Advances in the study of naturally fractured hydrocarbon ...

$: Advances in the study of naturally fractured hydrocarbon ...$
Advances in the study of naturally fractured hydrocarbon reservoirs:

a broad integrated interdisciplinary applied topic

GUY H. SPENCE1*, GARY D. COUPLES2, TIM G. BEVAN3, ROBERTO AGUILERA4,

JOHN W. COSGROVE5, JEAN-MARC DANIEL6 & JONATHAN REDFERN1

1School of Earth Atmospheric and Environmental Sciences, University of Manchester,

Oxford Road, Manchester M13 9PL, UK2Institute of Petroleum Engineering, Heriot-Watt University, EdinburghEH14 4AS, UK

3BP Exploration, BP International Centre for Business & Technology,

Chertsey Road, Sunbury-on-Thames, Middlesex TW16 7LN, UK4Schulich School of Engineering, University of Calgary, Room CCIT 220, 2500 University Drive

NW, Calgary, Alberta T2N 1N4, Canada5Department of Earth Sciences and Engineering, Imperial College London,

South Kensington Campus, London SW7 2AZ, UK6IFP Energies Nouvelles, 1 & 4 avenue de Bois-Preau, 92852 Rueil-Malmaison Cedex, France

*Corresponding author (e-mail: [email protected])

Abstract: Naturally fractured reservoirs, within which porosity, permeability pathways and/orimpermeable barriers formed by the fracture network interact with those of the host rock matrixto influence fluid flow and storage, can occur in sedimentary, igneous and metamorphic rocks.These reservoirs constitute a substantial percentage of remaining hydrocarbon resources; theycreate exploration targets in otherwise impermeable rocks, including under-explored crystallinebasement, and they can be used as geological stores for anthropogenic carbon dioxide. Theircomplex fluid flow behaviour during production has traditionally proved difficult to predict,causing a large degree of uncertainty in reservoir development. The applied study of naturally frac-tured reservoirs seeks to constrain this uncertainty and maximize production by developingnew understanding, and is necessarily a broad, integrated, interdisciplinary topic. Some of themethods, challenges and advances in characterizing the interplay of rock matrix and fracturenetworks relevant to fluid flow and hydrocarbon recovery are reviewed and discussed via the con-tributions in this volume.

Global estimates of conventional hydrocarbonresources are typically subdivided based on litho-logical reservoir types for example, carbonate orsiliciclastic (e.g. Roehl & Choquette 1985). How-ever, many of these sedimentary rock reservoirsmay contain fractures to a greater or lesser degree.The recent boom of unconventional reservoirs high-lights once again the key role that natural fracturescan play in helping production of fluids. It alsorequires an improved understanding of the geologyand physics of natural fracture networks to meetpublic expectations regarding safety issues. More-over, fracture networks can be present in other-wise impermeable crystalline basement rocks (e.g.Sanders et al. 2003; Murray & Montgomery2012; Slightam 2012) and igneous intrusions(e.g. Gudmundsson & Løtveit 2012), also allowingthese rocks to form potential fractured reservoirs.Historically, fractured crystalline basement rocks

have been under-explored as potential hydrocarbonreservoirs. Naturally fractured reservoirs constitutea substantial percentage of remaining hydrocarbonresources.

Naturally fractured reservoirs

A reservoir fracture is a general term used todescribe a ‘naturally occurring macroscopic planardiscontinuity in rock due to deformation, or phys-ical diagenesis’ (Nelson 2001). Reservoir fracturesencompass both extensional ( joints) and shear(faults) structures. Fractures formed by brittle tec-tonic deformation are the most common focusfor studies of naturally fractured reservoirs. How-ever, reservoir fractures may also include struc-tures that formed by desiccation (e.g. shrinkagecracks) and syneresis (e.g. chickenwire texture) insediments, and structures that formed by thermal

From: Spence, G. H., Redfern, J., Aguilera, R., Bevan, T. G., Cosgrove, J. W., Couples, G. D. & Daniel, J.-M. (eds)Advances in the Study of Fractured Reservoirs. Geological Society, London, Special Publications, 374,http://dx.doi.org/10.1144/SP374.19 # The Geological Society of London 2014. Publishing disclaimer:www.geolsoc.org.uk/pub_ethics

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contraction during cooling in volcanic rocks (e.g.columnar joints; Bratton et al. 2006). Naturallyoccurring high fluid pressure may also be capa-ble of creating extensional fractures in a similarway to hydraulic fracturing (Mandl & Harkness1987); this may provide a means by which tensilefractures might form at deeper burial depths.

The distribution of fractures in a reservoir issometimes referred to as ‘fracture stratigraphy’(Laubach et al. 2009), ‘joint-network architecture’(Shackleton et al. 2005) or ‘fracture network’ (e.g.Lonergan et al. 2007), as used here. Naturally frac-tured reservoirs are generally defined as such whenthe fracture network has a significant influence onfluid flow in the reservoir such that: (1) the fracturenetwork provides the main conduits for fluid flowand is the dominant control on reservoir per-meability, with the rock matrix acting as the maincontrol on reservoir storage capacity; (2) fracturesfurther improve the permeability of a reservoirthat has good matrix porosity and permeability;(3) the fracture network controls both fluid flowand storage in crystalline or other tight rocks withlittle or no matrix porosity; or (4) mineralizationin fractures (e.g. by clay-fills such as dickite andcalcite-healed and quartz veins) and fine-grainedfault gouges cause them to have low permeability,allowing these features to act as barriers or bafflesrather than conduits for fluid flow, causing reservoiranisotropy (Aguilera 1995; Nelson 2001; Lonerganet al. 2007). The presence of low-permeability frac-tures can also cause compartmentalization of thereservoir (e.g. Fernandez et al. 2011). The precedingcriteria have been used to classify naturally frac-tured reservoirs into a series of different types(Table 1; Nelson 2001). Hybrids of these naturallyfractured reservoir types may also occur. Each ofthese reservoir types will experience different flowcharacteristics during production (e.g. Aguilera1995; Nelson 2001; Bratton et al. 2006).

In addition to characterizing stratigraphic andspatial variations in the permeability and porosityof the reservoir matrix through which the fracture

network extends, important fracture attributesaffecting fluid flow pathways include fracture setorientations, fracture lengths and heights, strati-graphic distributions, spacing, apertures, fracture-surface topography and fracture-network connectiv-ity. These attributes can be quantified using fractureindices (e.g. Dershowitz & Herda 1992) and used toconstruct deterministic and stochastic discrete frac-ture network (DFN) models to provide inputs tonumerical flow models. However, accurately andquantitatively characterizing fracture networks infractured reservoirs is a challenging enterprise (see‘Characterizing fracture networks’ below).

Fractured reservoirs currently in production arespread across the globe and are particularly com-mon in tight (low-matrix porosity and permeability)carbonate rocks (Aguilera 1995). Usually produc-tion from non-fractured reservoirs can be predictedaccurately to within an acceptable margin. Histori-cally however there has been a much larger rangein variability of recovery achieved from fracturedreservoirs (Aguilera 1999). This has traditionallymade it difficult to reliably predict recovery fromfractured reservoirs, leading to a large degree ofuncertainty in reservoir development.

Aguilera (1980, 1995) and Nelson (1985, 2001)highlighted the necessity of treating fractured re-servoirs as a distinct category of reservoir. This isessential in order to optimize well placement tointersect the greatest number of productive frac-tures, improve recovery and efficiently managefractured reservoirs, including the design of gas/steam or fluid injection schemes to enhance pro-duction. Subsequent work has generated continuousadvances in our understanding of fundamental frac-turing processes, including diagenetic influences,and the development of methods and applied tech-niques for characterizing fracture networks andmodelling fluid flow in fractured reservoirs.

Previous relevant themed volumes addressingvarious aspects of the theory-based and appliedstudy of fractured rocks include: GeologicalSociety of London Special Publications 29 (Jones

Table 1. Classification of fractured reservoir types (definitions from Nelson 2001)

Naturally fracturedreservoir types

Classification description

Type 1 Fractures provide the essential porosity and permeability in the reservoir.

Type 2 Fractures provide the essential permeability in the reservoir. Rock matrixprovides the essential porosity (storage capacity).

Type 3 Fractures assist permeability in an already producible reservoir. Rockmatrix has good porosity and permeability.

Type 4 Fractures provide no significant additional porosity or permeability butcreate significant reservoir anisotropy (barriers to flow).

G. H. SPENCE ET AL.



& Preston 1987), 92 (Ameen 1995), 127 (Cowardet al. 1998), 155 (McCaffrey et al. 1999), 169 (Cos-grove & Ameen 2000), 209 (Ameen 2003), 214(Petford & McCaffrey 2003), 231 (Cosgrove &Engelder 2004), 270 (Lonergan et al. 2007), 292(Jolley et al. 2007), 367 (Healey et al. 2012) and370 (Garland et al. 2012); special issues of theAmerican Association of Petroleum Geology Bul-letin volume 93, number 11 (Hennings 2009); andthe Journal of Structural Geology, volume 32, num-bers 9 (Agosta & Tondi 2010), 11 (Wibberley et al.2010) and 12 (Dunne et al. 2010).

The 18 papers in this Special Publication reflectan integrated interdisciplinary approach to theapplied study of fractured hydrocarbon reservoirs.Important interdependent steps in reducing uncer-tainty in flow modelling and efficiently developingfractured reservoir to maximize recover include:(1) increasing the accuracy and constraining theuncertainty in quantifying fracture networks; and(2) using these data to construct deterministicfracture networks and/or stochastic (determinedprobabilistically accounting for randomness) dis-crete fracture networks (DFNs) and DFN anddiscrete fracture matrix (DFM) models.

An integrated interdisciplinary approach

The applied study of fractured reservoirs involvescollaboration between geologists, geophysicists,petrophysicists and petroleum engineers. Thedegree of complexity in fractured reservoirs andresulting uncertainty in flow behaviours requiresthe adoption of an integrated, interdisciplinaryapproach to their study that includes input from along list of different specialities including structuralgeology, rock mechanics, geomechanics, petro-physics, petroleum engineering, fractography, sedi-mentology, metamorphic and igneous petrology,geophysics, outcrop laser scanning and digital mod-elling, photogrammetry, physics, chemistry, math-ematics, statistics, computer programming andnumerical modelling. Such is the very broad rangeof sub-disciplines that have been applied to thestudy of fractured reservoirs that reports of recentadvances can be spread widely across a large numberof disparate discipline-specific journals, publica-tions and academic and professional conferences;so that workers involved in different aspects ofthe study of fractured reservoirs cannot always befully aware of the entire breadth of advances beingmade. The goal of this Special Publication is tobring together into a single volume contributionsfrom a number of the major sub-disciplines involvedin the applied study of naturally fractured reservoirs,in order to increase cross-disciplinary awareness ofthe challenges and progress being made in the

different branches of this interdisciplinary subject,from characterizing fracture networks though tonumerical simulation of fluid flow. However, asingle volume cannot cover each sub-disciplinecomprehensively.

This Special Publication includes contributionsfrom industry and academia representing advancesin the use of subsurface data, outcrop analogues,digital outcrop models and numerical methods tomodel natural fracture networks and simulate fluidflow together with geomechanics and statisticalapproaches. A feature of the 18 papers in this vol-ume is their cross-disciplinary nature and integra-tion of different techniques and data types. Thesepapers are very broadly organized into three sec-tions: (1) investigating fracture networks using out-crop, core and geophysical data; (2) numerical andstatistical simulations and models; and (3) case stud-ies. Many of the papers cross these boundaries how-ever, reflecting their multi-disciplinary approach.

Examples of petroleum-industry-based casestudies of fractured reservoirs in both sedimentaryand crystalline rocks are also presented, including:two examples of industry case studies of naturallyfractured crystalline basement reservoirs (Murray& Montgomery 2012; Slightam 2012); four casestudies of carbonate reservoirs (Bosworth et al.2012; Saoudi et al. 2012; Ward et al. 2012;Delorme et al. 2013); and one naturally fracturedtight-gas sandstone reservoir (Sonntag et al. 2012).

Fractured geological reservoirs, includingdepleted hydrocarbon reservoirs, are also consid-ered as long-term subsurface repositories for stor-ing anthropogenically produced carbon dioxide;this is one measure being contemplated to addressglobal climate change. A key consideration in asses-sing reservoir suitability for storage is the possi-bility of CO2 leakage via fracture networks in thereservoir seal and escape back into the atmosphere.A paper on this topic is included in this volume(Ogata et al. 2012). The study of fractured reser-voirs also has relevance to the problem of construct-ing long-term geological disposal sites for nuclearwaste, where understanding the influence of thefracture networks on fluid flow and migration isimportant in ensuring containment. This volume isprimarily focused on naturally fractured hydro-carbon reservoirs. The important topic of artificialfracturing, also known as hydraulic fracturing or‘fracking’ and which is widely employed in thedevelopment of tight shale oil and gas reservoirs,is not directly addressed here.

Some controls on fracture networks

The flow behaviour of fractured reservoirs is influ-enced by the interaction of a wide range of variables

INTRODUCTION



that are reservoir specific. Mechanical stratigraphyis a major control on the development of fracturenetworks and their influence on fluid flow path-ways (e.g. Hanks et al. 1997; Underwood et al.2003; Cooke et al. 2006; Zahm and Hennings2009; Sonntag et al. 2012; Couples 2013). Mechan-ical stratigraphy partitions stratified rocks intomechanical units based on physical rock propertiesincluding tensile strength and elastic moduli, withYoung’s modulus being particularly important(e.g. Laubach et al. 2009). Differences in the mech-anical behaviour of the rock types in response toregional tectonic loads, and their stratigraphic andspatial arrangement and settings, generate uniquereservoir-specific fracture networks but with manycommonalities. Fractures may be present in a frac-tured reservoir at multiple length scales rangingfrom faults and joints/veins though to microfrac-tures. Complex combinations of these different-scale discontinuities, their orientations, the extentto which they are open and their network connec-tivity will govern the fracture-related fluid flowpathways, making it important to resolve a fracturenetwork at all of these scales. Compaction bands(granulation seams) with lower permeability thanthe host rock matrix can also occur in the samerock volume as high-permeability fractures, andhave a complex combined effect on fluid flow (e.g.Zhou et al. 2013).

Mechanical stratigraphical properties of strati-fied rocks have been shown to influence fracturepropagation, arrest and distribution in response totectonic loading. Important aspects of understand-ing fracture networks, these properties include:mechanical layer thicknesses (e.g. Pollard &Aydin 1988; Wu & Pollard 1995; Bai & Pollard2000; Bai et al. 2000; Schopfer et al. 2011); con-trasts in physical properties at layer interfaces,especial in Young’s modulus (e.g. He & Hutchinson1989; Cooke et al. 2006; Lezin et al. 2009); and thebonded strength of interfaces between mechanicallayers (e.g. Cooke & Underwood 2001; Wang &Xu 2006; Larsen et al. 2010). However, the exist-ence of non-stratal bound fractures (e.g. Odlinget al. 1999; Odonne et al. 2007; Sonntag et al.2012) indicates that other factors are also in play.Mechanical stratigraphy and/or lithofacies cansometimes be used to predict fracture distributionsin the subsurface (e.g. Sonntag et al. 2012).

Reservoir shape evolution, then-current rockproperties and local mechanical state are primarycontrols on the evolution of reservoir fracturenetwork geometries and orientations formed dur-ing tectonic deformation. These factors are some-times described in terms of principal palaeostressdirections and magnitudes (e.g. Haimson & Rud-nicki 2010), where shear and extension fracturesdevelop in regular orientations relative to the

three principal stress directions, s1 (maximum), s2

(intermediate) and s3 (minimum) (Handin 1969).Knowledge of regional or local palaeostress his-tory can therefore be used to assist in characteriz-ing reservoir fracture set orientations, and viceversa. Additional considerations include structuralposition (e.g. proximity to a fault, or whether thelocation is in a high-curvature part of an anticlineor on a planar limb). The observed complexity ofsome fracture patterns (e.g. Stearns 1967) servesas a warning that simple rules about fractures andstress states may not capture the full story aboutfracture development.

The current stress field is widely viewed ashaving a significant control on reservoir fractureapertures. Geomechanical rules-of-thumb that areextensively used in industry to predict fluid flowhave met with some limited success. Commonlyused rules include: (1) fractures aligned parallel tothe present-day maximum principal stress tend tobe open; and (2) changes in pore pressure causechanges in permeability due to resulting changesin effective stress that modify fracture apertures.Couples (2013) argues that the assumptions under-pinning these rules are too simplistic and cannot beapplied in the subsurface, and that they do notaccount for non-linear interactions between fluids,the geomechanics of the fractured systems andthermal changes, potentially significantly limitingtheir usefulness. An alternative hypothesis proposesthat flow performance during fractured reservoirproduction is dominantly dependent on motionsoccurring within the fractured rock mass (Couples2013) (see ‘Numerical geomechanical modelling’below). If these rules are however generalized,then it seems correct to say that the current mechan-ical state of a fractured reservoir has a significantinfluence on fracture network characteristics (aper-ture distributions, connectivity) and thus fluid flow(e.g. Heffer 2012; Couples 2013;).

Diagenetic influences

Diagenesis may also have an important control onthe properties of fracture networks, both at thetime of fracture formation and subsequently. Com-plexity in the fracture network may result fromtemporal modifications in mechanical stratigraphycaused by diagenetic changes occurring betweenmulti-phase fracturing events (Shackleton et al.2005; Laubach et al. 2009). Observed depositionalstratigraphy and bedding/layering may not alwayshave matched extant mechanical stratigraphy. Forexample, pervasive carbonate cementation of abedded carbonate package may homogenize thephysical properties of originally dissimilar bedsmaking a single mechanical unit, although the

G. H. SPENCE ET AL.



original bedding may still be observed (e.g. Larsenet al. 2010). This may lead to inaccuracies whenusing depositional stratigraphy to predict beddingcontrols on fracture networks. A fracture networkis the result of the superimposition of different frac-ture sets that may have formed at different times.Because the mechanical stratigraphy is likely tochange through time as a result of compaction, dia-genesis and tectonism, the mechanical history andfracture network that characterize a particularreservoir will be reservoir specific (e.g. Shackletonet al. 2005; Laubach et al. 2009). For these reasons,extant mechanical stratigraphy and the accumulatedfracture networks should not be uncritically con-flated as being coeval when characterizing fracturedreservoirs (e.g. Shackleton et al. 2005; Laubachet al. 2009). In successions where diagenesis hasplayed a significant role in modifying mechanicalstratigraphy, the use of depositional stratigraphy orextant mechanical stratigraphy to predict subsurfacefractured networks may be misleading.

In addition to influencing the properties of thehost rock, diagenesis can also effect fracture proper-ties by the processes of dissolution along fractures(enhancing fracture permeability) and precipitationof cement in fractures (generally decreasing, andpotentially eliminating, fracture permeability). Inthis way diagenesis can have an important influenceon fluid flow pathways within the fracture network(e.g. Olson et al. 2007; Hooker et al. 2012). In sedi-mentary rocks the entire fracture may be filled withcement (and may be referred to as a vein), totallyeliminating porosity and permeability, or isolatedbridges of cement between the fracture walls maybe precipitated which may impede fluid flow butwhich leaves the fracture with a high degree of por-osity (Laubach 1988; Lander et al. 2002; Laubachet al. 2004a). The precipitation of cement bridgeswithin fractures may also assist in keeping high-porosity fractures open (e.g. Aguilera 1999;Hooker et al. 2012). Diagenetic precipitation ofcement within fractures can occur both duringand/or following fracturing events (e.g. Laubach2003; Laubach et al. 2004a, b).

Fluid flow and fracture–rock

fluid transfer

Rock porosities and permeabilities, capillary press-ures, viscous forces and rock wettability are allimportant variables that need to be consideredwhen predicting fluid movement within the matrixrocks in fractured reservoirs (Bakke & Øren 1997;Lindquist et al. 2000; Vogel & Roth 2001; Arnset al. 2004; Blunt et al. 2013), with a further needto consider the controls on fluid transfer betweenopen fractures and the rock matrix. X-ray

tomography of core plugs can be used to character-ize the 3D shapes and topological connections of thepore networks of matrix rocks (e.g. Jiang et al. 2007;Youssef et al. 2007), and these pore systems can beidealized into networks that allow multi-phase flowproperties to be calculated efficiently (Valvatne &Blunt 2004; Ryazanov et al. 2009; Al-Dhalhi et al.2013). The extension of pore-network models toinclude explicit fractures (Jiang et al. 2012) pro-vides an important step forwards in understandingthe controls on fluid transfer between the rockmatrix and fractures. Heat and mass transfer arealso important processes that need to be considered.In this volume Geiger & Matthai (2012) discusssome of the issues related to numerical modellingand simulation of fluid flow (see ‘Numerical simu-lations of fluid flow’ below).

Characterizing fracture networks

Detecting and characterizing subsurface fracturenetworks in sufficient detail to accurately under-stand their influence on fluid flow is a challengingenterprise; multiple techniques, often in combi-nation, have been brought to bear in an attempt toachieve this (Fig. 1). In situ subsurface characteriz-ation of larger-scale aspects of a fracture networkcan be derived from reflection seismic surveys(examples in this volume include Murray & Mon-tgomery 2012 and Slightam 2012). A varietyof data can be used to investigate seismic- andsubseismic-scale elements of a fracture network.These include borehole data derived from wirelinelogs, especially image logs including FMITM andFMSTM resistivity images (e.g. Bosworth et al.2012; Delorme et al. 2013; Saoudi et al. 2012Ward et al. 2012) and sonic acoustic images (e.g.Prioul & Jocker 2009; Slightam 2012), VSP (verti-cal seismic profile; e.g. Emsley et al. 2007; Sligh-tam 2012), core analysis (e.g. Bosworth et al.2012; Sonntag et al. 2012; Sagi et al. 2013) anddrill cuttings (Ortega & Aguilera 2014). Geologi-cally appropriate outcrop analogues are also fre-quently studied as proxies for subsurface fracturenetworks (e.g. Bosworth et al. 2012; Rotevatn &Bastesen 2012; Slightam 2012; Sonntag et al.2012; Seers & Hodgetts 2013), often in combi-nation with other subsurface geophysical data.Numerical modelling including the finite elementmethod (e.g. Leckenby et al. 2007; Smart et al.2009; Strijker et al. 2013) and the discrete elementmethod (e.g. Camac & Hunt 2009; Abe et al.2013; Virgo et al. 2013; Spence & Finch 2014)can be used to investigate fracturing processes andto simulate the creation of fracture networks fromgeologically realistic mechanical stratigraphies.Data derived from geophysical investigations, the

INTRODUCTION



Fig 1. Illustration of some of the multiple methods that can employed to quantitatively characterize fracture parameters,examples of which can be found in this volume: (a) direct measurements from outcrop analogues (from Sonntag et al.2012); (b) digital outcrop models (DOM) constructed from LIDAR data (from Seers & Hodgetts 2013); (c) resistivityimage logs (FMI); (d) acoustic image logs (UBI); (e) orbital sonic VSP (from Slightam 2012); (f) core slabs (fromBosworth et al. 2012); (g) core rubble (from Sagi et al. 2013); (h) discrete element modelling (DEM) (from Spence &Finch 2014); (i) reflection seismic survey (from Slightam 2012). Characterizing fracture networks at all scales ofresolution requires the integration of multiple methods. When transferring fracture network data to modellers it isimportant that they are aware of the uncertainties in the data due to the different methods used to acquire the data. Seetext for discussion (and papers in this volume for details).

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study of core, the study of outcrop analogues andnumerical modelling may be integrated by employ-ing scaling and statistical techniques to produce thebest possible multiscale picture of the fracture net-work in the reservoir (e.g. Bertotti et al. 2007b;Hall et al. 2007; Prioul & Jocker 2009; Bosworthet al. 2012). Fracture networks characterized usingsubsurface techniques, outcrop analogues and geo-mechanical modelling can be used in both deter-ministic reservoir models and/or in statisticalapproaches in which fracture parameters derivedfrom these multiple methods are used to populatestochastic reservoir models for use in fluid flowsimulations. When transferring fracture networkdata to modellers, it is important that they areaware of the uncertainties in the data resultingfrom the limitations of the different methods thatwere used to acquire it.

Subsurface data acquisition methods

Seismic reflection surveys and borehole

log data

When using 2D or 3D reflection seismic surveysto study fractures and fracture networks, a criticallimiting factor is image resolution. Resolution ofstandard reflection seismic data is typically suita-ble for detecting brittle structures at the scale offaults with a minimum of several metres of displace-ment across them. This leaves considerable uncer-tainty in assessing the possible elements of thefracture network with length scales below this resol-ution, and precludes the direct seismic imaging ofextensional fractures which dominate the fracturenetworks of many fractured reservoirs. Boreholesonic and radial and orbital VSP can be used toassist in resolving elements of fracture networksbelow the scale of traditional seismic reflectionsurveys (e.g. Emsley et al. 2007; Prioul & Jocker2009; Slightam 2012).

Passive microseismic data can be used to imageseismic anisotropy and to estimate fracture charac-teristics (e.g. Wuestefeld et al. 2010; Geiser et al.2012), and amplitude versus offset and azimuthanalysis can also be used to characterize naturallyfractured reservoirs from seismic data (e.g. Hallet al. 2007; Far et al. 2013). Subseismic-scale frac-ture density may also be indirectly predicted basedon seismic-scale fold style and curvature when themechanical properties of the folded lithologies areknown (e.g. Bergbauer et al. 2007; Pearce et al.2011). Empirical geological rules can be used toreduce uncertainty in the seismic interpretations offractures (e.g. Freeman et al. 2010).

Fractures penetrated by boreholes can bedetected in wireline resistivity images such as

FMSw (Formation MicroScanner) and FMIw (Full-bore Formation MicroImager) and in sonic acousticimage logs, allowing the orientation and frequencyof fractures encountered in boreholes to be mea-sured. However, resistivity image logs only recordthat portion of a fracture through which the bore-hole penetrates; they do not directly quantifyfracture lengths, distribution or fracture networkconnectivity in the reservoir. Beyond the usual con-siderations of drilling-induced fracturing (e.g. Fuen-kajorn & Daemen 1992), there is little evidence tosuggest that consideration is given to the possibil-ity that well construction itself has altered thelocal detectability of fractures. Stoneley responsesfrom sonic tools such as the SonicScannerw, atten-uated using the normalized differential energies(NDE) technique, can assist in differentiatingbetween natural fractures and drilling-inducedfractures around the borehole (Brie et al. 1988;Donald & Bratton 2006).

The borehole diameter is typically of the scaleof centimetres, whereas the length of the boreholemay be many hundreds to thousands of metres. Itfollows that fractures in the reservoir aligned paral-lel to the borehole axis will be statistically under-represented relative to those that are inclined tothe borehole axis. A statistical approach is thereforefrequently adopted to upscale and extrapolate bore-hole data to characterize the reservoir away fromthe well. Statistical power-law or fractal character-ization is often employed to calculate fracture par-ameters from borehole data (e.g. Dershowitz et al.1998; Bastesen & Braathen 2010); however, thereare currently few independent means of corroborat-ing the results of this approach. Moreover, dataderived from individual boreholes are only repre-sentative of very limited and localized volumes ofthe reservoir for example, if fractures are clus-tered into corridors (e.g. Questiaux et al. 2009)that a borehole does not intersect. Integrating resis-tivity image logs, VSP and seismic survey datacan assist in identifying fractures that are signifi-cant at the seismic and subseismic scale and, to adegree, extrapolate fracture geometries away fromthe borehole (e.g. Emsley et al. 2007).

Core analysis

A statistical approach can also be applied toextrapolate and upscale fracture data derived fromrock cores for input into reservoir models (e.g. Bas-tesen & Braathen 2010; Sagi et al. 2013). Several ofthe papers in this volume integrate data derived fromcore analysis with other data types (e.g. Bosworthet al. 2012; Slightam 2012; Sonntag et al. 2012;Sagi et al. 2013). Sagi et al. (2013) describe andcompare two independent methods of determiningthe density and connectivity of subseismic-scale

INTRODUCTION



fractures and veins in the Upper Cretaceous–LowerPalaeocene naturally fractured chalk from theSkjold Field in the Danish sector of the North Sea,using cohesive cores and incohesive core rubblefragments. The Skjold Field is a four-way domalclosure positioned above a salt diaper. The twomethods used are: (1) image analysis of slabs fromcohesive core samples; and (2) rubble-sized mea-surements from incohesive samples. Incohesivecore-rubble fragments represent stratigraphic inter-vals with high fracture intensity and so are particu-larly important. Using these methods, Sagi et al.show quantitatively that fracture density and con-nectivity is higher in crestal wells compared towells on the dome rim. This case study illustrateshow quantitative analysis of rubble-ized core sam-ples can assist in constraining fracture density andconnectivity of subseismic-scale elements of frac-ture networks that affect reservoir transmissibility.

Integrated subsurface studies

Ward et al. (2012) highlight the beneficial impactof reprocessing existing seismic data, with anexample from the Machar Oil Field located in theUK sector of the Central North Sea. The MacharField is a complex, naturally fractured, Cretaceous-chalk/Palaeocene-sandstone oil reservoir above atall salt diaper. This field has had a phased devel-opment since 1998. Extensive reprocessing ofreflection seismic survey data from the previouslyundrilled eastern flank, that had previously lackedcoherent reflectivity, supported a geological modelindicating the possibility of an undiscovered reser-voir, thereby reducing the subsurface risk associatedwith the area. Confidence in the reprocessed seismicinterpretation allowed new productive wells to bedrilled opening up a new phase of development forthe Machar Field.

In one of two case studies in this volume on natu-rally fractured crystalline basement reservoirs,Slightam (2012) presents a workflow to investigatethe presence of movable oil in fault zones and uses itto explore a viable target in Lewisian crystallinebasement west of Shetland in the UK sector of theNorth Sea. Before drilling, 3D seismic data, offsetwell data and outcrop analogues were interpretedto initially characterize the fault network in theLewisian basement, and two seismically definedfault zones were targeted as potential reservoirsfor an inclined basement well. Subsequent drillinggenerated extensive suites of log data that havebeen integrated with the 3D seismic data usingleading-edge techniques, increasing the number ofmapped faults and constrained quantitative par-ameters (including fault frequency, orientations,length and rock lithologies) in the model. Frac-tures do not appear to be affected by lithological

variability in the crystalline basement. This work-flow establishes that seismically identified faultzones are viable exploration targets in the LewisanBasement on the UK continental shelf west ofShetland. A similar workflow could be adoptedfor characterizing other faulted crystalline base-ment reservoirs.

In the second case study of a fractured crystal-line basement reservoir presented in this volume,Murray & Montgomery (2012) describe an inte-grated multidisciplinary industry case study of thecharacterization of the naturally fractured BayfootField in the Say’ un Masila Basin in the Republicof Yemen. The fracture network in the Archeancrystalline basement is principally characterizedfrom analysis of extensive resistivity image logdata from ten boreholes, coupled with 3D reflectionseismic data and geomechanical modelling. No cor-relations are identified between fracture networkparameters, including orientations and density, androck lithologies; this possibly indicates that suchrelationships have been overprinted by the com-plex tectonic history. Although prediction of pro-ductivity remains uncertain, the study has led to animproved well planning strategy involving highlydeviated to subhorizontal wells oriented to intersectthe maximum number of productive fractures andthe major seismic-scale fault damage zones achiev-ing the greatest production.

Saoudi et al. (2012) also present an industrycase study of the impact of fractures on the increasein water cut during production from a Miocenesyn-rift dual-porosity fractured dolomite reservoirin the Issaran Field in the Gulf of Suez, Egypt, andthe measures taken to address this problem. Anintegrated approach used image resistivity and wire-line logs from a large number of wells, alongsidepetrographically determined diagenetic history and3D seismic data to characterize fracture stratigra-phy, sets and densities. Mechanical stratigraphy isshown to have been a major control on the frac-ture densities. Drilling-induced fractures and bore-hole breakouts identified in resistivity images wereused to determine present-day stress state in thereservoir, which is used to infer the orientation ofthe fractures most likely to be open. Wellhead temp-erature, oil production, steam injection and waterproduction data from a large number of wells werealso used to characterize fracture connectivity andfluid flow. This allowed remedial measures to bedesigned that resulted in a substantial decrease inwater cut.

Outcrop analogues

Geologically appropriate outcrops have beenwidely used as analogues for subsurface fractured

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reservoirs. Outcrop analogues have been used toinvestigate both fundamental controls on fracturingand to assist in characterizing fracture networks inthe target subsurface fractured reservoir (e.g. Bos-worth et al. 2012; Rotevatn & Bastesen 2012;Sonntag et al. 2012) and to construct deterministic(e.g. Wilson et al. 2011; Geiger & Matthai 2012)and stochastic (e.g. Seers & Hodgetts 2013)models. When using fractured outcrop analogues,important considerations are: (1) the influence ofweathering and erosion on how well the originalfracture network and depositional stratigraphy ispreserved in the outcrop; (2) methods that capturequantitative fracture and stratigraphic data fromthe outcrop with the highest resolution and accuracyto minimize sample bias; and (3) the degree towhich the outcrop fracture network is representativeof the subsurface reservoir.

Outcrop analogues provide 2D samples of frac-ture networks in either stratigraphic or bed-parallelorientations. Such analogues can yield both strati-graphic information from sedimentary logging andstatistical spatial data on fracture densities, orien-tations, heights (trace length) and distributions usingstandard structural geology techniques for scan-lines, sampling windows and trace maps (e.g. LaPointe & Hudson 1985; Dershowitz & Herda1992; Priest 2004). Several forms of bias mayaffect fracture data collection using these techniques(e.g. discussed in Sturzenegger et al. 2011), and stat-istical sampling approaches – such as using circularsampling windows (Zhang & Einstein 1998;Mauldon et al. 2001) and semi-trace length sam-pling along scan lines (Priest 2004) – have beendeveloped to minimize them.

Manual data collection may also introducesampling bias however, as only those parts of theoutcrop that are physically accessible can be quanti-tatively examined. To overcome this limitationfracture networks from outcrops have also beencharacterized by: using photogeology, althoughthis generates inaccuracies by projecting 3D struc-tural features onto a 2D image; using a hybrid ofphotographs placed in a digital GIS (GeographicInformation System) environment integrated withstructural and stratigraphic data measured manuallyfrom the outcrop (Bertotti et al. 2007a, Boroet al. 2013; Hardebol & Bertotti 2013); and gather-ing data remotely from outcrop surfaces that have3D topography using photogrammetry (e.g. Voyatet al. 2006) and laser scanning techniques (e.g.Wilson et al. 2011; Seers & Hodgetts 2013 togenerate 3D digital outcrop models of the exposure(see ‘Digital outcrop models’ below).

The exactness with which data from outcropanalogue fracture networks can be extrapolatedto subsurface reservoirs is subject to limitations.Exhumation of fractured outcrops causes them to

have experienced a different loading/unloadinghistory relative to that of the fractured reservoir,for example, uncemented joints form at shallowburial depths and are therefore unlikely to be signifi-cant in relation to natural fractured hydrocar-bon reservoirs (Nelson 2001; Sanders et al. 2003;Hooker & Laubach 2013). It is therefore necessaryto filter out such fractures when extrapolating out-crop data to the subsurface.

Hencher (2013) questions the standards forcharacterizing discontinuities and fractures in out-crops and core, and argues that existing defini-tions are too broad to sufficiently characterize thevariety of geological features observed betweenincipient rock traces through to open fractures.This is illustrated using a wide range of outcropexamples. Hencher proposes that fractures developfrom micro-cracks to full-scale mechanical dis-continuities though time in response to changes instress and environmental conditions, and that theterminology for discontinuities needs to adequatelydifferentiate between these different developmentalstages. To address these concerns, Hencher pro-poses incorporating relative tensile strength of thediscontinuity compared to that of the host rock todifferentiate between discontinuities. Hencheremphasizes that tectonics, unloading and weather-ing may all play roles in the development andweakening along discontinuities/fractures. Oneconsequence of the concept of dynamic discontinu-ity development proposed by Hencher is that usingcurrent classification standards to describe dis-continuities in the outcrop may not be representativeof the discontinuities in the subsurface. Hencherillustrates how both fracture frequency and extentin an outcrop can vary depending on the level ofweathering and erosion it has experienced.

As mentioned above, potential diagenetic alter-ation of mechanical stratigraphy may also haveinfluenced the formation of the extant fracturenetwork. Uncritically referencing fracture networksto depositional stratigraphy in outcrop and thenextrapolating this to make subsurface predictionsmay therefore be misleading.

Integrated outcrop studies

In this volume Sonntag et al. (2012) investigatesedimentation controls on the fracture network ofa naturally fractured tight-gas sandstone reservoirin the Mesaverde Group, Uinta Basin, Utah, USAwhich is currently in production. This integratedstudy uses data derived from pavement outcrops,resistivity image and well logs, well core, thin-section petrography and microstructural analysis.Fracture character and distribution in the MesaverdeGroup are shown to be controlled by a hierar-chy of sedimentary and diagenetic characteristics.

INTRODUCTION



First-order sedimentary characteristics that directlyinfluence the fracture network are identified as sand-stone bed thickness and bed geometries. Second-order controls, which are only developed whenall other variables remain constant, include thedegree and type of cementation. The results of thisstudy allow prediction of subsurface natural fracturedensity based on the depositional environment ofthe sandstone body (lithofacies). Outcrop and sub-surface data show that higher fracture densitiesoccur in well-cemented discontinuous channel sandbodies deposited in meandering river environments,making these the best reservoir targets. Sonntaget al. propose that, in the Mesaverde Group, morehighly fractured well-cemented lithologies may beidentified in the subsurface by low sonic well logtransit times.

Rotevatn & Bastesen (2012) present a detailedstructural field study of Eocene carbonates of theSuez Rift exposed in west-central Sinai in orderto investigate the influence of fault linkage anddamage zone architecture on permeability alongsegmented normal faults. From structural obser-vations the authors are able to predict that, alongsegmented normal faults, fault linkage zones in car-bonate rocks with systematically increased cross-and along- fault permeability will occur. Faultlinkage zones may increase fluid flow both acrossfaults and also vertically within fault zones. Theresults of this field study may be extrapolated tofault linkage and damage zones and fracture net-works associated with seismically imaged segmen-ted normal faults in carbonate reservoirs to bettercharacterize their influence on fluid flow.

Bosworth et al. (2012) present an industrialcase study of the investigation and well testing ofthe low-porosity naturally fractured Eocene lime-stones in the Darat and Thebes formations at theEast Budran concession, Gulf of Suez, Egypt. Datafrom naturally fractured outcrop analogues, exposedin the west-central Sinai desert, are integrated withborehole image and core data to define the orien-tations of major fracture sets. Borehole breakoutdata and drill-induced fractures are used to identifyminimum horizontal stress directions to predictthe orientation of fractures likely to exhibit the larg-est open apertures in the subsurface. The structuralframework was used to optimize well placement,and a near-horizontal test well drilled to intersectthe highest number of potentially open fractures pro-duced a flow rate of 19,000 barrels of oil a day.

Digital outcrop models

Laser scanning

A potentially transformative advance in the studyof fractured outcrop analogues is the use of

close-range terrestrial laser scanning to generatedigital outcrop models from which quantitativestratigraphic and structural spatial data can thenbe extracted (e.g. Buckley et al. 2008; Sturzenegger& Stead 2009a, b; Wilson et al. 2011; Seers &Hodgetts 2013). Remote laser scanning of outcropsusing terrestrial LIDAR (light detection andranging) generates point clouds with x, y, z coordi-nates. Point clouds can be processed to generate tri-angulated meshes (also referred to as triangulatedirregular network or TIN) of the scanned surface(e.g. Buckley et al. 2008; Seers & Hodgetts2013). Differential GPS information for each pos-ition of the scanner is used to georeference theLIDAR data to global co-ordinates that can beused to integrate scans made from multiple scanpositions and with other types of geospatially refer-enced data and images. Calibrated digital photo-graphic images gathered at the same time as laserscanning are used to assign a true colour to eachpoint in the point cloud, and/or the photographicimages may be merged with the triangulatedmesh to generate photorealistic digital outcropmodels (e.g. Buckley et al. 2008; Gillespie et al.2011). Quantitative spatial data can be manuallypicked from fracture traces and planes observedeither in the digital point cloud, the triangulatedmesh and/or the photorealistic model (e.g. Sturtze-negger & Stead 2009a, b; Hodgetts 2013). The verylarge size of discontinuity datasets generatedfrom digital outcrop models means that manualdata picking is very time consuming; softwaremethods for semi- and automatic picking of frac-tures are therefore being developed (e.g. Latoet al. 2009; Gillespie et al. 2011; Wilson et al.2011). The emerging application of remote hyper-spectral imaging (to map mineral distribution oninaccessible outcrop surfaces) may be combinedwith LIDAR datasets as one means of includingcompositional lithological information (e.g. dolo-mite v. limestone) in digital outcrop models (e.g.Kurtz et al. 2011; Buckley et al. 2013). Visualiza-tion of mineral composition can be made usingfalse-colouring in a digital outcrop model to assistthe interpretations of lithological controls on frac-ture networks. Terrestrial LIDAR has also beenused to determine other fracture parameters, suchas directional joint dilation angle values (naturalroughness of the joint surface) (Mansfield &Kemeny 2009).

The surface topography of an outcrop mayobscure the view from a single scan position, poten-tially introducing interpretation bias. Integrationof multiple laser scans from different scanning pos-itions produces a more complete 3D surface datasetand reduces this effect (e.g. Lato et al. 2010).Remote laser scanning using multiple scanningpositions can capture most of an outcrop in 3D.

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This reduces subjective bias in the positioning ofscan-lines/sample windows and allows very large,statistically significant fracture datasets (includ-ing fracture heights, orientations, spacing, layer/bed thicknesses and stratigraphic data) to be har-vested and interpreted from digital outcrop mod-els (e.g. Strouth & Eberhardt 2006; Olariu et al.2008; Lato et al. 2009, 2010; Mansfield & Kemeny2009; Sturzenegger & Stead 2009a, b; Spenceet al. 2010; Garcıa-selles et al. 2011; Gillespieet al. 2011; Pearce et al. 2011; Sturzenegger et al.2011; Wilson et al. 2011; Hodgetts 2013; Seers &Hodgetts 2013).

Although digital models can capture most of anoutcrop, weathering, erosion and vegetation on theoutcrop surface and fracture attenuation due tooutcrop surface topography and at the edge of theoutcrop may mean that data gathered from thewhole outcrop is not all suitable for inclusion infracture analysis. Digital outcrop models allowobjective choices to be made on where to harvestdata by taking these factors into account. Digitaloutcrop models allow topographic sampling win-dows that are unrestricted by the need for physicalaccess to be used for quantitative discontinuitymapping (e.g. Sturzenegger et al. 2011).

As with all remote sensing techniques, theresolution and accuracy with which laser scanningcaptures the outcrop needs to be critically assessedwhen using the acquired dataset to characterizefractured reservoir models. Different data proces-sing software for LIDAR may produce differentresults and limit the size of point clouds that canbe processed (e.g. Varela-Gonzalez et al. 2013).Moreover, narrow fractures can be very difficult todetect in digital outcrop models (especially whenviewed only as true-colour point clouds or trian-gulated meshes); when the fracture plane is notexposed and the fracture trace is present on a flatrock surface of uniform colour and/or where frac-ture density is high (i.e. when fractures are closelyspaced). This can potentially lead to some biasin the data (e.g. Sturzenegger et al. 2011). Thismeans that, in the same way that seismic surveysmay omit smaller-scale elements from the fracturenetwork, digital outcrop models may not image allfracture traces and fracture planes present on theoutcrop in sufficient detail for them to be picked.The degree to which this may occur for typicalLIDAR resolutions and point cloud size dependson the choice of data processing software used andthe magnitude of the surface topography andcolour variations in the outcrop.

Fracture data from LIDAR surveys of outcropshave been used to construct discrete fracture net-works used in flow models (e.g. Wilson et al.2011; Seers & Hodgetts 2013). Seer and Hodgettsassess the effect of uncertainty attributable to using

LIDAR to characterize fracture networks fromreservoir analogues that are used to model fluid flow.Fracture statistics collected in abandoned mine tun-nels using laser scanning are compared to a corre-sponding dataset collected using traditional fracturesurvey methods to characterize Triassic, naturallyfractured, reservoir analogues in the Helby Forma-tion Sandstone in England. Comparison of thesetwo datasets identifies an under-representation infracture size and fracture density parameters in theLIDAR-derived dataset in comparison to manuallyderived data, resulting in an underestimate of theupscaled modelled flow capacity of the fracture net-work. This study strikes a cautionary note about thepossibility of LIDAR introducing bias into fracturedatasets. In Seers and Hodgetts’s study, fracturedensities were not especially high; it may be thatwhen using LIDAR to characterize more denselyfractured rocks this bias effect might be morepronounced.

Digital outcrop models constructed from LIDARdata offer great potential for characterizing frac-ture networks from outcrops. However, the differ-ences revealed in comparisons between manualfield based and LIDAR derived fracture data sets(e.g. Sturzenegger et al. 2011; Seers & Hodgetts2014), indicate that there are limitations in thisapproach and that more work is required beforethis potential is fully realized. However, the criticaluse of digital outcrop models offers several signifi-cant advantages for studying fractured networks inoutcrop analogues over conventional field-basedstudies. Manual ‘ground truth’ data is currentlydesirable in order to constrain potential bias thatmight arise during the acquisition of the LIDAR-derived data. Using laser scanning and digitalmodels to study fracture networks remains rela-tively new, but is an area of intense research activityand will become increasingly important. Areas forfuture development and investigation includeimproving the resolution of digital outcrop modelsto capture smaller-scale surface detail to ensureall discontinuities are detected. This will requirelarger point clouds and advances in both hardwareand software (necessary to gather, process andmanipulate this increase in size) and the develop-ment of new discontinuity sampling techniquesand statistical approaches that fully exploit thebenefits of the 3D topographic outcrop surfaces inthese models.

Photogrammetry

Another method for producing digital outcropmodels from which discontinuity data can beextracted is the use of photogrammetry (e.g. Voyatet al. 2005; Sturzenegger et al. 2011). Photogram-metry can deliver 3D coordinates of features by

INTRODUCTION



incorporating multiple 2D photographic imagestaken from different aspects. Several softwarepackages exist for this purpose (e.g. Favalli et al.2012). The accuracy of discontinuity data extractedfrom digital models generated using photogram-metry depends on several factors (e.g. discussed inVoyat et al. 2005). For example, unlike LIDAR,photogrammetry does not make direct primarymeasurements from the outcrop surface duringdata collection, but rather from the scaling ofthe 3D digital outcrop model generated from thephotographic images; and so may be slightly lessaccurate by comparison. However, the compactsize of hardware used for photogrammetry (thesize of a high-quality digital camera) raises thepotential for it being mounted onto a relatively inex-pensive remote-controlled unmanned aerial vehicle(UAV) allowing for more complete coverage ofthe outcrop surface. For example, a UAV photo-graphic survey can capture data from above rockoverhangs and other surface topography on a cliffface which can obscure parts of the outcropsurface from a ground-based LIDAR scanner.

Geomechanical considerations

Simulating creation of fracture

networks

Geomechanical studies seek to understand how rockmaterials respond within a context that includesconsiderations of material properties and loadingarrangements (Couples 2005). Relative to frac-tured reservoirs, this approach can be used to gainunderstanding of how the characteristics of frac-ture systems – which are an expression of defor-mation – may depend upon circumstances andconditions (e.g. components, material properties,loading arrangements and interactions) that existedat the time of fracture formation. This understand-ing can provide knowledge to assist in predictingfracture distributions in subsurface volumes wheredirect fracture data cannot be obtained. Althoughgeomechanical reasoning can be applied in simple,idealized situations – for example, where a modelis assumed in which fractures initiate or grow withina rock layer that is bounded above and below bylayers with differing material properties (McDer-mott et al. 2013) – this sort of analysis cannotbe reliably transferred to the circumstances of awhole-reservoir example, where the spatial andtemporal evolution of mechanical state of thereservoir cannot be usefully assessed by conjecture.

To overcome this limitation, geomechanicalsimulations can be used to represent deformationin whole systems of rocks subjected to trap-formingdeformation processes. Geomechanical ideas are

expressed in terms of constitutive relationships,defining parameter dependencies between stressesand strains plus possibly other factors such astemperatures and strain rates. Constitutive relation-ships are used within simulation software tools tocalculate the response of a whole model system touser-assigned boundary loads and other controls.Both continuum (e.g. Leckenby et al. 2007; Smartet al. 2009; Segura et al. 2011; Strijker et al.2013) and discontinuum approaches (e.g. Hardy &Finch 2007; Camac & Hunt 2009; Abe et al. 2013;Spence & Finch 2013, 2014; Virgo et al. 2013)can be used. Both calculate an output that isexpressed in terms of stresses/strains (continuum)or forces/displacements (discontinuum). Conti-nuum methods can examine whole-reservoir defor-mations, while discontinuum approaches are moresuited to local investigations. The continuumoutputs must be interpreted and extrapolated todown-scale the strains into plausible fracture pat-terns, but the discontinuum outputs may be able torepresent fracturing processes in an almost directway (depending on the length scale of the discreteelements). Combined continuum/discontinuumapproaches show some promise for capturing theresponses at the intermediate length scale (e.g.Grasselli et al. 2014).

Each of these methods involves the division ofa selected physical region (in 2D or 3D) into alarge number of individual elements. In continuumapproaches, the element boundaries are virtual andsimply represent arbitrary divisions of the spaceinto convenient mathematical entities necessaryfor the formulation of the equations. In contrast,in discontinuum methods the element boundariesof the ‘particles’ are conceptually related to phys-ically realistic particle interactions such as inter-particle sliding or the breakage of inter-particlebonds. In discrete element approaches, the particlescan have a one-to-one relationship with real ele-ments of the system such as grains, or the discreteelements can be much larger; in the latter case theinteractions between particles are less directlylinked to fundamental physics. In discrete elementmethods, the rock mass is treated as an assemblageof circular (in 2D models) or spherical (in 3Dmodels) elements that interact in pairs that undergomotion relative to one another as if connected bybreakable elastic springs. By modifying the assignedcharacteristics of the springs, different rock proper-ties such as rock stiffness can be approximated. Theconsequences of these parameters can then be testedusing an appropriate loading arrangement (e.g.Hardy & Finch 2007).

Spence & Finch (2014) use discrete elementmodels to investigate the effects of mechanicalheterogeneity at layer interfaces, caused by thepresence of stratified chert nodules, on the

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development of fracture networks within carbonatesedimentary cycles. Geologically appropriate,layered mechanical stratigraphies are used to sim-ulate shallow-water sequence-stratigraphic para-sequence sets (and physically uniform successionsto take into account possible diagenetic homo-genization of layers), both with and without chertbeing present at layer interfaces. The differentmechanical stratigraphies tested generate distinctpatterns of broken bonds and openings (strain),which can be used to predict real-world fracturingin the subsurface with a sequence stratigraphicframework. The simulation outcomes are used togenerate 2D fracture maps from which quantitat-ive fracture indices (in the sense of Dershowitz& Herda 1992) are calculated, leading to the for-mulation of sequence-stratigraphic rules for pre-dicting the influence of nodular chert-rhythmiteson fracture networks in shallow-water carbonatesedimentary cycles.

Given the challenges of quantitatively character-izing fracture networks from subsurface and outcropdata, it is predicted that the use of geomechani-cal simulations, based on geologically appropriateapproaches, will serve to underpin efforts to under-stand or create discrete fracture network models,which can then be incorporated into reservoir flowsimulations (Gonzalez et al. 2014). The rapid andcontinuing advances in relatively inexpensive com-puter power will make this approach more practicaland less specialized.

Numerical geomechanical modelling

Flow rates from fractured reservoirs are related inlarge part to the real-time geomechanical behaviourof the reservoir, including how fracture-boundedblocks interact with natural loads, thermal altera-tions and production-induced changes in fluid ener-gies. Couples (2013) critically examines some ofthe geomechanical rules-of-thumb about fractureapertures that are widely used in industry to pre-dict fluid flow, but which have met with only alimited amount of success. These rules are basedon the assumptions that: (1) alterations of effectivestress are directly related to pore pressure changes;and (2) changes in fracture apertures are the resultof stress changes. Couples uses both simple reason-ing and numerical models to challenge the validityof these underpinning assumptions. The numericalsimulations presented demonstrate the occurrenceof strong non-linear dynamic interactions betweenfluids, the geomechanics of the fractured blockysystems and thermal changes, which cause temporaland spatial variations in the effective flow propertiesof the rock mass. Couples argues that flow perform-ance discrepancies during production from frac-tured reservoirs are dominantly a consequence of

motion occurring within the fractured rock mass,and that this alternative analysis could lead to animprovement in the reliability of predicting fluidflow in fractured hydrocarbon reservoirs.

Heffer (2012) uses numerical modelling to ex-amine several potential geomechanical mechanismsto account for inferred changes in hydraulic conduc-tivity of faults and fractures in reservoirs resultingfrom production operations, where these effectsare recorded by correlated changes in flow at pro-duction and injection wells. In his study, statisticalcorrelations in flow-rate observations betweenwells with very large separation distances in theNorth Sea seem to be related to both stress andfaults. Of the four geomechanical mechanisms con-sidered to explain long-range stress- and fault-related characteristics of statistical correlations inflow rates between wells, Heffer concludes thatthe dilation or compaction of aligned (micro-) frac-tures is the most credible.

Igneous sills can form hydrocarbon reservoirsin sedimentary basins and can also act as potentialreservoir seals. Gudmundsson & Løtveit (2012)describe examples of sills and, to a lesser extent,dykes and numerically model stresses generatedby these igneous intrusions in an attempt to char-acterize potential fractured reservoirs createdboth within and around sills. Their study examinesthe roles of the lateral dimension and the length/thickness ratios of these intrusions on their fracturepotential.

Numerical simulations of fluid flow

Geiger & Matthai (2012) review and discuss recentadvances in single- and multi-phase flow using dis-crete fracture and rock matrix simulations (DFM).DFM takes into account the flow effects of bothinterconnected fractures and the rock matrix usinga mixed finite element (FE) and finite volume(FV) numerical approach. Geiger & Matthai pre-sent arguments as to why mixed methods withunstructured grids are more appropriate than stan-dard reservoir simulation methods for calculatingsingle- and multi-phase flow processes. Usingoutcrop analogues, they show how the DFMnumerical method can preserve the complex struc-tures seen in fractured outcrops without the needto simplify them and thus lose some of theirimpact. The DFM methodology is demonstratedfor 2D simulations using fractured limestone out-crop analogues from the Bristol Channel coast inSomerset, England and key issues relating to fluidflow, heat transfer, mass transport and multi-phaseflow are discussed. These authors also discussfuture challenges in the development of DFM simu-lations including 3D simulations, estimating theextent of fractures in the third dimension from

INTRODUCTION



essentially 2D outcrop data, determining accu-rate fracture apertures, addressing the additionalcomputational complexity of 3D compared to2D simulations and up-scaling from outcrop toreservoir scale.

DFM is potentially a powerful tool for investi-gating fluid flow. However, a prerequisite for thisapproach is the reliance on very high-quality inputmodels, usually based on outcrop. The creation ofsuch high-quality outcrop models is a sub-disciplinein itself, with many technical challenges of itsown. As discussed earlier in ‘Digital outcrop mod-els’, even the highest-quality digital outcropmodels from laser scanning are currently subjectto sampling bias. Moreover, there remains the ques-tion as to what degree an outcrop analogue is repre-sentative of the subsurface reservoir. Criticalassessment of elements of the fracture network inoutcrop, such as near-surface features that are notrelevant to subsurface reservoirs, need to be ident-ified and filtered out prior to DFM analysis. Allthe potential bias resulting from outcrop char-acterization will be carried forwards into DFMsimulation.

Zhou et al. (2013) use 2D and 3D numericalmodelling to examine the effects on fluid flowcaused by the intersection of compaction bands(granulation seams) with joints and faults in aporous sandstone host rock. In the porous JurassicAeolian Aztec sandstones exposed in Nevada,USA, compaction bands with permeability lowerthan the host rock and joints and faults with per-meability higher than the host rock occur together.A series of 2D and 3D permeability up-scaling andwater flood simulations are used to quantitativelyinvestigate the influence on fluid flow of differentconfigurations and combinations of compactionbands, joints and faults. Among other findings fromthese numerical experiments, Zhou et al. (2013)demonstrate that the direction of flow relative tothe orientation of intersecting compaction bandsand other structures can affect the efficiency ofoil recovery. Their results emphasize the impor-tance of taking into account the presence of com-paction bands in flow simulations of fracturedreservoirs.

Statistical methods integrating production

data

Iterative statistical history matching of produc-tion and well test behaviours can be used to decreaseuncertainty in future reservoir development.Delorme et al. (2013) present an industrial casestudy from a Cretaceous naturally fractured carbon-ate reservoir in the Campos basin, offshore Brazil,which describes a statistical methodology andworkflow to improve the initial fractured reservoir

model by integrating hydrodynamic informationfrom actual production and well test data. Thisdynamic data was used to determine fracture proper-ties and identify previously undetected structuralfeatures in the original model by calibrating thefluid flow or reservoir pressure measured at wells.This iterative methodology established the exist-ence of compartmentalization within the reservoirand has assisted in constraining uncertainty in pro-duction forecasts.

Fractured reservoirs and carbon

dioxide storage

An emerging topic in the study of fractured reser-voirs is their evaluation and utilization as potentiallong-term storage sites for sequestering carbondioxide (e.g. Dockrill & Shipton 2010; Idlinget al. 2011; Ogata et al. 2012; Senger et al. 2011,2013; Bao et al. 2013; Jordan et al. 2013). Thisis referred to as CO2 capture and storage or CCS.Deep geological reservoirs, including depletedhydrocarbon reservoirs, may provide long-termstorage repositories for anthropogenic CO2. One ofthe appeals of using depleted hydrocarbon reser-voirs is that they have already demonstrated theirlong-term reservoir potential over a geological timescale. They also have the advantage of having alarge wealth of legacy geological data available.Moreover, some of the existing hydrocarbon indus-try infrastructure such as offshore platforms, pipe-lines and wells could be converted for thispurpose. However, hydrocarbon extraction andreservoir development, and CO2 injection, may allmodify reservoir characteristics and behaviour.The crucial consideration in the long-term storageof CO2 in geological reservoirs is establishing thatCO2 will not leak though the fracture network tothe atmosphere in examples where the reservoirfracture system also affects the cap rock or seals.

Other important factors relating to successfulsequestration include determining the CO2 storagecapacity of the reservoir and establishing the diffi-culties linked to injection. Both these factors aredetermined by the nature of the fracture networkand injection-time geomechanical behaviour. WhenCO2 is injected into a reservoir, the fracture networkmay influence pressure evolution within the reser-voir and the distribution pattern of the CO2 plume(e.g. Idling et al. 2011). To address these issues itis essential to characterize the fracture networkand determine its interaction with the plume. Allthe proceeding techniques discussed above can beemployed. To help assess the risk of leakage, faultpopulation statistics can be used to calculate theprobabilities of the CO2 plume encountering faultsalong which leakage might occur though the seal

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at different distances from the injection well (Jordanet al. 2013). If fluid pressure is too high during CO2

injection, it may engender stresses that reactivateexisting faults and create new fractures. This maycompromise the integrity of the seal and/ormodify reservoir porosity and permeability. Toaddress this, numerical modelling including sensi-tivity analysis (how uncertainty in the output ofnumerical models can be assigned to differentsources of uncertainty in its inputs) can be usedto characterize geomechanical responses to CO2

injection (e.g. Farokhpoor et al. 2010, 2011; Baoet al. 2013). Potential chemical reactions betweenthe injected CO2 and the existing pore fluid andreservoir host and cap rocks may also increaseporosity though dissolution and/or decrease poros-ity though calcite precipitation (e.g. Gherardiet al. 2007).

Ogata et al. (2012) describe the LongyearbyenCO2 laboratory project (LYB CO2 lab) locatedin Spitsbergen, Arctic Norway, which is beingused to test the feasibility of injecting CO2 into aTriassic – Jurassic naturally fractured, tight clasticreservoir containing dolerite intrusions (Kapp Tos-canna Group; e.g. Farokhpoor et al. 2010, 2011;Senger et al. 2011, 2013). Ogata et al. (2012) inves-tigate the influence of different litho-structuraldomains on fluid pathways in this heterolithic reser-voir, characterized from detailed study of boreholeand outcrop data. The differential pressure in theoverburden and the targeted reservoir suggest aneffective cap rock seal. The storage potential ofthis tight reservoir is dependent on the fracturelengths, apertures and connectivity of the fracturenetwork, with dynamic interaction between the frac-ture network and the host rock causing additionaluncertainty. This investigation is ongoing but ifthis tight, naturally fractured reservoir proves to bea suitable repository, it may initially be used as atest site for storing CO2 generated by a coal-powered station located 5 km from the proposedinjection site.

An example of one of the larger-scale currentlyactive industrial projects for geological storage ofCO2 is the In Salah Gas Development, KrechbaField in Algeria where, since 2005, CO2 has beenstripped from natural gas production in the In Salahfield and then re-injected into the gas-producingnaturally fractured Krechba field 4 km away (Idlinget al. 2011). Former hydrocarbon reservoirs in theNorth Sea have also been proposed as potentiallong-term CO2 storage sites.

Concluding remarks

A substantial percentage of the world’s remain-ing hydrocarbon resources occur in naturally

fractured reservoirs. Naturally fractured hydro-carbon reservoirs display complex production be-haviour. The principal objective of the appliedstudy of such reservoirs is to better understand thefluid flow within them and use this information tomost efficiently manage reservoir development inorder to maximize recovery. Achieving this goal isa multi-component process involving the character-ization of the stratigraphy, the fracture networkand matrix, the structural setting, physics of fluidflow, numerical simulations of fluid flow and,during development, iteratively analysing pro-duction behaviour data. Each of these steps maybe achieved using several different analyticalmethods or combinations of multiple techniquesthat involve different expertise (e.g. fracture net-works can be characterized using subsurface geo-physics, borehole data, outcrop analogues andgeomechanical and numerical simulations; Fig. 1).Moreover, the different stages in studying natu-rally fractured reservoirs may involve widely dis-parate skills sets. To exchange knowledge anddata between different sub-disciplines, someshared understanding of the analytical methodsand quality of the data is required. It is thereforeimportant to adopt an integrated interdisciplinaryapproach to the study of fractured reservoirs, sothat the value and limitations of the interpreta-tions and data generated by different sub-disciplinescan be critically combined to produce the best poss-ible reservoir models. The accuracy of numericalflow models is dependent on the quality of thedata derived from other sub-disciplines to character-ize the reservoirs properties and the fracturenetwork, as much as the numerical techniquesused to calculate the flow processes. The papers inthis volume reflect both the technical advances inthe applied study of fractured reservoirs and thebroad collaborative interdisciplinary nature ofthis topic.

The current boom of unconventional hydrocar-bons is providing a large amount of data concerningnatural fracture networks. Apart from standardapproaches such as seismic and borehole imagery,the number of high-quality micro-seismic surveyswith detailed in situ stress measurements shouldprovide key insight into the dynamic response offracture network to pressure variations as well asnew tools to characterize fracture connectivity inthe subsurface in the coming years. Finally, thestudy of fractured hydrocarbon reservoirs also hasrelevance for the use of geological reservoirs aslong-term repositories for carbon dioxide and,although not included in this volume, the construc-tion of long-term subsurface disposal sites fornuclear waste where fracture networks needed tobe assessed to ensure leakage back to the biospheredoes not occur.

INTRODUCTION



We thank A. Hill, T. Gregg and the staff of the GeologicalSociety Publishing House for their assistance in producingthis volume and R. Law for reviewing this manuscript. Thespringboard for the volume was the NARG workshop on‘Naturally Fractured Hydrocarbon Reservoirs: OutcropAnalogues, Subsurface Studies and Case Histories’ con-vened by G. H. Spence and J. Redfern at ManchesterUniversity in January 2011, and they acknowledgeNARG funding. Over 80 delegates from industry and aca-demia attended the 2 days of presentations. The volumeeditors would like to thank all the manuscript contributorsand reviewers for their time and effort. Guy thanks Joanand Malcolm Spence for getting him started, and Aliceand Emmy for keeping him going.

References

Abe, S., Urai, J. L. & Kettermann, M. 2013. Fracturepatterns in nonplane boudinage- insights from 3D dis-crete element studies. Journal of GeophysicalResearch: Solid Earth, 118, 1304–1315.

Agosta, F. & Tondi, E. (eds) 2010. Faulting andfracturing of carbonate rocks: New insights into defor-mation mechanism, petrophysics and fluid flow pro-perties. Special Issue. Journal of Structural Geology,32, 1185–1402.

Aguilera, R. 1980. Naturally Fractured Reservoirs. 1stedn. Pennwell Publishing Company, Tulsa, Oklahoma,USA.

Aguilera, R. 1995. Naturally Fractured Reservoirs. 2ndedn. Pennwell Publishing Company, Tulsa, Oklahoma,USA.

Aguilera, R. 1999. Recovery factors and reserves in natu-rally fractured reservoirs. Journal of Canadian Pet-roleum Technology, 38, 15–18.

Al-Dhahli, A. R. S., Van Dijke, R. & Geiger-

Boschung, S. 2013. Accurate modelling of pore-scalefilms and layers for three-phase flow processes inclastic and carbonate rocks with arbitrary wettability.Transport in Porous Media, 98, 259–286.

Ameen, M. S. (ed.) 1995. Fractography: Fracture Topo-graphy as a Tool in Fracture Mechanics and StressAnalysis. Geological Society, London, Special Publi-cations, 92.

Ameen, M. S. (ed.) 2003. Fracture and In-situ StressCharacterization of Hydrocarbon Reservoirs. Geo-logical Society, London, Special Publications, 209.

Arns, J.-Y., Robins, V., Sheppard, A. P., Sok, R. M.,Pinczewski, W. V. & Knacksted, M. A. 2004.Effect of network topology on relative permeability.Transport in Porous Media, 55, 21–46.

Bai, T. & Pollard, D. D. 2000. Fractured spacing inlayered rocks: a new explanation. Journal of StructuralGeology, 22, 43–57.

Bai, T., Pollard, D. D. & Gao, H. 2000. Explanation forfracture spacing in layered materials. Nature, 403,753–756.

Bakke, S. & Øren, P. E. 1997. 3D pore-scale modeling ofsandstone and flow simulations in pore networks. SPEJournal, 2, 136.

Bao, J., Xu, Z., Lin, G. & Fang, Y. 2013. Evaluating theimpact of aquifer layer properties on geomechanical

response during CO2 geological sequestration. Com-puters and Geoscience, 54, 28–37.

Bastesen, E. & Braathen, A. 2010. Extensional faultsin fine grained carbonates – analysis of fault corelithology and thickness-displacement relationships.Journal of Structural Geology, 32, 1609–1628.

Bergbauer, S. 2007. Testing the predictive capabilityof curvature analyses. In: Jolley, S. J., Barr, D.,Walsh, J. J. & Knipe, R. J. (eds) Structurally Com-plex Reservoirs. Geological Society, London, SpecialPublications, 292, 185–202.

Bertotti, G., Hardebol, N., Taal-Van Koppen, J. &Luthi, S. 2007a. Towards a quantitative definitionof mechanical units: new techniques and results froman outcropping deep water succession. AmericanAssociation of Petroleum Geologists Bulletin, 91,1085–1098.

Bertotti, G., Taal-Van Koppen, J., Beek, T., Luthi, S.& Hardebol, N. 2007b. Integration of outcrop withborehole data to constrain fractured reservoir models.First Break, 25, 73–77.

Blunt, M. J., Bijeljic, B. et al. 2013. Pore-scaleimaging and modelling. Advances in Water Resources,51, 197–216.

Boro, H., Bertotti, G. & Hardebol, N. J. 2013.Distributed fracturing effecting isolated carbonateplatforms, the Latemar platform natural laboratory(Dolomites, Northern Italy. Marine and PetroleumGeology, 40, 69–84.

Bosworth, W., Khalil, S., Clare, A., Comisky, J.,Abdelal, H., Reed, T. & Kokkoros, G. 2012.Integration of outcrop and subsurface data during thedevelopment of a naturally fractured Eocene carbonatereservoir at the East Ras Budran concession, Gulf ofSuez, Egypt. In: Spence, G. H., Redfern, J., Agui-

lera, R., Bevan, T. G., Cosgrove, J. W., Couples,G. D. & Daniel, J.-M. (eds) Advances in the Studyof Fractured Reservoirs. Geological Society, London,Special Publications, 374, First published online July31, 2012, http://dx.doi.org/10.1144/SP374.3

Bratton, T., Canh, D. V. et al. 2006. The nature ofnaturally fractured reservoirs. Oilfield Review, 18,4–23.

Brie, A., Hsu, K. & Eckersley, C. 1988. Using theStoneley normalized differential energies for frac-tured reservoir evaluation. Transactions of the Soci-ety of Professional Well Log Analysts (SPWLA)29th Annual Logging Symposium, San Antonio, TX,USA, 5–8 June 1988, 29, XX1–XX25.

Buckley, S. J., Howell, A., Enge, H. D. & Kurtz, T. H.2008. Terrestrial laser scanning in geology: dataacquisition, processing and accuracy considerations.Journal of the Geological Society, 165, 625–638.

Buckley, S. J., Kurz, T. H., Howell, J. A. & Schnei-

der, D. 2013. Terrestial lidar and hyperspectral datafusion products for geological outcrop analysis. Com-puters and Geoscience, 54, 249–258.

Camac, B. A. & Hunt, S. P. 2009. Predicting theregional distribution of fracture networks using thedistinct element numerical method. American Asso-ciation of Petroleum Geologists Bulletin, 93,1571–1583.

Cooke, M. L. & Underwood, C. A. 2001. Fracture ter-mination and step-over at bedding interfaces due to

G. H. SPENCE ET AL.


http://dx.doi.org/10.1144/SP374.3



frictional slip and interface opening. Journal of Struc-tural Geology, 23, 223–238.

Cooke, M. L., Simo, J. A., Underwood, C. A. & Rijken,P. 2006. Mechanical stratigraphic controls on frac-ture patterns within carbonates and implicationsfor groundwater flow. Sedimentary Geology, 184,225–239.

Cosgrove, J. W. & Ameen, M. S. (eds) 2000. ForcedFolds and Fractures. Geological Society, London,Special Publications, 169.

Cosgrove, J. W. & Engelder, T. (eds) 2004. The Initi-ation, Propagation and Arrest of Joints and OtherFractures. Geological Society, London, Special Publi-cations, 231

Coward, M. P., Daltaban, T. S. & Johnson, H. (eds)1998. Structural Geology in Reservoir Characteriz-ation. Geological Society, London, Special Publi-cations, 127.

Couples, G. D. 2005. Seals: the role of geomechanics. In:Boult, P. & Kaldi, J. (eds) Evaluating Fault and CapRock Seals. American Association of Petroleum Geol-ogists, Hedberg Series, 2, 87–108.

Couples, G. D. 2013. Geomechanical impacts on flowin fractured reservoirs. In: Spence, G. H., Redfern,J., Aguilera, R., Bevan, T. G., Cosgrove, J. W.,Couples, G. D. & Daniel, J.-M. (eds) Advances inthe Study of Fractured Reservoirs. GeologicalSociety, London, Special Publication, 374. First pub-lished online June 25, 2013, http://dx.doi.org/10.1144/SP374.17

Delorme, D., Mota, R. O., Khvoenkova, N., Fourno,A. & Noetinger, B. 2013. A methodology tocharacterize fractured reservoirs constrained by stat-istical geological analysis and production: a realfield case study. In: Spence, G. H., Redfern, J.,Aguilera, R., Bevan, T. G., Cosgrove, J. W.,Couples, G. D. & Daniel, J.-M. (eds) Advancesin the Study of Fractured Reservoirs. GeologicalSociety, London, Special Publication, 374. First pub-lished online July 29, 2013, http://dx.doi.org/10.1144/SP374.14

Dershowitz, W. S. & Herda, H. H. 1992. Interpretationof fracture spacing on intensity. In: Tillerson, J. R. &Wawersik, W. R. (eds) Rock Mechanics. Balkema,Rotterdam, 757–766.

Dershowitz, W., Lapointe, P. & Cladouhos, T. 1998.Derivation of fracture spatial pattern parameters fromborehole data. International Journal of Rock Mech-anics and Mining Sciences, 35, 508.

Dockrill, B. & Shipton, Z. K. 2010. Structural con-trols on leakages from a natural CO2 storage site:central Utah, USA. In: Wibberley, C., Faulkner,D., Schlische, R., Jackson, C., Lunn, R. &Shipton, Z. (eds) Fault Zones. Journal of StructuralGeology, 32, 1768–1782.

Donald, A. & Bratton, T. 2006. Advancement in acous-tic techniques for evaluating open natural fractures.Transactions of the Society of Professional Well LogAnalysts (SPWLA) 47th Annual Logging Symposium,Veracruz, Mexico, 4–7 June 2006, Petrophysics,Houston, TX, 47, 156–157.

Dunne, W., Laubach, S., Hilgers, C. & Eichhubl, P.(eds) 2010. Structural Diagenesis. Special issue.Journal of Structural Geology, 32, 1865–2092.

Emsley, S. J., Shiner, P., Enescu, N., Beccacini, A. &Cosma, C. 2007. Using VSP surveys to bridge thescale gap between well and seismic data. In: Loner-

gan, L., Jolly, R. J. H., Rawnsley, K. & Sanderson,D. J. (eds) Fractured Reservoirs. Geological Society,London, Special Publications, 270, 83–91.

Far, M. E., Sayers, C. M., Thomsen, L., Han, D. & Cas-

tagna, J. P. 2013. Seismic characterization of natu-rally fractured reservoirs using amplitude v. offsetand azimuth analysis. Geophysical Prospecting, 61,427–447.

Farokhpoor, R., Toesæter, O., Bashbanbashi, T.,Mørk, A. & Lindberg, E. G. B. 2010. Experimentaland numerical simulation of CO2 injection into upper-Triassic sandstones in Svalbard, Norway. SPE Inter-national Conference on CO2 Capture, Storage, andUtilization, New Orleans, Louisiana, USA, 10–12November 2010, Society of Petroleum Engineers,Richardson, TX, Paper SPE-139524.

Farokhpoor, R., Bashbanbashi, T., Toesæter, O.,Lindberg, E. G. & Mørk, A. 2011. Experimental andsimulation analysis of CO2 storage in tight and frac-tured sandstones under different stress conditions. SPEEurope/EAGE Conference and Exhibition Vienna,Austria, 23–26 May 2011. Society of PetroleumEngineers, Richardson, TX, Paper SPE-143589.

Favalli, M., Fornaciai, A., Isola, I., Tarquini, S. &Nannipieri, L. 2012. Multiview 3D reconstructionin geosciences. Computers and Geosciences, 44,168–176.

Fernandez, O., Kieft, R., Dee, S., Sanderson, D.,Bowman, A. & Evans, P. 2011. The Role of Fracturesin Reservoir Compartmentalization (abstract). NARG,Naturally Fractured Reservoirs: Outcrop Analogues,Subsurface Studies and Case Histories Case Histories,10–11 January 2011. Manchester University, Work-shop Programme and Abstracts, 20.

Freeman, B., Boult, P. J., Yielding, G. & Menpes, S.2010. Using empirical geological rules to reduce struc-tural uncertainty in seismic interpretation of faults.Journal of Structural Geology, 32, 1668–1676.

Fuenkajorn, K. & Daemen, J. J. K. 1992. Drilling-induced fractures in borehole walls. Journal of Pet-roleum Technology, 44, 210–216.

Garcıa-Selles, D., Falivene, O., Arbues, P., Grata-

cos, O., Tavani, S. & Munoz, J. A. 2011. Supervisedidentification and reconstruction of near-plane geologi-cal surfaces from terrestrial laser scanning. Computerand Geosciences, 37, 1584–1597.

Garland, J., Neilson, J. E., Laubach, S. E. & Whidden,K. J. (eds) 2012. Advances in Carbonate Explorationand Reservoir Analysis. Geological Society, London,Special Publications, 370.

Geiger, S. & Matthai, S. 2012. What can we learn fromhigh-resolution numerical simulations of single- andmulti-phase fluid flow in fractured outcrop ana-logues? In: Spence, G. H., Redfern, J., Aguilera,R., Bevan, T. G., Cosgrove, J. W., Couples, G. D.& Daniel, J.-M. (eds) Advances in the Study ofFractured Reservoirs. Geological Society, London,Special Publications, 374. First published online Sep-tember 5, 2012, http://dx.doi.org/10.1144/SP374.8

Geiser, P., Lacazette, A. & Vermilye, J. 2012. Beyond“dots in a box”: an empirical view of reservoir

INTRODUCTION











permeability with tomographic fracture imaging. FirstBreak, 30, 63–69.

Gherardi, F., Xu, T. & Pruess, K. 2007. Numerical mod-eling of self-limiting and self-enhancing caprockalteration induced by CO2 storage in a depleted gasreservoir. Chemical Geology, 244, 103–129.

Gillespie, P., Monsen, E., Maerten, L., Hunt, D.,Thurmond, J. & Tuck, D. 2011. Fractures in carbon-ates: from digital outcrops to mechanical models.In: Martinsen, O. J., Pulham, A. J., Haughton,P. D. W. & Sullivan, M. D. (eds) Outcrops Revita-lized: Tools, Techniques and Applications. SEPM(Society for Sedimentary Geology), Concepts inSedimentology and Paleontology Special Publication,10, 32–51.

Gonzalez, L., Nasreldin, G., Rivero, J. A., Welsh, P.& Aguilera, R. 2014. 3D modelling of multi-stage hydraulic fractures and two-way-coupling geo-mechanics/fluid-flow simulation of a horizontal wellin the Nikanassin tight gas formation, westernCanada sedimentary basin. SPE Reservoir Evaluationand Engineering, Society of Petroleum Engineers,http://dx.doi.org/10.2118/159765-PA

Grasselli, G., Lisjak, A., Mahabadi, O. & Tatone,B. 2014. Influences of pre-existing discontinuitiesand rock fabrics on hydraulic fracturing initiation.European Journal of Environmental and CivilEngineering, http://dx.doi.org/10.1080/19648189.2014.906367

Gudmundsson, A. & Løtveit, I. F. 2012. Sills as frac-tured hydrocarbon reservoirs: examples and models.In: Spence, G. H., Redfern, J., Aguilera, R.,Bevan, T. G., Cosgrove, J. W., Couples, G. D. &Daniel, J.-M. (eds) Advances in the Study of Frac-tured Reservoirs. Geological Society, London,Special Publications, 374. First published online Sep-tember 10, 2012, http://dx.doi.org/10.1144/SP374.5

Haimson, B. & Rudnicki, J. W. 2010. The effect of theintermediate principal stress on fault formation andfault angle in siltstone. Journal of StructuralGeology, 32, 1701–1711.

Hall, S. A., Lewis, H. & Macle, X. 2007. Enhancementof seismic identification of inter-fault damage via alinked seismic-geomechanics approach. In: Lewis, H.& Couples, G. D. (eds) The Relationship betweenDamage and Localization. Geological Society,London, Special Publications, 289, 187–208.

Handin, J. W. 1969. On the Coulomb-Mohr failurecriterion. Journal of Geophyscial Research, 74,5342–5348.

Hanks, C. L., Lorenz, J., Teufel, L. & Krumhardt,A. P. 1997. Lithological and structural controlson nature fracture distribution and behaviour withinthe Lisburne Group, northeastern Brooks Rangeand North Slope subsurface, Alaska. AmericanAssociation of Petroleum Geologists Bulletin, 81,1700–1720.

Hardebol, N. & Bertotti, G. 2013. DigiFract: a softwareand data model implementation for flexible acquisitionand processing of fracture data from outcrops. Compu-ter and Geosciences, 54, 326–336.

Hardy, S. & Finch, E. 2007. Mechanical stratigraphyand the transition from trishear to kink-band fault-propogation fold forms above blind basement thrust

faults: A discrete element study. Marine and Pet-roleum Geology, 24, 75–90.

He, M. Y. & Hutchinson, J. W. 1989. Crack deflection atinterfaces between dissimilar elastic materials. Inter-national Journal of Solids and Structures, 25,1053–1067.

Healey, D., Sibson, R. H., Shipton, Z. & Butler, R.(eds) 2012. Faulting, Fracturing and Igneous Intrusionin the Earth’s Crust. Geological Society, London,Special Publications, 367.

Heffer, K. J. 2012. Geomechanical mechanisms involv-ing faults and fractures for observed correlationsbetween fluctuations in flowrates at wells in North Seaoilfields. In: Spence, G. H., Redfern, J., Aguilera,R., Bevan, T. G., Cosgrove, J. W., Couples, G. D.& Daniel, J.-M. (eds) Advances in the Study ofFractured Reservoirs. Geological Society, London,Special Publications, 374. First published onlineAugust 28, 2012, http://dx.doi.org/10.1144/SP374.2

Hencher, S. R. 2013. Characterizing discontinuities innaturally fractured outcrop analogues and rock core:the need to consider fracture development over geo-logical time. In: Spence, G. H., Redfern, J., Agui-

lera, R., Bevan, T. G., Cosgrove, J. W., Couples,G. D. & Daniel, J.-M. (eds) Advances in the Studyof Fractured Reservoirs. Geological Society, London,Special Publications, 374. First published online May9, 2013, http://dx.doi.org/10.1144/SP374.15

Hennings, P. (ed.) 2009. AAPG-SPE-SEG Hedbergresearch conference on the geological occurrence andhydraulic significance of fractures in reservoirs. TheAmerican Association of Petroleum Geologist,Special themed issue, 93, 1407–1648.

Hodgetts, D. 2013. Laser scanning and digital outcropgeology in the petroleum industry: a review. Marineand Petroleum Geology, 46, 335–354.

Hooker, J. N. & Laubach, S. E. 2013. Natural fracturing,by depth. Geophysical Research Abstracts Vol. 15,EGU2013-13725, EGU General Assembly, 7–12April 2013, Vienna, Austria.

Hooker, J. N., Gomez, L. A., Laubach, S. E., Gale,J. F. W. & Marrett, R. 2012. Effects of diagenesis(cement precipitation) during fracture opening onfracture aperture-size scaling in carbonate rocks.In: Garland, J., Neilson, J., Laubach, S. E. &Whidden, K. J. (eds) Advances in Carbonate Explo-ration and Reservoir Analysis. Geological Society,London, Special Publications, 370, 187–206.

Idling, M., Ringrose, P., Wightman, R., Leary, S.,Lescofit, G. & Paasch, B. 2011. The importanceof fracture characterisation and modelling for CO2storage in Salah Gas Development, Krechba Field,Algeria (abstract). NARG Naturally Fractured Hydro-carbon Reservoirs: Outcrop Analogues, SubsurfaceStudies and Case Histories Workshop, 12–13 January2011, Manchester University, UK, Programme andAbstracts, 30.

Jiang, Z., Wu, K., Couples, G., Van Dijke, M. I. J.,Sorbie, K. S. & Ma, J. 2007. Efficient extraction ofnetworks from three-dimensional porous media.Water Resources Research, 43, W12S03, http://dx.doi.org/10.1029/2006WR005780

Jiang, Z., Van Dijke, R., Geiger, S., Couples, G. &Wood, R. 2012. Extraction of fractures from 3D rock

G. H. SPENCE ET AL.


http://dx.doi.org/10.2118/159765-PA



http://dx.doi.org/10.1080/19648189.2014.906367

http://dx.doi.org/10.1080/19648189.2014.906367

http://dx.doi.org/10.1080/19648189.2014.906367







http://dx.doi.org/10.1029/2006WR005780

http://dx.doi.org/10.1029/2006WR005780

http://dx.doi.org/10.1029/2006WR005780


images and network modelling of multi-phase flow infracture-pore systems. Proceedings 2012 InternationalSymposium of the Society of Core Analysts, Aberdeen,Scotland (SCA2012-87), 12 p.

Jolley, S. J., Barr, D., Walsh, J. J. & Knipe, R. J. (eds)2007. Structurally Complex Reservoirs. GeologicalSociety, London, Special Publications, 272.

Jones, M. E. & Preston, R. M. F. (eds) 1987. Defor-mation of Sediments and Sedimentary Rocks. Geologi-cal Society, London, Special Publication, 29.

Jordan, P. D., Curtis, M., Oldenburg, C. M. & Nicot,J.-P. 2013. Measuring and modeling fault density forCO2 storage plume-fault encounter probability esti-mation. American Association of Petroleum GeologistsBulletin, 97, 597–618.

Kurtz, T. H., Buckley, S. J., Howell, J. A. & Schnei-

der, D. 2011. Integration of panoramic hyperspectralimaging with terrestrial lidar data. The Photogram-matic Record, 26, 212–228.

La Pointe, P. R. & Hudson, J. A. 1985. Character-isation and interpretation of rock mass joint pat-terns. Geological Society of America Special Paper,199, 37.

Lander, R. H., Gale, J. F. W., Laubach, S. E. &Bonnell, L. M. 2002. Interaction between quartzcementation and fracturing in sandstones. AnnualMeeting Expanded Abstracts, American Associationof Petroleum Geologists Annual Convention Pro-gramme 11, A98–99.

Larsen, B., Grunnaleite, I. & Gudmundsson, A. 2010.How fracture systems affect permeability develop-ment in shallow-water carbonate rocks: an examplefrom the Gargano Peninsula, Italy. Journal of Struc-tural Geology, 32, 1212–1230.

Lato, M., Diederichs, M. S., Hutchinson, J. D. &Harrap, R. 2009. Optimisation of LIDAR scann-ing and processing for automated structural evalua-tion of discontinuities in rockmasses. InternationalJournal of Rock Mechanics and Mining Science, 46,194–199.

Lato, M. J., Diederichs, M. S. & Hutchinson, D. J.2010. Bias correction for view limited lidar scan-ning of rock outcrops for structural characteri-zation. Rock Mechanics and Rock Engineering, 43,615–628.

Laubach, S. E. 1988. Subsurface fractures and theirrelationship to stress history in east Texas Basin sand-stones. Tectonophysics, 156, 37–49.

Laubach, S. E. 2003. Practical approaches to identifyingsealed and open fractures. American Association ofPetroleum Geologists Bulletin, 87, 561–579.

Laubach, S. E., Lander, R. H., Bonnell, L. M., Olson,J. E. & Reed, R. M. 2004a. Opening histories of frac-tures in sandstones. In: Cosgrove, J. W. & Engelder,T. (eds) The Initiation, Propagation and Arrest ofJoints and Other Fractures. Geological Society,London, Special Publications, 231, 1–9.

Laubach, S. E., Reed, R. M., Olso, J. E., Lander, R. H.& Bonnell, J. M. 2004b. Coevolution of crack-seal texture and fracture porosity in sedimentaryrocks: cathodoluminescence observations of regionalfractures. Journal of Structural Geology, 26, 967–982.

Laubach, S. E., Olson, J. E. & Gross, M. R. 2009.Mechanical and fractures stratigraphy. American

Association of Petroleum Geologists Bulletin, 93,1413–1426.

Leckenby, R. J., Longeran, L., Rogers, S. F. &Sanderson, D. J. 2007. Study of fracture-inducedanisotropy from discrete fracture network simulationof well test responses. In: Longeran, L., Jolly, R.J. H., Rawnsley, K. & Sanderson, D. J. (eds) Frac-tured Reservoirs. Geological Society, London, SpecialPublications, 270, 117–137.

Lezin, C., Odonne, F., Massonnat, G. J. & Escadeil-

las, G. 2009. Dependence of joint spacing on rockproperties in carbonate strata. Bulletin AmericanAssociation of Petroleum Geologist, 93, 271–290.

Lindquist, W. B., Venkatarangan, A., Dunsmuir, J. &Wong, T. F. 2000. Pore and throat size distributionsmeasured from synchrotron X-ray topographic imagesof Fontainebleau sandstone. Journal of GeophysicalResearch, 24, 157–177.

Lonergan, L., Jolly, R. J. H., Rawnsley, K. &Sanderson, D. J. (eds) 2007. Fractured Reser-voirs. Geological Society, London, Special Publi-cations, 270.

Mandl, G. & Harkness, R. M. 1987. Hydrocarbonmigration by hydraulic fracturing. In: Jones, M. E. &Preston, R. M. (eds) Deformation of Sediments andSedimentary Rocks. Geological Society, Special Publi-cations, 29, 39–53.

Mansfield, C. H. & Kemeny, J. 2009. The use of terres-trial LIDAR in determining directional joint dilationangle values. 43rd US Rock Mechanics Symposiumand 4th US-Canada Rock Mechanics Symposium,Asheville, NC, June 38–1 July, America Rock Mech-anics Association ARMA 09-98.

Mauldon, M., Dunne, W. M. & Rohrbaugh, M. B.2001. Circular scan lines and circular windows: newtools for characterising the geometry of fracturetraces. Journal of Structural Geology, 23, 247–258.

McCaffrey, K., Lonergan, L. & Wilkinson, J. (eds)1999. Fractures, Fluid Flow and Mineralization.Geological Society, London, Special Publications,155.

McDermott, C. I., Edlmann, K. & Haszeldine, R. S.2013. Predicting hydraulic tensile fracture spacing instrata-bound systems. International Journal of RockMechanics and Mining Sciences, 63, 39–49.

Murray, A. & Montgomery, D. W. 2012. Characteriz-ation of highly fractured basement, Say’un MasilaBasin, Yemen. In: Spence, G. H., Redfern, J., Agui-

lera, R., Bevan, T. G., Cosgrove, J. W., Couples,G. D. & Daniel, J.-M. (eds) Advances in theStudy of Fractured Reservoirs. Geological Society,London, Special Publications, 374. First publishedonline July 24, 2012, http://dx.doi.org/10.1144/SP374.1

Nelson, R. A. 1985. Geological Analysis of NaturallyFractured Reservoirs. 1st edn. Gulf Professional Pub-lishing, Elsevier, Oxford, UK.

Nelson, R. A. 2001. Geological Analysis of NaturallyFractured Reservoirs. 2nd edn. Gulf Professional Pub-lishing, Elsevier, Oxford, UK.

Odling, N. E., Gillespie, P. et al. 1999. Variations infracture system geometry and their implications forfluid flow in fractured hydrocarbon reservoirs. Pet-roleum Geoscience, 5, 373–384.

INTRODUCTION






Odonne, F., Lezin, C., Massonnat, G. & Escadeillas,G. 2007. The relationship between joint aperture,spacing distribution, vertical dimension and carbonatestratification: an example from the Kimmeridgianlimestones of Pointe-du-Chay (France). Journal ofStructural Geology, 29, 746–758.

Ogata, K., Senger, K., Braathen, A., Tveranger, J. &Olaussen, S. 2012. The importance of naturalfractures in a tight reservoir for potential CO2

storage: a case study of the upper Triassic–middle Jur-assic Kapp Toscana Group (Spitsbergen, ArcticNorway). In: Spence, G. H., Redfern, J., Aguilera,R., Bevan, T. G., Cosgrove, J. W., Couples, G. D. &Daniel, J.-M. (eds) Advances in the Study of Frac-tured Reservoirs. Geological Society, London, SpecialPublications, 374. First published online September10, 2012, http://dx.doi.org/10.1144/SP374.9

Olariu, M., Ferguson, J. F. & Aiken, C. L. V. 2008.Outcrop fracture characterization using terrestriallaser scanners: deep-water Jackfork sandstone at BigRock Quarry, Arkansas. Geosphere, 4, 247–259.

Olson, J. E., Laubach, S. E. & Lander, R. H. 2007.Combining diagenesis and mechanics to quantifyfracture aperture distribution and fracture patternpermeability. In: Lonergan, L., Jolly, R. J. H.,Rawnsley, K. & Sanderson, D. J. (eds) FracturedReservoirs. Geological Society, London, SpecialPublications, 270, 101–116.

Ortega, C. & Aguilera, R. 2014. Quantitative propertiesfrom drill cuttings to improve the design of hydraulicfracturing jobs in horizontal wells. Journal of Cana-dian Petroleum Technology, 53, 55–68, http://dx.doi.org/10.2118/155746-PA

Pearce, M. A., Jones, R. R., Smith, S. A. F. & McCaf-

frey, K. J. W. 2011. Quantification of fold curva-ture and fracturing using terrestrial laser scanning.American Association of Petroleum Geologists Bul-letin, 95, 771–794.

Petford, N. & McCaffrey, K. J. W. (eds) 2003. Hydro-carbons in Crystalline Rocks. Geological Society,London, Special Publications, 214.

Pollard, D. D. & Aydin, A. 1988. Progress in under-standing jointing over the past century. GeologicalAssociation of America Bulletin, 100, 1181–1204.

Priest, S. D. 2004. Determination of discontinuity sizedistributions from scanline data. Rock Mechanics andRock Engineering, 37, 347–368.

Prioul, R. & Jocker, J. 2009. Fracture characterizationat multiple scales using borehole images, sonic logs,and walkaround vertical seismic profile. AmericanAssociation of Petroleum Geologists Bulletin, 98,1503–1516.

Questiaux, J-M., Couples, G. D. & Ruby, N. 2009. Frac-tured reservoirs with fracture corridors. GeophysicalProspecting, 58, 278–295.

Roehl, P. O. & Choquette, P. W. 1985. Carbonate Pet-roleum Reservoirs. Springer, New York.

Rotevatn, A. & Bastesen, E. 2012. Fault linkage anddamage zone architecture in tight carbonate rocksin the Suez Rift (Egypt): implications for the per-meability structure along segmented normal faults.In: Spence, G. H., Redfern, J., Aguilera, R.,Bevan, T. G., Cosgrove, J. W., Couples, G. D. &Daniel, J.-M. (eds) Advances in the Study of

Fractured Reservoirs. Geological Society, London,Special Publications, 374. First published online Sep-tember 10, 2012, http://dx.doi.org/10.1144/SP374.12

Ryazanov, A. V., Van Dijke, M. I. J. & Sorbie, K. S.2009. Two-phase pore-network modeling: existenceof oil layers during water invasion. Transport ofPorous Media, 80, 79–99.

Sanders, C. A. E., Fullarton, L. & Calvert, S. 2003.Modelling fracture systems in extensional crystallinebasement. In: Petford, N. & McCaffrey, K. W. J.(eds) Hydrocarbons in Crystalline Rocks. Geo-logical Society, London, Special Publications, 214,221–236.

Sagi, D. A., Arnhild, M. & Karlo, J. F. 2013.Quantifying fracture density and connectivity offractured chalk reservoirs from core samples: impli-cations for fluid flow. In: Spence, G. H., Redfern,J., Aguilera, R., Bevan, T. G., Cosgrove, J. W.,Couples, G. D. & Daniel, J.-M. (eds) Advancesin the Study of Fractured Reservoirs. GeologicalSociety, London, Special Publications. 374. First pub-lished online June 26, 2013, http://dx.doi.org/10.1144/SP374.16

Saoudi, A., Moustafa, A. R. et al. 2012. Dual-porosity fractured Miocene syn-rift dolomite reservoirin the Issaran Field (Gulf of Suez, Egypt): a casehistory of the zonal isolation of highly fracturedwater carrier bed. In: Spence, G. H., Redfern, J.,Aguilera, R., Bevan, T. G., Cosgrove, J. W.,Couples, G. D. & Daniel, J.-M. (eds) Advances inthe Study of Fractured Reservoirs. GeologicalSociety, London, Special Publications, 374. First pub-lished online September 5, 2012, http://dx.doi.org/10.1144/SP374.7

Schopfer, M. P. J., Arslan, A., Walsh, J. J. & Childs, C.2011. Reconciliation of contrasting theories for frac-ture spacing in layered rocks. Journal of StructuralGeology, 33, 551–565.

Seers, T. D. & Hodgetts, D. 2013. Comparisons ofdigital outcrop and conventional data collectionapproaches for the characterization of naturallyfractured reservoir analogues. In: Spence, G. H.,Redfern, J., Aguilera, R., Bevan, T. G., Cosgrove,J. W., Couples, G. D. & Daniel, J.-M. (eds) Advancesin the Study of Fractured Reservoirs. GeologicalSociety, London, Special Publications, 374. First pub-lished online April 19, 2013, http://dx.doi.org/10.1144/SP374.13

Segura, J. M., Fisher, Q. J. et al. 2011. Reservoir stresspath characterization and its implications for fluid-flowproduction simulation. Petroleum Geoscience, 17,335–344.

Senger, K., Ogata, K., Tveranger, J. & Braathen, A.2011. Towards a simulation of CO2 flow through anaturally fractured reservoir, Spitsbergen, Svalbard(abstract). In: NARG Naturally Fractured Hydro-carbon Reservoirs: Outcrop Analogues, SubsurfaceStudies and Case Histories Workshop, 12–13 Jan-uary 2011, Manchester University, UK, Programmeand Abstracts, 53.

Senger, K., Ogata, K., Tveranger, J., Braathen, A. &Olaussen, S. 2013. Outcrop based reservoir model-ling of a naturally fractured siliciclastic CO2 sequestra-tion site, Svalbard, Artic Norway (extended abstract).

G. H. SPENCE ET AL.




















In: European Association of Geoscientists & EngineersSustainable Earth Sciences 2013, 30 September–4October, Pau, France. http://dx.doi.org/10.3997/2214-4609.20131650

Shackleton, J. R., Cooke, M. L. & Sussman, A. J.2005. Evidence for temporally changing mechanicalstratigraphy and effects on joint network architecture.Geology, 33, 101–104.

Slightam, C. 2012. Characterizing seismic-scale faultspre- and post-drilling; Lewisian Basement, West ofShetlands, UK. In: Spence, G. H., Redfern, J., Agui-

lera, R., Bevan, T. G., Cosgrove, J. W., Couples, G.D. & Daniel, J.-M. (eds) Advances in the Study ofFractured Reservoirs. Geological Society, London,Special Publications, 374. First published online Sep-tember 11, 2012, http://dx.doi.org/10.1144/SP374.6

Smart, K. J., Ferrill, D. A. & Morris, A. P. 2009.Impact of interlayer slip on fracture prediction fromgeomechanical models of fault-related folds. Ameri-can Association of Petroleum Geology, Bulletin, 93,1447–1458.

Sonntag, R., Evans, J. P., La Pointe, P., Deraps, M.,Sisley, H. & Richey, D. 2012. Sedimentologicalcontrols on the fracture distribution and networkdevelopment in Mesaverde Group sandstone lithofa-cies, Uinta Basin, Utah, USA. In: Spence, G. H.,Redfern, J., Aguilera, R., Bevan, T. G., Cosgrove,J. W., Couples, G. D. & Daniel, J.-M. (eds) Advancesin the Study of Fractured Reservoirs. GeologicalSociety, London, Special Publications, 374. First pub-lished online September 10, 2012, http://dx.doi.org/10.1144/SP374.4

Spence, G. H. & Finch, E. 2013. 2D discrete ele-ment numerical modelling of carbonate mechanicalstratigraphy to generate discrete fracture networks(extended abstract). 75th EAGE Conference & Exhibi-tion incorporating SPE EUROPEC, London, England,10–13 June 2013, http://dx.doi.org/10.3997/2214-4609.20131031

Spence, G. H. & Finch, E. 2014. Influences of nod-ular chert rhythmites on natural fracture networks incarbonates: an outcrop and two-dimensional dis-crete element modelling study. In: Spence, G. H.,Redfern, J., Aguilera, R., Bevan, T. G., Cosgrove,J. W., Couples, G. D. & Daniel, J.-M. (eds) Advancesin the Study of Fractured Reservoirs. GeologicalSociety, London, Special Publications, 374. First pub-lished online March 7, 2014, http://dx.doi.org/10.1144/SP374.18

Spence, G. H., Hodgetts, D., Horsfall, C., Rarity, F.& Redfern, J. 2010. 3-D digital outcrop analoguesof naturally fractured carbonate reservoirs- integratingmechanical and sequence stratigraphy: examples fromthe Eocene Thebes Formation of Egypt. GeologicalSociety of America Annual meeting, Denver, 31Oct–3 Nov 2010, Abstracts with Programs, 42, No.5, Paper No. 109-9.

Stearns, D. W. 1967. Certain aspects of fracture in natu-rally deformed rocks. In: Riecker, R. E. (ed.) RockMechanics Seminar. Air Force Cambridge ResearchLaboratories, Bedford, Massachusetts, ContributionAD669375, 97–118.

Strijker, G., Beekman, W. W. W., Bertotti, G. &Luthi, S. M. 2013. FEM analysis of deformation

localization mechanisms in a 3D fractured mediumunder rotating compressive stress conditions. Tectono-physics, 593, 95–110.

Strouth, A. & Eberhardt, E. 2006. The use of LiDARto overcome rock slope hazard data collection chal-lenges at Afternoon Creek, Washington. In: Proceed-ings of the 41st US Symposium on Rock Mechanics(USRMS): 50 Years of Rock Mechanics – Landmarksand Future Challenges. Golden Rocks, 17–21 June,Paper No. 06-993.

Sturzenegger, M. & Stead, D. 2009a. Quantifying dis-continuity orientation and persistence on high rockslopes and large landslides using terrestrial remotesensing techniques. Natural Hazards and EarthSystem Sciences, 9, 267–287.

Sturzenegger, M. & Stead, D. 2009b. Close range ter-restrial digital photogrammetry and terrestrial laserscanning for discontinuity characterisation on rockcuts. Engineering Geology, 106, 163–182.

Sturzenegger, M., Stead, D. & Elmo, D. 2011. Terres-trial remote sensing-based estimation of mean tracelength, trace intensity and block size/shape. Engineer-ing Geology, 119, 96–111.

Underwood, C. A., Cooke, M. L., Simo, J. A. &Muldoon, M. A. 2003. Stratigraphic controls on ver-tical fracture patterns in Silurian dolomite, northeast-ern Wisconsin. American Association of PetroleumGeologists Bulletin, 87, 121–142.

Valvatne, P. H. & Blunt, M. J. 2004. Predictivepore-scale modeling of two-phase flow in mixed wetmedia. Water Resources Research, 40, W07406,http://dx.doi.org/10.1029/2003WR002627

Varela-Gonzalez, M., Varela-Gonzalez-Jorge, H.,Riveiro, B. & Arias, P. 2013. Performance testingof LiDAR exploitation software. Computers & Geo-sciences, 54, 122–129.

Virgo, S., Abe, S. & Urai, J. L. 2013. Extensional fracturepropogation in rocks with veins: insights into thecrack-seal process using discrete element method mod-elling. Journal of Geophysical Research: Solid Earth,118, 5236–5251.

Vogel, H. J. & Roth, K. 2001. Quantitative morphologyand network representation of soil pore structure.Advances in Water Resources, 24, 233–242.

Voyat, I., Roncella, R., Forlani, G. & Ferrero, A. M.2006. Advanced techniques for geo structural sur-veys in modelling fractured rock masses: applica-tion to two Alpine sites. Paper No 06-1138, presentedat the 41st US Symposium on Rock Mechanics(USRMS): 50 Years of Rock Mechanics- Land markand future challenges, American Rock MechanicsAssociation (ARMA), Golden, Colorado, USA, June17–21.

Wang, P. & Xu, L. R. 2006. Dynamic interfacialdebonding initiation induced by incident cracks.International Journal of Solids and Structures, 43,6535–6550.

Ward, M. V., Pearse, C., Jehanno, Y., O’Hanlon,,Zett, A. & Houliston, D. 2013. The Machar OilField, UK Central North Sea: impact of seismicreprocessing on the development of a complex chalkfield. In: Spence, G. H., Redfern, J., Aguilera, R.,Bevan, T. G., Cosgrove, J. W., Couples, G. D. &Daniel, J.-M. (eds) Advances in the Study of

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Fractured Reservoirs. Geological Society,London, Special Publications, 374. First publishedonline October 17, 2012, http://dx.doi.org/10.1144/SP374.10

Wibberley, C., Faulkner, D., Schlische, R., Jackson,C., Lunn, R. & Shipton, Z. (eds) 2010. Fault zones.Special Issue. Journal of Structural Geology, 32,1553–1863.

Wilson, C. E., Aydin, A. et al. 2011. From outcrop toflow simulation: constructing discrete fracture modelsfrom a LIDAR survey. American Association of Pet-roleum Geologists Bulletin, 95, 1883–1905.

Wu, H. & Pollard, D. D. 1995. An experimental study ofthe relationship between joint spacing and layer thick-ness. Journal of Structural Geology, 17, 887–905.

Wuestefeld, A., Al-Harrasi, O., Verdon, J. P.,Wookey, J. & Kendall, J. M. 2010. A strategy forautomated analysis of passive microseimic data toimage seismic anisotropic and fracture characteristics.Geophysical Prospecting, 58, 755–773.

Youssef, S., Rosenberg, E., Gland, N. F., Kenter, J. A.,Skalinski, M. & Vizika, O. 2007. High resolution CTand pore-network models to assess petrophysical prop-erties of homogeneous and heterogeneous carbonates.

SPE/EAGE Reservoir Characterization and Simu-lation Conference, Abu Dhabi, 28–31 October, UAE,Society of Petroleum Engineers, http://dx.doi.org/10.2118/111427-MS

Zahm, C. K. & Hennings, P. H. 2009. Complex fracturedevelopment related to stratigraphic architecture:Challenges for structural deformation prediction, Ten-sleep Sandstone at the Alcova anticline, Wyoming.American Association of Petroleum Geologists Bulle-tin, 93, 1427–1446.

Zhang, L. & Einstein, H. H. 1998. Estimating the meantrace length of rock discontinuities. Rock Mechanicsand Rock Engineering, 31, 217–235.

Zhou, X., Karimi-Farad, M., Durlofsky, L. J. &Aydin, A. 2012. Fluid flow though porous sand-stone with overprinting and intersecting geolog-ical structures of various types. In: Spence, G. H.,Redfern, J., Aguilera, R., Bevan, T. G., Cos-

grove, J. W., Couples, G. D. & Daniel, J.-M.(eds) Advances in the Study of Fractured Reser-voirs. Geological Society, London, Special Publi-cations, 374. First published online October 19,2012, updated March 14, 2013, http://dx.doi.org/10.1144/SP374.11

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