28 Oilfield Review

Seismic Detection of Subtle Faultsand Fractures

For decades, operators have relied on seismic images for illuminating the geometry

and location of major faults and folds to target their wells. Now, advances in process-

ing and visualization techniques are helping reveal information about the patterns of

small-scale faulting and fracturing that were beyond the detection capabilities of

previous techniques. Operators are using this new knowledge to drill and manage

their reservoirs with greater certainty.

Victor AarreDonatella AstrattiStavanger, Norway

Taha Nasser Ali Al DayyniSabry Lotfy MahmoudAbu Dhabi Company for Onshore Oil OperationsAbu Dhabi, UAE

Andrew B.S. ClarkPetroleum Development OmanMuscat, Sultanate of Oman

Michael J. StellasJack W. StringerSpectra Energy CorporationHouston, Texas, USA

Brian ToelleDenver, Colorado, USA

Ole V. VejbækGillian WhiteHess CorporationCopenhagen, Denmark

Oilfield Review Summer 2012: 24, no. 2. Copyright © 2012 Schlumberger.For help in preparation of this article, thanks to Art Bonett and Ismail Haggag, Abu Dhabi, UAE.FMI and PowerV are marks of Schlumberger.

Over the last decade, oil and gas companies have had increased success placing wells within pro-ductive zones—sweet spots—of fractured reser-voirs. These fracture zones often display subtle expressions in seismic data, but recent advances in seismic attributes and visualization tech-niques are helping geophysicists identify and characterize them. By combining these geophysi-cal results with geologic and engineering data, companies are reducing risk and increasing their drilling and production successes.

Optimal well placement requires the operator to factor the predominant trend of natural frac-tures into the selection of wellbore orientation. Production may be enhanced by intersecting mul-tiple fractures. Fractures may also redirect the path of injected fluids, thus limiting the fluids’ effi-cacy in contacting, sweeping and displacing hydro-carbons. In this case, production benefits must be balanced by offsetting inefficiencies caused by fracture systems. An operator’s objective is, there-fore, to maximize production from fractured reser-voirs while limiting the deleterious effects of those very same fractures.

Fractures tend to be aligned along preferred directions, or azimuths, and often cross strati-graphic layers. Fractures occur at many scales but most are smaller than the seismic wave-lengths typically used for surveys, and thus they are not visible in standard seismic displays. Although seismic methods may not be able to detect individual fractures, the measurable seis-mic response from the aggregate fracture system may indicate their presence. As an analogy, the human eye cannot see a single droplet of water from a kilometer away, but can see a collection of water droplets—a cloud—in the sky. The same applies to seismic methods and fractures. Accordingly, some of the most successful seismic fracture detection techniques rely on specialized processing designed to highlight seismic attri-butes that reveal faults and fracture systems.1

Historically, certain seismic methods have proved successful in detecting naturally frac-tured reservoirs. Such methods include the anal-ysis of shear-wave (S-wave) data, vertical seismic profiling, compressional- and shear-wave (P- and S-wave) anisotropy and waveform scattering.2

1. Seismic attributes are measurements, characteristics or properties derived from seismic data. Attributes can be measured at one instant in time or over a time window and may be measured on a single trace, a set of traces, a surface or a volume extracted from seismic data. Their calculation is useful because they help to extract patterns, relationships or features that may not be apparent otherwise. The derivation or calculation of seismic attributes usually involves data processing such as windowing, smoothing, averaging, filtering, calculating statistical measures, finding maxima and minima, performing differentiation and integration, analyzing polarity changes or conducting spectral or wavelet analysis.

2. A shear wave (S-wave) is an elastic wave that travels through a medium and vibrates perpendicular to its direction of travel. For more on shear waves: Caldwell J, Christie P, Engelmark F, McHugo S, Özdemir H,

Kristiansen P and MacLeod M: “Shear Waves Shine Brightly,” Oilfield Review 11, no. 1 (Spring 1999): 2–15.

Vertical seismic profiles (VSPs) include a variety of borehole seismic surveys. However, the defining VSP survey refers to measurements in a vertical well using a seismic source on the surface near the well transmitting to receivers distributed inside the well. For more on VSPs: Christie P, Dodds K, Ireson D, Johnston L, Rutherford J, Schaffner J and Smith N: “Borehole Seismic Data Sharpen the Reservoir Image,” Oilfield Review 7, no. 4 (Winter 1995): 18–31.

Seismic waveform scattering refers to the changing propagation direction of seismic waves resulting from heterogeneity and anisotropy of the medium. For more on waveform scattering: Revenaugh J: “Geologic Applications of Seismic Scattering,” Annual Review of Earth and Planetary Sciences 27 (May 1999): 55–73.

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Studies have also indicated that spectral decom-position, typically used in stratigraphic analysis, may be used to locate subtle structural features that control the distribution of fractures within a reservoir.3

To identify the stratigraphic and structural fab-ric, texture or grain within the reservoir, state-of-the-art seismic methods focus on determining how seismic properties and attributes vary direction-ally. Such reservoir fabric affects the directional—anisotropic—properties of seismic signals.4 Seismic methods include techniques that scruti-nize the seismic signal for subtle variations in fre-quency and amplitude response with azimuth and dip. The orientation or grain of fibers in a piece of wood is analogous. Woodworkers use the wood grain to maximize strength, minimize splintering and enhance the beauty of the finished product.

With the exception of large-scale faults that the seismic interpreter can pick by hand, most structural lineaments are ignored as being too small and too numerous to be interpreted manu-ally. Moreover, it is not straightforward to account for the effects of these small features in reservoir models. Advanced seismic imaging and process-ing techniques and workflows have been devel-oped to assist geoscientists in this challenging interpretation task.

This article describes reservoir studies that incorporate seismic methods for characteriz-ing fracture systems. Case studies demonstrate how these methods inform operators as they make well placement and reservoir manage-ment decisions. An example from Pennsylvania, USA, describes the optimal placement of wells for an underground gas storage reservoir that has shear zones that control fracture orienta-tion and distribution. In a North Sea fractured chalk reservoir, advanced seismic attribute

analysis reveals details of a complex fault sys-tem. In a UAE giant carbonate field, fracture network modeling helps represent fractures that are too numerous to be picked by hand but are known to affect the movement and sweep of injected fluid.

Natural Fractures and Their DetectionRocks respond to stress in predictable ways, form-ing fractures, joints and faults (left).5 Fractures are rock failure planes that result from stress. Rocks experience stress during folding, faulting, burial, uplift, erosion and metamorphism. Additionally, in shale formations, endogenous fractures can form through dewatering and devolatilization during thermal maturation of hydrocarbons.

The stress field that formed these features may change significantly after their formation. Consequently, the structural configuration of faults and fractures indicates the paleostress condition that existed at the time of their for-mation but may not correspond to the current stress field.

Natural fractures are ubiquitous and occur in many forms: open, closed, healed or partially healed. They occur at all scales, from those asso-ciated with tectonic faults hundreds of kilome-ters long to cracks on the micrometer scale.

However, the importance of natural fractures in the subsurface has not been fully appreciated until recently. Historically, oil and gas wells have primarily been drilled vertically. Stress condi-tions in the subsurface often cause open natural fractures—the ones of interest for production—

> Principal stresses and the creation of fractures. The three principal compressive stresses—the maximum stress, σ1, the minimum stress, σ3, and the intermediate stress, σ2—may give rise to several types of fractures and dictate fracture movement (black arrows). The colored arrows are compressive stress directions and their size indicates relative magnitude.

σ1

σ1

σ3 σ3

σ2

Joint, ortension fracture

Conjugate faults,or shear fractures

3. Neves FA, Zahrani MS and Bremkamp SW: “Detection of Potential Fractures and Small Faults Using Seismic Attributes,” The Leading Edge 23, no. 9 (September 2004): 903–906.

4. Anisotropy is the variation of a physical property, such as P- or S-wave velocity, with the direction of its measurement. For a discussion of 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.

5. A fracture is any break in rock regardless of origin. A joint, or Mode I fracture, is a fracture formed by opening displacement, normal to the fracture plane, under tensile stress conditions. A fault is a fracture formed by shearing displacement, in the plane of the fracture, under shear stress conditions. Faults form under sliding (Mode II) or tearing (Mode III) conditions depending on whether the shear stress acts perpendicular or parallel to the fracture front.

Pollard DD and Aydin A: “Progress in Understanding Jointing over the Past Century,” Geological Society of America Bulletin 100, no. 8 (August 1988): 1181–1204.

Aydin A: “Fractures, Faults, and Hydrocarbon Entrapment, Migration and Flow,” Marine and Petroleum Geology 17, no. 7 (August 2000): 797–814.

6. Within the Earth, open natural fracture planes are parallel to the principal stress plane that contains the maximum and intermediate principal compressive stresses. This plane tends to be vertical because the vertical stress is often one of these principal stresses.

7. Fingered flow is the instability that arises at the interface between two immiscible fluids when one invades the other. The result of differences in fluid viscosity and mobility, fingered flow may occur during waterflooding when water infiltrates oil or during air sparging when air bubbles through water.

8. For more on fractured reservoirs: Bratton T, Canh DV, Que NV, Duc NV, Gillespie P, Hunt D, Li B, Marcinew R, Ray S, Montaron B, Nelson R, Schoderbek D and Sonneland L: “The Nature of Naturally Fractured Reservoirs,” Oilfield Review 18, no. 2 (Summer 2006): 4–23.

9. Dershowitz WS and Herda HH: “Interpretation of Fracture Spacing and Intensity,” in Tillerson JR and Wawersik WR (eds): Proceedings of the 33rd U.S. Symposium on Rock Mechanics. Rotterdam, The Netherlands: AA Balkema Publishers (1992): 757–766.

Crosta G: “Evaluating Rock Mass Geometry from Photographic Images,” Rock Mechanics and Rock Engineering 30, no. 1 (January 1997): 35–58.

10. Florez-Niño J-M, Aydin A, Mavko G, Antonellini M and Ayaviri A: “Fault and Fracture Systems in a Fold and Thrust Belt: An Example from Bolivia,” AAPG Bulletin 89, no. 4 (April 2005): 471–493.

11. Zahm CK and Hennings PH: “Complex Fracture Development Related to Stratigraphic Architecture: Challenges for Structural Deformation Prediction, Tensleep Sandstone at the Alcova Anticline, Wyoming,” AAPG Bulletin 93, no. 11 (November 2009): 1427–1446.

12. For more on seismic attributes: Chopra S and Marfurt KJ: “Seismic Attributes—A Historical Perspective,” Geophysics 70, no. 5 (September– October 2005): 3SO–28SO.

Chopra S and Marfurt KJ: “Emerging and Future Trends in Seismic Attributes,” The Leading Edge 27, no. 3 (March 2008): 298–318.

Chopra S and Marfurt K: “Gleaning Meaningful Information from Seismic Attributes,” First Break 26, no. 9 (September 2008): 43–53.

13. For more on elastic anisotropy: Armstrong et al, reference 4. Hardage B: “Measuring Fractures—Quality and

Quantity,” AAPG Explorer 32, no. 7 (July 2011): 26–27. Hardage B: “For Fractures, P + S = Maximum Efficiency,”

AAPG Explorer 32, no. 8 (August 2011): 32.14. For more on azimuthal seismic anisotropy analysis:

Barkved O, Bartman B, Compani B, Gaiser J, Van Dok R, Johns T, Kristiansen P, Probert T and Thompson M: “The Many Facets of Multicomponent Seismic Data,” Oilfield Review 16, no. 2 (Summer 2004): 42–56.

Grimm RE, Lynn HB, Bates CR, Phillips DR, Simon KM and Beckham WE: “Detection and Analysis of Naturally Fractured Gas Reservoirs: Multiazimuth Seismic Surveys in the Wind River Basin, Wyoming,” Geophysics 64, no. 4 (July–August 1999): 1277–1292.

Lynn HB, Campagna D, Simon KM and Beckham WE: “Relationship of P-Wave Seismic Attributes, Azimuthal Anisotropy, and Commercial Gas Pay in 3-D P-Wave Multiazimuth Data, Rulison Field, Piceance Basin, Colorado,” Geophysics 64, no. 4 (July–August 1999): 1293–1311.

Summer 2012 31

to be vertically oriented.6 Vertical wells rarely intersect these vertical fractures. However, in some types of reservoirs, such as tight sandstone and carbonate layers, shale gas, oil shale and coalbed methane plays, fracture systems provide the only permeability in the formation; achieving commercial production rates requires that the wellbore traverse fractures. Drilling wells to con-nect as many fractures as possible has become a principal objective, but the task must be per-formed carefully. Fractures are able to dominate permeability both positively and negatively. On the one hand, they provide the essential permea-bility to give tight reservoirs improved productiv-ity and recovery efficiency. On the other hand, fractures may harm productive reservoirs by cre-ating thief zones, and in enhanced oil recovery efforts, they may cause early breakthrough and reservoir flow instabilities—fingered flow.7

For both exploration and production of a hydrocarbon reservoir, operators need to charac-terize natural fracture systems to identify the best opportunities for placing wells and planning horizontal well trajectories. To characterize frac-tures, scientists require information about frac-ture orientation, aperture, porosity, permeability, density, size, location, stress anisotropy and

direction and fluid content.8 Orientation is quan-tified by the strike and dip of a fracture surface. Aperture, the perpendicular width of an open fracture, is a key parameter for determining frac-ture porosity and permeability, but its measure-ment is complicated by factors such as fracture wall roughness, infill by minerals and gouge, and continuity along fracture planes.

Density, or intensity, of fracturing is quanti-fied by measuring the number, length, width, area and volume of fractures in a prescribed length, area or volume of rock.9 Fracture density and size are influenced by lithology, rock proper-ties, bed thickness and the compressive or ten-sile strain imposed during tectonic deformation.10 In a tectonic setting, the distribution of fracture density and dimension ranges from many small fractures confined to individual beds, to fewer intermediate-scale fractures that cut across a few beds and sometimes to a few kilometer-scale tectonic faults that deform entire stratigraphic sequences (above left).11

The scale, displacement and aperture of most fractures are too small to be detected by surface seismic techniques alone. To delineate fractures and quantify their properties, geophysicists use attributes of seismic data derived from the elas-tic and geometric properties of fractured rocks.12

Attribute analyses take advantage of the volume averaged response from the fracture system to obtain quantitative and qualitative estimates of seismic properties within the reservoir rock vol-ume (above right).

Aligned natural fractures in a formation cause elastic anisotropy—the variation of elastic wave properties with direction—that, if present, may be observed in properly acquired and pro-cessed seismic data.13 Seismic attributes that vary with azimuth include velocity, reflection amplitude and S-wave birefringence, or splitting. Azimuthal variations of these properties are deduced from analysis of 3D surface and bore-hole seismic data and surveys that have been acquired in multiple azimuths.14

> Folds, faults and fractures along an anticline. In folded rocks, faults and fractures may be oriented parallel or perpendicular to the fold axis. Fractures form in response to stress; joints form by means of tensile stresses, and faults form by means of shear stresses. Further deformation causes fractures to extend and may change the direction of motion along fracture planes. Faults and fractures may be stratabound and confined to a single layer or become throughgoing—crossing all sedimentary sequences and spanning many formations. Their connectivity ranges from isolated individual fractures to widely spaced fracture swarms or corridors to fully interconnected fracture networks. Drilling horizontal wells parallel to the fold axis should ensure the greatest chance of intersecting fractures. (Adapted from Florez-Niño et al, reference 10.)

JointIntermediate faultsFold axis

Sheared joints,incipient faults

Throughgoingfault zones

> Computing attributes on a time surface in a 3D seismic volume. Geophysicists analyze the character of each seismic trace at a selected time slice surface (top, red) and assign a value. For example, each trace’s amplitude is mapped onto an amplitude attribute surface (middle). Higher amplitudes near the center of the 3D seismic volume plot as higher values in the center of the 2D amplitude time slice. Other attribute surfaces, such as frequency, are computed in the same way (bottom).

Seismic Data Cube

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In the case of velocity anisotropy caused by oriented natural fractures alone, P- and S-wave velocities are at their maximum in the direction parallel to the fractures and at their minimum in the direction perpendicular to the fracture trend. As the present-day stresses may not coincide with the paleostresses active at the time of frac-ture formation, this velocity anisotropy may be modified by the present-day maximum compres-sive stress, preferentially closing fractures per-pendicular to it and opening fractures parallel to it. The resultant velocity anisotropy is the super-position of the anisotropies caused by preexisting fractures and the present-day in situ stress field.

Rocks that contain natural fracture systems have been stressed and strained—compressed, elongated, bent and broken—which deforms their original shapes. The seismic attributes of variance, coherence, curvature and distance to flexures, folds and faults are all useful indicators of strain. Variance and coherence have a recipro-cal relationship; variance measures the differ-ences between seismic traces and coherence measures the similarities. Variance emphasizes the unpredictability of seismic horizons—their

edges and interruptions—while coherence emphasizes their predictability: their connected-ness and continuity.15 High variance and low coherence may indicate faults or fracture zones, clusters or swarms. Geologists use similar char-acteristics of seismic horizons for interpreting faults or fractures when analyzing a seismic data-set; via the graphical data display, geologists fol-low along a seismic horizon or surface until it ends, breaks or becomes displaced up, down or sideways to a different location.

The curvature attribute at points on a horizon can be a measure of structural strain.16 Areas in which curvature is high or tight may have been subjected to high strain to transform them into areas of flexure, folding, faulting or high fracture intensity. The attribute of distance to flexure, folding and faulting is a geometric strain indica-tor; fracture intensity is expected to increase with proximity to these structural elements.

Coherence and curvature provide comple-mentary structural information. Folded hori-zons are expected to display curvature but no disruption in coherence; conversely, faulted

horizons do show breaks in coherence. But this is not always the case. For example, if fault movement has been small relative to the seis-mic wavelength, the faulted horizon may appear to have high coherence.

Another sensitive attribute is derived from analysis of the frequency content of seismic sig-nals: Spectral decomposition, or time-to-fre-quency analysis, is a method for separating seismic signals into their frequency compo-nents.17 The spectral content of recorded seismic data depends on cumulative effects of the seis-mic properties and interfaces of rock strata encountered by the propagating signals. By iso-lating certain frequencies, interpreters may be able to extract subtle features. For example, higher frequency components contain informa-tion about shorter wavelength structural features hidden within a dominantly long wavelength sig-nal of the full-frequency seismic data. Scientists apply spectral decomposition for image enhance-ment—improving resolution, balancing fre-quency content or suppressing noise. They also use it for reservoir characterization—evaluating sequence stratigraphy and depositional features,

> Steckman Ridge gas storage field. The Appalachian Valley and Ridge Province arcs from south-central Pennsylvania to the northeast (black outline). Many NW–SE structural lineaments cut across the Appalachian axis (red dashed lines), some of which are unnamed. The western boundary of Bedford County (pink) approximately separates the smoother topography of the Allegheny Plateau to the west from the more rugged Appalachian Valley and Ridge topography to the east. [Topographic surface map adapted from the US National Oceanic and Atmospheric Administration National Geophysical Data Center, http://www.ngdc.noaa.gov/cgi-bin/mgg/topo/state2.pl?region=pa.jpg (accessed June 6, 2012).]

Allegheny PlateauProvince

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estimating stratigraphic thickness and determin-ing fracture properties and fluid content. Spectral decomposition is a powerful tool for illu-minating subtle features such as shear faults that control the geometry of the fracture system but that are below the resolution of the full-frequency surface seismic data, as demonstrated in an Appalachian basin gas storage facility.

Intersecting Fractures with Horizontal WellsThe Steckman Ridge field is a joint venture between New Jersey Resources (NJR) Steckman Ridge Storage Company and Spectra Energy Corporation, together known as the partnership. The facility is operated by Spectra Energy as a mul-ticycle underground gas storage (UGS) facility, regulated by the US Federal Energy Regulatory Commission (FERC). The field is in the Valley and Ridge Province of the Appalachian basin in Bedford County, Pennsylvania, USA (previous page). The reservoir is in the Devonian-age Oriskany Formation, which at reservoir depths is a fractured quartzite. It is a Type 1 fractured reser-voir, in which fractures provide the primary poros-ity and permeability.18

Steckman Ridge LP acquired the depleted gas field in 2004; the field had yielded 12.5 Bcf [354 million m3] of gas cumulatively from five vertical wells. Production from the individual wells varied considerably, leading the partner-ship experts to suspect that a fracture network, rather than matrix properties, was controlling porosity and permeability. The company received approval from FERC in 2008 to convert the field to a gas storage facility, with an operating capac-ity of 17.7 Bcf [501 million m3], comprising 12 Bcf [340 million m3] of working gas and 5.7 Bcf [161 million m3] of cushion gas, with a maximum delivery rate capability of 300 MMcf/d [8.5 mil-lion m3/d] and maximum injection rate of 227 MMcf/d [6.43 million m3/d].19 The original plan called for converting the five existing production

wells to storage wells and drilling a substantial number of new vertical storage wells. Each well was designed for a 50- to 70-year life span.

Steckman Ridge field contains three anticli-nal structures that formed along the leading edge

of thrust faults (below).20 The original operator, Pennsylvania General Energy Company (PGE), had acquired 3D surface seismic data and FMI fullbore formation microimager logs in two of the production wells. To prepare for conversion to

15. Bahorich M and Farmer S: “3-D Seismic Discontinuity for Faults and Stratigraphic Features: The Coherence Cube,” The Leading Edge 14, no. 10 (October 1995): 1053–1058.

Caldwell J, Chowdhury A, van Bemmel P, Engelmark F, Sonneland L and Neidell NS: “Exploring for Stratigraphic Traps,” Oilfield Review 9, no. 4 (Winter 1997): 48–61.

16. Curvature describes how bent a 2D curve or 3D surface is at a point. At a point on a 2D curve, the curvature is the reciprocal of the radius of the largest circle capable of touching the point with tangent contact. The curvature, or the amount of bending, increases as the radius of the circle decreases because of their reciprocal relation. This concept can be extended to 3D surfaces. Many curves may be defined through a point on a surface by cutting the surface with planes through the point.

> Top of the Oriskany Formation at Steckman Ridge. Three anticlines, A, B and C, at the leading edge of thrust faults (red lines) formed primarily during the Allegheny (Permian) orogeny, although earlier Taconic (Ordovician) and Acadian (Devonian) orogenies also affected the basement and the sedimentary cover of the region. Five vertical wells, Clark 1663, Clark 1664, Clark 1665, Stup 1557 and Quarles 1709, depleted the original gas reservoir.

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Common types of 3D curvature are the maximum, minimum, strike and dip curvatures. For more on curvature: Roberts A: “Curvature Attributes and Their Application to 3D Interpreted Horizons,” First Break 19, no. 2 (February 2001): 85–100.

17. Partyka G, Gridley J and Lopez J: “Interpretational Applications of Spectral Decomposition in Reservoir Characterization,” The Leading Edge 18, no. 3 (March 1999): 353–360.

Castagna JP and Sun S: “Comparison of Spectral Decomposition Methods,” First Break 24, no. 3 (March 2006): 75–79.

18. There are four principal fractured reservoir types based on the importance of fractures in providing reservoir porosity and permeability. For a more detailed discussion of fractured reservoir types: Bratton et al, reference 8.

19. “Steckman Ridge LP—Order Issuing Certificates,” US Federal Energy Regulatory Commission, Docket No. CP08-15-000 (June 5, 2008), http://www.ferc.gov/eventcalendar/Files/20080605185040-CP08-15-000.pdf (accessed July 14, 2012).

For more on underground gas storage: Bary A, Crotogino F, Prevedel B, Berger H, Brown K, Frantz J, Sawyer W, Henzell M, Mohmeyer K-U, Ren N-K, Stiles K and Xiong H: “Storing Natural Gas Underground,” Oilfield Review 14, no. 2 (Summer 2002): 2–17.

20. Scanlin MA and Engelder T: “The Basement Versus the No-Basement Hypotheses for Folding Within the Appalachian Plateau Detachment Sheet,” American Journal of Science 303, no. 6 (June 2003): 519–563.

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> Initial seismic attributes. Maps of seismic attributes—reflection amplitude (left), distance to faults (center) and curvature (right)—show the large-scale trends consistent with the NNE strike of the Appalachian fold-and-thrust structures of the Oriskany Formation in the Steckman Ridge field.

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> Exposures of natural fractures in the Steckman Ridge vicinity. Fractures in an Oriskany quartzite quarry (left) in West Virginia, USA, located about 60 mi [100 km] southeast of Steckman Ridge field, occur in two main fracture sets that strike to the northwest. The quarry wall faces northwest and the red and green lines point to fracture planes that strike 330° and 290°, respectively. In a view from the SSE, fractures exposed in a pipeline ditch (right) near Anticline C are oriented at 350°. FMI data (not shown) from the SR17 well on Anticline C showed the same 350°orientation for open fractures.

NW-trending fracture planes that strike 290°

NW-trending fracture planes that strike 330°

NW-trending fracture planes that strike 350°

Bed dip

Summer 2012 35

gas storage operations, the partnership and Schlumberger consulting geophysicists reexam-ined these datasets and conducted field studies.

Initial examination of seismic attributes—reflection amplitude, curvature and distance to faults—revealed large-scale trends consistent with the NNE strike of the thrust-and-fold struc-tures that formed the valley and ridge topography in the region (previous page, top). In contrast, the field studies revealed a NW orientation of fractures in pipeline ditches, outcrops and creek bottom incisions through topographic ridges (previous page, bottom). These observations cor-roborated FMI interpretations of WNW- to NNW-oriented natural fractures and the NW orientation of the present-day maximum horizontal stress deduced from the direction of drilling-induced fractures (right). Further more, regional satellite imagery, gravity and magnetic studies indicated

NW-oriented cross-strike structural discontinui-ties (CSDs) or lineaments (above).21 Results from these studies suggested that natural fractures may be exerting significant control on the poros-ity and permeability in the field as well as on the gross structures of the Steckman Ridge anti-clines. If so, evidence of the NW-oriented fracture system should have been visible in the seismic attributes extracted from the seismic data. Therefore, the 3D seismic data were reexamined using advanced fracture detection analyses to identify and map the more subtle effects of the open fracture systems.

Spectral analysis of the seismic data indicated that the frequency content of the seismic wavelet was fairly consistent, ranging from 25 to 75 Hz at the well locations. However, the shape of the seis-mic wavelet along the top of the Oriskany horizon varied from location to location across the field.22

> Fracture characterization. An FMI tool was used to detect fractures in the Clark 1663 well. These fracture trends were plotted in a rose diagram and helped geoscientists see the predominant NW–SE trend of the fractures. They also showed that most fractures in this well were open or partially open and their directions corresponded to the direction of a set of faults.

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> Cross-strike structural discontinuities (CSDs) on a magnetic anomaly map. Interpretation of a portion of the North American magnetic anomaly map shows northwest to southeast CSDs (dashed red lines) crossing the Appalachian basin. There is a clear break in the magnetic field anomaly in southwest Pennsylvania along the Washington County CSD that is interpreted to be a shear zone related to the NW–SE fractures in the Steckman Ridge field, which is in Bedford County (black outline). [Magnetic anomaly map adapted from the US Geological Survey (Bankey et al, reference 21).]

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21. For more on jointing in the Appalachian basin: Engelder T, Lash GG and Uzcátegui RS: “Joint Sets That Enhance Production from Middle and Upper Devonian Gas Shales of the Appalachian Basin,” AAPG Bulletin 93, no. 7 (July 2009): 857–889.

Bankey V, Cuevas A, Daniels D, Finn CA, Hernandez I, Hill P, Kucks R, Miles W, Pilkington M, Roberts C, Roest W, Rystrom V, Shearer S, Snyder S, Sweeney R, Velez J, Phillips JD and Ravat D: “Digital Data Grids

for the Magnetic Anomaly Map of North America,” Reston, Virginia, USA: US Geological Survey, Open-File Report 02-414, 2002.

22. For a tutorial on seismic wavelets: Henry SG: “Catch the (Seismic) Wavelet,” AAPG Explorer 18, no. 3 (March 1997): 36–38.

Henry SG: “Zero Phase Can Aid Interpretation,” AAPG Explorer 18, no. 4 (April 1997): 66–69.

36 Oilfield Review

This variability did not affect large-scale structural interpretation but would affect stratigraphic inter-pretation and the search for small-scale features.

Scientists performed spectral decomposi-tion on the 3D seismic data volume and exam-ined selected frequency volumes, which revealed subtle structures within the data (left). They extracted the 30-Hz isofrequency volume through spectral decomposition, iso-lated the top of the Oriskany horizon as a vol-ume slab—bounded 12 ms above and below the horizon pick—and then, using time slices, sliced through this 24-ms thick subvolume. They saw clear evidence of NW-trending shear zones cutting across the NNE strike of the anticline axes (next page, top). These shear zones were the only structural features discovered with the same orientation as that of the fracture system observed in both the local outcrops and the FMI data from the nearby Clark 1663 vertical well-bore.23 The scientists determined that these shear zones were the structural features con-trolling the highly permeable fracture system believed to hold the actual storage capacity for the field’s gas.

Schlumberger geoscientists designed a dual-porosity discrete fracture network (DFN) model to help with designing well trajectories, to update with data from the drilling program and to use for production modeling of gas storage and retrieval (next page, bottom). Input for the model included the shear zones and fracture sets mapped from seismic interpretation, frac-ture aperture, fracture fill, dip angle and dip azimuth from FMI images and fracture conduc-tivity from resistivity logs; high electrical con-ductivity spikes on the resistivity logs correlated with more open and, presumably, more hydrauli-cally conductive fractures.24

The data revealed two fracture sets within the field. One fracture set ran west to east in the southern portion of the field, and the other ran NW–SE. Moving north across the field, both frac-ture trends rotated clockwise. Scientists theorize that this rotation is associated with the rotation of the stress field away from the NW-trending shear zones.

> Spectral decomposition. Spectral decomposition of a seismic wavelet (top left), which contains a wide range of frequencies, separates it into many single-frequency traces (top right). The spectral decomposition process proceeds from left to right, and spectral summation—the reverse process of spectral decomposition—proceeds from right to left. In spectral decomposition of a volume of 3D full-frequency seismic data (bottom), bandpass filtering produces volumes that contain data of narrow frequency ranges.

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23. Strike-slip displacement or motion refers to the movement of the other side of the strike-slip fault relative to the reference side—the side on which one is standing, facing the fault. The motion is right lateral when the other side of the fault moves to the right and left lateral when other side moves to the left.

24. For procedures of DFN model development: Souche L, Astratti D, Aarre V, Clerc N, Clark A, Al Dayyni TNA and Mahmoud SL: “A Dual Representation of Multiscale Fracture Network Modelling: Application to a Giant UAE Carbonate Field,” First Break 30, no. 5 (May 2012): 43–52.

Summer 2012 37

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, Isofrequency amplitude of the top of the Oriskany Formation. A seismic time slice map at 746-ms two-way traveltime through the 30-Hz isofrequency volume, after spectral decomposition, is centered on the top of the Oriskany Formation within Anticline A. Amplitude variations highlight right and left lateral strike-slip offsets through the anticline. An example is the NW–SE right lateral offset (dashed red line) cutting the large blue amplitude area. To the southwest, left lateral offsets of the same blue amplitude area parallel the dashed red line. These NW–SE offsets are consistent with NW–SE structural lineaments mapped throughout Pennsylvania. They are interpreted to be cross-strike shear zones that control the gas storage and flow regime of the Steckman Ridge reservoir.

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> Discrete fracture network modeling. A discrete fracture network (DFN) model was constructed for the Oriskany reservoir, which was divided vertically into five zones. The model incorporated results of seismic and log interpre-tations. Results from Zone 5 show, from left to right, the fracture dip, fracture azimuth, matrix porosity and traces of the 27,367 fractures. A fracture trace is a curve formed by the intersection of a fracture crossing a horizon surface. The radial pole plot (bottom right) summarizes the dips and dip directions of the modeled fracture planes, which dip 45° to 90° in the southwest to northeast directions. A pole is a line perpendicular to a fracture plane; a fracture that has a strike azimuth of 135° and dip angle of 75° to the NE plots as a point at direction azimuth 45°—reading clockwise around the plot—and inclination 75°—reading from the center toward the edge—on a pole plot.

38 Oilfield Review

Spectra Energy well planners working for the partnership used this model to design horizontal wells along NE to SW trajectories to maximize interception of the NW- to SE-oriented cross-strike fracture systems (left). Wells SR10 and SR14, the first and second wells drilled into these seismically defined features, were drilled into Anticlines A and C, respectively. Well plan-ners intended to drill 1,000-ft [305-m] horizon-tal sections for both wells. However, the drillers encountered large open fracture systems imme-diately upon entering the reservoir. In the two horizontal sections, after drilling only 130 ft [40 m] and 172 ft [53 m], respectively, drillers lost circulation in the open fracture system, which forced them to suspend operations. Having encountered good zones for gas injec-tion, the operators deemed these wells suitable for gas storage. Both wells were barefoot open-hole completions with casing set 50 ft [15 m] into the top of the reservoir to ensure isolation of the storage unit.

The remaining wells were completed in con-junction with updates to the DFN model; the pro-cess consisted of drilling a well to TD, running an FMI log, updating the DFN model and drilling the next well. For example, fractures interpreted in the FMI log run in Well SR21 were used to update the model before drilling the next well (left). In addition, the drillers used the DFN model for geo-steering all these horizontal wells.

Because of the complicated geologic struc-ture in the field area, steering the wells was a challenge. Engineers obtained sonic and density logs at critical points during drilling to create synthetic seismic traces for correlation with actual seismic traces. They used these prelimi-nary well-to-seismic ties to compare the then-current drilling location with the drilling target that had been planned from the seismic data. This geophysically guided borehole placement methodology helped engineers adjust the well trajectories. Schlumberger engineers executed the well plans using Schlumberger directional drilling tools. The PowerV rotary steerable verti-cal drilling system was used to keep the hole straight to the kickoff point, and directional drill-ers helped steer the wellbore to the intended cas-ing, landing and final lateral TD targets.

The partnership considered this gas storage conversion successful. Through careful analysis, integration and interpretation of geologic, geo-physical and engineering data, the team identi-fied and confirmed the controlling fracture system within the reservoir. The original plan was to drill all new vertical wells to achieve the designed injection and withdrawal capability

> Planning horizontal wells to intersect open fractures. Some studies suggest that vertical wells have only a slight chance of intersecting vertical fractures. At the Steckman Ridge field, engineers planned to drill horizontal wells parallel to the anticline axis and through the cross-axis shear and fracture zones identified from analyses of seismic, geologic and surface mapping data.

Horizontalwell

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> Controls on fracture density. The horizontal section of Well SR21 (purple line) was drilled parallel to the axis of Anticline B and intersected fractures (brown disks) as interpreted from FMI images. Fracture density increased as the well crossed a shear fault (dashed red line). The blue lines represent NNE-oriented faults mapped during the initial seismic interpretation effort. The contours (black) and colors indicate depth to the top of the Oriskany Formation.

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Summer 2012 39

of 227 and 300 MMcf/d of gas, respectively. The partnership has currently installed com-pressor capacity for injecting 150 MMcf/d [4.2 million m3/d] of gas. To date, the original five vertical production wells have been reentered and recompleted with varying degrees of success, and the partnership has drilled and completed substantially fewer wells than originally planned. The newly drilled wells were highly successful horizontal wells. The well performance indicates rates near the target levels for withdrawal. The partnership is evaluating whether further hori-zontal wells may be required, but the potential to inject and withdraw gas at or near the design rates, with significantly fewer horizontal wells than originally planned, will result in substantial cost savings.

To convert the Steckman Ridge field to an underground gas storage facility, engineers made use of attributes from seismic data to identify subtle cross-strike shear zones and associated fracture systems. In the North Sea, geoscientists are using advanced seismic attribute analysis for detailed mapping of fault networks that provide additional reservoir production capacity.

Detailed Mapping of Fault NetworksThe South Arne field is in the Danish sector of the North Sea, about 250 km [155 mi] WNW of Esbjerg, Denmark. Hess has operated the field since 1994; its partners are DONG Energy A/S and Danoil Exploration A/S. The reservoir is in chalks of the Late Cretaceous Tor and overlying Early Paleogene Ekofisk formations, situated on an elongated structure that trends NW–SE.25

Oil production began in 1999 from horizontal wells that were drilled parallel to the structural axis. Production is supported by water injection from horizontal wells drilled parallel to and inter-laced with the production wells. To aid production, both well types underwent fracture stimulation pro-grams using either acid to erode the induced frac-ture surface or proppant to keep fracture channels open. The induced fractures have vertical fracture planes oriented NW–SE, parallel to the anticline structure. The well pattern and stimulation pro-gram promoted homogeneous sweep across the res-ervoir.26 After a few years, production data indicated that reservoir fluids were not flowing as projected, and the reservoir sweep was becoming more heterogeneous.

Consequently in 2005, Hess and Schlumberger commenced a time-lapse seismic program to investigate flow patterns indicated in the pro-duction data and to compare them with patterns inferred from interpretation of time-lapse seis-mic data. Time-lapse seismic interpretation

compares one or more recent surveys against a reference survey to uncover production-related changes within the surveyed reservoir volume. Time-lapse seismic surveys help operators mon-itor a reservoir, map pathways and barriers to fluid movement and understand reservoir phe-nomena such as compaction from changes in the distribution of reservoir fluid content.27 For the South Arne field, a preproduction 3D seis-mic survey acquired in 1995 served as the refer-ence survey. A 3D survey acquired in 2005 served as the monitor survey.

A key result of the time-lapse seismic analysis was a strong indication that faults were affecting reservoir flow. These faults were providing addi-tional flow capacity parallel to their strike while impeding the flow perpendicular to their strike (above). Engineers have incorporated this aniso-tropic flow behavior into reservoir simulation models; predictions of reservoir flow have

25. Mackertich DS and Goulding DRG: “Exploration and Appraisal of the South Arne Field, Danish North Sea,” in Fleet AJ and Boldy SAR (eds): Petroleum Geology of Northwestern Europe—Proceedings of the 5th Petroleum Geology Conference. London: Geological Society (1999): 959–974.

26. Herwanger JV, Schiøtt CR, Frederiksen R, If F, Vejbæk OV, Wold R, Hansen HJ, Palmer E and Koutsabeloulis N: “Applying Time-Lapse Seismic Methods to Reservoir Management and Field Development Planning at South Arne, Danish North Sea,” in Vining BA and Pickering SC (eds): Petroleum Geology: From Mature Basins to New Frontiers—Proceedings of the 7th Petroleum Geology Conference. London: Geological Society (2010): 523–535.

27. For more on time-lapse seismic analyses: Pedersen L, Ryan S, Sayers C, Sonneland L and Veire HH: “Seismic Snapshots for Reservoir Monitoring,” Oilfield Review 8, no. 4 (Winter 1996): 32–43.

Aronsen HA, Osdal B, Dahl T, Eiken O, Goto R, Khazanehdari J, Pickering S and Smith P: “Time Will Tell: New Insights from Time-Lapse Seismic Data,” Oilfield Review 16, no. 2 (Summer 2004): 6–15.

, South Arne time-lapse amplitude difference map. The time-lapse amplitude difference map (left) shows changes in seismic amplitude along the top of the Tor horizon between 1995 and 2005. NW–SE faults (green) dominate the structure. Blue colors indicate a decrease in reflection strength and red to yellow indicates an increase. Geoscientists interpret the reflection amplitude increase and decrease to signal, respectively, compaction and dilation of the formation pore volume. The distribution of changes in reflection strength results from fault-controlled flow and circulation of reservoir fluids during oil production that was supported by water injection. The fault orientations promoted structural crest collapse and compaction (orange and yellow, top right) and preferential flow of and pressure support from fluids and dilation toward the flanks of the structure (blue, bottom right).

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40 Oilfield Review

improved, providing closer agreement between estimated pressures and actual pressures mea-sured in appraisal wells drilled for field extension to the north.28 Since that study, Hess and Schlumberger have continued to collaborate to improve imaging of the fault pattern within the South Arne field.29

A promising approach for revealing fault pat-terns follows a workflow that identifies three independent attributes of seismic dip, combines them into an aggregate attribute and then uses edge enhancement processing to enhance fault zones (above). The independent attributes—chaos, curvature and variance—describe the structural uncertainty, structure and amplitude sensitivity of fault dips interpreted from seismic data. Although dip is difficult to estimate cor-rectly, geophysicists used global constraints to estimate dip reliably and consistently.30

The chaos attribute results from the struc-tural uncertainty or variability of the seismic dip and azimuth estimates. It measures the chaotic or disordered quality from statistical analysis of local seismic responses—abruptly changing sig-nals are chaotic, but smoothly varying signals are not—thus helping identify faults and fractures, which cause disruptions in the seismic volume.31 Chaos is an independent attribute because it does not vary with seismic amplitude or dip ori-entation, meaning that the chaos value will be

the same whether in a low- or high-amplitude or dipping or flat region of the 3D seismic volume.

The second attribute, the curvature attribute, describes the lateral structural variation in dip. Large values of curvature highlight abrupt changes in dip and are common indicators of fractures and faults.32

The third attribute, amplitude variance, is a seismic attribute of the coherence family. Amplitude variance reveals the lack of continuity in the signal, which is useful for identifying faults as well as stratigraphic features.

The three independent attributes—chaos, curvature and variance—are combined into an aggregate seismic attribute using a weighted summation of the independent inputs; weighting equalizes each of the contributions so that they affect the aggregate output attribute similarly. This combined attribute volume undergoes edge enhancement processing using “ant tracking” to bring out the fault planes and suppress other nonstructural features.33 The resulting seismic volume—a fault cube—provides a detailed description of the fault network associated with the fractures that control reservoir production (next page). These details are important inputs into fractured reservoir simulation and geome-chanical earth models, which engineers use for predicting reservoir properties and their evolu-tion with production.

Fracture Network Modeling at Multiple ScalesIdeally, reservoir models should include all that is known about the geology, rock and fluid proper-ties and production history of a reservoir. Faults and fractures deserve special treatment because they represent discontinuities in the rocks. Changes in properties near faults and fractures are as important as changes in properties near stratigraphic surfaces and horizons—bedding, sequence and unconformity boundaries. Lithology may be displaced slightly or drastically across faults, while porosity and permeability may change in their vicinity. Faults and fractures may affect fluid flow regimes by acting as preferential channels for flow when they are open or as obsta-cles to flow when sealed.

Using seismic data to detect a fault and frac-ture network, a geoscientist team from Abu Dhabi Company for Onshore Oil Operations (ADCO), the operator, and Schlumberger con-ducted a study of a giant carbonate field south-east of Abu Dhabi, UAE, to determine how best to capture the details of the network, which was suspected of affecting reservoir production.34 The objective was to represent the seismic lineaments in reservoir models as completely and efficiently as possible within the restrictions set by the com-puting environment.

Production comes from the Lower Cretaceous Thamama Formation. The structure is a broad, gentle anticline elongated in the northeast direc-tion and crossed by four fracture sets identified both in wells and 3D seismic data. The main shear fracture set has a WNW–ESE orientation, right lateral strike-slip displacement, and en ech-elon regular spacing of 3 to 4 km [2 to 2.5 mi].35 Data show that the set may be related to the reac-tivation of Precambrian basement strike-slip faults. The second set is oriented NW–SE and interpreted to be the right lateral synthetic Riedel shear set associated with the main set.36 The third set is oriented N–S and interpreted to be the left lateral antithetic Riedel shear set. A fourth minor set, oriented NNW–SSE, consists of extension relay fractures that propagated between fractures in the main WNW–ESE shear fracture set.

The dataset for this study included 3D prestack time-migrated (PSTM) seismic data that were converted from time to depth over the reservoir, a comprehensive well log dataset of 55 image logs and 18 production logs from horizon-tal and vertical wells and a 3D static model of the reservoir based on the ADCO asset team’s inter-pretation of the geology, stratigraphy, lithology and rock and fluid properties from well log, core, petrophysical and fluid analyses.

No Yes

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> Globally consistent dip estimation for fault and fracture mapping. The workflow starts with seismic data input (top left, purple) into a dip estimator (top, blue). Comparison against dip constraints (center, yellow) determines convergence. The result is a dip volume (top right, green) along with the three dip attributes (center right, green) used for fault and fracture identification. The dip attributes undergo a weighted summation and edge detection to yield an estimated volume of potential faults and fractures (bottom, right to left). Geologists, geophysicists and well log analysts screen and validate (bottom left, orange) these faults and fractures as real or as other geologic features or seismic artifacts.

Summer 2012 41

> Faults and fractures from dip mapping. These images are grayscale shaded relief maps of the two-way traveltime surface at the top of the Ekofisk Formation; in the bottom right corner of each image, the green arrow points north. A view from the southeast of the two-way traveltime surface (top left) shows the NW–SE trending structure of the South Arne field, with a vertical seismic section in the background. The other views are from the north and are seismic results superimposed on the two-way traveltime surface. Reflection amplitude (top right) depends on the rock contrast across the surface; the blue amplitude shows the negative reflection polarity caused by a decrease in the seismic impedance at the top of the Ekofisk Formation, which has lower seismic impedance than the shales immediately overlying it. The structural dips (bottom left) that result from dip estimation show the dip at every point on the surface and are independent of reflection strength. The gray scale indicates dip magnitude and direction and ranges from white to black; white indicates dips toward the west and black indicates dips toward the east. Ant tracking edge detection and enhancement processing of the dips accentuates the traces of faults and fractures (yellow and orange, bottom right) that cut across the surface.

Top of the Ekofisk Formation: Time Surface Top of the Ekofisk Formation: Amplitudes

Top of the Ekofisk Formation: Dips Top of the Ekofisk Formation: Ant Tracking

28. Herwanger et al, reference 26.29. Aarre V and Astratti D: “Seismic Attributes for Fault

Mapping—The Triple Combo,” presented at the Petroleum Exploration Society of Great Britain Geophysics Seminar on Amplitudes and Attributes; Uses and Abuses, London, June 15–16, 2011.

30. Aarre V: “Globally Consistent Dip Estimation,” Expanded Abstracts, 80th SEG Annual Meeting, Denver (October 15–17, 2010): 1387–1391.

31. Randen T, Monsen E, Signer C, Abrahamsen A, Hansen JO, Sæter T, Schlaf J and Sønneland L: “Three-Dimensional Texture Attributes for Seismic Data

Analysis,” Expanded Abstracts, 70th SEG Annual Meeting, Calgary (August 6–11, 2000): 668–671.

32. Roberts, reference 16.33. For more on the patented ant tracking procedure:

Pedersen SI, Randen T, Sønneland L and Steen Ø: “Automatic Fault Extraction Using Artificial Ants,” Expanded Abstracts, 72nd SEG Annual Meeting, Salt Lake City, Utah, USA (October 6–11, 2002): 512–515.

Pedersen SI: “Image Feature Extraction,” US Patent No. 8,055,026 (November 8, 2011).

34. Souche et al, reference 24.

35. En echelon is a stepped or shingled arrangement of similar objects, either to the right or left of the reference object.

36. Riedel shear structures are secondary structures that form in shear zones. They include two conjugate sets of en echelon slip surfaces. The synthetic set has the same sense of displacement as the primary shear and is inclined at a low angle to the primary direction of relative motion. The antithetic set has the opposite sense of displacement as the primary shear and is at a high angle to it.

42 Oilfield Review

> Evaluation of seismic estimates of faults and fractures. Faults (cyan) were interpreted in vertical sections (top left) and in depth slices (bottom left) close to well trajectories—in this case Well E (yellow). These seismically identified faults were the result of dip estimation and ant tracking and were compared with faults picked by hand from seismic data (red lines) and faults and fractures interpreted from FMI image logs (orange and red disks along Well E). Faults and fractures interpreted on the image logs from Well E are plotted on a radial pole plot stereonet (top right) and well log section (bottom right) for more detailed comparison with other borehole measurements and seismic data. The blue and green rectangles in Track 1 of the well log section show intervals where water (blue) and oil (green) entries into the well were detected during production log testing and interpreted as associated with faults crossing the horizontal well. Track 2 shows intervals where faults were identified through ant track processing of seismic data; the gray rectangles mark where Well E crosses faults. The dip tadpoles in Track 3 indicate the depth and orientation of fractures observed in the FMI image log: The tadpole color indicates fracture classification; the circle plots at the depth and dip of the fracture and the tail gives the fracture dip azimuth. Track 4 (light green) shows the grid cell boundaries crossed by the representation of Well E in the 3D model of the fracture system in the reservoir. (Adapted from Souche et al, reference 24.)

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Summer 2012 43

To extract fault and fracture information from the 3D PSTM seismic data, the workflow followed a procedure similar to that used for the South Arne field; the interpretation team fol-lowed up by comparing the seismic results with image logs. They accomplished this task using seismic cross sections along well trajectories and seismic depth slice maps within the reser-voir interval or along the horizontal sections of horizontal wells. Seismic lineaments were retained in the fault cube if they showed close agreement with image log interpretation (previ-ous page). The remaining lineaments were screened further to categorize them as sedi-mentary boundaries or as artifacts from seismic data acquisition and processing.

The team incorporated the verified fault cube into the 3D reservoir model. Including and representing so many elements with enough detail to be faithful to the reservoir geology and meaningful to reservoir engineers—while keep-ing model computations manageable—were the challenges. To address these challenges, the team chose a hybrid model using multiscale rep-resentation.37 The large fractures, thought to con-trol the flow of injected fluids in this reservoir,

were modeled explicitly using a discrete fracture network (DFN). The small fractures, believed to augment the matrix permeability, were repre-sented statistically using an implicit fracture model (IFM). The size threshold between large and small fractures was grid-size dependent: The large fractures provided connectivity within the cells and the small fractures contributed to the cell properties. DFN and IFM models may be combined and scaled up for dynamic reservoir simulation purposes (above). The primary out-come of the hybrid model is that a single model accounts for the predominant effects from large fractures and the contributions from smaller fractures. The hybrid model also results in a con-siderable speedup in computation time, which is reduced from hours to minutes, making it possi-ble to test several reservoir development sce-narios and their production outcomes efficiently and quickly.

Seeing Fractures in the FutureTo ensure successful reservoir development and production, engineers must have an accurate geo-logic understanding of natural fractures and faults. Analysis of seismic data is fundamental to this process, and seismic attributes play a crucial role in helping interpreters identify subtle fea-tures. Also vital is integration of seismic results with large-scale geologic trends, log data, outcrop studies and real-time drilling results.

Knowledge of natural fracture systems and their orientations, dimensions and physical prop-erties allows operators to plan well trajectories to intersect these sweet spots in reservoirs con-trolled by fracture porosity and permeability—or to avoid them if necessary. And although most fractures are too small to be sensed individually by seismic waves, sets and networks of fractures can have a collective impact on seismic response.

New capabilities for high-fidelity seismic data acquisition, greater data storage and faster com-puting spur the quest for even more-accurate geo-logic maps and models to support and sustain decisions about developing reservoirs, drilling wells and planning surface support facilities and infrastructure. Completing this quest will require new and innovative ways to design seismic attri-butes for better identification and characteriza-tion of fractures in reservoirs. —RCNH

> Hybrid model of a natural fracture system. The hybrid model combines a discrete fracture network (DFN) for large fractures (left) and an implicit fracture model (IFM) for small fractures (center) into a single coherent framework (right). Upscaling the model enables efficient testing of reservoir development plans and their production outcomes. Each color in the DFN plot represents a distinct DFN set. The model covers an area of 33 km2 [13 mi2]. (Adapted from Souche et al, reference 24.)

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37. Souche L, Kherroubi J, Rotschi M and Quental S: “A Dual Representation for Multiscale Fracture Characterization and Modeling,” Search and Discovery Article 50244 (December 2009), http://www.searchanddiscovery.com/documents/2009/50244souche/ndx_souche.pdf (accessed July 15, 2012).

Lee SH, Lough MF and Jensen CL: “Hierarchical Modeling of Flow in Naturally Fractured Formations with Multiple Length Scales,” Water Resources Research 37, no. 3 (March 2001): 443–455.