08-1A New Technology for the Characterization of Micro Fractured Reservoirs

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AUTHORSMohammed S. Ameen $ Geological Tech nical Services Division, Saudi Aramco, P.O Box 2817, Dhahran 31311, Saudi Arabia; [email protected]

Mohammed S. Ameen was awarded his Ph.and Diploma of Imperial College in structurgeology and geomechanics from ImperialCollege, London, in 1988. He has more tha20 years of academic and industrial experienHe joined Saudi Aramco Reservoir Characterzation Department in 1998, and is currentlleading the Structural Geology and Rock Mechanics Group in the Geological TechnicalServices Division, Saudi Aramco. He is an amember of the AAPG, Society of PetroleumEngineers, European Association of Geoscietists and Engineers, and the Geological Soc(London).

Ernest A. Hailwood $ Core Magnetics,The Green, Sedbergh LA10 5JS, United KingErnest A. Hailwood graduated from the Uni versity of Newcastle upon Tyne, United Kindom, with a Ph.D. in paleomagnetism in 19and joined the University of Southampton, where he became head of Marine Geology aGeophysics and established a highly successresearch laboratory specializing in sedimentmagnetism. He founded the company CoreMagnetics in 1992 to provide services in palmagnetic and rock magnetic measurementsfor the hydrocarbon industry.

ACKNOWLEDGEMENTS

The authors thank Saudi Aramco for sponsorthis work and the permission to publish. Tharticle benefited from constructive reviews oan earlier version by Wayne Narr, Ronald Nelson, and Laird B. Thompson.

A new technology for thecharacterization of microfractured reservoirs(test case: Unayzah reservoir,Wudayhi field, Saudi Arabia)Mohammed S. Ameen and Ernest A. Hailwood

ABSTRACTThis articlepresents a test case of a new technology using artificiallyenhanced anisotropy of magnetic susceptibility (referred to here asEAMS) for the characterization of microfractured reservoirs. Thesearereservoirs in whichmicrofracturesareessential to porosityand/orpermeability. A conventional geological characterization is costly,time consuming, and difficult to quantify in terms of assessing frac-ture impact on porosity andpermeability. Therefore, an efficientandeffective method is required to characterizethese microfractures andto determine their contribution to porosity and permeability. TheEAMS technology, which we developed and tested, allows rapidanalysis thatbridges reservoirgeologyand engineering. Usingpetrog-raphy, the margin of error to detect microfractures that impact po-rosity and/or permeability is 43%; however, it requires three timesthe sampling rate of the new EAMS technology.

The lower part of the Unayzah reservoir (Unayzah-B/C) in the Wudayhi field, Saudi Arabia, where fractures were studied and mi-crofractures are known to impact reservoir performance, is usedto develop and verify the EAMS technology. The results show thatEAMS-derived microfracture fabric strikes east-northeastwest-southwest, consistent with that obtained by geological means. Theeffective-porosity profile obtained from EAMS tests is similar tothat of theconventionally acquired porosity. Open microfracturesin tested samples increase mean values of reservoir effectiveporosityby 36 50% in Unayzah-B/C. The occurrence of connected micro-fractures is estimated to cause an increase in average permeability of 75% in Unayzah-B/C. This is in agreement with the fact that wells

GEOHORIZON

AAPG Bulletin, v. 92, no. 1 (January 2008), pp. 3152 31

Copyright# 2008. The American Association of Petroleum Geologists. All rights reserved.Manuscript received August 5, 2006; provisional acceptance October 27, 2006; revised manuscriptreceived August 6, 2007; final acceptance August 20, 2007.DOI:10.1306/08200706090

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in microfractured Unayzah-B/C have 4.514 times theproductivity of wells as nonfractured sections of thisreservoir. A maximum permeability trend of northeast-southwest permeability anisotropy is detected. Theimplementation of theEAMS technology in other fieldswith microfractured reservoirs will directly impact op-erational and simulation effort.

INTRODUCTION

Definitions

The following definitions are based on Ameen (2003).Fractures aredefined here as all discontinuities that

occur in rocks caused by brittle and semibrittle defor-mation. In hydrocarbon reservoirs, these include nat-ural fractures and induced fractures. Natural fracturesare thoserelated to the natural deformation of the rock.They include faults, cracks, joints, veins, and tectonicstylolites. Induced fractures are thoseinduced artificially,e.g., by coring, core handling, drilling, fluid injection, etc.In the context of the current work, there are two naturalfracture types, according to their size: mesofractures andmicrofactures. Mesofractures can be characterized fullyfrom borehole-scale observations using cores and bore-hole images, and microfractures can only be character-ized fully using optical and electron microscopy of coresamples.

Fracture characterization is the science that dealswith the detection, diagnosis (identification of naturalversus induced and type of each), and quantification of fractures (single fracture properties such as orientation,aperture, fault offset, and length and fracture popula-tion properties such as number of sets, orientation of each set, density, etc.). Fracture characterization is amultidisciplinary subject that integrates multitools andmultiscale observations like microscopic, borehole im-age, core, and three-dimensional (3-D) seismic data.

In-situ stresses are the present-day natural stresses

present in the Earths crust. They are the result of sev-eral components:

1. Gravitational stresses caused by the weight of theoverburden

2. Current tectonic stresses related to present-day tec-tonic forces such as those resulting from the activecollision of the Arabian and the Eurasian continentsin the Arabian Gulf region

3. Remnant and residual stresses locked in the rock dur-ing past episodes of tectonic and gravitational stresses

In-situ stress characterization is the process of de-termining the orientation and estimating the relativeand absolute magnitudes of the three principal in-situstresses (maximum, intermediate, and minimum in-situstresses, referred to as s 1 , s 2 , and s 3 , respectively). Thisis done using an integrated suite of tools like boreholeimages, borehole logs, extended leakoff tests, hydrofrac-turing tests, and active seismicity analysis. Using a Car-tesian system relative to the Earths surface, the present-day in-situ stress can be resolved into three mutuallyperpendicular stresses, referred to as maximum hori-zontal stress ( s H ), minimum horizontal stress ( s h ), andvertical stress ( s V ).

Microfractured Reservoirs

Fractures can impact permeability and/or porosity and,hence, reservoir performance (Nelson, 2001). This isbecoming more apparent with the advancement of technology and the shifting of frontiers to deeper andtighter reservoirs, in increasingly high-pressurehigh-temperature environments. Therefore, the need forfracture characterization is no longer limited to classicalfractured reservoirs (in which fractures are the mainsource of permeability). Deep tight reservoirs rely onfractures as the source of porosity and permeability.The subject of the current work is reservoirs in whichmicrofractures are the main source of porosity and per-meability and, therefore, they are referred to here asmicrofractured reservoirs. To that effect, a reservoirsample is referred to as having fractured pore fabric if ithasopen, connected natural fractures that contribute tothe effective porosity and permeability of the reservoir.If natural fractures are absent, low in density, or oc-cluded so they have insignificant or no impact on reser-voirporosityand/or permeability, then thereservoir sam-ple is referred to as having a nonfractured pore fabric.

Objectives

Microfractured reservoirs are characterized using main-ly petrographic and conventional petrophysical meth-ods. The objectives of our work are to develop and testa quick, economical, and nonconventional method formicrofractured reservoir characterization that combinesbothgeological and petrophysical properties through onetest. The Unayzah-B/C reservoir in the Wudayhi field,Saudi Arabia, where fractures were previously studiedand known to impact reservoir performance from welltests (Al-Hawas et al., 2003), is considered as a goodexample of a microfractured reservoir. Therefore, it is

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used for developing and testing the EAMS (artificiallyenhanced anisotropy of magnetic susceptibility) tech-nology for microfractured reservoir characterization asan alternative to the conventional method. For this pur-pose, two key wells from the Wudayhi field are used,referred to as well A and well B. These wells have sev-eral hundred feet of core and borehole images and wereincluded in the previous fracturecharacterization effortreferred to above.

The United States Patent and Trademark Officegranted U.S. Patent number 7,126,340 for the inven-tion titled A Method to Characterize MicrofracturedHydrocarbon Reservoirs by Artificially Induced Anisot-ropy of Magnetic Susceptibility on October 24, 2006.This article deals with this technology.

PRINCIPLES OF THE ANISOTROPY OFMAGNETIC SUSCEPTIBILITY

Magnetic susceptibility is themagnetization induced ina rock by the application of a relatively weak magnetic

field. This behavior is reversible, and the magnetiza-tion will decrease to zero when the field is removed.Natural anisotropy of magnetic susceptibility (referredto here as NAMS) is the anisotropy of induced mag-netization in a rock under an artificially imposed, rela-tively small magnetic field (e.g., 0.1 mT). The fabricof NAMS in a rock is affected by the mineralogicalcomponents to degrees that vary as a function of theirintrinsic susceptibility. Therefore, NAMS reflects thepreferred orientationsof naturalmagnetic mineralgrainsthathaverelativelystrongmagneticsusceptibilities (such

as ferromagnetic iron oxides and/or sulfides and alsoparamagnetic clay minerals). The magnetic susceptibil-ity, referred to as K, is expressed as the ratio betweeninduced magnetization M and the artificially imposedmagnetic field H of a rock sample. It depends on thedirection of measurement: i.e., it is an anisotropic physi-cal property. K is mathematicallyexpressed by a second-order tensor and, geometrically, as a triaxial ellipsoid,with Kmax , K int , and Kmin as the long, intermediate,and short axes (Figure 1). The shape of the NAMS el-lipsoid is described by two important parameters: amagnetic foliation, referred to as F , which physicallycorresponds to the plane perpendicular to the mini-mum magnetic susceptibility, and a magnetic lineation,referred to as L (the direction of maximum suscepti-bility). The magnitudes of these two parameters aredetermined from the principal susceptibility values asfollows:

L Kmax =Kint 1F Kint =Kmin 2

A further useful magnitude parameter is the anisot-ropy degree, P , where

P Kmax =Kmin 3Such directional NAMS parameters and the inher-

ent nature of NAMS in the mineralogical compositionof rocks have led to important applications in geosci-ences (Hamilton and Rees, 1970; Tarling, 1971; Kirsch-vink, 1980; OReilly, 1984; Tarling and Hrouda, 1993;

Figure 1. (A) Natural magnetic suscepbility (NAMS) ellipsoid. The manifestatof the microfractures in the measuredEAMS (artificially enhanced anisotropymagnetic susceptibility) ellipsoid orientation, where theK min is the pole to thefracture set, and the fracture plane is pre

sentedby theplane including K max and K int .(B) Block diagram of a cubic rock samp with a dominant set of open, connectedmicrofractures impregnated with ferroflu

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Hailwood and Ding, 1995; Hirt et al., 1995; Kodama,1995; Opdyke and Channel, 1996). Such applicationsinclude determining

1. depositional history, including paleocurrent direc-tions in sediments

2. orientation of the magma flux direction in igneousrocks

3. deformation history in igneous and metamorphicrocks

METHODOLOGY

Background and Previous Work

The technology used in the current work is based onthe process of enhanced anisotropy of magnetic suscep-

tibility (referred to here as EAMS). This is the anisot-ropy of artificially induced magnetization in a rock thathas been impregnated by ferrofluid, under laboratory-imposed, relatively small magnetic field (e.g., 0.1 mT).EAMS borrows from nature the principles of NAMS byacquiringa magnetic cast of open, connected pore space(by injecting ferrofluid into the rock samples) and thenmeasuring the anisotropy parameters ( L, F , and P asdefined above), which give the orientation of the con-nected pore fabric. In addition, porosity values can becalculated from the known concentration of the mag-

netic suspension and the magnitude of the magneticsusceptibility. The availability of smart magnetic fluidsmakes it possible to create a magnetic fluid cast of theconnected pores by injecting the micropores with mag-netic fluid.

The application of magnetic susceptibility anisot-ropy of samples saturated with magnetic suspension tocharacterize connected open pores has been applied suc-cessfully todeterminethepore fabricandthedirectionof maximum permeabilityandoptimum fluid flow throughconventional nonfractured synthetic material and out-crop sandstones (Pfeiderer and Halls, 1990, 1994; Hail-wood etal.,1996, 1999a,b; Hailwood and Ding, 2000).

Conventional Geological Characterization of Microfractures

Microfracturescanonly be effectively detected andchar-

acterized by microscopy (Figure 2). This type of fractureis ubiquitous in rocks (Kranz, 1983) and includes open,partly mineralized, and fully mineralized fractures. Char-acterizing mineralized microfractures is considerablyeasier than open fractures. Scanned cathodolumines-cence imaging was used to map quartz-filled micro-fractures (lengths of micrometers to millimeters) inquartz-cemented sandstones in an attempt to predictthe occurrence and orientation of larger fractures thatare otherwise not encountered in the borehole coresor images (Laubach, 1997). Natural open or partly

Figure 2. Illustration of the proceduresinvolved in the conventional geologicalcharacterization of microfractures. Theseprocedures are petrographic, and geo-metrical description involves laborious,destructive, and costly processes (re-quire acquiring three mutually perpen-

dicular thin sections parallel to the cubefaces 1, 2, and 3) and yet do not givea direct and precise assessment of rock petrophysics.

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mineralized fractures are critical to hydrocarbon reser-voirs that have otherwise low intrinsic porosity and/orpermeability. However, reservoir-scale characterizationof such open microfractures is a challenging task. Thisrelies on microscopic analysis of core samples that, inaddition to natural fractures, can also have artificiallyinduced fractures by drilling, coring, corehandling, orsampling (Santarelli and Dusseault, 1991).Distinguish-ing natural open fractures (that show no evidence of mineralization) from the induced fractures is an essen-tial preliminary step in microfracture characterization.Natural microfractures tend to show staining, whereasinduced fractures are fresh looking. In addition, naturalmicrofractures develop parallel to nearbynatural meso-fractures, parallel to microfractures that show evidenceof mineralization, and develop in clearly defined sets.Coring-induced fractures may be oriented relative tothecore circumference in a concentric or radialpattern.Drilling-induced microfracture orientation can be re-lated to present-day in-situ stresses and their modifica-tion around the borehole (especially in wells that arenot vertical or horizontal). Natural microfractures aresystematically related to local structural fabric or re-mote stress regime, which is not necessarily parallel tothe present-day in-situ stress. The development of spe-cialized seismic technologies may, in some cases, offer areservoir-scale tool to predict the presence of a domi-nant set of open natural fractures under reservoir con-ditions (Gaiser et al., 2002). The combination of theborehole-scale characterization using cores, boreholeimages, full-wave sonic logs, and vertical seismic profile(VSP) logs offers comprehensive characterization andconsiderably reduces uncertainties associated with anyof these tools when used alone. This multidisciplinaryborehole-scale method was combined with a reservoir-scale seismic anisotropy approach to characterize themicrofractured Unayzah-B/C reservoir in the Wudayhifield and successfully helped in well planning (Al-Hawaset al., 2003). Therefore, the Unayzah-B/C reservoir of-fers a good testing ground for EAMS technology.

Fracture density in conventional methods is assessedin termsof fracture count per unit lengthof an imaginaryscan line perpendicular to the fracture set average plane(one-dimensional estimate) or as the cumulative lengthof fractures per unit area (two-dimensional estimate).Ideally, the best way to estimate fracture density is thecumulative area of fracture surfaces per unit volumeof the rock. This is, however, affected by the uncer-tainties associated with the limited field of observationwithin the boundaries of the borehole images and/orcores. For reservoir appraisal, what really matters are

the open, connected fractures because they impact po-rosity and/or permeability. Therefore, there is a need toassess effective fracture porosity; this is defined hereas the cumulativevolume of open, connected fracturespace (voids) per unit volume of the rock at the scale of observation. This is equivalent to effective fracture po-rosity in the tested sample. Conventional geologicalmethods (e.g., petrography for microfractured reser-voirs) are not reliable to assess this. However, the EAMSmethod is developed to directly give effective fractureporosity in rocks where fractures are the only source of porosity and permeability and indirectly for rocks withboth fracture-related and nonfracture-related poros-ity and permeability.

Characterizing Microfracture Fabrics Using EAMS

Microfractures contribute to porosity and/or perme-ability in certain reservoirs. Such reservoirs, referred tohere as microfractured reservoirs, are increasingly en-countered because of the advancement of drilling anddevelopment technologies targeting deeper, tighter res-ervoirs (Energy Information Administration, 2002).Conventional characterization methods described above(Figure 2) are costly, time consuming, and difficult toquantify in terms of assessing fracture impact on po-rosity and permeability. Therefore, seeking innovativecharacterization of the microfractures in a way that re-veals their impact on reservoir petrophysics is impor-tant. The Unayzah-B/C reservoir in the Wudayhi field,where microfractures are well studied and known toimpact reservoir performance (Al-Hawas et al., 2003),is a good example of a microfractured reservoir. There-fore, we have used this reservoir for developing andtesting the EAMS technology as an alternative to theconventional method.

The EAMS technology is based on the assumptionthat if we inject ferrofluid into a rock sample charac-terized by a dominant set of planar, open microfrac-tures and low effective porosity, the fluid fills the frac-

ture network. The magnetic anisotropy magnitude andellipsoid orientation of such a sample will be controlledby the fracture pattern, fracture size, and density and,therefore, can be used to predict the fracture orientation(Figure 1) and fracture-related porosity. Results fromlaboratory experiments on artificially induced fracturesin nonporous media (marble) conducted in the CoreMagnetics Laboratory as part of the calibration processand on prism-shaped pores (can be considered as frac-tures here) in Plexiglas (Pfeiderer and Halls, 1990) con-firm that the resulting minimum susceptibility ( Kmin )


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axis is perpendicular to the mean plane orientation, sothat EAMS measurements provide a precise measure of the dominant planar pore fabric. This premise shouldapply in microfractured reservoirs that have developeda dominant microfracture set as in the Unayzah-B/Creservoir, Wudayhi field.

Core Sampling

Core pieces from the two key wells (wells A and B)were fitted together into intervals in which all pieces hada commonorientation.Each such interval is referredto asa core run. Runs are separated by breaks, across which areliable fitcannotbe made. Elevenruns were sampled inwell A, the upper three being in the Unayzah-A forma-tion and the lower eight in the Unayzah-B/C. Three runswere sampled in well B, all of them in the Unayzah-B/C.The mean run lengths in the two wells were 14.2 and1.3 m (46.5 and 4.2 ft), respectively.

A specially manufactured, nonmagnetic plugging

bit, with a 25 mm (1 in.) diameter, was used to extractcylindrical plug samples from each of the fixed core runs.In most cases, three pairs of plugs were taken from eachrun, and the two plugs in each pair were drilled fromopposite sides of the core to aid in the identification andvector removal of any spurious components of remanentmagnetism associated with plugging and related pro-cesses (Hailwood and Ding, 1995). As far as possible,the six plug samples in each run were distributed uni-formly throughout that interval of core. A total of 142 plug samples were acquired: 112 from well A and

30 from well B. Two separate specimens were cut fromeach plug sample, a 15-mm (0.6-in.) cube for EAMSanalyses and a 25-mm (1-in.) right-cylindrical speci-men for paleomagnetic reorientation of the cores.

Core Reorientation

The method requires oriented cores or oriented wire-line core plugs to acquire true orientation of the mea-surements. Cores from two wells (wells A and B) in the Wudayhi field were sampled for the present study.Measurements of microfracture orientations using theEAMS method and of mesofracture orientations usingcore goniometry were made in core coordinates. Themeasured relative directions were then referred to thegeographic north using thepaleomagnetic core reorien-tationmethod(Hailwood andDing,1995).The25-mm(1-in.) right-cylindrical specimens sampled from thecore runs were subjected to incremental thermal de-magnetization to isolate the viscous remanent magne-

tism (VRM) acquired in the Holocene geomagneticfield. The mean VRM in each core run was then used todefine the direction of the geographic north within thatinterval of core.

The paleomagnetic core orientations were then ver-ified using the calibration of the orientation of distinc-tive geological features in borehole images versus theirorientation in thecores (Figure 3). Thecalibration showsthat the difference between the paleomagnetic core ori-entation and the borehole image orientation is on theorder of a few to 10 j .

Figure 3. Examples of geological fea-tures that occur in both the cores and theborehole images that were used to cali-brate the core orientation in the Wudayhi-A and Wudayhi-B wells. (A) Syndeposi-tional fault in core clearly visible in theborehole image (B). (C) Two syndeposi-

tional faults in core truncated by overlyingbed apparent in the borehole image (D).

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Saturation of Reservoir Samples with Ferrofluid

The 15-mm (0.6-in.) cube samples collected from coresare saturated with a magnetic fluid (ferrofluid). Thiscomprises a suspension of ultra fine-grained (nanome-ter size) particles of isotropic magnetite in a suitablecarrier medium, which may be oil based or water based.The particles are coated with an antiflocculent to pre-ventaggregation. Their size is within the superparamag-netic range, so that they do not carry remanent mag-netism, but instead exhibit a strong induced magnetismin the presence of applied field. The saturation is doneusing a specially designed unit consisting of a pressurecell in which the rock specimen is evacuated from airusing a vacuum valve and then immersed in ferrofluidunder pressure (Figure 4). The pressure used is suffi-ciently low (80 psi; 551kPa) to avoid inducing fracturesinto the tested samples. The pressure choice was cali-brated by experiments to optimize saturation withoutinducing fractures. The saturation process was opti-mized and validated by conducting a petrographic in-spection of dried samples after saturation. The micro-scopic inspection shows the ferrofluid distributed in allopen, connected pores.

EAMS Testing

The ferrofluid-saturated, 15-mm (0.6-in.) cube sampleswere subjected to EAMS measurements. The shape andorientation of the magnetic susceptibility ellipsoid ineach tested samplewere determined from the magnitudeand direction of the measured susceptibilities Kmax ,K int , and Kmin . The magnitude of magnetic foliation F ,magnetic lineation L, and the anisotropy degree P arethen derived from Kmax , K int , and Kmin using equa-tions 1, 2, and 3 respectively. The EAMS parameterswere then analyzed to detect the existence of fracturesanddetermine their orientation(Figure1), porosity, andpermeability anisotropy.

Detection of Fractures and Their Orientations

Microfracture-type fabrics can be distinguished from de-positional-style (nonfractured) fabrics using four sep-arate criteria:

1. The magnetic susceptibility (per unit volume) of sam-ples with open, connected microfractures tends to besystematically greater than that of samples with de-

positional fabrics. This reflects the enhanced poros-ity caused by the microfractures, which results in ahigher volume of ferrofluid within these samples.

2. The magnetic foliation parameter, F , for sampleswith a dominant, open, microfracture set also tendsto be systematically greater than that for sampleswith depositional-style fabrics (i.e., the magnetic sus-ceptibility ellipsoid for the former tends to be moreoblate than for the latter). This is caused by the con-centration of ferrofluid within the planar fractures,which enhances the foliar structure of the fabric.

3. Primary depositional fabrics (after restoring beddingto syndepositional orientation) are generally char-acterized by relatively shallow Kmax axes and steepKmin axes (within $2025

j of the horizontal andvertical, respectively). In contrast, microfracture-typefabrics are aligned in a direction related to the meanfracture plane orientation. Thus, apart from the rarecase of subhorizontal fractures, Kmin axes of micro-fracture-type fabrics will commonly have steeperinclinations than those of depositional-style fabrics.

4. When the fracture fabric has shallow dip angles sim-ilar to those of samples with depositional fabrics, thedip directions of the microfracture fabrics are gen-erally quite distinct from those of planar structuresassociated with the depositional fabrics. This crite-rion should be verified by petrography.

Verification of Fracture Occurrence and Orientation

To verify that the magnetically detected fabric is causedby microcracks, we compared results from EAMS anal-yses with those from conventional (petrographic) obser-vations on the same samples. We selected 12 EAMScube samples as representative of the two main classesof EAMS-diagnosed fabrics: microfracture-type fab-rics (five samples) and nonfractured fabrics (seven sam-ples). Three mutually perpendicular thin sections werecut from each cube, one horizontal (section 2; Figure 2)

and the other two vertical (sections 1, 3; Figure 2). Thesections were analyzed using optical and electron mi-croscopy for the presence and the orientations of nat-ural microfractures (Figure 2). Paleomagnetic reorien-tation of thecube samples andconstituent thin sectionsfacilitated a referral of directions observed in the sec-tions to the geographic north. The use of three mu-tually perpendicular thin sections gave an approxima-tion to 3-D observation of visible microfractures andreduced the chance of missing features, had only one ora pair of thin sections been used.


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Characterization of Microfracture Porosity Using EAMS

The effective porosity of the samples was determinedfrom their magnetic susceptibility after ferrofluid satu-ration. The total volume of ferrofluid within each plugsample can be calculated from the known magnetic sus-ceptibility of the ferrofluid, coupled with results fromprevious calibration experiments. Knowing the samplevolume, this provides a measure of the EAMS porosityof the sample using equation 4.

effective porosity X X =0:45 4 X is the measured enhanced magnetic susceptibility(SI units).

The possibility of predicting fracture porosity fromcomparing preinjection natural magnetic susceptibility

with the postinjection EAMS is investigated and foundinaccurate. This is related to the very lownatural suscepti-bilityof thetested reservoir samples,which wascommon-ly belowthe accuracy threshold of laboratoryequipment.

Verification of EAMS-Derived Porosity

Conventional petrophysical analysis of the cores is usedto verify the porosity trends and porosity values ob-tained using the EAMS technology. This can be doneon the same set of plug samples used for the EAMS test

(before injection by the magnetic fluids) or on a sep-arate set of plug samples acquired from the same cores.In the current casestudy,weuseda separateset ofplugs,which were acquired and tested independently. Themethod used in the conventional testing includes acquir-ing cylindrical plug samples 1.5 in. (3.8 cm) in diameterand 3 in. (7.6 in.) in length. A total of 197 samples wereacquired from well A, and 225 samples were acquiredfrom well B for the conventional tests. The porosity andpermeability of the core plug samples areanalyzed usingconventional methods. The plug samples were cleanedin a Soxhlet extractor, first by toluene as organic solventto remove hydrocarbons and then by methanol to re-move salt and water. The cleaned samples were dried inan oven to remove water and solvent and then trans-ferred todesiccators to cool them andabsorbwater.Theplug samples were tested using helium gas for porosityand nitrogen gas for permeability.

When assessing fracture porosity on reservoir scale,it is essential to consider that such porosity is a functionof fracture dimensions, fracture density (or spacing),and fracture abundance or distribution and clustering.If fractures are localized in a narrow cluster, their contri-bution to reservoir porosity decreases with the increasein core sample size. In addition, random sampling maymiss the fractures. However, if fractures are sufficientlysmall (microfractures) to be captured in a core sample,pervasive in a relatively large reservoir body or layer(such as thecase with the Unayzah-B/C reservoir in thisstudy), then the fracture porosity from core samplestends to be representative of the whole of the micro-fractured reservoir body. The dynamic performance of areservoir, such as productivity (e.g., from well tests), isessential in any verification of the impact of fractures onporosityand permeability, particularly in tight reservoirs.

Characterization of Permeability Anisotropy

EAMS-determined pore-fabric anisotropy is related tothe gross geometrical anisotropy of the effective con-

nected pore spaces. If we assume that permeability iscontrolled by theconnected porespace, including micro-fractures, then the geometry of the EAMS is expectedto impact permeability anisotropy. The degree of per-meabilityanisotropycanbecalculated from EAMSusingcalibrated (empirically derived) standard equations. Thecalibrationwasperformedin theCore MagneticsLabora-tory over a period of time by comparing EAMS-deriveddata with directly measured permeability anisotropyvalues obtained from conventional core testing. Thecali-bration is based on results (unpublished) from studies

Figure 4. Schematic section of the cell used for saturating thereservoir samples with ferrofluid under 80 psi (551 kPa) pressure.

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of North Sea porous reservoirs (fluvial and deep-watersands). Permeability anisotropy data are expressed bytwoparameters. The first is theazimuthalpermeabilityanisotropy, which represents the percentage differencebetween maximum and minimum permeability in thehorizontal plane (i.e., parallel to bedding). The secondis thetotal permeability anisotropy,which quantifies thepercentagedifference between theoverall maximumandminimum permeability in 3-D. These are determinedby the following equations:

permeability anisotropy 8:1 ffiffiffiffi X p 5where X (referred to as X aa for azimuthal anisotropyand X ta for total anisotropy) is the enhanced suscepti-bility (SIunits), calculated fromthefollowingequations:

X aa X 100 L 1 6where L is the magnetic lineation (equation 1), and

X ta X 100 P 1 7where P is the magnetic anisotropy density (equation 3).

Verification of Permeability Anisotropy

Thedirectional properties of permeability, on reservoirscale, can be verified from conducting interference testson sufficient number of adjacent wells. However, thiscould not be achieved in the studied field because of thelack of sufficient wells.

THE STUDY AREA (THE WUDAYHI GAS FIELD)

Location and General Geology

The Wudayhi gas field (discovered in 1998) is an east-northeasttrending anticlinal structure, 30 km (18 mi)in length and 10 km (6 mi) in width. It is located in theeastern province of Saudi Arabia (Figure 5A), with struc-tural and potential stratigraphic traps. The Wudayhi an-ticline is a forced basement-involved fold formedby thedraping of the PaleozoicCenozoic sedimentary coverover fault-bound basement blocks. The anticline is gen-tle (dip angles rarely exceed several degrees) and asym-metric, with south vergence. The 3-D seismic and bore-hole data show no clear evidence of major faults (with

seismically resolvable offset) in the sedimentary rocks.An east-northeasttrending lineament along the steeper,southern limb of the anticline is evident from the dip-magnitudeattribute of the seismic data (Figure 5B). Thisfeature may reflect a deep-seated, basement fault zone.

The Unayzah Reservoir

TheUnayzah is a sandstone reservoir, divided into threeunits (Figure 6). In descending order, these are

1. Unayzah-A: mostly fluvial- and coastal-plain facies,with alluvial fan and eolian facies

2. Unayzah-B: fluvial and lacustrine facies3. Unayzah-C: glaciofluvial and eolian facies

For further details concerning the stratigraphic as-pects of the Unayzah, see Senalp and Al-Duaiji (2001).

Impact of Fractures on Productivity

TheUnayzah-B/C reservoir in theWudayhi field dependson thepresence of fractures (mainly microfractures). Thisis evident from well tests that show that productivityfrom a nonfractured matrix forms only 19% of the totalgas production and 7% of condensate production.

Fracture Modes in the Unayzah

The existence and properties of the fractures in theUnayzah reservoir were thoroughly studied and docu-mented using a combination of borehole-scale tools(cores, borehole images, full-wave sonic logs, and ver-tical seismic profile processing log [VSP]) and field-scale seismic anisotropy (Al-Hawas et al., 2003). Thismultidisciplinary approach confirmed the presence of open gas-filled microfractures with east-northeast west-southwest and west-northwesteast-southeast strike(Figure 7) and helped in the well planning. Analysis of drilling-induced fractures and breakouts in the field

shows that themaximum horizontal in-situ stressdirec-tion is east-northeastwest-southwest, i.e., subparallelwith the east-northeaststriking detected open fractures(Figure 7) and, therefore, is expected to enhance the frac-ture aperture of this set under reservoir conditions.

Core and borehole image studies show that most of the observed open fractures in the Unayzah-B/C are mi-crofractures. Mesofractures are low in density and small,up to several tens of centimeters in length (Figure 8).Furthermore, theopenfracturedensity increases greatlywithdepth,withminimumdensity in Unayzah-A(higher


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porosity sandstones, and low-porosity, shale-rich softerrocks)and maximum density in Unayzah-B/C, whichcon-sists of low-porosity,well-lithified sandstones (Figure 9).

Origin of Natural Fractures in the Unayzah

Natural fractures in the Unayzah include four distincttypes:

1. Early, soft-sediment deformations, including faults,granulation seams, and slump structures, which occurmostlyin theupperpart of theUnayzah (Unayzah-A):These are dominated by a north-northweststrikingset, are well cemented, are related to local gravitystresses controlled by local slopes, and may be trig-gered by seismicity in basement faults.

2. Earlydiagenetic, fullymineralizedfracturescontortedby the vertical compaction with a dominant north-northeaststriking set

3. Stylolite-related fractures (defined by Nelson, 2001;Narr et al., 2006) that emanate from bedding stylo-

lites and die out awayfromthem: These are small (upto a few tens of centimeters in length), mostly occurin the lower section of the Unayzah (Unayzah-B/C),and are partially to fully mineralized.

4. Nonstylolite fractures that have no apparent link to bedding stylolites: These fractures are mostlyopen with partial mineralization, mostly occur inthe lower section of the Unayzah (Unayzah-B/C),and are nearly vertical, with two sets striking east-northeastwest-southwest and northwest-southeast,respectively.

Figure 5. (A) Location map of the Wudayhi field. (B) Thelocation of the studied key wells on a time-dip structuremap of the Unayzah reservoir, Wudayhi field. Reprinted withpermission from Al-Hawas et al. (2003).

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The nonstylolite open fractures are most dominantand affect reservoir performance. They are mostly mi-crofractures. These fractures are not systematically ori-ented around the local anticlinal Wudayhi structure.However, they are systematically oriented relative to theplate tectonic remote stresses associated with the colli-sion of the Arabian and the Eurasian plates (Late Creta-ceous up to now). Thepreservation of open apertures in

most of these fractures (mineralization is only partial)can be related to the fracturing being contemporaneouswiththehydrocarbonplacement (Cretaceous toTertiary)that helped in slowing thediagenesis and preserving thefracture-related pore spaces. This is evident from thecommon occurrence of hydrocarbon lining of part of the microfracture walls and the occurrence of hydro-carbons in fluid inclusions of quartz crystals lining the

Figure 6. (A) Generalized stratigraphy of the Upper CarboniferousPermian reservoirs in the study area. (B) Porosity profUnayzah reservoir in the Wudayhi field.

Figure 7. Rose diagrams of the strikes the open fractures and the trend of themaximum horizontal in-situ stress (SHin the Unayzah reservoir, Wudayhi fieldThe diagrams show the presence of twopen fracture sets striking east-northeas west-southwest and west-northwesteassoutheast, with the latter set nearly parallel to SH. The in-situ stress diagramsare derived from borehole breakouts andrilling-induced tensile fractures (Al-Haet al., 2003) (Figure 9).


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fractures.Such inclusionswere also observedalong healedfractures in the Unayzah in other fields in Saudi Arabia(W. J. Carrigan, P. J. Jones, and R. H. Worden, 2003,personal communication; W.J.Carrigan andS. G.Franks,2006, personal communication; S. G. Franks and W. J.

Carrigan, 2006, personal communication).

EAMS-DERIVED RESULTS

Microfracture Trends

The EAMS-detected microfractures have a dominantnortheast-southwest to east-northeastwest-southweststrike in the studied wells (Figure 10).

Reservoir Petrophysics

Fracture and Matrix Porosity from EAMS DataEAMS-determined porosity in the Unayzah-B/C forwell A and well B are plotted inFigure 11. EAMS-based

porosity values for microfractured samples (samplesacquired from zones identified geologically as micro-fractured from the previous fracture characterizationwork published by Al-Hawas et al., 2003) are systema-ticallygreater than thosefor nonfractured samples (sam-ples acquired from zones identified geologically as non-fractured by Al-Hawas et al., 2003). This reflects theporosity enhancement caused by the presence of themicrofractures. The estimated porosity enhancementcaused by microfractures is summarized in Table 1.The increase in the mean value of reservoir porosity

Figure 8. Modes of the open fractures in the Unayzah-B/C. (A) Partly mineralized (by quartz), mesofractures in whole co(B) Formation microimaging borehole images with small, conductive mesofractures. (C) Plane-light photomicrograph showinnetwork of open microfractures. Note the hydrocarbon lining (dark brown to black) in the fractures.

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Figure 9. Fracture density in the two studied key wells, well A (A), and well B (B), which are fully cored and imaged

Figure 10. The strikes of EAMS-derivmicrofractures in the Unayzah-B/C pre-sented as rose diagrams for wells A andsuperimposed on the Wudayhi field maEAMS = artificially enhanced anisotropof magnetic susceptibility.


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caused by fracture occurrence ranges from 36 to 50% inthe Unayzah-B/C. The impact of fractures on porosityis also illustrated in the histograms of porosity dis-tribution in fractured and nonfractured samples ineach of the studied wells (Figure 12).

Pore Fabric Anisotropy

The preferred orientations of the long axes of EAMS-derived, connected pores ( Kmax azimuths) in all the sam-ples from wells A and B (irrespective of fracture occur-rence) are plotted as point and azimuthal rose diagramsin Figure 13A. This is characterized by one dominantnearly horizontal trend (N45 j E) and two subordinatenearly horizontal east-west and north-northwestsouth-

southeast trends. The same pattern is evident from sim-ilar plots for the nonfractured samples from both wells Aand B, respectively (Figure 13B) and for all the sam-ples in well A (Figure 13C). The plot for all the sam-ples in well B shows the east-west trend as marginallymore dominant than the northeast-southwest trend(Figure 13D). This is most probably related to a scatterassociated with the relatively small number of samplesin well B (29 samples) compared to that in well A (111samples). The dominant northeast-southwest trend of the nonfractured pore fabric (Figure 13B) lies at about2535 j counterclockwise from the dominant fracturetrend (Figure 10). The pore fabric of the fractured sam-ples shows a dominant east-northeast to east-west trend(Figure 13E, F).

Figure 11. EAMS-derived porosity values for Unayzah-B/C samples withmicrofracture-type fabricsanddepositional-style fabrics, compared with conventionalporosity from plug samples, in wells A and B. Notice the higher porosity in thefractured samples compared to the non-fractured samples and the similarity of theporosity trends in theconventional andthe EAMS methods. EAMS = artificially enhanced anisotropy of magneticsusceptibility.

Table 1. EAMS-Derived Porosity*

Well Sample Type

Effective Porosity (%), Derived from EAMSIncrease in Effective Porosity

Caused by Fractures (%)

Mean Median Standard Deviation Skewness Mean Median

A Fractured 9 9 1.7 0.1 50 50Nonfractured 6 6 1.9 0.5

B Fractured 15 15 4.9 2.2 36 25Nonfractured 11 12 3.8 1.1

*Expressed as mean, mode, and median for microfracture-type and depositional style fabrics in the Unayzah-B/C, of the studied wells, and percentage increaseporosity for microfractured samples compared with nonfractured samples. EAMS = artificially enhanced anisotropy of magnetic susceptibility.

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Permeability Anisotropy: Relative Ratio of Directional Permeability

The EAMS-based permeability anisotropy was calcu-lated from using equations 57. Permeability anisot-ropy includes the horizontal (azimuthal) permeabilityanisotropy and the maximum (3-D) permeability an-isotropy (defined in the methodology section). Histo-grams of these two parameters for wells A and B areshown in Figure 14. These show that azimuthal perme-ability anisotropy ranges from about 3 to 15% in bothwells, with a mean of about 6.5%, and total permeabil-ity anisotropy ranges from 5 to 28%, with an overallmeanof approximately 14%. Mean permeability anisot-ropy values for samples with microfracture-type anddepositional-style fabrics, respectively,are summarizedin Table 2A. No significant difference exists betweenthe degrees of permeability anisotropy of samples withthe two types of fabric in either well (within the var-iability represented by the standard deviation of themean).These results suggest that although thepresenceof microfracture fabrics increases porosity, it does notappear to have a significant effect on the degree of per-meability anisotropy.Thedegree of anisotropy is relatedto several factors, including fracture size, aspect ratio,density, the existence of nonfracture pores, and theirrelative abundance and geometries.

Figure 12. Frequency distribution of the EAMS-based porosity in the key wells A and B. EAMS = artificially enhanced anisotropy of magnetic susceptibility.

Figure 13. Trend and plunge (points) anazimuthal rose diagrams of the long axeof EAMS-derived, connected pores ( K max azimuths) in (A) all the samples from bo wells A and B (irrespective of fractureoccurrence); (B) the nonfractured samplfrom both wells A and B; (C) all the saples in well A; (D) all the samples in we(E) the fractured samples from well A;(F) the fractured samples from well B. Tplots in (A)(C) are characterized by adominant, nearly horizontal trend (N45j E),and two subordinate, nearly horizontaleast-west and north-northwest south-southeast trends, whereas (D)(F) showthe east-west or east-northeast west-southwest trend as the marginally moredominant trend thanthenortheast-southwes


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Trends of Permeability Anisotropy

The maximum permeability direction in microfrac-tured rocks depends on fracture properties, includingthe number of sets, their relative frequency and orien-tation, their aperture, the presence of propping fea-tures like partial mineralization or fracture wall geo-metrical mismatch, and fluiddissolution enhancement.In addition, the orientation of the present-day stress re-gime is a significant factor in enhancing or closing open

fractures, thus affecting their permeability (Bartonet al.,1995). In the current study, there is one dominant mi-crofracture set (Figure 10) that is open, nearly parallelto the maximum horizontal in-situ stress and perpen-dicular to the minimum horizontal in-situ stress (com-pare Figure7 with Figure 10).Therefore, themaximumpermeability direction in the microfractured samplesis expected to lie within the mean microfractureplane, whereas that of samples with depositional fab-rics is controlled by the nonfracture pore fabric. The

Figure 14. Frequency distribution of the azimuthal and total permeability anisotropy values in wells A and B.

Table 2. Estimates of (A) Permeability Anisotropy Mean Values and (B) Fracture-Related Increase in Permeability

(A) Mean Permeability Anisotropy Values*

Well

Azimuthal Permeability Anisotropy (%)from Equation 5 (See Text)

Total Permeability Anisotropy (%)from Equation 5 (See Text)

Microfracture-Type Fabrics Depositional-Style Fabrics Microfracture-Type Fabrics Depositional-Style Fa

A 7 2.5 7 2.1 17 2.5 15 2.2B 6 4.4 7 3.9 12 4.0 12 6.1

(B) Permeability Increase in the Unayzah-B/C, well A**

Well Estimated Permeability Increase (%), Unayzah-B/C

A 75

*With associated standard deviations for samples with microfracture-type and depositional-style fabrics in the key wells from Wudayhi field.**Caused by the microfractures calculated using EAMS-derived porosity.

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microfracture strike in the Wudayhi field is orientedeast-northeast, forming an angle of 2535 j clockwisefrom the northeast-trending dominant depositionalpore long axis (compare Figure 10 with Figure 13C), sothat maximum permeability directions associated withthe two types of fabric are broadly similar.

Permeability

The EAMS test setup used in this work does not allowfor accurate permeability measurements. Permeabilityfor matrix rocks is derived from conventional petro-physical tests of core-plug samples. Fracture permeabil-ity is generally more difficult to assess and is a functionof the percolation threshold (Odling et al., 1999). How-ever, if weassumethata microfractured reservoir is atorbelow the percolation threshold because of the micro-scopic size of the dominant fractures and their pervasivenature, we may predict the minimum impact of themicrofractures on permeability using the correlationof conventionally acquired porosity and permeability.Using theporosity of themicrofractured EAMS-testedsamples and applying the porosity-permeability cor-relation from conventional tests (well A) of core plugs,it is estimated that microfractures increase the averagepermeability by 75% in Unayzah-B/C (Table 2B). Theactual permeability impact will be significantly higheras fractures reach and exceed thepercolation threshold.

VERIFICATIONS OF THE EAMS-BASED RESULTS

The validation of the technology aims at verifying thefollowing aspects:

1. The existence of natural open fractures in samplesdiagnosed as fractured by the EAMS tests and theirlack in those diagnosed as nonfractured

2. The orientation of the fractures as detected fromthe EAMS analysis

3. The porosity profile as detected from the EAMSanalysis

Verification of Fracture Occurrence and Trend

The verification of the first and second aspects is achievedusing conventional geological (petrographic) methodsas described above on 12 keysamples presenting micro-fractured and nonfractured samples as identified fromthe EAMS tests. The occurrence or lack of fractures istherefore verified for each EAMS sample from their

occurrence inone or moreof the three key thin sections.The results are summarized in Table 3. The followingconclusions are derived from these observations:

1. Fractures were geologically verified in 100% of thecube samples that were diagnosed as fractured fromthe EAMS tests. These include fractures occurringalong grain boundaries and fractures that cut acrossgrains (Figure 15).

2. The orientation of the petrographically identifiedfractures was analyzed. The petrographically ob-served orientation is similar to that of the micro-fractures identified from the EAMS fabrics (compareFigures 16, 17).

3. Microfracture orientations determined from theEAMS tests are similar to the east-northeastwest-southwest regional in-situ stress and open fracturedirection in the Wudayhi field (compare Figures 7,10). This is further supported by observations madein this study on mesofractures in the immediate vi-cinity of samples diagnosed as microfractured byEAMS. These mesofractures show trends similarto those of the EAMS-delineated microfractures(compare Figures 10, 18).

4. The instances of fractures detected by microscopy(43% of cubes) in samples that are diagnosed as non-fracturedby theEAMStechnology were investigatedand found to represent low-density, localized, iso-lated microfractures related to microstylolites. Thesehave no significant impacton effectiveporosity.Thisdemonstrates further the efficiency of EAMS in de-tectingonlyopen, connected, pervasive fractures thathave an impact on the reservoir petrophysics. Petro-graphic methods maydetect fractures; however, thishas no reliable indication as to their petrophysicalimpact. Therefore, the margin of error in using pe-trography to detect microfractures that impact po-rosity and/or permeability is 43%; however, the re-quired sampling rate is three times that of EAMS.

Petrophysical Verification

Porosity The conventionally measured porosity values are usedto verify the values and trends of the EAMS porosityvalues. The results show the following:

1. Theporosity trend detected from theEAMS isplottedversus depth and compared with the plot of conven-tionallyacquiredporosities. Thetwosets of data showsimilar porosity profile, although the conventionally


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Table 3. Summary of EAMS Diagnoses*

EAMS ValuesEAMS-

Micofracture

SampleEAMS

Porosity (%)

K max K min K int

Strike Azimuth Plunge Azimuth Plunge Azimuth PlungeL F P

1 2.3 339 4 188 85 1.007 1.036 1.033

2 7.5 232 42 3 36 3 36 1.006 1.027 1.032 93

3 9.1 141 58 16 22 276 2 1.002 1.049 1.051 106

4 1.8 49 2 310 78 1.004 1.061 1.065

5 2.3 333 9 41 82 1.005 1.01 1.015

6 2.8 57 12 217 77 1.012 1.037 1.049

7 3.5 239 2 140 80 1.007 1.038 1.045

8 4.6 250 11 57 78 1.008 1.023 1.032

9 4.1 320 3 220 74 1.003 1.009 1.012

10 9.0 247 45 118 32 9 28 1.004 1.035 1.039 208

11 8.9 11 59 134 18 233 25 1.003 1.049 1.052 224

12 8.7 92 54 320 26 219 24 1.007 1.034 1.041 50

*In terms of microfracture occurrence and their EAMS porosity, EAMS parameters and orientation, and the petrographic verification from the three mutually of the EAMS-derived fractures and their petrographic verification, see Figures 16 and 17. EAMS = artificially enhanced anisotropy of magnetic susce

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measuredporosity was obtained independently froma set of plugs different to that used in the EAMS anal-ysis (Figure 11, well A).

2. Porosity magnitude from the EAMS in microfrac-tured samples at any particular depth is consistentlyhigher than those in nonfractured samples from thesame interval (Figure 11). This is also evident fromthecorrelatingporosity distribution of fractured sam-ples with nonfractured samples (Figure 12).

Permeability The impact of fractures on permeability is evident fromwell tests on the two key wells. The tests show that theproductivity within the Unayzah-B/C could not be ac-counted for solely by matrix porosity and permeability.The directional properties of permeability might be ver-ified by conducting interference or tracer tests on mul-tiple wells. However, this could not be done because of the lack of sufficient wells.

Figure 15. (A) Plane-polarized light photomicrograph of vertical thin section (from well A) shows open, tensile, steepmicrofractures. The fractures are along grain boundaries (I), and cutting across grains (II). (B) Scanning electron microsc(from well A) of open, tensile, primary, and secondary fractures. Note that some of the fractures are mineralized, indicatinorigin.


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DISCUSSION AND CONCLUSIONS

The study successfully developed and proved the EAMStechnology for the characterization of microfracturedreservoirs. The Wudayhi gas field presented an idealtesting ground for the technology because previousgeological characterization and well testing proved thatone of the main reservoir sections (Unayzah-B/C) is mi-crofractured. Results of the EAMS method agrees withthose acquired conventionally in previous studies of the

Wudayhi field (Al-Hawas et al., 2003). In addition, veri-fication of the EAMS method in a selection of theEAMS-tested samples shows its reliability in detectingfractures, compared to using thin sections of the samesamples (petrographic methods).Thepetrographicmeth-ods require three times the sampling rate as the EAMSmethod. One or two thin sections are not sufficient forthe detection and orientation of fractures. Three mutu-allyperpendicular thin sectionsareessential (threetimestheEAMS sampling rate).Therefore, theEAMS method

Figure 16. Lower hemi-sphere, equal-area polarplot (A) and strike rosediagram (B) of the petro-graphically measured mi-crofracture orientation

from the key EAMS sam-ples (2, 3, 11, and 12 inTable 3). Note that sample10 in Table 3 is not plottedhere because it was only observed inone of the threeorthogonal thin sections,and therefore, it was notpossible to orientaccurately.Compare with Figure 17.EAMS= artificiallyenhancedanisotropy of magnetic

susceptibility.

Figure 17. Lower hemisphere, equal-area point diagrams showing trend andplunge of the EAMS ellipsoid axes from thekey EAMS samples (2, 3, 10, 11, and 12in Table 3).K min presents the pole to theEAMS-based microfracture set. Compare with Figure 16.EAMS = artificiallyenhanced

anisotropy of magnetic susceptibility.

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is more efficient than petrographic methods. Further-more, the margin of error in petrographically detectingmicrofractures that impactreservoirporosity and/orper-meability is high: 43%. In addition, in the conventionalcharacterization method, a fourth set of sampling is re-quired for petrophysical testing. One important aspectabout the EAMS technology is its link to petrophysics.In addition to fracture orientation, we acquired effective3-Dporosity of fracturedsamples. Theeffectiveporosityof the fractures is obtained from comparing the EAMS-derived effectiveporosity of fracturedand nonfracturedsamples. Therefore, EAMS gives us fracture-effectiveporosity andpermeabilityanisotropy, an importantbridgebetween reservoir geology and engineering. This willimpact our operational and simulation effort directly.

TheEAMS technology requires a baseline geologicalstudy prior to its application on a new reservoir or field todetermine the existence and orientation of open con-nected natural fractures. In addition, during the imple-mentation of the technology, a random choice of EAMS-tested samples should be dissectedand petrographicallyverified for the presence, orientation, and type of frac-tures predicted from the EAMS tests. A selection of the samplepopulation allocated forEAMS testingshouldbe subjectedto conventional petrophysical testing beforethe EAMS test to verify the EAMS-derived porosity.

The applicability of the EAMS technology to de-tect open connected microfractures and determine theirorientation and petrophysical impact depends on thedegreeof fracturing, and the presence, degree, and rela-tive orientationof other open andconnected rock fabric(e.g., depositional, diagenetic pore space). Microfrac-tured reservoirs with nonexisting depositional or non-fracture pore fabric are good candidates for the imple-mentation of the EAMS technology. This also appliesif these nonporous matrix rocks have microfractureswith clearly defined sets or fractures that are random inorientation(e.g., dilatational cataclasites). For the latter,an EAMS test will be applicable to assessing fractureporosity and relative density. If depositional or non-tectonic pore fabric exists, but is distinctivefrom micro-fracture orientation, the EAMS technology applies.

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08-1A New Technology for the Characterization of Micro Fractured Reservoirs

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