stimulation design for unconventional resources
TRANSCRIPT
34 Oilfield Review
Stimulation Design for Unconventional Resources
The oil and gas industry has undergone a renaissance brought on by the development
of ultralow-permeability reservoirs, made possible through horizontal drilling and
hydraulic fracturing. Recent innovations in systematic engineering design are improv-
ing stimulation effectiveness and well production. Completion engineers are able to
perform the entire design loop, from reservoir characterization to stimulation plan,
monitoring and calibration and production evaluation.
Babatunde AjayiSeneca Resources CorporationPittsburgh, Pennsylvania, USA
Iroh Isaac AsoIra J. “Jay” Terry, Jr.Kirby Walker Kevin WutherichCanonsburg, Pennsylvania
Jacob CaplanDewey W. GerdomPDC Mountaineer LLCBridgeport, West Virginia, USA
Brian D. ClarkUtpal GangulyHouston, Texas, USA
Xianwen LiYonggao XuHua YangPetroChina Changqing Oilfield CompanyXi’an, Shaanxi, People’s Republic of China
Hai LiuBeijing, People’s Republic of China
Yin LuoChengdu, Sichuan, People’s Republic of China
George WatersOklahoma City, Oklahoma, USA
Oilfield Review Summer 2013: 25, no. 2. Copyright © 2013 Schlumberger.For help in preparation of this article, thanks to Paul A. Babasick, Houston; John P. McGinnis and Barry L. McMahan, Seneca Resources Corporation, Houston; and Michael Yang, Beijing.Mangrove, Petrel, RST, Sonic Scanner, StimMAP LIVE and UFM are marks of Schlumberger.INTERSECT is a joint mark of Schlumberger, Chevron and Total.
The ability to efficiently exploit ultralow-permea-bility plays has invigorated the oil and gas indus-try around the globe. The transition from vertical to horizontal wells was spurred by development of revolutionary techniques for drilling and com-pletion. Eventually, completion and stimulation design for horizontal wells evolved into a stan-dard template—the geometric method, whereby engineers divide the horizontal wellbore length evenly into the number of planned intervals, or stages, designated for fracture treatment. To pro-mote fracture growth from multiple starting points, engineers then design stages typically with two to eight perforation clusters distributed uniformly along the stage length.
The geometric approach for fracture design ignores the vertical and horizontal heterogeneity of unconventional reservoirs. Vertical wells may penetrate a stack of highly variable sandstone and shale strata. Horizontal wells may wander through heterogeneous portions of a reservoir, or even completely out of a reservoir, depending on how closely the driller was able to follow the target zone. Geologic heterogeneity along wellbores causes wide variability of rock properties that, in turn, directly affect where fracturing stages will encounter producible reservoir rock. Consequently, the geometric placement of stages often results in poor well performance, leading completion engi-neers to use manual, time-intensive methods of picking stage and perforation locations based on subtle well log characteristics.
Increasingly, directional wells are being drilled and steered based on logging-while-drill-ing (LWD) data.1 Engineers can use these measurements to characterize small-scale het-erogeneities that horizontal wells encounter as they penetrate stratified formations. However, even with the addition of LWD data to help in planning stimulation programs, well perfor-mance has been difficult to predict.
Recently, Schlumberger engineers analyzed production logs from more than 100 horizontal shale gas wells in six US shale basins to identify factors that influence the effectiveness of hydrau-lic fracture completions.2 The analysis indicated that perforation efficiency—the percentage of perforation clusters that contribute to produc-tion—was about 70%. Nearly a third of the clus-ters contributed nothing to production. The investigators looked deeper into the data to explain this inefficiency.
The data showed that increasing the number of fracture stages and decreasing the distance between stages and between perforation clusters correlated with a rise in production rate from a well. Stimulation design is a compromise between the extremes of a single customized fracture stage and of multiple stages to cover a wide vari-ety of rocks. Increasing the number of perfora-tion clusters and stages is not a guarantee for success. The analysis suggested that focused staging is important: Fracture stages should tar-get rocks with similar petrophysical and geome-chanical properties.
1. For more on current horizontal drilling technology: Felczak E, Torre A, Godwin ND, Mantle K, Naganathan S, Hawkins R, Li K, Jones S and Slayden F: “The Best of Both Worlds—A Hybrid Rotary Steerable System,” Oilfield Review 23, no. 4 (Winter 2011/2012): 36–44.For more on steering horizontal wells: Amer A, Chinellato F, Collins S, Denichou J-M, Dubourg I, Griffiths R, Koepsell R, Lyngra S, Marza P, Murray D and Roberts I: “Structural Steering—A Path to Productivity,” Oilfield Review 25, no. 1 (Spring 2013): 14–31.
2. Miller C, Waters G and Rylander E: “Evaluation of Production Log Data from Horizontal Wells Drilled in Organic Shales,” paper SPE 144326, presented at the SPE North American Unconventional Gas Conference and Exhibition, The Woodlands, Texas, USA, June 14–16, 2011.
Summer 2013 35
36 Oilfield Review
Because it was apparent that not every stage contributed equally to well productivity, the investigators also examined the contribution of perforation clusters within fracture stages. They determined that, like fracture stages, not every cluster contributed equally to production, and they concluded that the optimal number of perfo-ration clusters per stage ranged from two to five. The analysis suggested that strategic placement of clusters within productive and fracturable geo-logic units was more important than the number of clusters.
The study results led to fundamental design questions:• Is there an optimal number of treatment stages?• Is there an optimal location for each treatment
stage along a wellbore?• Is there an optimal place for perforation clus-
ters within stages?To address these questions, Schlumberger com-
pletion engineers developed the Mangrove reservoir
stimulation design software for engineering, modeling and designing hydraulic stimulations. The software facilitates a systematic strategy for designing multistage stimulations centered on single wells embedded within the context of a 3D earth model of the reservoir. Completion and stimulation design is based on multidisciplinary reservoir characterization that is combined with microseismic information for model calibration and integrated with production forecasting for design evaluation.3
This article describes the Mangrove software and outlines case studies that demonstrate how the software helps operators improve well pro-ductivity. Two examples from the eastern US show side by side comparisons of well produc-tivities that result from conventional and engi-neered completions in the Marcellus Shale. An example from the Ordos basin of China illus-trates improvements to production from low-permeability sandstones.
Engineered StimulationsWhile Mangrove software provides a specific engineering workflow intended for predictive model building and evaluation of hydraulic frac-ture treatment in unconventional reservoirs, it also continues to support workflows and model-ing necessary for conventional reservoirs. The Mangrove system is capable of accommodating reservoir heterogeneity, rock fabric, physical properties and geomechanical properties at a fine level of detail without compromising compu-tational efficiency.4
Input to the workflow comes from geologic, core, well log, seismic, production log and engi-neering data. Geologists, geophysicists and engineers compile, synthesize and interpret these data and summarize them in a common 3D earth model. This integration and display are performed within the Petrel E&P software plat-form. The earth model forms the basis for geo-logic, discrete fracture network (DFN) and geomechanical models that are input to the completion advisor as well as to a number of hydraulic fracture models and to production and forecasting simulators accessible within the Mangrove workflow.
Engineers use the Mangrove completion advi-sor to assign levels of reservoir quality and com-pletion quality to the reservoir rock (above left).Reservoir quality (RQ) is a prediction of how prone the rock is to yield hydrocarbon. Completion quality (CQ) is a prediction of how effectively the rock may be stimulated using hydraulic fractures. The RQ and CQ parameters typically receive binary scores of good or bad based on cutoff criteria for a reservoir. They are then combined into composite scores that grade the intervals from best to worst for placing frac-turing stages and perforation clusters within each stage. The best locations have good RQ and CQ grades, meaning the rock should be produc-tive and fracturable (next page).5 The completion advisor also allows similar quality rocks to be grouped in the same stage, leading to the most effective multistage treatment. The completion advisor is able to accommodate user-provided operational constraints, such as the maximum stage interval or minimum and maximum perfo-ration interval, and structural constraints such as fault locations and distances of perforation clusters from these faults.
After deciding where to locate stages and per-foration clusters, engineers design the stimula-tion treatments using hydraulic fracture (HF) simulators. In situations in which the geology is
3. Cipolla C, Weng X, Onda H, Nadaraja T, Ganguly U and Malpani R: “New Algorithms and Integrated Workflow for Tight Gas and Shale Completions,” paper SPE 146872, presented at the SPE Annual Technical Conference and Exhibition, Denver, October 30–November 2, 2011.Cipolla C, Lewis R, Maxwell S and Mack M: “Appraising Unconventional Resource Plays: Separating Reservoir Quality from Completion Effectiveness,” paper IPTC 14677, presented at the International Petroleum Technology Conference, Bangkok, Thailand, February 7–9, 2012.
4. Fabric refers to the spacing, arrangement, distribution, size, shape and orientation of the constituents of rocks such as minerals, grains, porosity, layering, bed boundaries, lithology contacts and fractures.
5. For more on fracture staging algorithms: Cipolla et al (2011), reference 3.
6. For more on conventional hydraulic fracture models: Brady B, Elbel J, Mack M, Morales H, Nolte K and Poe B: “Cracking Rock: Progress in Fracture Treatment Design,” Oilfield Review 4, no. 4 (October 1992): 4–17.
7. Jeffrey RG, Zhang X and Thiercelin M: “Hydraulic Fracture Offsetting in Naturally Fractured Reservoirs: Quantifying a Long-Recognized Process,” paper SPE 119351, presented at the SPE Hydraulic Fracturing Technology Conference, The Woodlands, Texas, January 19–21, 2009.
> Reservoir quality and completion quality factors.
Reservoir Quality (RQ) Completion Quality (CQ)
Mineralogy—mainly clay, carbonate and silica
Mechanical properties—Young’s modulus,Poisson’s ratio and tensile strength
Natural fractures—presence, density, orientationand condition (open, closed or cemented)
In situ stress—variations between intervals accounting for mechanical properties anisotropy
Organic content
Thermal maturity
Effective porosity
Intrinsic permeability
Fluid saturations—oil, gas,condensate and water
Organic shale thickness
Hydrocarbons in place
Suárez-Rivera R, Deenadayalu C, Chertov M, Hartanto RN, Gathogo P and Kunjir R: “Improving Horizontal Completions on Heterogeneous Tight Shales,” paper CSUG/SPE 146998, presented at the Canadian Unconventional Resources Conference, Calgary, November 15–17, 2011.Suárez-Rivera R, Burghardt J, Stanchits S, Edelman E and Surdi A: “Understanding the Effect of Rock Fabric on Fracture Complexity for Improving Completion Design and Well Performance,” paper IPTC 17018, presented at the International Petroleum Technology Conference, Beijing, March 26–28, 2013.
8. For more on the wiremesh model: Xu W, Thiercelin M, Ganguly U, Weng X, Gu H, Onda H, Sun J and Le Calvez J: “Wiremesh: A Novel Shale Fracturing Simulator,” paper SPE 132218, presented at the CPS/SPE International Oil and Gas Conference and Exhibition in China, Beijing, June 8–10, 2010.
9. For more on the UFM model: Weng X, Kresse O, Cohen C, Wu R and Gu H: “Modeling of Hydraulic Fracture-Network Propagation in a Naturally Fractured Formation,” SPE Production & Operations 26, no. 4 (November 2011): 368–380.Kresse O, Cohen C, Weng X, Wu R and Gu H: “Numerical Modeling of Hydraulic Fracturing in Naturally Fractured Formations,” paper ARMA 11-363, presented at the 45th US Rock Mechanics/Geomechanics Symposium, San Francisco, June 26–29, 2011.
Summer 2013 37
relatively simple, conventional HF simulators are adequate. These time-tested 2D and pseudo-3D models treat HFs as planes propagating away from the well in the direction of the maximum principal compressive stress.6 Engineers have the option to use these models in the Mangrove work-flow and determine which model is best suited for a given reservoir.
Conventional models are not comprehensive enough for heterogeneous and naturally frac-tured reservoirs. Hydraulic fracture growth is complex, and its characterization requires 3D models that incorporate interactions of HFs with natural fractures while also considering the impact of HFs on local principal stresses.7 To address complex situations, the Mangrove system provides two fracture models: the wiremesh hydraulic fracturing model and the UFM uncon-ventional fracture modeling simulator.
The wiremesh model provides a mathemati-cal equivalent representation of the hydraulic fracture network.8 The wiremesh approach is relatively fast and suitable for environments that lack significant reservoir characterization data. To improve well productivity, completion design-ers are able to iterate and parameterize the input values to obtain an optimal stimulation design for fracture length, height, surface area and prop-pant distribution.
The UFM model is the first commercially available complex hydraulic fracture model to incorporate fracture-to-fracture interactions.9
The model accounts for the effects of natural fractures and geomechanical properties on hydraulic fracture growth and predicts den-dritic—multiple branching—hydraulic fracture propagation as well as fluid flow and proppant transport. Hydraulic fracture growth is governed by the rock fabric and geomechanical properties of the reservoir, the preexisting fracture network and prevailing in situ stress magnitudes and anisotropy. As the HF network develops, it per-turbs the stress field as each fracture surface becomes pressurized, opened and propped. Engineers may use the UFM simulator for HF net-work design to optimize well productivity.
Regardless of the HF model engineers use to prepare their initial design, the result must be calibrated during HF stimulations. The Mangrove workflow is able to incorporate results obtained from monitoring microseismicity induced by propagating HFs to calibrate the predicted model. Geophysicists process the microseismicity data to locate seismic emissions from small slip events associated with the development of the
> Dividing horizontal laterals into segments and stages. This horizontal well (top center) targets a reservoir zone near the boundary horizon (purple) between the upper and lower Eagle Ford Shale, which was deposited above the Buda Limestone and below the Austin Chalk. The other horizons are the top surfaces of the Buda Limestone (blue) and the upper Eagle Ford Shale (brown). Engineers divided the lateral into segments based on location within the reservoir, the wellbore trajectory and rock properties. Each segment contains similar lithology along its length. Engineers further subdivided the segments into stages (bottom center) based on similar minimum horizontal stress gradients, reservoir quality (RQ) and completion quality (CQ) along the length of each stage. Each stage is then a candidate for hydraulic stimulation. A color-coded rock quality index, shown above the well, combines RQ and CQ and indicates the best intervals for stimulation. The relative magnitude of the far field minimum horizontal stress gradient, shown along the bottom of the well, indicates the relative pressure levels at which the reservoir interval will fracture. [Adapted from Cipolla et al (2011), reference 3.]
HighLow
Stress gradient
Well segments
Rock Quality
Rock quality
Stress gradient
Austin Chalk
Segments of Similar Lithology
Stages of Similar Rock Quality and Stress Gradient
Austin Chalk
Upper Eagle Ford Shale
Eagle Ford Shale
Buda Limestone
Buda Limestone
Lower Eagle Ford Shale
Hydraulic fracturing stages
Good RQ and good CQ
Bad RQ and good CQGood RQ and bad CQ
Bad RQ and bad CQ
38 Oilfield Review
HFs.10 Often, to increase the precision and accu-racy of the event locations, geophysicists adjusttheir geologic and velocity models. These adjust-ments, in turn, are used to update the geome-chanical and the DFN models for the HF models.
Before and after completion of HF stimula-tions, production engineers run reservoir flowmodels to predict the resulting production per-formance. These models couple mechanicaldeformation and pore volume changes. The
fracture models simulate rock deformation, thecreation of conductive fractures and channels inthe reservoir and the placement of proppant intothem. The reservoir simulators predict the flow offluids from the reservoir into and through thehigher conductivity pathways created by HFs thathave been propped open. Within the Mangroveworkflow, these calculations may be performedusing the INTERSECT reservoir simulator, whichallows unstructured gridding for a range of grid
densities. Fine gridding in the vicinity of the well-bore and HF network captures fine-scale details.Coarse gridding is usually sufficient far from thewellbore and HF network.11
The Mangrove workflow provides analysisfrom data entry to model updates. In this process,geologic and engineering field data are input forbuilding models of the reservoir. Engineers usethe models to estimate RQ and CQ (above).Engineers input the completion design into 2D or
> Comparing hydraulic fracture designs for a horizontal well in the Eagle Ford Shale. In a geometricdesign (top), fracture stages (inset, four disks of the same color) and perforation clusters (individualdisks) were distributed uniformly along the length of the lateral. In the engineered design from theMangrove workflow (bottom), engineers determined the location and length of each fracture stageand the placement of each perforation cluster from analysis of the composite rock quality scores andminimum horizontal stress gradients. The optimal design is for all perforation clusters (PCs) to breakdown and initiate fractures at more or less the same pressure. The composite RQ and CQ rock qualityindex is shown along the top of the well. The relative magnitude of the far field minimum horizontalstress gradient is shown along the bottom of the well. [Adapted from Cipolla et al (2011), reference 3.]
HighLow
Stress gradient
Rock Quality
Geometric Placement of Fracture Stages and Perforation Clusters
Engineered Placement of Fracture Stages and Perforation Clusters
Rock quality
Stress gradient
Rock quality
Stress gradient
Perforation cluster
Fracture stage
Good RQ and good CQ
Bad RQ and good CQGood RQ and bad CQ
Bad RQ and bad CQ
Summer 2013 39
3D HF simulators for evaluating the fracture stimulations that will be pumped and then feed the stimulation design into reservoir simulators to forecast production.
The system is able to incorporate microseis-micity monitoring to calibrate steps in the Mangrove workflow. Such calibration comes from locating microseismic events precisely and com-paring these locations with predicted HF growth. The location of microseismic events may help the system estimate the effective stimulated reser-voir volume, which may then be used to adjust the completion and stimulation strategies of subse-quent fracture stages or make adjustments even while stimulation is occurring in some stages.
In addition, to obtain precise microseismic event locations, geophysicists conduct seismic velocity inversion, and in the process, adjust the starting model of the geologic and mechanical properties within the reservoir zone. The adjusted model may be used to update predictions of hydraulic fracture growth and forecasts of reser-voir production.
The Mangrove workflow centers around com-pletion and stimulation design for single wells within the 3D context of a larger reservoir model. The focus on single wells reduces model size, enables faster calculations and gives completion engineers flexibility to make quick decisions and adjustments to stimulation programs.
The Mangrove software may be run on a sin-gle platform, which eliminates the need to migrate data from one software application to another and to address problems of software interfaces and interoperability.
A software-mediated systematic approach to planning, engineering and executing stimulations has proved to be more effective than convention-ally planned stimulations. PDC Mountaineer LLC and Schlumberger obtained favorable results with engineered completions in the Marcellus Shale.
Comparing Completion MethodsPDC Mountaineer LLC (PDCM) focuses primarily on natural gas production from the Marcellus Shale formation. In the company’s efforts to develop a Marcellus Shale field near Bridgeport in Harrison County, West Virginia, USA, its first three horizontal wells were only marginally eco-nomic. Consequently, PDCM wanted to deter-mine how to improve production.
The company started each of these first wells by drilling and logging a vertical pilot well. Engineers used these data to determine the tar-get reservoir zone and the landing point for the horizontal well, or lateral. PDCM then drilled the laterals using data derived from mud logs and logging-while-drilling (LWD) gamma ray for guidance to stay within the target zone. The lat-erals were completed using designs based on a geometric method—stages and perforation clusters distributed uniformly—followed by slight manual adjustments to the design to move perforation clusters within each stage to zones that were estimated to have lower minimum horizontal stress.12
PDCM and Schlumberger engineers analyzed the data from the first three wells and concluded that the completion designs paid little attention to specific conditions in each well—lithology, reser-voir quality, mechanical properties and in situ stresses. Furthermore, examination of stimula-tion-induced microseismicity monitored during the treatments showed a relationship between the locations of perforation clusters, predicted mini-mum in situ horizontal stress and microseismic activity; the highest microseismic activity concen-trated near perforations in rocks of low stress, and lower activity occurred elsewhere. Fractures started and grew by taking paths of least resis-tance. Areas near the geometrically located perfo-ration clusters were effectively stimulated only when the clusters happened to be located in easily fractured rock. Otherwise, areas tended to be understimulated because the perforation clusters were not strategically located.
The analysis indicated that optimal stimula-tions would result if the completions were engi-neered so each stage and each perforation cluster contributed to the overall production in propor-tion to their number. Horizontal wells would be
divided into segments of similar lithology that did not include discontinuities—primarily faults, fractures and highly laminated intervals. The seg-ments would then be divided into stages and per-forated in rocks of similar minimum horizontal stress. During each fracture stage, all perfora-tions would initiate fractures at roughly the same pumping pressure, the fractures would extend and propagate together, and eventually, produc-tion would flow from the fractures in proportion to the stimulated reservoir volume they contact.
To test this procedure, the PDCM team selected three new well locations, near the origi-nal three wells, which had similar reservoir and completion quality. Except for the engineered design for distributing the staging and perfora-tion locations along the laterals, the new wells would be completed in the same way as the ear-lier wells.
The wells were drilled in the direction of the regional minimum in situ principal horizontal stress to facilitate opening of hydraulic fractures emanating perpendicularly from the wells. The lateral wells cut across rocks of variable lithology and, consequently, mechanical properties, which dictate how the regional stress field is transmit-ted through the rock to the local borehole wall.
After drilling the wells and before designing the completions, the team collected the follow-ing well information: wellbore directional sur-veys, gamma ray logs, petrophysical and mechanical properties for evaluating RQ and CQ, planned fracture fluid types and properties, pumping rates, number of stages, number of perforation clusters per stage and perforation diameter, density and phasing. The completion design called for slickwater to be pumped at 80 bbl/min [13 m3/min] through five perforation clusters in each stage.
Engineers assembled this information in the Mangrove workflow software and constructed 3D earth models of each well. Based on data from the 3D earth models, engineers were able to segment the wells into lengths of similar lithology; each segment was subdivided into stages, such that each stage length contained rock of similar reservoir quality and was capable of accepting the planned pumping rate. The team selected perforation locations based on completion quality. The perforation locations were adjusted until the models showed that fractures initiated at each perforation cluster within a stage at the same pressure within a tol-erance of 0.01 psi/ft [0.23 kPa/m] for the
10. For more on hydraulic fracture monitoring: Bennett L, Le Calvez J, Sarver DR, Tanner K, Birk WS, Waters G, Drew J, Michaud G, Primiero P, Eisner L, Jones R, Leslie D, Williams MJ, Govenlock J, Klem RC and Tezuka K: “The Source for Hydraulic Fracture Characterization,” Oilfield Review 17, no. 4 (Winter 2005/2006): 42–57.Burch DN, Daniels J, Gillard M, Underhill W, Exler VA, Favoretti L, Le Calvez J, Lecerf B, Potapenko D, Maschio L, Morales JA, Samuelson M and Weimann MI: “Live Hydraulic Fracture Monitoring and Diversion,” Oilfield Review 21, no. 3 (Autumn 2009): 18–31.
11. For more on the INTERSECT simulator: Edwards DA, Gunasekera D, Morris J, Shaw G, Shaw K, Walsh D, Fjerstad PA, Kikani J, Franco J, Hoang V and Quettier L: “Reservoir Simulation: Keeping Pace with Oilfield Complexity,” Oilfield Review 23, no. 4 (Winter 2011/2012): 4–15.
12. Walker K, Wutherich K, Terry J, Shreves J and Caplan J: “Improving Production in the Marcellus Shale Using an Engineered Completion Design: A Case Study,” paper SPE 159666, presented at the SPE Annual Technical Conference and Exhibition, San Antonio, Texas, October 8–10, 2012.Gerdom D, Caplan J, Terry IJ Jr, Wutherich K, Wigger E and Walker K: “Geomechanics Key in Marcellus Wells,” The American Oil & Gas Reporter 56, no. 3 (March 2013): 84–91.
40 Oilfield Review
minimum in situ stress gradient.13 When theteam was satisfied with the completion plans,the wells were stimulated (below).
Completion engineers conducted each frac-ture treatment according to the intended prop-pant schedule. Compared with the treatments inthe original three horizontal wells, the engi-neered completions were pumped at 10.3% higheraverage pumping rates and 5.7% lower averagetreating pressures. In addition, the treatmentssucceeded in placing 30% more of the designedproppant load per lateral and experienced noscreenouts (next page, top left).
The team compared the first 30 days of produc-tion from each well, which revealed a second mea-sure of success. Compared with the original wells,the engineered completions resulted in significantly
higher production. During the first 30 days, theengineered completions resulted in 106% higher ini-tial cumulative production per foot of stimulatedwellbore length than the original three wells.
Based on these positive results, PDCMountaineer now performs engineered comple-tion designs for all its horizontal wells. The com-pany has determined that the time and effortspent on the design are more than offset by thesavings from operational effectiveness during com-pletions and revenue from increased production.14
Perforating Low-Stress IntervalsSeneca Resources Corporation and Schlumbergerconducted another test of engineered completiondesign. Seneca Resources produces natural gasfrom Marcellus Shale reservoirs in Pennsylvania
and New York, USA. The company sought toincrease production by maximizing reservoir con-tact through hydraulic fracture stimulations fromhorizontal wells.
Seneca Resources had been stimulating wellsin the Marcellus Shale but results were highlyvariable, even from apparently identical wells.However, the Marcellus Shale comprises manythin laminations, each distinct from its neighborin terms of physical and mechanical properties.As horizontal wells cut through the formation,they intercept these varied laminations. Thecompany teamed with Schlumberger to conduct acontrolled pilot study to test the effectiveness ofengineered completions compared with what hadbeen standard practice for the company—geo-metric completions.
> Segments, stages and clusters. Stresses typically change from one lithology to another. To prevent a fracture stage from crossing a lithology barrier,engineers divide the well into segments of similar lithology. Stimulation stages (left , Track 9, green and light blue) should be contained within a segment,and their lengths should be within prescribed minimum and maximum values. Engineers position the perforation clusters (Track 9, short horizontal lines tothe left and right of the fracture stages) based on preset design criteria: the number of clusters per stage, the minimum and maximum distance betweenclusters and a minimum horizontal stress gradient (Track 2) tolerance of 0.01 psi/ft [0.23 kPa/m]. During completion design and modeling, these criteria mayneed to be relaxed to account for the minimum horizontal stress variation. A close-up of the red box (right) from Track 2 shows the stress gradient rangesfrom high (blue) to low (red). The original stress gradient logs were recorded every half foot (inset , Track 1) and smoothed using a 5-ft [1.5-m] movingaverage algorithm (inset , Track 2) to account for imprecision during the perforating operation. (Adapted from Walker et al, reference 12.)
X1,000Segment 1
MeasuredDepth,
MinimumStress
GradientPoisson’s
RatioYoung’sModulus
CalciteVolume
QuartzVolume
EffectivePorosity
StimulationStages Original
MinimumStress Gradient
Smoothed MinimumStress Gradient
5-ft Moving AverageKerogenVolume
Segment 2
Segment 3
Segment 4
X2,000
X3,000
X4,000
X4,000
X3,950
X3,900
X3,850
0 0.67 –0.17 0.44 2.33 0 1003.93psi/ft MMpsi % 0 100% 0 25% 0 15%1.01460
GammaRay
gAPIft Mea
sure
dDe
pth,
ft
0.67 1.01psi/ft 0.67 1.01psi/ft
X4,050
X5,000
X1,500
X2,500
X3,500
X4,500
HighLow
Stress gradient
PerforationCluster
Stage 1
Stage 2
Stage 3
Stage 4
Stage 5
Stage 6
Stage 7
Stage 8
Stage 9
Stage 10
Stage 11
Stage 12
Stage 13
Stage 14
13. The rate of these stress variations within a few boreholediameters of the wellbore, away from the immediateinfluence of the borehole, is the wellbore-parallel stressgradient and, for wells drilled parallel to the minimumin situ principal stress direction, is equivalent to theminimum stress gradient.
14. Walker et al, reference 12.
15. Wutherich K, Walker K, Aso I, Ajayi B and Cannon T:“Evaluating an Engineered Completion Design in theMarcellus Shale Using Microseismic Monitoring,” paperSPE 159681, presented at the SPE Annual TechnicalConference and Exhibition, San Antonio, Texas,October 8–10, 2012.
16. Waters G and Zhao R: “Measuring the Impact ofGeomechanical Heterogeneity in Organic Shales onHydraulic Fracture Initiation and Propagation,”paper CSUG/SPE 147597, presented at the CanadianUnconventional Resources Conference, Calgary,November 15–17, 2011.
Summer 2013 41
The company drilled three horizontal wellsinto the same Marcellus Shale reservoir zonefrom the same drilling pad. The laterals weredrilled parallel to one another, 800 ft [240 m]apart and aligned to the northwest, in the direc-tion of the regional minimum in situ principalhorizontal compressive stress (above right).Well A, the base case, was completed using thestandard geometric method.15
Wells B and C were completed using the engi-neered approach. The RST reservoir saturationtool and Sonic Scanner acoustic scanning toolwere run along each lateral after casing had beenset to determine the extent of variation betweenlithologic and mechanical properties and theresolved stresses in the three wells.16 These mea-surements were compiled and interpreted usingthe Mangrove workflow software to produce anengineered completion strategy for each well.
Although completion strategies were custom-ized to optimize production from each well,engineers kept a number of completion vari-ables—fluid, proppant type and size and pump-ing flow rate—the same and also kept thenumber of stages, number of perforation clustersper stage and amounts of proppant per length oflateral similar for both wells. Nonetheless, somevariability existed across the three wells. By theirnature and because they are intended to accountfor the rock and stress heterogeneity along thewellbore, engineered completion designs inevita-bly result in variable stage lengths, perforationcluster spacings and pumping schedules.
To accommodate these variations and main-tain the spirit of consistency, the company stag-gered the timing of the well stimulations using a
zipper-fracture method, whereby plug and perfora-tion operations followed by stimulation of stageswere rotated from one well to the next. As Well Awas being stimulated, Well C was undergoing plug-ging and perforating. Then stimulation moved toWell B, while plugging and perforating moved toWell A. This process continued until stimulation ofall stages in all the wells was complete.
The stimulation engineering team analyzedpilot study results by comparing treatment,microseismicity and initial flowback data fromthe geometrically designed completion inWell A to similar data from the engineeredcompletions in Wells B and C. Because all ofthe perforation clusters were engineered to belocated in wellbore intervals of relatively lowminimum principal stress, the average fracturebreakdown and treatment pressures were 7%
> Summary of completion design and results. Data from six horizontal wells drilled into the MarcellusShale illustrate the results of nonengineered and engineered completion methods (top). Wells 1 to 3were drilled and completed conventionally. Wells 4 to 6, which were drilled near Wells 1 to 3, werecompleted using an engineered design method that specifies stage and perforation cluster placement.The engineered completions were more effective than the nonengineered completions (bottom); thesuccess of the engineered completions is measured by lower treating pressures, higher pumpingrates, more efficient proppant placement and higher cumulative production after 30 days comparedwith those in the nonengineered completions. (Adapted from Walker et al, reference 12.)
Nonengineered Slickwater 3,375 1,670 80241
Nonengineered Slickwater 2,312 1,220 80330
Nonengineered Slickwater 2,140 1,320 80306
Average 2,609 1,400 80292
Engineered Slickwater 4,500 1,080 80375
Engineered Slickwater 3,950 1,230 80329
Engineered Slickwater 3,925 1,240 80327
Average
Average
Average
4,125 1,180 80
14
7
7
9.3
12
12
12
12 344
5
5
5
5
5
4.5
4.5
4.7
Stages
AverageStage
Length, ftLateral
Length, ftFluidCompletion
Method
Well 1
Well 2
Well 3
Well 4
Well 5
Well 6
Well
PerforationClusters
per Stage
DesignPumping
Rate,bbl/min
DesignProppant
per Lateral,lbm/ft
Design Summary
Gross,Mcf
226%
63,194
42,396
65,039
128,363
56,876
185,240
162,652
180,436
212,631
–437
–5.7%
7,749
7,557
7,716
7,674
7,308
7,105
7,298
7,237
AverageTreating
Pressure,psi
10.3%
7.6
78.1
76.3
66.3
73.6
79.2
81.9
82.3
81.1
AverageTreatment
Rate,bbl/min
Averagedifference
Percent averagedifference
Well 1
Well 2
Well 3
Well 4
Well 5
Well 6
Well
Completion Summary 30-Day Cumulative Production
153%
4,514
6,057
9,291
17,719
9,343
6,094
15,437
13,554
15,036
Normalizedby Numberof Stages,
Mcf/ft
106%
18.7
18.3
30.4
47.3
23.1
21.8
44.9
41.2
46.0
Normalizedby Lateral
Length,Mcf/ft
30.0%
107.0%
55.0%
65.0%
92.8%
22.7%
75.7%
98.3%
101.7%
100.5%
Percentageof Proppant
PlacedVersus Design
5.7%
1,783
672
855
1,002
63
1,103
1,166
1,251
1,245
PlacedProppant
per Lateral,lbm/ft
Normalizedby Number of
PerforationClusters,
Mcf/cluster
171%
903
1,211
1,858
3,544
2,089
1,219
3,308
3,012
3,341
>Well plan. From a single pad, SenecaResources drilled horizontal Wells A, B and C anddrilled a vertical monitor well for recordingstimulation-induced microseismicity. Well A wascompleted following a geometric design andWells B and C were completed according toengineered completion designs. The disks oneach well, which represent perforation clusters,are grouped into fracture stages with adjacentstages differentiated by color. (Adapted fromWutherich et al, reference 15.)
Well A
Well B
Well C
0 ft 1,0000 m 305
N
Monitor well
42 Oilfield Review
and 3% lower and the average treatment rateand amount of proppant placed were 16% and22% higher in Wells B and C, respectively, thanin Well A. The treatment comparison indicatedthat the engineered completions were moreeffective than the geometric completion (above).
Initial gas flowback rates from Wells B and Cwere 33% and 40% higher than the rates fromWell A on the same 5/8-in. choke size. In addition,fracture-water flowback recovery from Wells Band C was twice that from Well A. These flowbackdata suggest that the wells stimulated by engi-neered completions were making better reservoircontact, leading to better production, than wasthe geometrically completed well.
During the pilot study, the team placed a verti-cal monitor well between Wells A and B; the wellwas instrumented with geophones for monitoringmicroseismicity induced by the stimulations in thethree wells. The StimMAP LIVE real-time micro-seismic monitoring service recorded and analyzedmicroseismicity. When compared with perforationcluster locations, microseismic event locationsfrom the StimMAP LIVE service revealed that as
17. Wutherich et al, reference 15.18. For more on the Ordos basin: Yang Y, Li W and Ma L:
“Tectonic and Stratigraphic Controls of HydrocarbonSystems in the Ordos Basin: A Multicycle CratonicBasin in Central China,” AAPG Bulletin 89, no. 2(February 2005): 255–269.
much as 35% of the perforation clusters in Well A,with the geometric completion, were not contrib-uting to the reservoir volume targeted for stimu-lation. In contrast, microseismicity from theengineered completions and stimulations inWells B and C showed improvement in the per-centage of perforation clusters that contributedto the stimulated reservoir volume—only 20% ofthe perforation clusters made little to no contri-bution (next page). The microseismicity compar-ison indicated that the engineered completionsresulted in better placement of perforation clus-ters than did the geometric completion.
The Mangrove workflow software not only pro-duced the designs that led to these positiveresults but also reduced completion design timefrom several hours to about one hour per well.Moreover, the software rationalized data han-dling and procedural operations, which led tofewer inaccuracies and improved perforationplacement. Seneca Resources continues to usecomputer-aided completion design and micro-seismic analysis on other wells in its fields.17
Stimulation of Tight Oil SandstoneConventional reservoirs are also candidates forthe application of the systematic, engineeringapproach to reservoir stimulation. ThePetroChina Changqing Oilfield Company con-ducted a pilot study using the engineeredapproach for designing reservoir stimulation in aconventional clastic reservoir.
The Ordos basin, in north-central China, is agentle monocline that dips stratigraphicallyabout 1° from east to west. Its fill, which consistsof sediments deposited during the Paleozoic,Mesozoic and Cenozoic eras, thickens in the dipdirection with an average thickness of 4 to 5 km[2.5 to 3.1 mi]. The Paleozoic sediments aremarine deposits that yield primarily natural gas,while the Mesozoic sediments have a continentalorigin and yield oil.18
> Summary of completion design and results. Of three horizontal wells drilled into the Marcellus Shale,Well A, the reference case, was completed following a geometric design (top). Wells B and C werecompleted according to engineered completion designs, which were more effective than thegeometric completion. Their relative success is measured by lower breakdown and treatingpressures, higher pumping rates, more effective proppant placement and higher flowback rates thanthose of Well A (bottom). (Adapted from Wutherich et al, reference 15.)
CompletionMethod Stages
AverageStage
Length, ftLateral
Length, ft
PerforationClusters
per Stage
DesignPumping
Rate,bbl/min
DesignProppant
per Lateral,lbm/ft
Geometric Slickwater 40/70 5,312 18 295 3 1,650 90Well A
Engineered 901,5853.7226204,52840/70SlickwaterWell B
Engineered 901,6753.9250204,99840/70SlickwaterWell C
Well FluidProppant
Size
Design Summary
Completion Summary Flowback Results
21%
231
1,122
1,353
PlacedProppant
per Lateral,lbm/ft
38%
600
640
170
450
MaximumFlow,
Mcf/d/1,000 ft
–182
–3%
7,277
7,095
AverageTreating
Pressure,psi
5,160
–412
–7%
5,572
AverageBreakdown
Pressure,psi
1,800
1,800
300
20%
1,500
TubingPressure,
psi
5/8
5/8
5/8
Choke, in.
11.4
16%
69.7
81.1
AverageTreatment
Rate,bbl/min
Well A
Well BWell C
Well
DifferencePercent
difference
83%
15%
22%
68%
Percentageof Proppant
PlacedVersus Design
Summer 2013 43
>Microseismicity comparison. Microseismicity resulting from four fracture stages in Well A (top) and Well B (bottom) indicate improved stimulations from the engineered completions in Well B over the stimulations from the geometric completions in Well A. In each panel, the data show results from a fracture stage; the disks along the colored well trace represent stimulated perforation clusters and the dots are induced microseismic event locations. To show correlation, the disks and dots have the same color. Above the well trace, the height and color of the orange-to-green bars indicate the number of microseismic events along each wellbore interval. Below the well trace on Well B, the minimum horizontal stress gradient is plotted; the amplitude and color of the pink-to-blue shading specify the closure stress gradient level. The company placed perforation clusters based on engineering design principles at locations with relatively low stress gradients. There is a better one-to-one correspondence between microseismicity and perforation locations in Well Bthan in Well A, indicating improved perforation performance results from an engineered completion design. (Adapted from Wutherich et al, reference 15.)
Even
t cou
nt35
0
Even
t cou
nt
100
0
40
0
Even
t cou
nt
40
0
Even
t cou
nt
250
0
Even
t cou
nt
40
0
Even
t cou
nt
Even
t cou
nt
100
0
Even
t cou
nt
200
0
Stress gradient
HighLow
Stress gradient
HighLow
Stress gradient
Low High
Stress gradient
Low High
A B
A B
C D
C D
Well A
Well B
44 Oilfield Review
The Yanchang Formation is a thick sequence oflake and delta sediments deposited during theLate Triassic period. The formation consists of 10lithologic members, named Chang 1 to Chang 10from top to bottom. The members are stacks ofalternating mudstone, siltstone and sandstone lay-ers that result in vertical heterogeneity. The reser-voirs in the Yanchang Formation are naturallyfractured, low-permeability sandstones in whichporosity is typically about 10% and permeability isgenerally 0.1 to 10 mD. The natural fractures occurin two sets that tend to dip steeply and generallystrike in the ENE and NNW directions.19
To produce oil from these low-permeabilityreservoirs, an operator must stimulate the pro-duction intervals through multistage hydraulicfracturing. Historically, most production wellshave been vertical, and after HF stimulation,their initial production rates have varied from5 to 8 m3/d [30 to 50 bbl/d]. In the few horizontalwells, the initial production rates after HF stimu-lation have averaged 32 m3/d [200 bbl/d]. Whilestill considered economic, these production ratesare only marginally acceptable. To improve theproduction outcomes from its stimulation pro-grams, the company partnered with Schlumberger
in a pilot project to test the Mangrove workflow inhorizontal wells in a tight oil reservoir zone in thesouthwest Ordos basin.20
The company drilled two 1,500-m [4,920-ft]parallel horizontal wells in the Chang 7 memberof the Yanchang Formation. The wells, 600 m[1,970 ft] apart, were drilled in the N15°W direc-tion, which is parallel to the minimum in situprincipal horizontal stress direction in the Ordosbasin. The company drilled three vertical wells500 m [1,640 ft] apart between and along a lineparallel to the horizontal wells; these verticalwells were added for microseismicity monitoring(MSM) during the fracture stimulations of thehorizontal wells (above).
The pilot study team constructed 3D geologic,geomechanical and DFN models from the pilotstudy well log data and from core descriptionsand geologic studies in the surrounding area(next page). These models were calibrated usingdata from the three monitoring wells and inte-grated using the Mangrove system to form thebases for modeling reservoir quality, completionquality, stimulation staging and perforationplacement, hydraulic fracture stimulation designand production performance forecasting.
Optimal stimulation design requires thateach stage and its perforation clusters be placedin wellbore intervals that have a high likelihoodof producing economic amounts of hydrocarbonand breaking down by fracturing in response toincreased pressure during stimulation. Thesewellbore intervals possess good RQ and good CQ.The team used the Mangrove completion advisorto select 18 stages per well.
In conjunction with the completion advisor,the team used the UFM simulator to predict HFpropagation, growth and interaction with naturalfractures (NFs) in the reservoir. Depending onthe in situ stress direction and anisotropy in rela-tion to the reservoir NF system, hydraulic frac-tures may take advantage of the NFs to produce
> Ordos basin, north-central China. A completions team conducted a pilot study to test engineered completiondesigns from Mangrove software. The field test area (white box) is in southwest Ordos basin. The well layout (inset)consists of two parallel horizontal production wells (HWs) and three vertical monitoring wells (MWs, blue circles)constucted for recording microseismicity. The Chang 7 member of the Yanchang Formation was the target horizon.(Adapted from Liu et al, reference 20.)
Ordos Basin
C H I N A
Shanghai
Beijing
Xi’an
Oil fieldGas fieldBasin
SouthChina Sea
N
300 m300 m
250
m
500
m
500
m
250
m
MW1
HW1
HW2
MW3
MW2
0 250 500 m
0 750 1,500 ft
19. For more on the Yanchang Formation: Lianbo Z andXiang-Yang L: “Fractures in Sandstone Reservoirs withUltra-Low Permeability: A Case Study of the UpperTriassic Yanchang Formation in the Ordos Basin, China,”AAPG Bulletin 93, no. 4 (April 2009): 461–477.
20. Liu H, Luo Y, Li X, Xu Y, Yang K, Mu L, Zhao W and Zhou S:“Advanced Completion and Fracturing Techniques inTight Oil Reservoirs in Ordos Basin: A Workflow toMaximize Well Potential,” paper SPE 158268, presentedat the SPE Annual Technical Conference and Exhibition,San Antonio, Texas, October 8–10, 2012.Yang H, Xu YG, Yang KW, Zhou SX, Liu H and Luo Y:“Optimized Treatment Design Shows Promise,” E&P 86,no. 2 (February 2013): 46–50.
21. Weng et al, reference 9.
Summer 2013 45
complex HF networks and, consequently, highfracture surface area to make contact with thereservoir. The production of complex HF net-works is more likely when the in situ stressanisotropy is low.21
During the UFM modeling, the team was alsoconcerned about determining how existing HFsaffected the behavior of subsequent HFs. After anHF is created and filled with proppant, the imme-diate vicinity of the HF changes forever. The HFimposes a compressive stress component, orstress shadow, that acts outward from the HF
plane in the minimum principal stress directionIt alters the local stress magnitude and anisot-ropy near the fracture and affects adjacent frac-tures through mechanical interactions. Toproperly space HF stimulation staging, engineersmust include such stress shadow effects whencalculating CQ.
After selecting the stage and perforation loca-tions, the team began to execute its design.During stimulation operations, the teamemployed the StimMAP LIVE real-time micro-seismic monitoring (MSM) service. After eachstage, the team used MSM results to recalibrate
the 3D models, UFM model and stimulationdesign. For the next stage, the engineers wantedto maximize the HF surface area and proppant-filled volume to obtain the best production fromthe stimulated reservoir interval. MSM data sug-gested that the HFs being created tended to belong and contained within the targeted Chang 7reservoir interval.
While monitoring the first five to six stages,the team observed considerable overlap of micro-seismicity from neighboring stages, indicatingsuboptimal stage spacing. The team decided to
>Model building for Ordos basin wells. Because there were no seismic or geologic data for the location, model building started after well logs wereacquired from the three vertical monitor wells (left , MWs). Logs for each well display resistivity (Track 1), neutron porosity and bulk density (Track 2) andgamma ray (Track 3). Geoscientists began model building by extracting geologic horizon surfaces based on well-to-well correlations between themonitoring wells. Engineers used the surfaces for well placement guidance (top right) and for 3D model development (middle right) by upscalingpetrophysical properties derived from well log data and filling in between the wells while honoring the horizon surfaces. Geologists created a simplediscrete fracture network (DFN) model (bottom right) based on geologic studies and core descriptions. The DFN contained two dominant steeply dippingfracture sets, characterized by average strike orientations of N75°E (cyan) and N15°W (purple) and average fracture spacing of 15 m [49 ft]. The DFN wascalibrated later and modified based on microseismicity data. (Adapted from Liu et al, reference 20.)
6
Hor
izon
Surfa
ce
Resistivity Gamma Ray
NeutronPorosity
(left)
Tota
l Ver
tical
Dept
h, m
X,100
X,200
7 0 200gAPI 0 200gAPI 0 200gAPI617ohm.m
0 100%
X,300
X,400
MW1 MW2 MW3
X,500
X,600
X,700
X,800
5
4
3
2
1
Bulk Density(right)
1 2.85g/cm3
Resistivity Gamma Ray
NeutronPorosity
(left)
2 2,200 ohm.mohm.m
0 100%
Bulk Density(right)
1 2.85g/cm3
Resistivity Gamma Ray
NeutronPorosity
(left)
3 1,700
0 100%
Bulk Density(right)
1 2.85g/cm3
N
MW1
MW2
MW3
HW1HW2
MW1 MW3 HW2MW2 HW1
1
2
3
456
7
46 Oilfield Review
> Completion advisor results. Engineers used the Mangrove completion advisor to compile and analyze petrophysical data to select fracture stages and perforation cluster locations for wells in the Ordos basin. Gamma ray (Track 1) and the minimum horizontal stress gradient (Track 2) were key parameters for the design. For the stress gradient profile, blue is high and red is low. Reservoir quality (Track 3),completion quality (Track 4) and composite (RQ plus CQ) quality scores (Track 5) provide color-coded quality indicators for stage and cluster selection. Initially, engineers proposed 18 stimulation stages (Track 6). After 5 stages were stimulated, engineers recalibrated the stimulation program using microseismic monitoring data and, as a result, reduced the number of stages to 13 (Track 7). The blue spikes (Tracks 6 and 7, left and right of stimulation stages) indicate proposed perforation cluster locations. (Adapted from Liu et al, reference 20.)
High Low
Stress Gradient
RQ CQ Com
posi
te
Stage 18
Mea
sure
d De
pth,
m
Gamma Ray
InitialStimulation
Stages
UpdatedStimulation
StagesMinimum StressGradient
Bad Bad BB
GGGood
Good
Good
Good
Good
Good
Good
Good
GG
Good GG
Good GG
Good GG
Good
Good
Good
Good
Good
Good
Good
Bad
Bad
BBGG
GG
Good
Good
Good
GGGG
GGGG
GG
Stage 17
Stage 16
Stage 15
Stage 14
Stage 13
Stage 13
Stage 12
Stage 11
Stage 10
Stage 9
Stage 8
Stage 7
Stage 6
Stage 5
Stage 4
Stage 3
Stage 2
Stage 1
Stage 12
Stage 11
Stage 10
Stage 9
Stage 8
Stage 7
Stage 6
Stage 5
Stage 4
Stage 3
Stage 2
Y,600
Y,000
Y,200
Y,400
X,400
X,200
X,600
X,800
0 0 psi/m 0.30250gAPI
Stage 1
Good
Bad
Good
Bad
PerforationCluster
PerforationCluster
Good RQ and good CQ
Bad RQ and good CQGood RQ and bad CQ
Bad RQ and bad CQ
Rock Quality increase the spacing of stages and reduce the number of stages from 18 to 13 per well (left).
After all 26 stages were stimulated in both horizontal wells, the operator put the wells into production. Initial production rates were 103.2 m3/d [649.1 bbl/d] and 124.5 m3/d [783.1 bbl/d], a three- to fourfold improvement over the average production rate of 32 m3/d from previous horizontal wells. After three months, the production rates from these wells stabilized and were 50% higher than the previous best production from any horizontal well in the formation.
Stimulation by DesignUnconventional reservoirs provide special chal-lenges because they are heterogeneous reservoirs composed of highly stratified sediments. Staying within a reservoir zone during horizontal drilling is difficult. Consequently, the wellbore intersects variable lithologies, which exhibit dissimilar pet-rophysical and mechanical properties.
Unconventional reservoirs are also usually anisotropic and naturally fractured. Shales pos-sess layering caused by the horizontal alignment of finely laminated sediments and platy clay miner-als. This layering causes rock properties, such as permeability, elastic moduli and electrical resistiv-ity, to be anisotropic.22 These properties may vary more from layer to layer than within layers. Natural fractures may cut across this layering and superimpose additional anisotropy on the shales. Both anisotropy and natural fractures complicate the propagation of hydraulic fractures.23
Recent advances in multistage stimulation tech-nology are making it possible to stimulate and develop unconventional hydrocarbon resources more successfully (see “Multistage Stimulation in Liquid-Rich Unconventional Formations,” page 26). Parallel advances in the Mangrove stimulation design software are making it possible to design completions that are more effective. Integration of the two technologies promises a positive future for unconventional resource development. —RCNH
22. For a discussion of permeability anisotropy: Ayan C, Colley N, Cowan G, Ezekwe E, Wannell M, Goode P, Halford F, Joseph J, Mongini A, Obondoko G and Pop J: “Measuring Permeability Anisotropy: The Latest Approach,” Oilfield Review 6, no. 4 (October 1994): 24–35.For more on elastic anisotropy: Armstrong P, Ireson D, Chmela B, Dodds K, Esmeroy C, Miller D, Hornby B, Sayers C, Schoenberg M, Leaney S and Lynn H: “The Promise of Elastic Anisotropy,” Oilfield Review 6, no. 4 (October 1994): 36–47.For more on the anisotropy of electrical properties: Anderson B, Bryant I, Lüling M, Spies B and Helbig K: “Oilfield Anisotropy: Its Origins and Electrical Characteristics,” Oilfield Review 6, no. 4 (October 1994): 48–56.
23. Wu R, Kresse O, Weng X, Cohen C and Gu H: “Modeling of Interaction of Hydraulic Fractures in Complex Fracture Networks,” paper SPE 152052, presented at the SPE Hydraulic Fracturing Technology Conference, The Woodlands, Texas, February 6–8, 2012.