Advanced Processing and Interpretation

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Advanced Processing and Interpretationof Gravity and Magnetic Data

Prepared by GETECH

Processing and Interpretation of G&M Data

This short document is intended to provide background theory and methodology of the uses of

gravity and magnetic data in exploration.

Section 1 discusses the interpretation process itself, outlining the importance of qualitative

interpretation and the complementary roles that gravity and magnetic data offer.

Section 2 provides examples of the various types of enhancements (or transforms) applied to

gravity and magnetic data to highlight particular characteristics or features to aid qualitative

interpretation.

Section 3 describes additional advanced methods of quantitative processing in support of

interpretation that can be applied to gravity and magnetic data, including 3D gravity inversion,

depth to source estimation and 2D modelling.

advanced_processing_and_interpretation.doc GETECH Group plc 2007 - page 1


1. The Interpretation Process

As with all geophysical interpretation, the analysis of gravity and magnetic data has two distinct

aspects: qualitative and quantitative.

The qualitative process is largely map-based and dominates the early stages of a study. The

resultant preliminary structural element map is the cornerstone of the interpretation. Qualitative

interpretation involves recognition of:

the nature of discrete anomalous bodies including intrusions, faults and lenticular intra-sedimentary bodies - often aided by reference to characteristic magnetic response charts

and perhaps performing simple test models

disruptive cross-cutting features such as strike-slip faults effects of mutual interference relative ages of intersecting faults structural styles unifying tectonic features/events that integrate seemingly unrelated interpreted features

The most important element in this preliminary qualitative stage surprisingly is not the

interpretation of anomalous bodies themselves (that follows later) but rather the network of

discontinuities e.g. lines of truncation and strike-slip faults that serve to compartmentalise and

delimit discrete anomalies that at first sight may appear as a confused pattern of unravellable

anomalies. Strike-slip faults/shear zones, small and large-scale, are commonplace particularly

within intra-continental situations where crust is old, bearing witness to countless fault

reactivations. They provide the principal means by which major structures are truncated and

crustal stress is decoupled (fully or partially) from one crustal block to another.

The quantitative process. Putting lines on maps during the qualitative process is the start of

quantitative phase. Refinement of these locations begins with the determination of z i.e. depth

values. For example, depth estimates to tops of anomalous magnetic bodies are generated by a

number of means including: slope measurement methods, analytic methods such as Euler and

Werner. Gravity and magnetic modelling (ideally seismically controlled) including forward and

inversion approaches contribute significantly to location in x, y and z. Accurate results of all these

rely upon sensible qualitative recognition of body types.


Processing and Interpretation of G&M Data Interplay of the qualitative and the quantitative soon develops, particularly as computer

modelling proceeds. Not infrequently, the results of modelling alert the interpreter to unexpected

geological scenarios that necessitate a qualitative re-appraisal of certain anomalies, perhaps for

example even alluding to a change in the interpreted structural style for an entire study area. The

likelihood of this happening depends on whether the study zone lies within an under-explored

frontier area or is mature. The greater the seismic control within the modelling process, the less

ambiguous the model will be.

Once modelling is complete, the qualitative process reasserts itself on the basis of the mapped

gravity and magnetic data alone, by the interpolation and extrapolation of modelled features into

regions that do not benefit from modelling / seismic / well control. In this way, body geometries

can be more accurately defined on a map-wide basis, more precise xyz location of bodies

determined, and, interfering/overprinted bodies better recognised for what they are. Depth to

basement contour maps can also be generated, conditioning the contours manually to the

interpreted structural framework.

1.1 The supporting roles of gravity and magnetic data

Interpretation of magnetic data is theoretically more complex than the corresponding gravity

data due to:

the dipolar nature of the magnetic field, in contrast with the simpler monopolar gravity field

the latitude/longitude dependent nature of the induced magnetic response for a given body due to the variability of the geomagnetic field over the Earths surface

However, in practice it is often simpler than that of gravity due to the smaller number of contributory sources. Often, though not always, there is just one source - the magnetic

crystalline basement. The gravity response is, by contrast, generated by the entire

geologic section.

In the case of intrasedimentary bodies, the dipolar nature of the magnetic response is particularly

diagnostic of the disposition (e.g. dip) of the source. It is for this reason that it is important for the

interpreter to be familiar with a wide range of induced magnetic responses produced by simple

geological bodies at the geomagnetic field inclination for the region. Seeking mutual consistency


Processing and Interpretation of G&M Data of both gravity and magnetic interpretations ensures that ambiguities within the interpretation

are minimized.

Characteristic geomagnetically induced magnetic responses for regions close to the geomagnetic

equator.

Modelling of potential field data is an important aspect of the interpretation, and is often

performed using a bottom-up / outside-in / magnetics-first approach. This ensures that deep

magnetic basement sources, which impact regionally on the study area, are understood first,

before attention is focused on the detail within the area of interest. The interpreter should always

be aware of the potential confusion generated by overprinting of similar wavelength responses

caused by: (i) deep crustal features, (ii) laterally distal crustal features, and, (iii) broad centrally

located shallow crustal features. Resolving this confusion is invariably achieved by seeking

consistency between the modelled gravity and magnetic data, while adhering to sensible

geological principles and experience. The following expands on this process.

A magnetics first approach recognises that the sedimentary section often possesses little

significant magnetic susceptibility. The major proportion of magnetic signal is generated at

crystalline (igneous or metamorphic) basement level. This is useful, because unlike gravity where

the entire section contributes to the observed field, all but the shortest wavelength magnetic

responses can be ascribed to the underlying basement. If shallow intra-sedimentary magnetic

sources do exist, these are usually of short wavelength and sufficiently discrete to be recognised

for what they are. The modelling of the magnetic data is particularly important for extending

interpretation below the effective level of seismic penetration. Once the magnetic data have


Processing and Interpretation of G&M Data been interpreted in this way, consistency is then sought with the longer wavelength gravity

features. Any remaining long wavelength gravity anomalies may be more properly ascribed to

broad shallow sources, rather than to deep sources.

1.2 Magnetic response of N-S orientated features located at the Equator

Interpretation of magnetic anomalies close to the magnetic equator is complicated for several

reasons:

Ambient field is horizontal Ambient field is weak (~35,000 nT compared to up to 70,000 nT in higher latitudes) Structures striking N-S are difficult to identify

Magnetic anomalies are generated when the flux density cuts the boundary of a structure. If the

structure strikes parallel with the field then in Equatorial areas the flux stays within the structure

and no anomaly is generated.

Induced magnetic response of a 2D rifted basin striking W-E and N-S at or near the geomagnetic

equator. The sediments are assumed to have low susceptibility and the basement high susceptibility.

Small arrows show the induced magnetisation vector directions.


Processing and Interpretation of G&M Data A similar effect is seen when a magnetic field is reduced to the equator (RTE) instead of to the

pole (RTP), where N-S structures are difficult or impossible to identify in RTE maps. This is shown

below. In this example the TMI has Inclination = 62 and Declination = 12, thereby allowing

both stable RTP and RTE anomalies to be derived. In magnetic equatorial regions where

Inclination is less than say 15 then RTP is generally unstable and can not be derived.

Since faults and many structures have irregular shapes, albeit in regional form they may be 2D,

then parts of the structure will be magnetically imaged where the flux cuts the structural interface

generating dipole shape anomalies. Thus N-S striking structures may be identified by a string of

pearls i.e. line of magnetic dipole anomalies. The Analytic Signal is the best derivative to recover

the N-S contacts in equatorial regions as is shown by the diagram below.



2. Enhancements and Transformations of Potential Field Data

The area used in this series of images is a region of Poland traversed (NW-SE) by the Teisseyre-

Tornquist Zone which divides the shallower crystalline basement of the East European platform

to the NE, from the deeper West European platform to the SW. The thick Palaeozoic and

Mesozoic sedimentary cover of central Poland has undergone significant deformation (folding

and faulting) during the Caledonian, Variscan and Alpine orogenic phases. This has generated a

set of clear magnetic and gravity responses from basement and the sedimentary section that

allow similarities and differences to be clearly observed in the images generated.

The gravity images are on the left hand side of the page and the magnetic images are on the

right.

All the techniques described in this section were generated using GETECHs own GETgrid

software package. The software utilises FFT and spatial domain operators and has a host of

additional features (e.g. boolean logic, vector overlays, grid arithmetic).



Reduction to the Pole (RTP)

This technique transforms induced magnetic responses to those that would arise were the

sources placed at the magnetic pole (vertical field). This simplifies the interpretation because for

sub-vertical prisms or sub-vertical contacts (including faults), it transforms their asymmetric

responses to simpler symmetric and anti-symmetric forms. The symmetric highs are directly

centred on the body, while the maximum gradient of the anti-symmetric dipolar anomalies

coincides exactly with the body edge. Pole reduction is difficult at low magnetic latitudes, since

N-S bodies have no detectable induced magnetic anomaly at zero geomagnetic inclination. Pole

reduction is not a valid technique where there are appreciable remanence effects.

Pseudo-Gravity and Pseudo-Magnetic Fields

A magnetic grid may be transformed into a grid of pseudo-gravity. The process requires pole

reduction, but adds a further procedure which converts the essentially dipolar nature of a

magnetic field to its equivalent monopolar form. The result, with suitable scaling, is comparable

with the gravity map. It shows the gravity map that would have been observed if density were

proportional to magnetisation (or susceptibility). Comparison of gravity and pseudo-gravity maps

can reveal a good deal about the local geology. Where anomalies coincide, the source of the

gravity and magnetic disturbances is likely to be the same geological structure. (see Automatic

Lineament Tracing). Similarly, a gravity grid can be transformed into a pseudo-magnetic grid,

although this is a less common practice.


Processing and Interpretation of G&M Data Traditional Filtering

Filtering is a way of separating signals of different wavelength to isolate and hence enhance

anomalous features with a certain wavelength. A rule of thumb is that the wavelength of an

anomaly divided by three or four is approximately equal to the depth at which the body

producing the anomaly is buried. Thus filtering can be used to enhance anomalies produced by

features in a given depth range.

Traditional filtering can be either low pass (Regional) or high pass (Residual). Thus the technique

is sometimes referred to as Regional-Residual Separation. Bandpass filtering isolates wavelengths

between user-defined upper and lower cut-off limits.



Pseudo-depth Slicing

A potential field grid may be considered to represent a series of components of different

wavelength and direction. The logarithm of the power of the signal at each wavelength can be

plotted against wavelength, regardless of direction, to produce a power spectrum. The power

spectrum is often observed to be broken up into a series of straight line segments. Each line

segment represents the cumulative response of a discrete ensemble of sources at a given depth.

The depth is directly proportional to the slope of the line segment. Filtering such that the power

spectrum is a single straight line can thus enhance the effects from sources at any chosen depth

at the expense of effects from deeper or shallower sources. It is a data-adaptive process involving

spectral shaping. As such, it performs significantly better than arbitrary traditional filtering

techniques described above. When gravity and magnetic depth slices coincide it is a good

indication that the causative bodies are one and the same.



First Vertical Derivative z

VDR =

This enhancement sharpens up anomalies over bodies and tends to reduce anomaly complexity,

allowing a clearer imaging of the causative structures. The transformation can be noisy since it

will amplify short wavelength noise. In our example it clearly delineates areas of different data

resolution in the magnetic grid.



Total Horizontal Derivative 22

+

=

yxHDR

This enhancement is also designed to look at fault and contact features. Maxima in the mapped

enhancement indicate source edges. It is complementary to the filtered and first vertical

derivative enhancements above. It usually produces a more exact location for faults than the first

vertical derivative, but for magnetic data it must be used in conjunction with the other

transformations e.g. reduction to pole (RTP) or pseudo-gravity. Specific directional horizontal

derivatives can also be generated to highlight features with known strikes. This technique can be

applied to pseudo-depth slices to image structure at different depths.



Second Vertical Derivative 22

2 =VD

The second vertical derivative serves much the same purpose as residual filtering in gravity and

magnetic maps, in that it emphasises the expressions of local features, and removes the effects of

large anomalies or regional influences. The principal usefulness of this enhancement is that the

zero value for gravity data in particular closely follows sub-vertical edges of intrabasement blocks,

or the edges of suprabasement disturbances or faults. As with other derivative displays, it is

particularly helpful in the processing stage where it can be used to highlight line noise or mis-

levelling.

Analytic Signal (Total Gradient) 222

+

+

=

zyxAS

The analytic signal, although often more discontinuous than the simple horizontal gradient, has

the property that it generates a maximum directly over discrete bodies as well as their edges. The

width of a maximum, or ridge, is an indicator of depth of the contact, as long as the signal arising

from a single contact can be resolved. This transformation is often useful at low magnetic

latitudes because of the inherent problems with RTP, (at such low latitudes).



Automatic Lineament Tracing

The automatic lineament detection algorithm requires the data to have been processed (or

transformed) such that the edge of a causative body is located beneath a maximum in the grid.

Several transforms satisfy this requirement e.g. horizontal derivative of gravity (or of pseudo-

gravity, for magnetic data) and also analytic signal. The results help to quantify the different

gravity and magnetic responses of structures located in the shallow and deep sedimentary

sections and in the basement.

A significance factor N, ranging in value from 0 to 4, is assigned to each grid cell depending on

the relation to its neighbours. N=1 might represent a point on a spur, N=2 and N=3 a point on a

ridge and N=4 a point on a peak. The values of N are colour coded and displayed as a grid. These

lineament grids can then be displayed on top of any other grid.



Grid Display

Aside from the data transformations applied to grids it is often beneficial to display grids

themselves in a variety of ways. This ensures that the maximum amount of information contained

in the transforms can be utilised in the interpretation phase. The following three grids of gravity

data show the same data displayed in grey-scale shaded relief, colour shaded relief and in a dip-

azimuth display. Vector data (station locations, flight lines, coastlines etc.) can be added as an

overlay. The dip-azimuth display highlights slope changes in all directions and is therefore useful

for picking out multiple trends in the data simultaneously.



Tilt Derivative

= THDRVDRTDR 1tan

The Tilt derivative (TDR) is similar to the local phase, but uses the absolute value of the horizontal

derivative in the denominator

Due to the nature of the arctan trigonometric function, all amplitudes are restricted to values

between + /2 and - /2 (+90and -90) regardless of the amplitudes of VDR or THDR. This fact makes this relationship function like an Automatic Gain Control (AGC) filter and tends to equalise

the amplitude output of TMI anomalies across a grid or along a profile.

The Tilt derivatives vary markedly with inclination but for inclinations of 0and 90, its zero

crossing is located close to the edges of the model structures.

The Total Horizontal derivative of the TDR is independent of inclination, similar to the Analytic

Signal, but is sharper, generating better defined maxima centred over the body edges, which

persist to narrower features before coalescing into a single peak.



3. Quantitative Interpretation Techniques

The enhancement techniques described in Section 2 generally help to estimate the 2D spatial

location of structures and their edges but do not generally provide estimates of the depth. The

exceptions are the pseudo-depth slicing and the analytic signal. This section describes semi-

automated methods of depth estimation (3D Euler, Werner and SPI) and forward modelling of 2D

and 3D data. These are routinely used to model sub-surface structures constrained by seismic and

well data.

Euler deconvolution

GETECH has developed several in-house 3D anomaly interpretation packages for application to

total magnetic intensity (TMI) data, which employ Euler's homogeneity equation to identify

location, depth and nature of any sources present (Reid et al., 1990):

( ) ( ) ( ) ( )TBNzTzz

yTyy

xTxx 000 =

++

where:

(x0, y0, z0): the position of a source whose total field T is detected at any point (x,y,z)

B: the background value of the total field

N: the degree of homogeneity, interpreted physically as the attenuation rate with distance,

and geophysically as a structural index (SI):

Geological Model Number of Infinite dimensions Magnetic SI Gravity SI

Sphere 0 3 2

Pipe 1 (Z) 2 1

Horizontal cylinder 1 (X or Y) 2 1

Dyke 2 (Z and X or Y) 1 0

Sill 2 (X and Y) 1 0

Contact 3 (X, Y and Z) 0 NA


Processing and Interpretation of G&M Data Specification of the structural index N permits the equation to be solved for source position for a

specific source geometry within a given data window. This window is progressively "moved"

across the magnetic data grid, and solutions are generated within each. The process is repeated

for various window sizes and structural indices, and the optimum parameters for the data are

determined by clustering of output depth solutions and comparison with other available

information.

Solutions are generated for every window location, but for display purposes it is sensible to apply

any of several "solution selector" methods, which eliminate poorly defined solutions. Numerous

authors have proposed such methods. A simple criteria is the value of standard deviation of the

calculated depth for each solution, expressed as a percentage of the depth value - solutions with

a standard deviation above a given threshold are rejected. More sophisticated techniques

include calculating multiple solutions in each window using both the observed field and its

Hilbert transforms (Nabighian and Hansen, 2001), or analysing the eigenvalues and eigenvectors

of the Euler equations (Mushayandebvu et al, 2004). Refined solution sets for different window

sizes and SI values can be more easily interpreted in terms of subsurface structure.

a b c (a) Model topography, (b) forward modelled TMI field and (c) Euler solutions


Processing and Interpretation of G&M Data The Euler deconvolution results for a given study area typically comprise several hundred

thousand solutions with a large spread of depths. Williams (2004) showed that for any given

source structure, the individual depth estimates derived from methods such as Euler

deconvolution often exhibit considerable scatter, but that the mean depths for a cluster of

solutions provide a much more reliable estimate of the source depth. Tests performed on a

realistic 3D model1 show that if the mean values of coherent clusters of Euler solutions are

calculated, these show a similar relationship to the real depths as the total Euler solutions but

with a tighter spread and closer to a 1:1 correlation (see figures below). This process greatly

reduces the number of solutions enabling them to be more easily used in constructing a final

depth to basement map.

1 the model was created by taking a real topography dataset for an area with numerous exposed fault scarps of

varying size and orientation and then scaling these data to provide a buried topography analogue for the

faulted basement surface of a sedimentary basin.



Buried topography test. Plot of 2D constrained Euler solution depth versus model depth at the same x,y

location for homogeneous susceptibility basement model (from Williams, 2004).

Buried topography test. (a) Manually defined polygons (shown in grey) to isolate clusters of 2D

constrained Euler solutions (blue dots) for analysis of averaged source parameters. (b) Plot of mean

solution depths, plotted at the mean solution x,y location, of the solution clusters defined in (a), with

contours showing the basement depth in the same colour scale (contour interval 200 m). (c) Mean 2D

constrained Euler solution depth versus model depth (from Williams, 2004)


Processing and Interpretation of G&M Data Spectral Depth Method

The spectral depth method is based on the principle that a magnetic field measured at the

surface can therefore be considered the integral of magnetic signatures from all depths. The

power spectrum of the surface field can be used to identify average depths of source ensembles

(Spector and Grant, 1970). This same technique can be used to attempt identification of the

characteristic depth of the magnetic basement, on a moving data window basis, merely by

selecting the steepest and therefore deepest straight-line segment of the power spectrum,

assuming that this part of the spectrum is sourced consistently by basement surface magnetic

contrasts. A depth solution is calculated for the power spectrum derived from each grid sub-set,

and is located at the centre of the window. Overlapping the windows creates a regular,

comprehensive set of depth estimates. This approach can be automated, with the limitation

however that the least squares best-fit straight line segment is always calculated over the same

points of the power spectrum, which if performed manually would not necessarily be the case.

It should be noted that not all analytical depth methods will produce useful results for every study

due to the inapplicability of theoretical assumptions associated with the method and certain

configurations of magnetic sources (often related to source width/depth ratios and disparate

source geometries in close proximity).

For small windows of data the limited number of grid nodes often leads to power spectra

becoming jagged at the start or end. This is the reason for omitting the first point in the

automated determination of the deepest straight-line segment of the power spectra. To define a

straight line on the basis of a set of points (in a least squares statistical manner) a minimum of 2

points is required, but more are preferable. Increasing the number of points used to define the

straight line segment may conflict with obtaining the deepest characteristic source depths, as the

slope of the power spectrum reduces for increasing wavenumber / decreasing wavelength.

Depth results are generated for the entire dataset using different wavenumber ranges and

window sizes.



a

b

Radially averaged power spectrum for a subset of the magnetic grid.

Colour coded basement depth estimates derived from slope of linear sections in power spectrum for

each subset.

The Tilt Depth method

The zero contour of the Tilt angle locates source edges (for vertical contacts). Salem et al. (in

press) show that the half-distance between the +/-45 degree contours provides an estimate to

source depth. The tilt angle is normalized to within +/-90 degrees, so can be advantageous in

highlighting low amplitude features, although the method is of inherently lower resolution than

the local wavenumber, for example, since it relies on plotting zones derived from a first order

derivative. The depths are most reliable where the +/-45 degree contour corridor is linear with

consistent width. Depths are less reliable where the corridor is irregular, suggesting complex

sources interference between neighbouring anomalies.



Local Wavenumber or Source Parameter Imaging (SPI). Source Parameter Imaging or SPI (Thurston and Smith, 1997, Fairhead et al, 2004) is a profile or grid-based method for estimating magnetic source depths, and for some source geometries the

dip and susceptibility contrast. The method utilises the relationship between source depth and

the local wavenumber (k) of the observed field, which can be calculated for any point within a

grid of data via horizontal and vertical gradients. At peaks in the local wavenumber grid, the

source depth is equal to n/k, where n depends on the assumed source geometry (analogous to

the structural index in Euler deconvolution) - for example n=1 for a contact, n=2 for a dyke. Peaks

in the wavenumber grid are identified using a peak tracking algorithm (for example Blakely and

Simpson, 1986) and valid depth estimates isolated. Advantages of the SPI method over Euler

deconvolution or spectral depths are that no moving data window is involved and the

computation time is relatively short. On the other hand, there is no way to assess the reliability of

each depth estimate, and the need to calculate second order derivatives of the observed data

means noise can be a problem. Errors due to noise can be reduced by careful filtering of the data

before depths are calculated.

Phillips et al (2006) proposed a method of analysing the local wavenumber to derive estimates of

source depth and structural index. This method looks at the peaks of the in terms of both the

amplitude and curvature, and a depth estimate is generated that is independent of structural

index. The structural index can in fact be estimated from the data, and the estimate of structural

index can provide a means of discriminating between reliable and spurious depth estimates.

a b (a) synthetic TMI field and (b) Local wavenumber depth estimates


Processing and Interpretation of G&M Data 3D Gravity Stripping and Inversion

A grid of gravity can be inverted to yield a grid of the depth variation of a significant density

boundary, commonly the base of a sedimentary basin. The technique involves stripping off the

gravity effects of known layers, seismically determined, within the sub-surface before inverting for

the structure of a deep density boundary. For example, the structure and densities of shallow

sedimentary horizons in a basin may be well known from seismic and well data, but the basement

may not be adequately imaged from the seismic data due to the presence of salt or volcanics.

The gravity effect of each of the known sedimentary layers is calculated from forward modelling

and subtracted from the observed gravity anomaly. The residual anomaly is then inverted to

provide the depth to the top of the basement.

2D Profile Modelling

GETECH uses the GM-SYS modelling software from Northwest Geophysical Associates, Inc. (NGA).

It is an interactive forward modelling program which calculates the gravity and magnetic

response from a user defined hypothetical geologic model. Any differences between the model

response and the observed gravity and/or magnetic field are reduced by refining the model

structure or properties (e.g. density or susceptibility of model components).

It should be noted that gravity and magnetic models are non unique, i.e. many earth models can

produce the same gravity and/or magnetic response, and similarly, several geological lithologies

may be interpreted from a given model blocks density and susceptibility properties. It is

therefore important to use as many independent sources of information as possible to help

constrain the model, e.g. seismic structural horizons and density logs from wells located near the

profile. Such control may be included in the GM-SYS model as image backgrounds (e.g. depth

converted seismic lines) or as symbols (e.g. wells with lithology tops annotated with depth).


Processing and Interpretation of G&M Data 2D modelling assumes two dimensionality of every model component block, i.e. the model may

change with depth (Z direction) and along the profile (X direction, perpendicular to strike), as

defined by the program user, but does not change along strike (Y direction). A 2D model may be

visualised as a number of tabular prisms with their axes perpendicular to the profile with blocks

and surfaces assumed to extend to infinity in the strike direction. These restrictions inherently

assume that the modelled profiles do not change direction along the model extent.

The models created by GM-SYS extend to depths of 50 km by default, and therefore the whole

crustal structure can be modelled. This is advantageous as the observed gravity field is

contributed to by the entire geologic section. To accurately model the upper crustal, residual

components requires accurate definition of the regional, lower crustal density variations, such as

Moho relief. In some cases, the positive regional gravity response from extended crust, giving rise

to an elevated Moho, can be relatively well constrained from the gravity profile itself. An example

is provided overleaf where the gravity profile shows negative perturbations (due to the basin

sediments) from a regional, long wavelength gravity high. Alternatively, two shorter wavelength

highs may be observed on either side of the basinal gravity low from which the regional may also

be interpolated:



The difficulty arises when the residual gravity lows due to the sedimentary fill almost cancel the

gravity high due to crustal thinning and an elevated Moho (i.e. the basin is isostatically

compensated), or if ramp flat detachment geometry prevails and the regional gravity high is not

laterally coincident with the basinal gravity low. In these cases as much additional information as

possible is used to constrain the model, such as well data or simultaneous magnetic modelling.

Werner Deconvolution

Werner deconvolution is a profile-based interactive technique used to analyse the depth to and

horizontal position of magnetic source bodies, and the related parameters of dip and

susceptibility. It is a rigorous, iterative, two-dimensional inversion technique that takes into

account interference from adjoining anomalies. Analysis of the total magnetic intensity data

yields these parameters for thin, sheet-like bodies such as dikes, sills, intruded fault zones, and

basement plates of minor relief compared to the source-sensor separation distance. Applied to

the horizontal gradient data Werner Deconvolution yields similar parameters for geologic

interface features such as dipping contacts, edges of prismatic bodies, major faults, and slope

changes of the basement surface.



References

BLAKELEY, R.J. AND SIMPSON, R.W, 1986. Approximating edges of source bodies from magnetic or

gravity anomalies. Geophysics, v51, No 7, pp 14941498.

FAIRHEAD, J.D., WILLIAMS, S.E. AND FLANAGAN, G., 2004. Testing Magnetic Local Wavenumber

Depth Estimation Methods using a Complex 3D Test Model. SEG Annual Meeting,

Denver, Extended Abstract.

MUSHAYANDEBVU, M.F., LESUR, V., REID, A.B. AND FAIRHEAD, J.D., 2004. Grid Euler deconvolution

with constraints for 2D structures. Geophysics, v69, pp 489-496

NABIGHIAN, M.N. AND HANSEN, R.O., 2001. Unification of Euler and Werner deconvolution in three

dimensions via the generalized Hilbert transform. Geophysics, v66, No 6, pp 1805-1810.

PHILLIPS, J.D., HANSEN, R.O., AND BLAKELY, R.J., 2006. The Use of Curvature in Potential-Field

Interpretation. ASEG2006, expanded abstracts.

REID, A.B., ALLSOP, J.M., GRANSER, H., MILLET, A.J., AND SOMERTON, I.W., 1990. Magnetic

interpretation in three dimensions using Euler deconvolution. Geophysics v55 pp 80-91.

SALEM, A., WILLIAMS, S., FAIRHEAD, J.D., RAVAT, D., AND SMITH, R., in press. Tilt-Depth method: A

simple depth estimation method using first order magnetic derivatives. Submitted to

The Leading Edge.

SPECTOR, A. AND GRANT, F.S., 1970. Statistical Models for Interpreting Aeromagnetic data.

Geophysics, v35, No 2, pp 293-302.

THURSTON, J.B., AND SMITH, R.S., 1997. Automatic conversion of magnetic data to depth, dip, and

susceptibility contrast using the SPI (TM) method. Geophysics, v62, No 3, pp 807 -813.

WILLIAMS, S.E., 2004. Extended Euler deconvolution and interpretation of potential field data from

BoHai Bay, China. PhD Thesis (unpublished), University of Leeds.


1. The Interpretation Process1.1 The supporting roles of gravity and magnetic data 1.2 Magnetic response of N-S orientated features located at the Equator

2. Enhancements and Transformations of Potential Field Data Reduction to the Pole (RTP)Pseudo-Gravity and Pseudo-Magnetic FieldsTraditional Filtering Pseudo-depth Slicing Automatic Lineament Tracing Grid Display

3. Quantitative Interpretation TechniquesEuler deconvolutionSpectral Depth MethodThe Tilt Depth methodLocal Wavenumber or Source Parameter Imaging (SPI().3D Gravity Stripping and Inversion2D Profile ModellingWerner Deconvolution

References

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Advanced Processing and Interpretation