Fractured Reservoir CharacterizationUsing Dynamic Data in a Carbonate

Field, OmanS.I. Ozkaya, Baker Atlas Geoscience, and P.D. Richard, Petroleum Development Oman

SummaryThe main objective of this study was to extract fracture data frommultiple sources and present it in a form suitable for reservoirsimulation in a fractured carbonate field in Oman. Production is bywater injection. A combination of borehole image (BHI) logs andopenhole logs from horizontal wells revealed that water encroach-ment occurs mostly through fracture corridors and appears as sharpsaturation spikes across fracture clusters. Dispersed backgroundjoints have little flow potential because of cementation, lack ofconnectivity, or small size. Image logs indicate that fracture cor-ridors are oriented dominantly in the west/northwest direction.Most of the several injector/producer short cuts are also oriented inthe west/northwest direction, supporting the view that fracture cor-ridors are responsible for the short cuts.

Flowmeter logs from vertical injector or producer wells inter-secting a fracture corridor show a step profile. A comparison of theinjection or production history of wells with or without a stepprofile provided a means to calculate permeability enhancement byfracture corridors. The field has more than 300 vertical wells andnearly 20 horizontal wells, which allowed us to generate detailedfracture-permeability enhancement and fracture-corridor densitymaps based on injector and producer data, short cuts, mud losses,openhole logs, and BHI logs. We also were able to build stochastic3D fracture-corridor models using corridor density from dynamicdata and orientation from BHI logs and seismic data. Fracture-corridor length and width were tied to fracture-permeability en-hancement using wells with both image logs and production data.The fracture-permeability enhancement maps were verified inde-pendently by waterflood-front maps. Notwithstanding the uncer-tainties, the fracture data were sufficiently accurate and detailed togenerate both single- and dual-porosity simulation results withgood field-scale history match.

IntroductionThe field was discovered in 1968 in Oman (Fig. 1). Production isfrom the Shua’iba and Kharaib reservoirs of the Lower Cretaceousage. The Kharaib is a poorly bedded stack of repetitive shoalingcycles. The Shua’iba reservoir consists of a deepening upwardsequence. The thick-bedded massive Lower Shua’iba-B gives wayto the well-layered Lower Shua’iba-A and Upper Shua’iba units.The Kharaib and the Lower Shua’iba are separated by a horizon oftight argillaceous limestone (Hawar or Kharaib-K1, Fig. 2). TheShua’iba reservoir is directly overlain unconformably by Pale-ocene Umr er Radhuma in this field.

The field consists of two low-relief eastern-A and western-Bdomes. Both the Kharaib and Shua’iba units are oil-bearing in theA and B fields. The A structure is subdivided into northern andsouthern fields. The southern field is located on a west/northwestfault zone through the southern flanks of the A field (Fig. 3). Amajor west/northwest graben connects the A south to B. Anothermajor fault zone is located on the northern flanks of the A field.

Production from the field started in 1976. Waterflooding wasstarted in 1986 following a series of pilot projects. The original

development involved waterflooding by means of an invertednine-spot vertical well. Soon after the initiation of the waterflood-ing program, early water breakthrough made it clear that the fieldwas more faulted and fractured than originally anticipated. Thedrilling pattern was subsequently changed in 1994–95 to a verticalline drive oriented parallel to the dominant northwest/southeast-trending fault/fracture pattern, following an assessment of 3D seis-mic faults and fractures, fault cutouts, BHI logs, and early pro-duction data (Arnott and Van Wunnik 1996).

The fractures and faults of the field were studied repeatedlybefore and after the drilling pattern was converted from an invertednine-spot pattern into a vertical line drive. Approximately 37 BHIlogs were obtained from horizontal wells, which provided valuableinformation and paved the way toward a comprehensive under-standing of fractures. The present study is the latest phase in theongoing appraisal of fractures, which is aimed at approaching amore predictive fracture model by integrating previous findingswith all available BHI logs and production and seismic data.

Geologic SettingThe area has been very active tectonically and has witnessed sev-eral depositional and deformational episodes since the Early Cre-taceous (Mount et al. 1998) (Fig. 2). The main paroxysmal eventstook place during the Campanian era, when Oman ophiolites wereobducted onto a carbonate platform (Loosvelt et al. 1996; Terken1999). The structure was formed during this event as a low-relieffault-bend-fold over a deep-seated blind thrust fault (Fig. 4). Someof the old Mafraq structural elements, including some northeast-trending faults, may have been reactivated at this compressionstage. The area was subjected to repeated tectonic activity duringCampanian and Maastrichtian times. The west/northwest- andnorthwest-trending normal and wrench faults of the Oman Moun-tain trend and related fractures must have formed during theseparoxysmal events. During the Tertiary period, the area was sub-jected to two major tectonic activities, first in Late Eocene-Oligocene times and later toward the end of Miocene time (Fig. 2).Some of the faults and fractures were reactivated during theseTertiary tectonic events. There are some indications on seismicprofiles that the Eocene carbonates were exposed locally and sub-jected to karstification, especially over the reactivated Cretaceousfaults, which facilitated the mixing of fresh and salt water. Thearea underwent a regional tilting during the Late Miocene tectonicactivity. Both seismic profiles and core data suggest that somenorthwest-trending faults were reactivated during this latest phase.

Three unconformities separate Tertiary shales and carbonatesfrom the underlying Shua’iba formation. Cretaceous shales arepreserved only at the flanks, and Shua’iba is directly overlain byTertiary shales and carbonates (Fig. 4). The Middle and Late Cre-taceous formations are completely missing at the crest of the field(Fig. 2).

Previous WorkAn impressive amount of work already has been done on fractures.Most of the critical questions have been answered already, and ahigh degree of control over fracture distribution already has beenachieved. Previous studies and significant results of the fracturesare summarized below before we discuss our findings.

A detailed structural, sedimentological, and petrographic analy-sis by Petroleum Development Oman (PDO) on the cores and BHI

Copyright © 2006 Society of Petroleum Engineers

This paper (SPE 93312) was first presented at the 2005 SPE Middle East Oil and Gas Showand Conference, Manama, Bahrain, 12–15 March, and revised for publication. Originalmanuscript received for review 8 January 2005. Revised manuscript received 9 February2006. Paper peer approved 1 March 2006.

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logs from a vertical well showed that faulting and fracturing tookplace mainly during Late Cretaceous emplacement of thrust sheetsin the Oman Mountains. The vast majority of natural fractures arecemented and therefore represent permeability baffles.

Arnott and Van Wunnik (1996) presented the injector/producerinfill patterns implemented to make optimum use of the fractures.They outlined a strategy to manage variable risk of drilling closeto previously unidentified faults. These authors noted that a num-ber of faults are often characterized by narrow but intense smallfracture zones and have a clear association with early water break-through from nearby injectors. The fracture-density variation alongthe well has similar patterns for both formations, but Shua’iba-A ismore fractured than Kharaib.

Lekhwair fractures were studied previously by two PDO ge-ologists (Everts and Leinster) to characterize downflank quality inthe A and B areas and to quantify fault and fracture geometry fromcore and BHI logs. They noted that deterioration of reservoir qual-ity within the down-flank areas may well be caused by pressuresolution affecting the reservoir after hydrocarbon migration. Theoccurrence of a tightly cemented matrix around the damage zonessuggests that faults will have limited connectivity with the matrixand may compartmentalize the reservoir. Anomalous fluid path-ways are more likely to be localized (karst pipes) rather than afieldwide open network of fractures. Close inspection reveals noconsistent relationship between the occurrence of (BHI-identified)fracture clusters and the presence of flushed zones.

Al-Busaidi (1997) discussed the use of BHI logs and reachedthe opposite conclusions. He saw fractures as the primary cause ofearly water breakthrough, based on integration of BHI logs andproduction logs. Densely fractured zones in most cases correspondto faults, and the number of open fractures in a well is correlatedwith water-cut percent.

A subsequent in-house study focused on the regional tectonicelements and attempted to identify fractures associated with Ma-fraq and Oman Mountain trends on the basis of fracture orienta-tion. The field is affected by three main fracture orientations,which are related to regional fault trends. The dominant fractureorientation is west/northwest parallel to faults of the Oman Moun-tain trend.

There is a general consensus that the majority of fractures arefault-related and are superimposed on a widely spaced background

jointing. Observations that support this conclusion include a highdegree of fracture clustering and an occurrence of fracture clustersnear faults. Fracture orientations from BHI logs reveal that thedominant fracture strike is parallel to the west/northwest OmanMountain trend with minor fracturing in the northeast and north-west directions. Fracturing seems to be controlled by stratigraphyto some extent. In general, all authors note that the Kharaib is farless fractured than the Lower Shua’iba reservoir unit. Existence ofmultiple phases of fracturing is evidenced by different episodes ofcalcite cementation detected by petrographic studies and the cross-cutting relationship of stylolites and fractures.

One point of divergence is the degree of cementation that frac-tures have undergone. Some PDO geologists regarded all openfractures as drilling-induced fractures and were very skepticalabout the existence of fluid-conductive open fractures. Arnott andVan Wunnik (1996) and Al-Busaidi (1997) had the opposite viewand held faults and fractures responsible for the early water break-

Fig. 1—Location map of the North Oman fields.

Fig. 2—North Oman stratigraphy (Al-Busaidi 1997).

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through and short cuts observed in many wells. The drilling patternwas changed on the basis of the hypothesis that faults and fracturesare fluid-conductive.

Data Sources and ProcedureThe main source of fracture information is BHI logs from morethan 35 horizontal wells and cores from one horizontal well andthe vertical well. Stratigraphic information (which was accumu-lated over the years from boreholes) and structural features (suchas faults from 3D seismic data) constitute the framework for frac-ture evaluation. The fracture data from BHI logs were analyzed inconjunction with dynamic flow data such as mud-loss occurrences,gross production and injection rates, water cut, and water shortcuts. Most of the horizontal wells are in the Lower Shua’iba A andB units. Only five wells are in Kharaib or have lower laterals inKharaib. Several wells intersect some section of the UpperShuaiba, and only one well is in the Upper Shua’iba itself. Thehorizontal wells provide a good coverage of the A-north sector.Most A-north wells are oriented northeast and, hence, may under-sample northeast-trending fractures.

The work started by identifying and distinguishing layer-boundjoints from fault-related hybrid fractures and fracture clusters. Al-though some coring-induced fractures were observed in cores, nodrilling-induced fractures are present in the image logs from hori-zontal wells. We first examined fractures that are identified on BHIlogs within a stratigraphic framework, searching for a correlationbetween fracture density and layer thickness in particular. Exam-ining fractures in relation to structural aspects followed the strati-

graphic evaluation. Seismic data were used to determine whetherit is possible to predict fractured zones from seismic data.

We evaluated fracture flow potential in the next phase of thework, cross-validating our findings by indirect fracture flow indi-cators such as mud-loss occurrences, water fingering, distributionof fracture injectors, and wells with high water cut. Open fractureclusters, which coincided with mud losses and water breakthrough,are regarded as high-confidence fluid-conductive fracture corri-dors. A set of low-confidence fracture corridors was identifiedfrom wells with mud losses, high water cut, fracture injectors, andearly water breakthrough. Orientation of these low-confidencefracture corridors is estimated by the orientation of nearly-high-confidence fracture corridors.

After fracture analysis, we made an attempt to generate a mapmodel of fracture corridors. The procedure was started by gener-ating maps of high-confidence fracture corridors and continued bymapping low-confidence corridors. Fracture clusters detected inBHI logs are regarded as high-confidence corridors. Low-confidence corridors correspond to mud losses, high-water-cutwells, fracture injectors, and water fingering. The composite mapswere used to interpolate between fracture corridors to generate apossible fracture-corridor map with anticipated position, orienta-tion, length, and width. The interpolated fracture fairway map wassubdivided into sectors, with each sector having nearly uniformfracture characteristics. Tables were prepared to summarize frac-ture-corridor statistics for each sector to provide fracture data forfuture reservoir simulation.

In the final phase of analysis, critical questions wereaddressed such as the timing of fractures, reactivation, and under-lying causes for the observed distribution of cemented and openfracture corridors.

Five main fracture types are recognized in the Shua’iba andKharaib reservoirs of the field:

• Dispersed background joints.• Clustered fractures.

� Joint swarms.� Fracture corridors.

• Disrupted zones.• Megafractures.• Faults.

The dispersed background fractures are typically observed as verywidely spaced, layer-bound small joints. The dispersed fracturesare mostly mineralized, although occasionally a few nonmineral-ized joints have been observed in BHI logs.

Fracture clustering can be interpreted in two different ways(Figs. 5a and 5b). A cluster is either a joint swarm or a fracturecorridor. Joint swarms are layer-bound fractures. A joint swarm isobserved in BHI logs when a horizontal well traverses a thin-bedded and highly fractured unit. Fracture corridors are clusters offractures that are confined to subvertical narrow tabular bands

Fig. 3—Base map of the field A-North and A-South sec-tors showing seismic faults, well locations, and horizontal-well trajectories.

Fig. 4—North-to-south seismic profile through the A-sector ofthe field, showing the deep-seated thrust fault, normal faultedflanks, and base tertiary unconformity (see Fig. 3 for location).

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(Figs. 5a and 5b). Fracture corridors are often, but not always,associated with faults. Tight curvatures, flexures, or deformationbands may also generate fracture corridors. Layer-bound mega-fractures often result from alignment of layer-bound fractures(Hedgeson and Aydin 1991; Cooke and Underwood 2001). Mega-

fractures are few in number, but they are believed to play a sig-nificant role in shaping the reservoir flow dynamics because thesefractures have large apertures (ranging from 0.2 to 0.5 mm).

A disrupted zone is characterized by one or more of the fol-lowing features: (1) bedding disturbance, (2) fragmentation, and(3) cementation (Fig. 5c). Disrupted zones are often small faults,fault splay, or deformation bands, but these could be related toother causes such as collapsing karstic cavities. Megafractureswith large apertures characteristically occur within fracture corri-dors (Fig. 5d), but a few isolated ones were also observed, whichmay be occasionally large open joints. Megafractures may havecemented walls.

Fracture CorridorsA previous fracture study by Ozkaya et al. (2003) shows thatfractures in most Oman carbonate fields consist of dispersed layer-bound fractures and fracture corridors (Fig. 6).

The previous study by Ozkaya et al. (2003) also suggested thatonly fracture corridors play a significant role in reservoir flowdynamics. Dispersed background fractures have limited flow po-tential and may be treated as a matrix property. The present studyplaces emphasis on the detection of fluid-conductive fracture cor-ridors and quantifies their attributes, such as permeability enhance-ment and density distribution. Therefore, identification of fluid-conductive fracture corridors is one of the main objectives of thisstudy. Fluid-conductive fracture corridors are identified on BHIlogs from dominance of electrically conductive fractures. Fracturecorridors often can be identified in BHI logs from the high degreeof clustering and the association of large and small fractures. Insome cases, it is not possible to determine whether a fracturecluster is a corridor or a highly fractured layer, and it is necessaryto probe further into the nature of the cluster by correlating thecluster with bedding thickness and faults (Fig. 7a). Fracture clus-ters that can be correlated between lower and upper laterals ornearby horizontal wells are interpreted as fracture corridors regard-less of faulting (Fig. 7b).

Fig. 5—BHI examples. (a) and (b) show fracture clusters, whichprobably represent fracture corridors. (c) is a disrupted faultzone, and (d) is a large conductive fracture (megafracture).

Fig. 6—Schematic fracture model of the Shua’iba and Kharaibreservoir units.

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The association of fracture corridors with mud losses is a strongindication that the fracture corridor is fluid conductive. If mud iswell balanced, mud loss is minimal and may be overlooked. Acemented cluster has no (or very few) open fractures and does notcorrespond to any mud loss or indication of fracture flow by wayof high water cut.

Once a fracture corridor is identified on the BHI logs, itsattributes must be quantified. The critical attributes of corri-dors include location; width; the number of open, cemented,and megafractures; corrected fracture spacing; and orientation.These attributes were quantified for all fluid-conductive and ce-mented corridors.

Our study on the fractures from BHI logs revealed that openfracture corridors are confined to the near crest of the A-northsector. Fracture corridors on the flanks are cemented. A possibleexplanation is that at least one stage of fracturing took place afteroil emplacement. Fractures within the oil leg remained open, whilethose within the water leg were sealed by carbonate cement(Fig. 8). The increasing degree of fracture cementation downflankis also accompanied by the deterioration of reservoir quality,which is attributed to pressure solution affecting the reservoir afterhydrocarbon migration (Terken 1999).

Identification of Fluid-Conductive Fracture Corridors in theAbsence of Image Logs. Only a limited number of BHI logs areavailable. The horizontal wells with image logs are mostly on theflanks, leaving a large gap on the crestal area with no image logs(Fig. 8). Therefore, it is necessary to resort to other indicators offracture corridors, which include openhole logs, flowmeter logs,and well performance histories from producer and injector wells.

Openhole Logs. In horizontal wells, openhole log plots oftenhelp identify and locate fluid-conductive fracture corridors. A

sharp drop in oil saturation with no corresponding change in po-rosity often indicates either a fracture corridor or water encroach-ment through the matrix. A comparison with BHI logs and patternrecognition may allow identifying corridors in the absence of BHIlogs (Fig. 9). Openhole logs from horizontal wells also can be usedto differentiate water fingering through fracture corridors andhighly permeable matrix streaks. Broad zones with high watersaturation (the wide bands in Fig. 9) represent water encroach-ment through permeable layers, whereas sharp spikes representfracture corridors.

Flowmeter Logs. Flowmeter logs are extremely useful in theidentification of fracture corridors and the determination of theirflow potential. Fracture corridors often cause highly prominentsteps in flow profiles. Fracture-permeability enhancement can becalculated from the magnitude of the step. Step size also differen-tiates between fracture corridors and high-permeability streaks,which are often located near the top of Lower Shua’iba-B. Theratio of rate of flow from step profiles to total flow outside stepprofiles is an indication of the transmissivity ratio of the featurecausing the step profile to the total matrix reservoir transmissivity.Transmissivity of fracture corridors ranges between two and seventimes the total matrix transmissivity (permeability times reservoirthickness, kh). Transmissivity of high-permeability streaks rangesbetween 0.25 and 1.25 times the total reservoir matrix transmis-sivity. High-permeability streaks were identified in 4 of the 32flowmeter logs. A total of 10 (out of 32) flowmeter logs showconspicuous step profiles that are interpreted as fracture corridors.

BHI and flowmeter logs form a powerful combination to quan-tify fracture corridors and tie in the flow potential to fracturedensity and corridor width. Unfortunately, only a small number ofvertical injector wells and vertical producer wells have flowmeter

Fig. 7—Fracture-corridor identification by fault association (a)and by correlation of multilaterals (b). Fig. 8—Stick plot map of high-confidence fluid-conductive and

cemented fracture corridors.

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logs. There are no horizontal wells with both flowmeter andBHI logs.

Mud Losses. Mud losses are mostly indicative of fluid-conductive fractures and faults, but karstic features and high mudpressure and hydrofracturing may also cause mud losses. Mudlosses are used as a backup and as cross-validation data in thisstudy, but not for the location of fracture corridors. Mud losses thatare coincident with fracture corridors are the prime indicator offluid-conductive fracture corridors on BHI logs.

Productivity Index and Total Well Permeability. Productivityindex (PI), especially initial PI, is a good indicator of fracture flow.

PI measurements are available for approximately the first 70 wells,and only about 20 of those are from the A-North sector (Fig. 10).The limited number of wells and variable timing reduce the valueof PI for identification of fracture corridors. Nevertheless, thehigh PI values are within the faulted southern flank of the A-north structure.

Total horizontal transmissivity (kh) is also highly indicative offracture flow. Total kh values are calculated for approximately thefirst 70 wells, with only about 20 being from the A-north sector ofthe field. The high values seem to be concentrated within thesouthern faulted sector, with a few high values at the crest(Fig. 11).

Well Performance Histories. Well performance histories areperhaps the most important source of information for identificationof fluid-conductive fracture corridors. High gross sustained pro-duction rates may be an indication of fracture flow. Average sus-tained gross is calculated from well performance history after ex-cluding the initial decline and eliminating all irregularities, such asshut-in periods. Map distribution provides an insight into the dis-tribution of fluid-conductive fracture corridors. Wells show highrates in the southern and northern faulted flanks, while the wells inthe middle crestal sector of the field are mostly low-rate matrixproducers (Fig. 12).

High injection rates and injection rate divided by tubinghead-pressure values also may be indicative of fracture flow. Injectionrates are calculated from well performance history. Only the initialinjection phase is taken into consideration before injection ratesstart to decline. Average injection rates divided by tubinghead-pressure values are used when there are changes in tubingheadpressure during injection. Injection-rate bubble plots indepen-dently confirm indications by producer wells that most fracturingis concentrated on the southern and northern faulted sectors(Fig. 13).

Wells Intersecting Fracture Corridors. Matrix and fractureproducers are differentiated on the basis of sustained gross rates.The threshold value is estimated to be 150 m3/d by averaging thegross rates of wells with gradual flowmeter profiles. This thresholdvalue is the total combined gross rate for the Lower Shua’iba andKharaib reservoirs. Wells with gross rates higher than 150 m3/d areregarded as fracture producers. Such wells are assumed to intersectfluid-conductive fracture corridors. The threshold value is vali-dated by flowmeter logs. A well with less than 150 m3/d produc-

Fig. 10—A bubble map of initial PI values from approximately20 wells.

Fig. 11—Bubble map of kh from approximately 20 wells in theNorth sector of the field.

Fig. 9—Porosity and water saturation from openhole logs andfracture density from image logs in a horizontal well.

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tion has no conspicuous step profiles that can be interpreted asfracture corridors.

Matrix and fracture injectors are separated on the basis of initialinjection rates divided by tubinghead pressures. The matrix/fracture threshold value is estimated as 0.08 m3/d/kPa on the basisof fracture and matrix injectors. The threshold rate is estimated asthe average injection rate of wells with gradual flowmeter profiles.Step profiles identify fracture injectors.

Because a large number of vertical producer and injector wellsare available in the field, the field-scale distribution of fluid-conductive fracture corridors is based mainly on these data(Fig. 14). From the map distribution of fracture producer or injec-tor wells, a clear concentration in the southern and northern faultedsectors is seen. In addition, the map distribution also reveals thealignment of fracture wells along some open or hidden fault zones,such as the north/northwest fault on the western flank and close tothe crest.

Wells Fractured by Injection. The injection history of approxi-mately 10 injector wells suggests hydraulic fracturing by excessinjection pressures. In these wells, injection rate jumps up sud-denly, with no corresponding change in injection pressure. Theinjection rate of some of these wells may reach injectors thatintersect natural fractures, probably because injection-inducedfractures link to the natural fracture system. These were regardedas matrix injectors.

Pressure-Transient Analysis. Well tests are very useful forquantifying fracture-corridor length and permeability; unfortu-nately, no well tests were available when this study was conducted.

Direction of Fracture Corridors. Producer or injector well per-formance or other indirect fracture-flow indicators do not provideinformation on the orientation of fracture corridors. A strike anddip must be assigned to each fracture corridor. The followingsources of information were used to assign direction to fracturecorridors from production data.

BHI Logs. The corridors from image logs have been identifiedand mapped, and the dominant orientation of fracture corridors andsecondary sets have been determined (Fig. 8). Most of the fracturecorridors on BHI logs are oriented in a northwest direction. Thereare two subordinate sets with north/northwest and northeast direc-tions. This information is used to assign an orientation to corridorsfrom production data in two ways:

• Statistically, the percentage of northwest, north/ northwest,and northeast corridors from production data are made equal tothe relative abundance of corridors in these directions fromBHI logs.

• Corridors with unknown orientation are assigned anorientation similar to nearby corridors from BHI logs withknown orientation.

Seismic Faults. Corridors in BHI logs and injector/producershort cuts are found to be parallel to seismic faults. This observa-tion provides an additional means to assign orientation to corridorsfrom production data. Corridors near seismic faults are assignedorientation parallel to the seismic fault.

Injector/Producer Fracture Short Cuts. An extensive investi-gation was performed to locate injector/producer short cuts bycomparing the well performance histories of injectors and nearbyproducer wells. This information is used to demonstrate theexistence and length of large-scale corridors (fairways) andtheir orientation.

Fig. 13—Normalized injection rates.

Fig. 14—Fracture producers: wells intersecting fracture corridors.

Fig. 12—Sustained gross rates.

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Dip Angle of Fracture Corridors. For horizontal wells with im-age logs, the corridor dip angle and dip azimuth are taken from theBHI logs. If a vertical well is on a corridor or fairway intersectedby horizontal wells with BHI logs, it is assigned the same dipangle. If a vertical well is away from known corridors, the averagecorridor dip is assigned to it; the average corridor dip is calculatedfrom BHI logs.

Length of Fracture Corridors. Length of fracture corridors canbe estimated by correlating fracture corridors in adjacent horizon-tal wells. Similarly, corridor height can be estimated from duallaterals (Fig. 7). Unfortunately, only a limited number of wellshave dual laterals or are close enough to allow correlation ofcorridors. We have estimated average corridor lengths as 150 mfrom the width/length ratio of the corridors from two nearbywells and the average width of corridors in other wells. We haveadopted a 3-to-1 length-to-height ratio based on the correlationof corridors between lower and upper laterals in two wells withdual laterals.

Individual corridors from production data are assigned lengthson the basis of the permeability enhancement they cause. Theaverage permeability enhancement is assigned to the averagecorridor length of 150 m. The corridor length is zero for ma-trix producers.

Fracture Corridors Encountered in Wells. Fracture corridorsare generated from production and image log data (Fig. 14) afterorientation, and length is assigned to each corridor. As noted ear-lier, orientation is based on BHI logs, adjacent seismic faults, andshort cuts. Length is based on permeability enhancement. Fracture-corridor length must be regarded as an index, rather than the actuallength, because no reliable length estimate is available.

Fracture Fairways and Short Cuts. The average length of frac-ture short cuts is more than 1 km, which suggests the existence ofinterconnected fracture corridors. Strong alignment of corridors,especially in the vicinity of seismic faults, supports the idea thatsuch interconnected clusters of fracture corridors do exist.

Fracture-Permeability Enhancement MapsFracture-permeability enhancements from producer and injectorswells are presented as bubble plots in Fig. 15 and as a contour mapin Fig. 16, with fracture corridors superimposed to show the mag-nitude as well as the direction of fracture-permeability enhance-

ment. Grid data for fracture-permeability enhancement have beengenerated for the three main directions northwest, north/northwest,and northeast. These are the essential fracture data to be incorpo-rated in a single-porosity simulation model.

Cross ValidationAn attempt has been made to validate fracture results by usingadditional data sources. Flood-front maps are used to validate themap distribution of fracture corridors from production data. Someflowmeter logs from producing wells and a few additional injectorwells are used to confirm fracture and matrix wells identified fromother sources. Injector wells and one crestal well with an image logare used to validate the ratio of corridors in the Lower Shua’ibaand Kharaib. Water fingering from openhole (OH) logs is usedto validate flood-front maps from BSW (bulk solids andwater—water cut). Reported faults from openhole logs with mudlosses are used to validate fluid-conductive corridors from hori-zontal wells.

Flood-Front Movement. Flood-front movement is one of the keyindicators of fracture flow. Therefore, water-movement maps werecorrelated with the fracture-corridor density maps. Flood-frontmaps were prepared to show wells with more than 60% BSW in1995 and 2000 (Fig. 17). There is a major convergence betweenhigh water cut and fracturing. Most of the water comes throughfractures except on the eastern flank, where some matrix waterencroachment is observed. This encroachment is caused by theLower Kharaib bringing in water because of its proximity to freewater contact. Although not indicated on these maps, high watercut has little correlation with the location of injector wells.

Previous examination of injector flowmeter logs revealed theexistence of a high-permeability streak at the top of LowerShua’iba B. In combination with fracture corridors, suchhigh-permeability streaks may facilitate water encroachment andoverriding, causing poor sweep efficiency. To answer thisquestion, water-encroachment maps were prepared from produc-tion data.

Water fingering was also mapped from vertical-well openhole-log saturation and porosity data for the Shua’iba A and B and theKharaib-5, respectively. Water-encroachment data are taken as thedifference between average observed and expected hydrocarbonsaturation in the three reservoir intervals Lower Shua’iba A and Band Kharaib-5. Kharaib-5 is the fifth subunit of the Kharaib res-ervoir from the top and is the main Kharaib subunit.

Fig. 16—Fracture-permeability index contour map.Fig. 15—Fracture-permeability index.

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One drawback of this method is that the openhole-log satura-tion is obtained immediately after drilling and reflects only thesituation at the drillsite at the time of drilling. Many of thestudy wells are, on average, 20 to 30 years old. Therefore, theresults cannot be regarded as a reflection of present-day actualwater encroachment.

In all three reservoir units, water fingering starts in the frac-tured northern and southern sectors, confirming the findings fromproduction data. Comparison of the maps shows that water finger-ing is most advanced in Lower Shua’iba-B (Figs. 18 and 19).Porosity and saturation logs from horizontal wells confirm thisobservation (Fig. 9). Of 21 horizontal wells, only 4 show slightflushing in Lower Shua’iba-A (only 2 in the Kharaib). The re-maining 15 wells show partial or complete flushing of theShua’iba-B unit.

The water-saturation bubble map from openhole logs of verti-cal wells shows that most of the water fingering in LowerShua’iba-B starts at faults and fracture corridors (Fig. 20). Thismap also can be interpreted as an indication of the waterfloodingmechanism. Water moves through faults and fracture corridors intohigh-permeability streaks within the Lower Shuiba-B unit first.The type of fracturing also may encourage early water break-through in the B unit, rather than the A unit. Although A is thinlybedded and far more fractured than B, the B unit has considerablymore megafractures (large conductive fractures).

Validation of Corridor Concept With Flowmeter Logs. Thisstudy is fundamentally based on the assumption that fracture cor-ridors are the main fracture-flow conduits. Dispersed fractureshave little flow potential either because of cementation or because

Fig. 18—A snapshot of water encroachment in Lower Shua’iba-A.

Fig. 19—A snapshot of water encroachment in LowerShua’iba-B.

Fig. 20—Rise in water saturation from openhole logs acquiredat different times in the Lower Shua’iba-B.

Fig. 17—Flood-front movement map.

235June 2006 SPE Reservoir Evaluation & Engineering

of their small size and lack of connectivity. Flowmeter logs pro-vide a means of validating this assumption. When a borehole in-tersects a fracture corridor, one or a few megafractures within thecorridor are expected to act as a permeability spike and cause astep profile in flowmeter logs. A pervasive fracture system isexpected to generate a smooth flow profile, even though total flowrate is higher than matrix rates. The flowmeter logs from fractureinjectors or producers are always marked by a step profile, sug-gesting corridors rather than pervasive layer-bound fracturing.

Validation of Corridor Density and Length From BHI Logs. BHIlogs provide a reliable means of measuring the scan-line density offracture corridors at different sectors of the field. These values areused to validate the corridor-density calculations from productiondata as follows. Four crestal wells are used to estimate corridorscan-line density within the highly fractured and faulted southernsector, the crestal area, and the northern faulted sectors, respec-tively. These results of the corridor scan-line density from BHIlogs and production data are compared. There is good agreementbetween the two results. For example, the north/south crestal wellsyield an average corridor spacing of 161 m for northwest corridors.Production data yield 125- to 167-m spacing in the highly frac-tured and faulted sector in which the wells were drilled.

UncertaintiesDefining uncertainties is an important step in fracture-data prepa-ration for simulation. We have made an attempt to identify themain uncertainties and quantify them whenever possible. These areexplained below.

Are Fractures Responsible for Permeability Enhancement? Thefundamental question is the connection between fractures and per-meability enhancement; no wells have both image logs and flow-meter logs to definitely match and identify fluid-conductive cor-ridors. Mud losses are highly supportive but do not constitutedefinite proof because mud losses may also be associated withkarstic dissolution features, or hydraulic fractures. The first mainobservation is that BSW is high when gross production rate isalso high. The second observation is that the high BSW andhigh production and injection-rate wells are clustered in the south-ern and northern highly faulted sectors of the field. These twoobservations suggest that fractures may be the cause of permeabil-ity enhancement.

If fractures are responsible for permeability enhancement, per-meability enhancement should correlate with corridor width andopen fracture spacing. Permeability enhancement of fracture cor-ridors, which are intersected by both vertical wells and horizontalwells with BHI logs, makes it possible to calculate the correlationcoefficients. The correlation coefficients between permeability en-hancement and corridor width and open fracture spacing are0.31 and 0.42, respectively. These correlation coefficients arelow and fail to remove the uncertainty surrounding the funda-mental assumption that fractures are responsible for permeabil-ity enhancement.

Threshold Values for Fracture/Matrix Producer and Injec-tors. The bulk of the fracture-corridor information is based on theperformance history of the producer and injector wells. The matrixand fracture producers and injectors are classified on the basis ofarbitrary threshold values. The frequency distribution of gross pro-duction and injection rates is log-normal, with no obvious differ-entiation of fracture and matrix producers. The threshold valuesare close to modal values in both cases, which implies a highdegree of sensitivity. For example, a change from 150 to 175would eliminate 40 wells as fracture producers. In the case ofinjector wells, the sensitivity is less. A change in the thresholdvalue from 0.08 to 0.1 would eliminate only 10 wells as fractureinjectors. Some matrix wells intersecting high-K matrix streaksmay have production rates higher than the 150 m3/d thresholdvalue. Some of the wells, which are interpreted as fracture pro-ducers or injectors at the crest of the field, may actually intersectonly high-K matrix streaks. The general map pattern, however,

suggests that the threshold value classifies most of the wellscorrectly. The error margin based on flowmeter logs is estimatedto be 10%.

Fracture-Corridor Length. Average corridor length estimation isbased on the length/width correlation from the BHI log and theonly two adjacent wells to calibrate the results. Corridor length isalso estimated indirectly by matching corridor density from BHIlogs with corridor density from production data. In both cases,there is a large degree of uncertainty. The uncertainty in length isnot critical if only fracture-permeability enhancement grid data areused to upscale and import fracture data into simulators. It be-comes critical, however, if fracture data are generated by upscalingstochastic models.

Corridor Density. Corridor density is calculated by counting thenumber of fracture producer or injector wells within a circularwindow. Corridor length, height, and shape affect density-gridcalculations to some degree. Although it is difficult to quantify theuncertainty, we found that changing the window size affects onlythe density spread, not the actual values. Fracture height is a criti-cal factor, and we have little control over the height of corridorsexcept in the assumption that corridors either cut through bothreservoir units or are confined to one unit only.

Fracture Communication Between the Kharaib and LowerShua’iba. There are no data to evaluate the degree of communica-tion between the Lower Shua’iba and Kharaib reservoirs throughthe low-permeability Hawar muddy carbonates. Some fracture cor-ridors are identified in both Kharaib and Lower Shua’iba in wellswith dual laterals. However, this does not provide any informationon pressure communication. The fracture corridors may consistonly of a few shear fractures within the Hawar unit with no pres-sure communication.

Relative Significance of Corridors and Dispersed BackgroundFractures. The present work is based on the assumption that frac-ture corridors are the main flow conduits. Flowmeter logs havebeen used to validate the corridor concept (see the previous sec-tion), but step profiles do not constitute solid proof of that concept.In some wells, wide zones of fractures, which merge to form apervasive fracture system, surround corridors. This is even moreconspicuous in the thin-bedded Lower Shua’iba-A. The relativeflow potential of narrow corridors with megafractures in compari-son to wide bands of dispersed joints is highly uncertain at thisstage. The fundamental observation, however, remains unchanged.Both corridors and dispersed fractures are more abundant in thehighly faulted northern and southern sectors of the field.

Fracture-Corridor Distribution Between Lower Shua’iba andKharaib. One important question is the distribution of fracturecorridors between the Lower Shua’iba and Kharaib reservoirs.This question is related to (i) rock-mechanical aspects of reservoirunits, (ii) the mechanism of corridor generation, and (iii) cemen-tation. The only well with dual laterals in the Lower Shua’iba andKharaib shows that the Lower Shua’iba is more fractured than theKharaib and has more open fractures and corridors (Fig. 7). Thefrequency of corridors in Lower Shua’iba or Kharaib is highlyvariable depending on the source of information.

Injector flowmeter logs and well image logs suggest a 3-to-1ratio for the Lower Shua’iba and Kharaib corridors. However,fracture producer and injector data suggest a 1-to-1 ratio. Obvi-ously, BHI and flowmeter data must be regarded as more reliablethan production data in this respect because in many wells, it isnot possible to determine conclusively which unit intersects a frac-ture corridor.

Clustering of Fracture Corridors. It appears that corridors aremore abundant in the vicinity of major faults, but no analysis hasbeen done to ascertain the affinity of corridors to major faults.Plotting the distance of corridors from the nearest fault as a fre-

236 June 2006 SPE Reservoir Evaluation & Engineering

quency plot and measuring deviation from random distributioncould provide a measure of the degree of corridor clustering.

Stochastic Modeling

A viable procedure to incorporate fracture-corridor data into asimulator is to generate stochastic corridor models, which can beused to extract fracture parameters for dual-porosity simulationsuch as matrix block size and effective fracture permeability andporosity. For this purpose, discrete stochastic models of fracturecorridors are generated using the corridor density-grid data forundifferentiated corridors. In these models, corridor distribution isassumed to follow the Poisson distribution. Corridor length is as-sumed to have exponential distribution with an average of 150 m.Corridors are simulated as three distinct (northwest, north/northwest, and northeast) sets. The corridor orientation has a uni-form distribution with 10° range around the average strike of thesethree sets.

Fig. 21 shows a stochastic realization. The actual corridors aresuperimposed on stochastic corridors. An equal number of sto-chastic corridors are removed to maintain the observed corridordensity. The location of stochastic corridors ignores wells that didnot actually intersect corridors (matrix producers). Some of thecorridors at the margins are removed because these are outside thearea of interest and generated by extrapolation. The width of thecorridors in plan view reflects the dip angle and height. Eachcorridor in these stochastic models is assigned a permeability en-hancement value based on its length and the relationship betweenlength and permeability enhancement for the actual corridors toallow upscaling.

Conclusions

The main conclusions are as follows:1. BHI and seismic data show that the main fracture direction is

northwest, with subordinate sets in the north/northwest andnortheast directions.

2. Fault-related fracture corridors are the main fracture-flow con-duits. Dispersed background joints have little flow potentialbecause of cementation, lack of connectivity, or small size.

3. Fracture corridors are fluid-conductive only within the oil legbut are cemented at the flanks within the water leg.

4. Integration of available BHI, flowmeter, and openhole logs with

seismic faults and production data allows us to generate thefollowing for the three main fracture directions:• Horizontal fracture-permeability enhancement map for both

the Lower Shua’iba and Kharaib reservoirs.• Fracture-corridor density maps and stochastic fracture

models. Each stochastic and observed corridor is assignednecessary attributes, including permeability enhancementfor upscaling.

5. The horizontal fracture-permeability enhancement maps maybe used to generate vertical-fracture enhanced permeabilitymaps, which can be imported directly into the reservoir simulator.

6. Alternatively, the stochastic fracture models can be used to gen-erate upscale fracture data into the simulator. In this case,it is necessary to perform single-well simulation runs to con-vert the fracture-permeability enhancement into fracture-corridor transmisisvity.

The main uncertainties are:1. Threshold value to differentiate fracture producer or injector

wells from matrix producer/injectors.2. Fracture-corridor length.3. Fracture communication between the Kharaib and Lower

Shua’iba reservoirs.4. Corridor distribution between Lower Shua’iba and Kharaib.5. Degree of clustering of fracture corridors.Notwithstanding the uncertainties, the fracture data are sufficientlyaccurate and detailed for reservoir-simulation purposes. Thefollowing additional data acquisition may be necessary to reducethe uncertainties:1. Tests to establish pressure communication between Lower

Shua’iba and Kharaib.2. Measurements to evaluate present-day oil saturation using sur-

veillance data.3. Additional flowmeter logs for better control of the frac-

ture corridors.4. Map distribution of bottomwater and injector water produced.5. Assessment of the imbibition characteristics of the matrix/

fracture system.6. Performance of several well tests to quantify fracture-corridor

length and transmissvity.

AcknowledgmentsWe would like to thank Petroleum Development Oman and theOman Ministry of Oil for permission to present this work. A.J.Everts and R.C. Leinster conducted a study entitled “FracturedCarbonate Reservoir Modeling—Lekhwair Field” in 1997; theirwork is available as an internal PDO report.

ReferencesAl-Busaidi, R. 1997. The Use of Borehole Imaging Logs to Optimize

Horizontal Well Completions in Fractured Water-Flooded CarbonateReservoirs. GeoArabia 2 (1): 19–32.

Arnott, S. and Van Wunnik, J.N.M. 1996. Targeting Infill Wells in theDensely Fractured Lekhwair Field, Oman. GeoArabia 1 (3): 405–416.

Cooke, M.L. and Underwood, C.A. 2001. Fracture Termination and Step-Over at Bedding Interfaces Due to Frictional Slip and Interface Open-ing. J. of Structural Geology 23 (2–3): 223–238.

Hedgeson, D.E. and Aydin, A. 1991. Characteristics of Joint PropagationAcross Layer Interfaces in Sedimentary Rocks. J. of Structural Geol-ogy 13 (8): 897–911.

Loosvelt, R.J.H., Bell, A., and Terken, J.J.M. 1996. The Tectonic Evolu-tion of Interior Oman. GeoArabia 1 (1): 29–51.

Mount, Van S., Crawford, R., I., S., and Bergman, S.C. 1998. RegionalStructural Style of the Central and Southern Oman Mountains: JebelAkhdar, Saih Hatat and the Northern Ghaba Basin. GeoArabia 3 (4):475–490.

Ozkaya, S.I., Kolkman, W., and Amthor, J. 2003. Mechanical Layer-Dependent Fracture Characteristics From Fracture Density vs. TVDCross Plots. Examples From Horizontal Wells in Carbonate Reservoirs,North Oman. Paper presented at the AAPG Intl. Exhibition and Con-ference, Barcelona, Spain, 21–24 September.

Terken, J.M.J. 1999. The Natih Petroleum System of North Oman.GeoArabia 4 (2): 157–180.Fig. 21—Stochastic fracture-corridor model.

237June 2006 SPE Reservoir Evaluation & Engineering

SI Metric Conversion Factorsbar × 1.0* E+05 � Pabbl × 1.589 873 E–01 � m3

ft × 3.048* E–01 � mmile × 1.609 344* E+00 � km

*Conversion factor is exact.

Sait I. Ozkaya is a geological consultant with Baker Atlas Geo-science in Manama, Bahrain. He worked as a professor of ge-ology at several universities and as an exploration geologist forChevron before joining Baker Atlas Geoscience in 1996. Hespecializes in integrated fractured reservoir characterizationusing static and dynamic data and has conducted many frac-

ture studies in various carbonate and clastics fields in theMiddle East. Ozkaya is the author of several publications oncomputer applications in fracture and structural analysis. Heholds an MS degree in computer science and a PhD degree instructural geology from the U. of Missouri. Pascal D. Richard is asenior structural geologist at the Study Centre of PetroleumDevelopment Oman (PDO) and Carbonate Technology Co-ordinator for PDO in Muscat, Oman. Previously, he joined Shellin 1991 and spent 4 years in the Research Structural GeologyDept. working on the modeling of structural styles, fault growth,and hydrocarbon systems. After working for 3 years with PDOas a structural geology consultant and seismic interpreter, heworked for 5 years on Shell E&P’s Research Carbonate Devel-opment Team, focusing on the characterization and modelingof fractured reservoirs. Richard is now implementing fracturetechnology at PDO and has a role in coaching and knowl-edge transfer. He holds a PhD degree in structural geologyfrom the U. of Rennes, France.

238 June 2006 SPE Reservoir Evaluation & Engineering