporting the idea that the
oceanic spreading inception is synchronous in the central Red Sea along the spreading
ridge.
Bouguer gravity anomalies are found strongly correlated with basement
depths from seismic reflection data within ~60 km of the axis. The apparent density
contrast implied by the correlation (220 to 580 kg m-3) is too small to be caused
primarily by the density contrast between evaporites and mantle across a crust of
uniform thickness and density structure, implying thickened crust and/or low mantle
densities beneath the ridge axis.
Geochemical data (Na8.0) suggest that the crust has normal thickness beneath
the present axis, while the rugged basement topography is consistent with a slow to
ultra-slow spreading ridge with cold, rigid lithosphere and thin crust. To reconcile the
axial high and gravity inversion results, which suggest thickening crust towards the
present day, with these other observations, this study suggests that the crust was
unusually thin earlier in the evolution of the basin and has recently thickened to a
more normal thickness for a slow-spreading ridge.
Finally, a geological map of the central Red Sea was produced based on the
studies in previous chapters. It shows that the transitions between oceanic and
215
extended continental crust tend to be symmetrical about the axis, suggesting that
seafloor spreading has been symmetric. The extended continental crust on either side
of the oceanic crust also appears to be symmetric implying that continental extension
was symmetric here too.
8.2 Future work suggestions
8.2.1 Future work in the Red Sea
To further study the transition from continental rifting to seafloor spreading
along the Red Sea rift, four suggestions are proposed:
(1) Basement geometry in the southern Red Sea
This study has suggested that the central Red Sea rift is an ultra-slow spreading
ridge influenced by the Afar hotspot, since there is an axial crustal high found along
the ridge. To some extent, this interpretation could be assessed by checking whether
there is a similar axial crustal high in the southern Red Sea or not, because the
southern Red Sea rift is an ultra-slow spreading ridge (e.g., Cochran, 1983; Girdler and
Styles, 1974; Phillips, 1970; Vine, 1966). Moreover, the comparison of axial reliefs in
the central and southern Red Sea could be used to assess indirectly effects of
differences in enhanced mantle melting volumes in these two regions.
Therefore, the basement geometry (corrected for isostatic loading) in the
southern Red Sea is suggested to be evaluated using seismic reflection, seismic
refraction, gravity, and magnetic data.
(2) Magnetic source distributions and susceptibilities in the southern and
northern Red Sea
Werner deconvolution method could be used to find the source of magnetic
anomalies in the southern Red Sea (where we are certain that seafloor spreading has
begun) and in the northern Red Sea, and compare the source depths, susceptibilities,
and numbers along the entire Red Sea. The trends with latitude in these parameters
could help to improve the understanding of the transition. Besides, there is a
possibility that these magnetic source properties instead reveal the influence of the
216
sedimentary magnetism, i.e., from magnetic minerals carried into the Red Sea by wind
at present and rivers during wetter periods of the past.
(3) Numerical modelling of structural development in the central Red Sea
To clarify the 28-0 Ma structural development of southeastern Red Sea margin,
Dwivedi and Hayashi (2009) carried out a numerical modelling using a 2D elastic finite
element (FE) package (Hayashi, 2008) in which the geological structure was
asymmetrical as suggested by Voggenreiter et al. (1988). This numerical modelling
was performed along a seismic refraction profile (Mooney et al., 1985), which
provided some constraints of crustal geometry. This seismic section is close to the
Farasan Islands. We suggest that similar numerical modelling could be performed
along the seismic refraction profile SO53-PIII of Egloff et al. (1991) in the central Red
Sea.
(4) Analogue modelling of the Red Sea rift
Analogue experiments carried out by Molnar et al. (2017) were used to
investigate how propagating rifts interact with preexisting structures during the
transition from continental rifting to seafloor spreading. However, these analogue
experiments only simulated the structural evolution around the Danakil microplate in
the southern Red Sea. We suggest that similar analogue experiments could be
performed along the whole Red Sea rift to help to assess the structural evolution in its
geological past.
8.2.2 Apply Werner deconvolution in other areas
This study has shown the feasibility and applicability of Werner deconvolution
of magnetic data in the central Red Sea. The Werner method could be useful in studies
of oceanic crust in other areas that lack of other information from seismic or other
methods. For example, lineaments in the central Pacific gravity field were originally
thought to originate from rolls in Earth’s mantle (Haxby and Weissel, 1986). The more
recent maps of the gravity field show them to be more extensive but with orientations
that may suggest other origins (Gans et al., 2003; Mitchell and Davies, 2018). The
Werner method could provide an alternative measure of basement elevations to help
217
to address the gravity lineament origins. In the Gulf of Mexico, the locations of ocean-
continent boundaries have not been precisely determined and the kinematics of
Jurassic opening still remain poorly known, because seismic imaging of underlying
crust structure is complicated by the thick evaporite and sediment layers, the
combination of which exceeds 12 km in thickness (Galloway et al., 2000; Ibrahim et al.,
1981; Nguyen and Mann, 2016). In this area, if not too badly affected by sedimentary
magnetic sources, the Werner method could be used to derive the basement
topography, which might be useful for addressing those unsolved questions.
The Woodlark Basin is another young ocean basin where the transition from
continental extension to seafloor spreading can be observed (Martinez et al., 1999;
Weissel et al., 1982). The structure of the crust and upper mantle in the Woodlark
Basin is important for understanding the processes of this transition (Ferris et al.,
2006). The correlation between the Bouguer anomalies and the basement depths
could be used to assess the variations in crustal thickness or density or in mantle
density in this region.
8.3 References
Augustin, N., F. M. van der Zwan, C. W. Devey, M. Ligi, T. Kwasnitschka, P. Feldens, R.
A. Bantan, and A. S. Basaham, 2016, Geomorphology of the central Red Sea
Rift: Determining spreading processes: Geomorphology, v. 274, p. 162-179.
Cochran, J. R., 1983, A model for development of Red Sea: AAPG Bulletin, v. 67, p. 41-
69.
Dwivedi, S. K., and D. Hayashi, 2009, Numerical modeling of the development of
southeastern Red Sea continental margin: Earthquake Science, v. 22, p. 239-
249.
Egloff, F., R. Rihm, J. Makris, Y. A. Izzeldin, M. Bobsien, K. Meier, P. Junge, T. Noman,
and W. Warsi, 1991, Contrasting structural styles of the eastern and western
margins of the southern Red Sea - the 1988 Sonne Experiment: Tectonophysics,
v. 198, p. 329-353.
218
Ferris, A., G. A. Abers, B. Zelt, B. Taylor, and S. Roecker, 2006, Crustal structure across
the transition from rifting to spreading: the Woodlark rift system of Papua New
Guinea: Geophysical Journal International, v. 166, p. 622-634.
Galloway, W. E., P. E. Ganey-Curry, X. Li, and R. T. Buffler, 2000, Cenozoic depositional
history of the Gulf of Mexico basin: AAPG bulletin, v. 84, p. 1743-1774.
Gans, K. D., D. S. Wilson, and K. C. Macdonald, 2003, Pacific Plate gravity lineaments:
Diffuse extension or thermal contraction?: Geochemistry, Geophysics,
Geosystems, v. 4, doi:10.1029/2002GC000465, 9.
Girdler, R., and P. Styles, 1974, Two stage Red Sea floor spreading: Nature, v. 247, p.
7-11.
Haxby, W. F., and J. K. Weissel, 1986, Evidence for small‐scale mantle convection
from Seasat altimeter data: Journal of Geophysical Research: Solid Earth, v. 91,
p. 3507-3520.
Hayashi, D., 2008, Theoretical basis of FE simulation software package: Bull. Fac. Sci.
Univ. Ryukyus, v. 85, p. 81-95.
Ibrahim, A., J. Carye, G. Latham, and R. Buffler, 1981, Crustal structure in Gulf of
Mexico from OBS refraction and multichannel reflection data: AAPG Bulletin,
v. 65, p. 1207-1229.
Martinez, F., B. Taylor, and A. M. Goodliffe, 1999, Contrasting styles of seafloor
spreading in the Woodlark Basin: Indications of rift ‐ induced secondary
mantle convection: Journal of Geophysical Research: Solid Earth, v. 104, p.
12909-12926.
Mitchell, N. C., and H. Davies, 2018, Equatorial Pacific gravity lineaments:
interpretations with basement topography along seismic reflection lines:
Marine Geophysical Research, p. 1-15.
Molnar, N., A. Cruden, and P. Betts, 2017, Interactions between propagating rotational
rifts and linear rheological heterogeneities: Insights from three‐dimensional
laboratory experiments: Tectonics, v. 36, p. 420-443.
Mooney, W. D., M. E. Gettings, H. R. Blank, and J. H. Healy, 1985, Saudi Arabian
seismic-refraction profile: a traveltime interpretation of crustal and upper
mantle structure: Tectonophysics, v. 111, p. 173-246.
219
Nguyen, L. C., and P. Mann, 2016, Gravity and magnetic constraints on the Jurassic
opening of the oceanic Gulf of Mexico and the location and tectonic history of
the Western Main transform fault along the eastern continental margin of
Mexico: Interpretation, v. 4, p. SC23-SC33.
Phillips, J. D., 1970, Magnetic anomalies in the Red Sea: Philosophical Transactions of
the Royal Society of London A: Mathematical, Physical and Engineering
Sciences, v. 267, p. 205-217.
Roeser, H. A., 1975, A detailed magnetic survey of the southern Red Sea: Geologisches
Jahrbuch, v. 13, p. 131-153.
Vine, F. J., 1966, Spreading of the ocean floor: new evidence: Science, v. 154, p. 1405-
1415.
Voggenreiter, W., H. Hötzl, and A. Jado, 1988, Red Sea related history of extension and
magmatism in the Jizan area (Southwest Saudi Arabia): indication for simple-
shear during early Red Sea rifting: Geologische Rundschau, v. 77, p. 257-274.
Weissel, J. K., B. Taylor, and G. D. Karner, 1982, The opening of the Woodlark Basin,
subduction of the Woodlark spreading system, and the evolution of northern
Melanesia since mid-Pliocene time: Tectonophysics, v. 87, p. 253-277.
220
Appendices
221
Appendices
Appendix 1
Depths derived from the seismic reflection profiles of Izzeldin (1982, 1987) and
Werner deconvolution of marine magnetic data
222
223
224
225
226
Figure A1.1 Depths derived from the seismic reflection profiles of Izzeldin (1982, 1987) and
Werner deconvolution of shipboard marine magnetic data. Line numbers are shown in the
lower right corner of each panel. Dark green, cyan, and red lines are the depths of the seabed,
the S-reflection at the top of the Miocene evaporites, and the basement, respectively, derived
from the seismic reflection data. Grey circles are Werner source depth solutions, with circle
size proportional to 𝑙𝑜𝑔2(𝜒𝑚 + 2). (For more details, please refer to Chapter 4 (Figure 4.4).)
227
Appendix 2
Matlab codes for 2D Werner deconvolution and Marquardt’s (1963) inverse
modelling method
(1) Codes for 2D Werner deconvolution
%%%%%%% clear; clc; close all; pathname='D:\Magneticdepth\forthesis\'; filename='78005111cut377_524distance9.txt'; fpath1=[pathname filename]; fid1=fopen(fpath1,'r'); data=fscanf(fid1,'%f %f %f %f',[4 inf]); %% Load data%% data=data'; fclose('all'); [mm_dat,nn_dat]=size(data); Lo1=data(:,1); %% Load longitude%% La1=data(:,2); %% Load latitude%% x1=data(:,3); %% Load distance%% y1=data(:,4); %% Load magnetic anomalies%% inter=1; inx=0:inter:max(x1); iny=interp1(x1,y1,inx,'PCHIP'); %%Interpolation, 'inx' has a resolution of 1 m%% inx=inx'; iny=iny'; n_iny=length(iny); result=zeros(n_iny,2); %% Array 'result' is used to save the distance and depth of the magnetic source%% result2=zeros(n_iny,8); %% Array 'result2' is used to save distance, a0, a1, a2, a3, a4, b0, and b1 (Chapter3; Equation 3.4)%% m_result=0; m_result2=0;
228
delt_x=100; %% Sample spacing is 100 m%% while delt_x<(n_iny/6) %% Sample spacing should be shorter than 1/6 length of the survey line%% disp(delt_x); start_i=3*delt_x+1; %% Starting point for the calculation %% for i_window=start_i:1000:n_iny-start_i %% Calculation window%% syms a0_w a1_w a2_w a3_w a4_w b0_w b1_w f_w=sym('A', [7 1]); TMAG=zeros(7,1); %% Magnetic anomalies at 7 sampling points%% TMAG(1)=iny(i_window-3*delt_x); TMAG(2)=iny(i_window-2*delt_x); TMAG(3)=iny(i_window-delt_x); TMAG(4)=iny(i_window); TMAG(5)=iny(i_window+delt_x); TMAG(6)=iny(i_window+2*delt_x); TMAG(7)=iny(i_window+3*delt_x); for i_werner=1:7 %% Conduct simultaneous equations (there are 7 equations) %% n_werner=i_werner-4; f_w(i_werner)= a0_w+a1_w*n_werner+a2_w*(n_werner)^2+... a3_w*(n_werner)^3+a4_w*(n_werner)^4+b0_w*TMAG(i_werner)... +b1_w*n_werner*TMAG(i_werner)-(n_werner)^2*TMAG(i_werner); end A_m=zeros(7,7); %% Initial coefficients (left side) %% b_m=zeros(7,1); %% Initial coefficients (right side) %% a_m=zeros(7,1); %% Initial solution for Marquardt's method%% for p_A=1:7 %% Get initial coefficients (both left and right sides) %% nn_A=p_A-4; A_m(p_A,1)=1; A_m(p_A,2)=nn_A; A_m(p_A,3)=nn_A^2; A_m(p_A,4)=nn_A^3; A_m(p_A,5)=nn_A^4; A_m(p_A,6)=TMAG(p_A); A_m(p_A,7)=nn_A*TMAG(p_A); b_m(p_A)=(nn_A^2)*TMAG(p_A); end
229
a_m=A_m\b_m; %% Compute initial solution for Marquardt's method%% j_illcodition=rcond(A_m); f_illcodition=j_illcodition<1e-12; fnan=any(isnan(a_m)); finf=any(isinf(a_m)); if fnan||finf||f_illcodition %% If the initial solution is derived from ill-conditioned equations or has some extraneous roots, use pseudoinverse to compute the initial solution again%% a_m=pinv(A_m)*b_m; x0_w=a_m'; else x0_w=a_m'; end [r,mf]=Marquardt(f_w,x0_w,0.4,1.2,1.5,[a0_w;a1_w;a2_w;a3_w;a4_w;b0_w;b1_w]); %% Solve the simultaneous equations using Marquardt's method%% solution_w=double(r); %% Solution of the simultaneous equations%% sa0_w=solution_w(1)*(delt_x^2); %% a0 %% sa1_w=solution_w(2)*delt_x; %% a1 %% sa2_w=solution_w(3); %% a2 %% sa3_w=solution_w(4)/delt_x; %% a3 %% sa4_w=solution_w(5)/(delt_x^2); %% a4 %% sb0_w=solution_w(6)*delt_x^2; %% b0 %% sb1_w=solution_w(7)*delt_x; %% b1 %% accurecy_w=double(mf); sx0=0.5*sb1_w; %% Distance of the magnetic source%% sD=sqrt(-sb0_w-(sx0^2)); %% Depth of the magnetic source%% if sD>300 && sD<16000 %% Depth between 300 m and 16000 m%% m_result=m_result+1; result(m_result,1)=inx(i_window)+sx0; %%% Save distance%% result(m_result,2)=sD; %%% Save depth%% m_result2=m_result2+1; result2(m_result2,1)=inx(i_window)+sx0; %%% Save distance%% result2(m_result2,2)=sa0_w; %% Save a0%%
230
result2(m_result2,3)=sa1_w; %% Save a1%% result2(m_result2,4)=sa2_w; %% Save a2%% result2(m_result2,5)=sa3_w; %% Save a3%% result2(m_result2,6)=sa4_w; %% Save a4%% result2(m_result2,7)=sb0_w; %% Save b0%% result2(m_result2,8)=sb1_w; %% Save b1%% end end delt_x=delt_x+500; end result=result(1:m_result,:); result2=result2(1:m_result2,:); M_print=result'; fidout1=fopen([fpath1(1:length(fpath1)-4),'_Distance_sourcedepth.dat'],'wt'); fprintf(fidout1, '%12.6f %12.6f\n',M_print); %% Write distances and depths of the magnetic sources to text file%% fclose('all'); M_print2=result2'; fidout2=fopen([fpath1(1:length(fpath1)-4),'_aANDb.dat'],'wt'); fprintf(fidout2, '%12.12f %12.12f %12.12f %12.12f %12.12f %12.12f %12.12f %12.12f\n',M_print2); %% Write distances, a0, a1, a2, a3, a4, b0, and b1 to text file%% fclose('all'); fpath2=[fpath1(1:length(fpath1)-4) '_Distance_sourcedepth.dat']; fid2=fopen(fpath2,'r'); if fid2>0 %% Confirm the text file is available%%
dat2=fscanf(fid2,'%f %f',[2 inf]); %% Load distances and depths of the magnetic sources%%
dat2=dat2'; fclose('all'); [mm_dat2,nn_dat2]=size(dat2);
data3=zeros(mm_dat2,4); %% Array 'mm_data3' is used to save distance, depth, and susceptibility of magnetic source%%
fpath4=[fpath1(1:length(fpath1)-4) '_aANDb.dat'];
231
fid4=fopen(fpath4,'r'); dat4=fscanf(fid4,'%f %f %f %f %f %f %f %f',[8 inf]); %% Load distance, a0, a1, a2, a3, a4, b0, and b1%%
dat4=dat4'; fclose('all'); mm_data3=0; %% Pointer of 'mm_data3'%% for kk=1:mm_dat2 flag1=dat2(kk,1)>0 && dat2(kk,1)<max(x1); %% Confirm the solutions in text file are available%% flag2=dat2(kk,2)>300 && dat2(kk,2)<16000; %% Depth between 300 m and 16000 m%% if flag1 && flag2 mm_data3=mm_data3+1; data3(mm_data3,1)=dat2(kk,1); data3(mm_data3,2)=dat2(kk,2); sa0_w=dat4(kk,2); %% a0%% sa1_w=dat4(kk,3); %% a1%% sa2_w=dat4(kk,4); %% a2%% sa3_w=dat4(kk,5); %% a3%% sa4_w=dat4(kk,6); %% a4%% sb0_w=dat4(kk,7); %% b0%% sb1_w=dat4(kk,8); %% b1%% sx0=0.5*sb1_w; sD=sqrt(-sb0_w-(sx0^2)); sC2=sa4_w; %% Compute C2 (Chapter3; Equation 3.4)%% sC1=sa3_w+2*sx0*sC2; %% Compute C1 (Chapter3; Equation 3.4)%% sC0=sa2_w+2*sC1*sx0-sC2*(sx0^2)-sC2*(sD^2); %% Compute C0 (Chapter3; Equation 3.4)%% sA=sa1_w+2*sC0*sx0-sC1*(sx0^2)-sC1*(sD^2); %% Compute A (Chapter3; Equation 3.4)%% sB=(1/sD)*(sa0_w+sA*sx0-sC0*(sD^2)-sC0*(sx0^2)); %% Compute B (Chapter3; Equation 3.4)%% sI=30; %% Magnetic inclination%% salp=45; %% Strike of the tabular body%% sVx=cosd(sI)*sind(salp);
232
sVz=sind(sI); b_width=100; %% Half of the dike thickness is assumed as 100 m%% sJx=((-1)*(sB*sVx+sA*sVz))/(2*b_width*((sVx)^2+(sVz)^2)); %% Compute magnetization in x direction%% sJz=(-sA*sVx+sB*sVz)/(2*b_width*((sVx)^2+(sVz)^2)); %% Compute magnetization in z direction%% H_earth=40000; %% Earth main field is assumed as 40000 nT%% M_total=sqrt((sJx)^2+(sJz)^2); sms=M_total/(H_earth); %% Susceptibility %% data3(mm_data3,3)=sms; data3(mm_data3,4)=M_total; end end data3=data3(1:mm_data3,:); Ds2=data3(:,1); depth=data3(:,2); Msms=data3(:,3); Mtotal=data3(:,4); M_print=[Ds2,depth,Msms]'; fidout1=fopen([fpath1(1:length(fpath1)-4),'_WernerSolutions.dat'],'wt');
fprintf(fidout1, '%12.6f %12.6f %12.6f\n',M_print); %% Write distance, depth, and susceptibility of magnetic source to text file%%
fclose('all'); figure subplot(2,1,1); %% Plot out magnetic anomalies%% plot(x1./1000,y1); xlim([min(x1)./1000 max(x1)./1000]); xlabel('Distance (km)'); ylabel('Magnetic anomaly (nT)'); ss=char(filename(1:length(filename)-4)); bb=strrep(ss,'_','\_'); title(bb,'fontsize',12); subplot(2,1,2); %% Plot out Werner Solutions%% plot(Ds2./1000,depth./1000,'* ','Linewidth',3); for j_s=1:length(Ds2)
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ssm=num2str(Msms(j_s),6); text(Ds2(j_s)./1000,depth(j_s)./1000,ssm(1:4)); end xlim([min(x1)./1000 max(x1)./1000]); set(gca,'YDir','reverse'); xlabel('Distance (km)'); ylabel('Depth (km)'); set(gcf, 'position', [20 50 1500 700]); saveas(gcf,[pathname,'WernerSolutions.emf']); saveas(gcf,[pathname,'WernerSolutions.fig']); close all; end %%%%%%%
(2) Codes for Marquardt’s (1963) inverse modelling method
%%%%%%% function [x,Marf] = Marquardt(f,x0,Pa,u,v,aANDb) %% f: simultaneous equations; x0: initial solution; Pa: coordination factor; u: damping factor; v: amplification factor; aANDb: Independent variables; %% format long; jin=1.0e-8; %% Required smallest value of dx (dx is increment of independent variables) is 1.0e-8%% FF=transpose(f)*f; %% Sum of the squares of f %% m=length(f); x0=transpose(x0); %% Transpose%% n=length(x0); A=jacobian(f,aANDb); %% Compute Jacobian matrix%% sw=1; %% sw is used to record the norm (size) of dx (dx is increment of independent variables) later%% nn=0; %% nn is the number of iterations%% while sw>jin&&nn<20000 nn=nn+1; Fx=zeros(m,1); for i=1:m Fx(i,1)=Funval(f(i),aANDb,x0); %% Values of f at x0 %% end
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FFx=Funval(FF,aANDb,x0); %% Value of FF at x0 %% Ax=Funval(A,aANDb,x0); %% Value of A at x0 %% gFFx=transpose(Ax)*Fx; %% Gradient of FF %% AW=transpose(Ax)*Ax; while 1 dx=-(AW+u*eye(size(AW)))\gFFx; %% Increment of independent variables%% x1=x0+dx; for i=1:m Fx1(i,1)=Funval(f(i),aANDb,x1); %% Values of f at x1 %% end FFx1=Funval(FF,aANDb,x1); %% Values of FF at x1 %% sw=norm(dx); %% The size of dx %% if sw<=jin %% If sw is small enough (smaller than the required smallest value), break the loop%% break; end if FFx1>=FFx+Pa*transpose(gFFx)*dx %% If FFx1 is not small enough (still >=FFx+Pa*transpose(gFFx)*dx), update u %% u=u*v; continue; %% Increase u and continue testing u in the present loop %% else u=u/v; break; %% Decrease u and go to the outer iteration, which is searching for the final solution %% end
end x0=x1; %% x1 becomes a new initial solution %%
end x=x0; %% The final solution %% Marf=Funval(FF,aANDb,x); %% The minimum value of FF%% format short; %%%%%%%
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References
Izzeldin, A., 1982, On the structure and evolution of the Red Sea: PhD Diss. Univ.
Strasbourg.
Izzeldin, A., 1987, Seismic, gravity and magnetic surveys in the central part of the Red
Sea: their interpretation and implications for the structure and evolution of the
Red Sea: Tectonophysics, v. 143, p. 269-306.
Marquardt, D. W., 1963, An algorithm for least-squares estimation of nonlinear
parameters: Journal of the Society for Industrial and Applied Mathematics, v.
11, p. 431-441.