A Combined Geological, Geophysical and Rock Mechanics Approach to Naturally Fractured Reservoir Characterization and Its Applications

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Copyright 2004, Society of Petroleum Engineers Inc.

This paper was prepared for presentation at the SPE Annual Technique Conference andExhibition held in Houston, Texas, U.S.A., 26-29 September 2004.

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Abstract

In this paper, we present a combined geological, geophysicaland rock mechanics approach to natural fractured reservoir

characterization. The local structure entropy analysis on 3D

seismic data is used to detect distributions of fault and sub-

fault systems. The curvature attribute along with modeledstrain and stress field, constrained with the log data measuring

P- and S-wave velocities and rock density and the invertedelastic modulus from pre-stack seismic data, reveal effects of

the geological structure, bed thickness and lithology on

fracturability of the reservoir layer. These analyses quantifythe relationships between the geologic factors and rockfracturability and describe physically the weighting factors for

geologic parameters in controlling the rock fracturing. The

comparison of the seismic azimuthal analysis results to theseof geological and rock mechanics modeling provides an

opportunity to verify whether the seismic anisotropy derived

from seismic data is caused by structure related naturalfracture patterns or by other mechanisms. The consistency

among different techniques provides the confidence in the

interpretation of the distribution of fractures induced bystructures. If azimuthal seismic attribute data can be

combined, the application of this procedure results in the

development of the fracture connectivity anisotropy byconsidering relationships between the present and palaeo-

stress fields. In addition, the scale depend analysis technique

in this approach can improve the ability to identify thedistribution of fractures with multiple length scales. In this

paper, case studies are used to illustrate applications of these

technologies and their efficiency.Introduction

Fractures are a crucial factor controlling the well performance

in reservoirs with low permeability. Fractured reservoirs are

highly heterogeneous. A practical approach in modeling ofnaturally fractured reservoir is from geology to flow

simulation, which consists of two parts, characterization of

fracture geometry and fracture network dynamic behaviorThe time-independent static data is mainly used for

characterizing fracture distribution. Dependent on scale a

which fracture network is observed, these data include

wireline logs, conventional cores, sub-seismic investigation(outcrop and structure data) and seismic data. The spatial

distributions of fractures and their geometry at the field scalederived from static modeling plays important role in the

reservoir modeling.

Studies show that structure, lithology, bed thickness, porosityand other geologic factors control the fracture intensity. The

complex interaction between all geologic factors needs to be

considered during the static modeling in order to make thesemodels to be expected input to the reservoir models. The rock

properties of a reservoir layer depend primarily on the

depositional process. Tectonic events act on the reservoir layercan lead to the spatial heterogeneous structures which resulted

from the heterogeneously distributed mechanical properties

The fracturability of a reservoir layer is not only influenced bymechanical properties, which are controlled by the lithology of

reservoir rocks such as shale content, matrix porosity, andcarbonate contents etc, but also influenced by the tectonicevents that the reservoir rocks have undergone.

To reduce the uncertainties in fractured reservoir modelingintegrating all available data from geology, geophysics

petrophysics and engineering is necessary. Since the

geological heterogeneity significantly controls fracturedistributions, the statistic assumptions between two or more

wells are hard to be made. Borehole data and analysis of core

data provide us the direct observation of fractures. The

fracture detecting can benefit from the 3D seismic data andobserved geological data.

Seismic data can be used to get better geologic models andmake geo-mechanical modeling physically efficient and

geologically meaningful. The discontinuity analysis or a

coherence-type attribute is often used to interpret the faultsand fractures at the seismic scale. The local discontinuity

related seismic attribute is computed from the seismic data secomparing each trace with surrounding traces. An analysis

cube can be selected by the interpreter, according to the type

of geological feature that is of interested.

The curvature analysis at the top of the reservoir can be

performed and a robust curvature map can be extracted from

SPE 90275

A Combined Geological, Geophysical and Rock Mechanics Approach to NaturallyFractured Reservoir Characterization and Its ApplicationsFeng Shen and Shuiquan Li, SPE, EP Tech


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structural interpretation1. The relationship between area of

high curvature and fracture density has been observed in a

large number of reservoirs in the Middle East, in the NorthSea and in North America2,3. The positive curvature value may

indicate the possible fracture locations whereas negativecurvature may indicate the non-fracture locations. The

curvature map only reflects the possibility of having fractures.

Resultant variations in curvature, strain and stress are theresults of displacement on faults, folding of the structure andheterogeneity of lithological properties.

Seismic anisotropy analysis is an efficient tool to characterize

fracture anisotropy. The comparison of the seismic azimuthal

analysis results to these from geological and rock mechanical

studies provides an opportunity to verify whether the seismicanisotropy derived from seismic data is caused by structure

related natural fracture patterns or by other mechanisms. Theconsistency among different techniques provides the

confidence in the interpretation of the distribution of fractures

induced by structures. Characterizing fractured reservoirs

needs integrated seismic analyses with all geological andmechanical studies.

Characterizing fracture distributions and their geometry is

very important and is a basis for flow simulation of fracture

networks. Most naturally fractured reservoirs include fractures

with multiple length scales. The fracture connectivities andtheir distributions will determine fluid transport in a naturally

fractured reservoir4. Field characterization studies have shownthat fracture systems are very irregular, often disconnected and

occur in swarms5. Incorporating the multiple length scale

fractures into the flow simulation will significantly improve

the modeling technology for fractured reservoirs.

In this paper, we propose a combined geological, geophysicaland rock mechanics approach to naturally fractured reservoircharacterization. With the case study, we demonstrate the

application of our fracture modeling technology to fractured

sandstone reservoir characterization. The scale dependanalysis technique used in this approach greatly improves the

ability to identify the distribution of fractures with multiple

length scales.

3D Seismic Data Multiscale Discontinuity Detection by

Using Local Structure Entropy

One of the most challenging tasks characterizing fractured

reservoirs is locating faults and sub-faults within 3D seismic

volume. The transmissibility features of fault system and theirscales are significant since they are often associated with

reservoir flow simulation. A major step forward in the

interpretation of 3D seismic data was the introduction of thecoherence cube by Bahorich and Farmer6. The disadvantage is

its lacking robustness when dealing with noisy data7.

Gersztenkorn and Marfurt8 introduced a coherence estimate

based on an eigenstructure approach. It was shown that thisapproach provides a more robust measure of coherence. Its

main drawback is the expansive calculations of dominanteigenvalues. Cohen and Coifman9 proposed an analysis

method for the estimation of seismic local structural entropy

which is both robust to noise and computationally efficient.

This method avoids the computation of large covariance

metrics and their dominant eigenvalues. Based on this work

multiple scale discontinuity analyses are applied to mappingfault and sub-fault systems.

Large scale structure features such as fault system are

analyzed with larger analysis data cubes. Stratigraphic feature

such as channels and sub-faults with shorter vertical durationneed smaller analysis cubes to characterize their spatiadiscontinuity. When seismic local structural entropy is

calculated at the small scale data volume, the calculation issensitive to smaller-scale discontinuity and provides the

sharper image of seismic discontinuities. When the scale of

data volume is increased, the effect of the large scale faults

becomes dominant. The smaller scales of local structureentropy calculations should indicate smaller faults and their

features. We use different scale analysis data cubes withsurface windows [2 2], [4 4] and [6 6], where the two number

between the square brackets designate, respectively, the

number of seismic inline traces and crossline traces (Figure 1)

The local structural entropy values are mapped; larger valuesindicate greater discontinuity. Our results clearly show that the

smallest analysis cube yields the sharpest image ofdiscontinuity. The detailed structures of fault networks and

their features on the time slice are observable. The

transmissibility of the fault system is related to these features

Furthermore, when the analysis data cube becomes large, thelarge scale fault frames are outlined clearly. The sensitivity to

the size of the data volume depends on the size of the faulsystem. The features of each fault segment can be maximized

observed on the discontinuity volume whose volume size is

sensitive to the fault scale. By combining local structure

entropy using various sizes of analysis cubes, high lateraresolutions can be obtained. The multiscale local structure

entropy volumes emphasize points which likely correspond tofault surfaces.

Multiscale Curvature Analysis and Related Strain

PropertiesAlmost all of techniques related to fracture detection consider

the present structures interpreted from the 3D seismic data. I

is difficult for us to have the knowledge regarding the exactthe tectonic history of the reservoir layer, while searching the

detailed information related to fracture distribution from the

present structural of the formation is possible. Curvatureanalysis has a long history of use in prediction of fractures1,10

It is usually accepted that where curvature exists, the fracture

can exist. The principal curvatures are directly proportional tothe principal strains, if it is assumed that the rock is elastic and

that all of the deformation associated with the curvature is

dilatational.

When the curvatures are calculated at the smallest mapping

scale, they are greatly affected by the displacement of fault

systems. When the curvature calculation scale is increased, thefault effect is reduced and large scale structures play importan

roles. The large scales of curvature calculations shouldindicate the occurrence of small fractures and related to

regional structural features. On the other hand, the small scales

of curvature calculations are closely related to local structures


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To identify multiple sizes of fractures, various scales of

curvatures should be considered. Our calculations show that

the combination of different scales can reveal the possibility ofoccurred fractures.

To investigate the effects of a specific fault on fracture

distributions and fluid flow transmissibility, scale-dependent

seismic discontinuity measures need to be combined withmapped curvatures along fault segments. The curvature mapsin specified directions and sizes can improve the ability to

analyze and interpret the fault properties. The calculated 3Dcurvatures at different scales and directions improve our

ability to detect the fractures induced by the fault system.

Strain is linearly related to surface curvature and distance fromthe neutral surface within the reservoir layer11. The positive

strain value may indicate the possible fracture locationswhereas extension may occur. With the increasing strain,

rocks undergoing fracturing exhibit increased fracture

intensity. The areas where faults could influence reservoir

properties should be mapped in the fractured reservoircharacterization, when faults are suspected to induce

significant strain accommodated, or when heterogeneousstrain is accommodated by a combination of faulting. Fault

orientation and its network structures contain useful

information. In addition, the effects of fault network on the

deformation are characterized by a fault density mapcomputed by summing the fault lengths weighted by their

throws in a moving window12. This measure has the samedimension as strain. The detailed interpretation of the fault

related strain field is given by Gauthier at al12.

In our study, faults are mapped from 3D seismic data withmultiple sizes of data volumes. The scale dependent

discontinuity analysis is able to reveal subtle lineaments thanany of the other conventional coherence methods in thereservoir layer and is able efficiently to highlight fault network

geometry and spatial variations. The calculated strain from

curvatures at different scales and directions can be combinedwith these constructed by the fault throw along fault traces to

predict variations in fracture distributions. Using this

approach, the observed and quantified fractures from wellsand image log interpretations can be used to constraint the

interpretation of fracture presence. Figure 2 shows the strain

map.

Effects of Lithology Heterogeneity on Stress Field

The fracturability of the reservoir rocks is a very importantindicator for the fractured reservoir characterization. Nelson13

documented the geological influences on the fracture intensity

in sedimentary layered rock such as composition, grain size,porosity, bed thickness and structural position. In addition to

the effects of structures, lithology/facies, shale contents and

porosity play an important role in determining the fracture

intensity and controlling the rock mechanical properties. If thefractures are induced by extensional deformation, fractures

could better develop in the brittle rocks than in ductilereservoir rocks. The rock fracturability increases with the

increasing of rock brittleness characterized by large elastic

modulus of rock matrix. The increase of dolomitic contents

and decrease in shale contents and porosity can enhance the

rock fracturability. The heterogeneity of rock fracturability

leads to the spatial variations of fracture intensity.

The fracture intensity is related to strain energy originallystored in the rock, which is defined as the half of stress

component multiplied with resulting strain component. In

general, the rock with relatively high strain energy will havelarge fracture intensity than a rock of equal thickness withrelatively low calculated strain energy. The historical stress

magnitudes and directions are related to heterogeneouslithology/facies distribution and stain. Mapping the

lithology/facies of the reservoir layer, i.e. distributions of 3D

mechanical properties, can make the geomechanical modeling

geologically meaningful. The 3D heterogeneity oflithology/facies can be described with elastic modulus of

rocks, i.e. with P- and S-wave velocities and rock density. Toobtain spatial variations of P- and S-wave velocities and rock

density of the reservoir, elastic impedance inversion proposed

by Connolley14provides a consistent and absolute framework

to calibrate and invert prestack seismic data to obtain the rockelastic modulus.

Figure 3 shows the distributions of maximum principal stress

magnitudes and directions. Compared to Figure 2, the

different properties shown on Figure 3 indicate the effects of

heterogeneity of 3D mechanical properties of reservoir rocksIn general, fractures will align with the maximum stress

directions. The present-day maximum horizontal stress canmodify the anisotropy of fracture connectivity. If the present-

day maximum horizontal stresses are in the same directions as

calculated stresses derived from structure and lithology data

the connectivity of fractures is enhanced. On the other hand, ifthe present-day maximum horizontal stresses are

perpendicular, the fracture connectivity will be reduced.

Fracture Detection Based on 3D Azimuthal Seismic Data

Analysis

Numerical simulations and physical experiments show that theexistence of vertically aligned fractures leads to azimutha

amplitude versus offset (AVO) variations, which can be used

to determine the principal direction of fractures. Lynn eal.15present field data examples showing a correlation between

azimuthal differences in P-wave AVO and S-wave anisotropy

and demonstrating the potential of using P-waves tocharacterize fractured reservoirs. Based on a 3-D AVO

technique, Ramos and Davis16 show spatial variations o

fracture intensity in coal-bed methane reservoirs. Shen etal.17use azimuthal offset dependence seismic amplitude and

frequency attributes to detect fractures in carbonate reservoirs.

The azimuthal variation of P-wave reflection amplitudes

(coefficients) is an important seismic characteristic for

detecting fractures. Seismic anisotropy analysis is an efficient

tool to characterize fracture distributions. Because of theeffects of elastic properties of background rocks, saturated

fluids and overburden anisotropy, anisotropy caused by highangle fractures does not necessarily correlate with the

magnitude of fracture density. However, the seismic

anisotropy can be used to detect the presence of fractures and


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map fracture distributions spatially. Due to the limited

frequency band, seismic data can provide limited lateral and

vertical resolution and help us identify fractures with thedominant effects. However, geologic data indicates that

fractures usually occur in multiple sets, and engineeringmodels require that more than one fracture set occurs before

fractures form networks capable of transmitting fluids.

Considering the uncertainties in seismic data analysis andinterpretation, fractured reservoir characterization by usingazimuthal amplitude variations in structural reservoirs needs to

combine other data sources to quantify weather spatialvariations of seismic anisotropy were caused by the natural

fracture patterns or were an artifact of the processing. To

better interpret the seismic anisotropy for fracture distribution,

it needs to understand natural fracture spatial geometry andgeological mechanism.

The comparison of the seismic azimuthal analysis results to

these of geological and rock mechanics modeling provides an

opportunity to verify whether the seismic anisotropy derived

from seismic data is caused by structure related naturalfracture patterns or by other mechanisms. The consistency

among different techniques provides the confidence in theinterpretation of the distribution of fractures induced by

structures. Characterizing fractured reservoirs needs integrated

seismic analysis tools to characterize all possible geological

and mechanical influences.

Application of the Combined Geological, Geophysical and

Rock Mechanics Approach to Naturally Fractured

Reservoir Characterization

Geological Modeli ng of Fr actured Sandstone Reservoir

The fractured sandstone reservoirs to be studied in our

working area are distributed in the Quantou Formation,deposited in the lower Cretaceous in the Songliao Basin ofChina. 3-D seismic surveys are acquired over the area. The

reservoir is located at 1200-1500 m in depth and its total

thickness is about 130 m. The reservoir intervals consist ofsandstone and shale and belong to channel and delta deposits.

The structural high is cut by normal faults trending north

south. Faulting system within the Quantou Formations iscomplex. Drilling results and production data reveal the

fractured reservoirs developed in sandstone reservoirs.

Geological modeling of sandstone reservoirs in the QuantouFormation is very important for detecting and predicting the

occurrence of fractures, understanding the effects of fractures

on reservoir properties and helping reservoir evaluation andmanagement.

Spectral decomposition provides a tool for imaging andmapping temporal bed thickness and geological discontinuities

over large 3-D seismic surveys18. This technique has been

used to delineate facies and depositional environments such as

channel sands and incised valley-fill sands19

. We apply ourinstantaneous spectral analysis technique based on wavelet

transform algorithm to image the reservoir distribution. Themethodology of the technology is discussed by Shen et al 20.

Mono-frequency energy data generated with this technology

from the seismic data are used to delineate temporal reservoir

thickness variability and reveal lateral geologica

discontinuities. We consider the optimum frequency band of

each set of reservoirs based on our well log modeling andquantify them in the time and frequency domains. Figure 4

shows imaged reservoirs with energy spectrum in theQuandou Formation. The sandstone reservoirs are composed

of two channel systems located in the north and south

respectively. Channels are oriented in the east-west directionwhich is consistent with the data of paleo-current studies inthis field. The impedance inversion technique is applied to

obtaining the rock mechanical properties.

The seismic discontinuity analysis reveals the fault structures

on the top of the reservoir (Figure 5). The curvature attribute

along with modeled strain and stress field, constrained withthe geological structure, lithology and layer thickness, are

used for fracture detection. Strain distribution is localizedalong faults in the N-S direction. There is localized strain

oriented along the E-W direction, which is observable in the

southern part (Figure 6). E-W orientated strain distribution

indicates that local structures could be responsible for not onlynorth-south oriented fractures but also E-W oriented ones.

Seismic Deri ved Geophysical Modeli ng of Fractur ed

Sandstone Reservoi r

Our seismic data processing focuses on preserving the seismic

amplitudes. Based on the offset and azimuth coverage ofseismic data on the target zone, the field seismic data is sorted

as six-azimuth data. Understanding how the fractures causeazimuthal amplitude variations is essential to the analysis of

seismic anisotropy and to the determination of the fracture

orientation. To identify the effects of fracture density and fluid

content on the azimuthal AVO responses, the forward seismicmodeling is very helpful to relate the seismic responses to

fracture properties. The modeled results will provide us howthe fluid contents and fracture density influence the azimutha

seismic responses and what relationships between the seismic

anisotropy and fracture orientation could be.

The seismic and log tie shows that the strong reflectivity

occurs at the top of fractured reservoirs. The modeled

azimuthal amplitude versus offset (AVO) responses show thathe presence of fractures causes the largest amplitude decay

with offset (Figure 7). The maximum AVO gradient occurs in

the fracture strike direction. The modeled results show that theorientation of amplitude anisotropy indicates the fracture

normal direction and oil saturated fractured reservoirs have

smaller seismic anisotropy than that of water saturated oneswhen the fracture density is the same. With the modeled

studies, the fracture orientations are consistent with the

directions of minimum axis of a amplitude ellipse.The orientation of fractures can be derived from the azimutha

analysis of calibrated seismic amplitudes in six azimuths. The

orientation of the minimum axis of the seismic amplitudeellipse indicates the fracture orientation. Meanwhile, the ratio

of elliptic maximum axis to the minimum axis is one of the

main seismic attributes to the determination of fracturedensity.


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I ntegrated Fr acture Modeli ng i n the Sandstone Reservoir

To characterize fracture density is a challenge process and

needs to relate quantitatively seismic attributes to fracturedreservoir properties. Seismic attributes used to quantify

fracture density should be statistically significant and robust,geologically meaningful and physically effective. Theoretical

studies on scattering characteristics in the heterogeneously

fractured reservoirs provide a basis to relate the seismicattenuation to the spatial variations in fracture density field21.In addition to amplitude variations with offset, the

heterogeneity of vertically aligned fractures will lead to theattenuation of the high frequency of seismic energy at the far

offset at the top of fractured reservoirs. The offset-depend

amplitude and frequency attributes can also be used to

characterize fractures22. In addition to the attribute ofanisotropic ratios extracted from seismic amplitude anisotropy

and modeled strain field, attributes related to wave attenuationcaused by fractures and their heterogeneity can also be used to

characterize fracture density.

Figure 8 shows the map of fracture density and orientation inthe working area. Our results show that fracture distribution is

mainly controlled by local structure properties and reservoirlihtological properties. E-W orientated fractures play

important roles in connecting flow units within the channel

reservoirs. Although N-S orientated fractures, perpendicular to

the channel direction, are well developed, effects of thesefractures on the fluid flow within reservoirs are very limited.

Production data also show that wells located in the area withhighly developed E-W orientated fractures have high fluid

production rate.

Discussion and ConclusionsTo reduce the uncertainties in fractured reservoir modeling,

integrating all available data from geology, geophysics,petrophysics and engineering is necessary. Since the fracturedistributions are characterized by multiple length scales and

orientations, the scale depend analysis technique should be

considered to improve the fracture detection. The fracturedetecting can benefit from the geomechanical modeling,

discontinuity detection and azimuthal seismic anisotropy of

3D seismic data. The consistent results from different dataresources and techniques provide the confidence in the

interpretation of the distribution of fractures induced by

structures.The case study has demonstrated our workflow and

technologies used in fractured reservoir characterization.

Fracturing is a complicated geological phenomenon controlledby geological and geomechanical factors. Modeling reservoir

sedimentary facies, distribution and spatial lithology

properties is the first step before fractured reservoircharacterization. In our working area, fractures are a major

contribution to azimuthal AVO variations. Our modeled

results show that seismic anisotropy increases with fracture

density and that the fracture striking direction corresponds tothe minimum gradient of amplitude decay with offset. The

heterogeneity of lithology is one of the major factorsinfluencing fracture distributions. Integrating rock physics

modeling and borehole data, attributes obtained from seismic

anisotropy analysis, geomechanical modeling and seismic

attenuation attributes could be used to calibrate and quantify

fractures under the well constraints. Our results show that

fracture orientation and density distributions are controlled bystructures and suggest that fractures can strongly influence

well performance. The case study shows that the detailedfracture distributions can be extracted from 3-D prestack

seismic and log data using a rigorous processing and that the

integrating engineering data and geological can help usachieve more useful information beyond the fracturedistributions.

Acknowledgements

The authors wish to thank EP Tech for their permission to

publish this work. The authors also wish to acknowledge the

support of colleagues in PetroChina.

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Figure 1a Interpreted Structure Map

Figure 1c Local structure entropy with horizontal size[4 4]

Figure 2Calculated principal strain distribution.

Figure 1b Local structure entropy with horizontal size[2 2]

Figure 1d Local structure entropy with horizontal size[6 6]

Figure 3Calculated principal stress distribution.


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Figure 4Mapped channel sandstone distribution.

Figure 6 Calculated principal strain on the top of the

reservoir.

Figure 8aFracture distributions on the top of reservoir.

Figure 5The discontinuity from local structure entropy for onthe top of reservoir

Figure 7Modeling the azimuthal AVA responses andbuilding the relationships between fracture parameters andazimuthal amplitude variations.

Figure 8b Amplified Fracture distributions on the top of

reservoir.

Documents

A Combined Geological, Geophysical and Rock Mechanics Approach to Naturally Fractured Reservoir Characterization and Its Applications