Fault damage zones may significantly affect subsurface fluid migration and the development of unconventional resources. Most analyses of fault damage zones are based on direct field observations, and we expand these analyses to the subsurface by investigating the damage zone structure of an approximately 32-km (∼105-ft)-long right-lateral strike-slip fault in Oklahoma. We used the three-dimensional (3-D) seismic attribute of coherence to first define its regional and background levels, and then we evaluated the damage zone dimensions at multiple sites. We found damage zone thickness of approximately 1600 m (∼5300 ft) at a segment that is dominated by subsidiary faults, and it is slightly thicker at a segment with a pull-apart basin. The damage zone intensity decays exponentially with distance from the fault core, in agreement with field observations and distribution of seismic events. The coherence map displays a strong asymmetry of the damage zone between the two sides of the 3-D fault, which is related to the subsidiary structures of the fault zone. We discuss the effects of heterogeneous stress field on damage zone evolution through the detected subsidiary structures. It appears that seismic coherence is an effective tool for subsurface characterization of fault damage zones.
Fault Zone Structure
Field analyses of fault zones have revealed three primary components: fault core, damage zone, and protolith (Figure 1; Caine et al., 1996; Sagy et al., 2001; Kim et al., 2004; Savage and Brodsky, 2011). The fault core is a discrete, quasi-tabular shear zone comprised of gouge layers that accommodate most fault displacement. If the fault is composed of strands with several anastomosing segments, its core could be up to meters thick (e.g., Faulkner et al., 2010; Savage and Brodsky, 2011). The fault core could be a sealing zone with thick clay bodies (e.g., Billi et al., 2003), a permeable conduit (e.g., Caine et al., 1996), or both, depending on the fault’s state in its seismic cycle (e.g., Sibson, 1990). The damage zone is constituted of fractured, brecciated, and pulverized rocks derived from the protolith and are generally confined to a zone on the scale of a kilometer between the fault core and intact protolith (Sibson, 2003; Busetti et al., 2012; Rempe et al., 2013). The fracture sets within the damage zone commonly provide a high-permeability conduit for fluid flow (Billi et al., 2003). The fault core and damage zone may vary along strike because of fault-related diagenesis, segmentation, and evolution (Laubach et al., 2014). The structural complexity within the damage zones, and particularly the distribution and openness of its fracture networks, can significantly affect the migration, accumulation, and leakage of subsurface fluids (e.g., Caine et al., 1996; Faulkner et al., 2010; Ellis et al., 2012) and earthquake rupture characteristics (e.g., Weng et al., 2016).
Figure 1. Schematic diagram showing the fault zone architectural components for a strike-slip fault modeled after Caine et al. (1996). Red indicates fault core, gray indicates damage zones, and blank white indicates the protolith.
Characterization of the structure of a subsurface fault zone, without borehole data, can be done only indirectly because fracture networks are invisible to seismic data. The properties of subsurface fault patterns, including geometry and internal architecture, can be determined, for example, by using seismic attributes (Chopra and Marfurt, 2007). Application of seismic mapping to a submarine fold-thrust system can detect structural deformation by recognition of reduced signal through volumes (Iacopini and Butler, 2011; Iacopini et al., 2012). The concept of a seismic distortion zone enhanced the understanding of the associated damage of a thrust system at seismic scales. This seismic characterization method is further used for fault structure and its surrounding deformation that is defined as a seismic disturbance zone (Iacopini et al., 2016). Although the fracture networks are invisible at seismic scale, their cumulative effects could be detected as distortion of the signal (Chopra, 2009; Li et al., 2015). Numerical simulations of synthetic fault models and associated seismic responses show the potential to characterize the damage zones using seismic attributes and seismic tomography, as presented by Botter et al. (2016, 2017). Their workflow provides information on fault structure at different seismic resolutions through the seismic images determined by the discrete element modeling.
The present study uses three-dimensional (3-D) seismic attributes for the analysis of damage and splays of a large, subsurface strike-slip fault in Oklahoma. It is demonstrated that the used seismic approach can reveal the dimensions and shapes of damage zones, with indications of the deformation intensity. We further show that the detected subsurface damage zone displays similar scaling relation to well-documented field observations.
Damage Zone Dimension
It is commonly observed that the intensity of fracturing and deformation within a fault damage zone decays with distance from the fault core toward the protolith (e.g., Caine et al., 1996; Sagy et al., 2001; Katz et al., 2003; Savage and Brodsky, 2011; Rempe et al., 2013). Sagy et al. (2001) analyzed a system of joints within dolomite layers close to a large normal fault of the Dead Sea basin. The joint density, reported by the fracture spacing ratio (FSR; the layer thickness–to–joint spacing ratio) decreased significantly from FSR = 28 close to the fault core to a background value of 2–3 at approximately 100 m (∼330 ft) away from the core (Figure 2A). Wilson et al. (2003) analyzed the brittle deformation around the Punchbowl fault in California. They found that the density of subsidiary fractures in the sandstone decreases from approximately 90 fractures/m (∼27 fractures/ft) at the subfault core to a regional background of approximately 20 fractures/m (∼6 fractures/ft) at an approximately 10-m (∼33-ft) distance (Figure 2B). In general, the observed damage decay can be fit by a power function or an exponential function (Figure 2); for example, the fracture density (D) decays as fault-normal distance (x).
where a and b are constants that reflect physical properties related to the layer thickness or brittleness of the rock (Cowie et al., 1995).
Figure 2. Density of fault damage as a function of fault normal distance from the fault center. (A) Joint density versus fault normal distance by Sagy et al. (2001). (B) Fracture density versus fault normal distance (DP10) by Wilson et al. (2003). (C) Seismic events versus fault normal distance by Powers and Jordan (2010). (D) Schematic diagram shows the decay relationship between inferred damage parameter versus fault normal distance. Note a and b are coefficients of D = a e-bx. FSR = fracture spacing ratio; R2 = coefficient of determination.
Determination of the dimension of subsurface damage zones is challenging. Peng et al. (2003) used synthetic wave modeling to determine a thickness of approximately 100 m (∼330 ft) for a shallow fault in Landers, California. They found that the fault zone has an approximately 50% decrease in seismic velocity compared with the surrounding protolith. Powers and Jordan (2010) analyzed the variation of seismicity rate around right-lateral strike-slip faults in California (Figure 2C). In the fault core, the number of seismic events is approximately 120/km (∼3300/ft) normal to the fault, and this seismicity rate decayed to 20/km (66,000/ft) at a distance of 10 km (33,000 ft) by a power-law relationship with distance from the fault core. Their estimates of thicknesses of the damage zones ranged from 120 to 440 m (∼400 to 1400 ft) along Elsinore–Temecula segment of the southern San Andreas, California fault system. Valoroso et al. (2014) used high-resolution earthquake locations to evaluate the damage zone of the L’Aquila normal fault, Italy. They found damage zone thicknesses ranging from 0.5 to 1.5 km (∼1600 to 5000 ft), with damage intensity decaying at an exponential rate, with distance from the fault core, which is in general agreement with field observations. Additional information can be derived from borehole logs. For example, the drilling across the San Andreas fault near Parkfield revealed a 200-m (660-ft)-thick damage zone based on reduced seismic velocities (e.g., Zoback et al., 2011).
DAMAGE ZONE OF A SUBSURFACE STRIKE-SLIP FAULT: THREE-DIMENSIONAL SEISMIC ANALYSIS
Approach and Observations
We investigate the damage zone of the El Reno fault (ERF), a 32-km (105-ft)-long right-lateral strike-slip fault in the Anadarko Basin, Oklahoma. The analysis uses the 3-D seismic coherence, which is defined as the energy of the coherent part of seismic traces divided by the average acoustic energy of the input seismic traces (Chopra and Marfurt, 2007; Chopra, 2009). This attribute is commonly used to identify lateral discontinuities under the premise that its low values indicate discontinuities in layers; for example, usage to detect faults and damage zones in the subsurface (e.g., Chopra and Marfurt, 2007; Liao et al., 2013; Iacopini et al., 2016; Botter et al., 2017). Here, we focus on using coherence for characterization of seismic-scale damage zone in 3-D to demonstrate the practical effectiveness of this attribute for damage zone analysis for an onshore case of a large fault in an oil province.
The study area is in westcentral Oklahoma (inset Figure 3) where the Devonian Woodford Shale was deposited in the Anadarko, Arkoma, and Ardmore Basins (Paxton et. al., 2006; Cardott, 2008) during a global sea level transgression (Johnson, 1988; Lambert, 1993). The Woodford Shale is an important petroleum source rock in the United States midcontinent, characterized as a laminated unit with alternating brittle and ductile layers (Slatt et al., 2012). The quartz- and calcite-rich brittle layers are fractured by layer-perpendicular open fractures (Bernal et al., 2012). Gale et al. (2014) observed widely distributed small fractures with heights less than 3 cm (<1 in.) in thin chert layers of the Woodford.
Figure 3. (A) Two-way traveltime map of the top of the Woodford Shale indicating its large-scale structure of gently dipping (<2°) to the southwest. The time structural is corendered with the three-dimensional determined coherence of a horizontal surface at this depth. The dark lineaments (interpreted R faults are marked by red dashed lines in the zoom-in figure on the right) reveal structural elements, including the north-south El Reno fault zone within the red rectangle. Note transparent color is used for high coherence area. General location of the study area in the Anadarko Basin, Oklahoma (red star in Oklahoma, upper left subfigure). (B) Seismic amplitude map corendered with the coherence along the top of the Woodford Shale. Index (C1–C11) shows lines of sampling numbered south to north, with 1520 m (5000 ft) in space.
The seismic data analyzed here were collected in 2012, and it includes nine narrow azimuth surveys that were reprocessed and prestack time migrated using a single datum and the same bin size (33.5 by 33.5 m [110 by 110 ft]). The frequency ranged from 10 to 60 Hz, yielding the increased impedance as positive amplitude. The coherence volume calculations followed the procedure of Marfurt and Rich (2010).
The general features of the study area are displayed by a time structure map corendered with a map-based extraction from the seismic coherence volume at the Woodford Shale level (Figure 3B). The dark zone (within the red box) indicates a north–south fault in the eastern part of the area that is the ERF. Our previous study (Liao et al., 2013) indicated that the ERF is a right-lateral strike-slip fault based on two distinguishing features: (1) it is a vertical fault with several subparallel vertical segments (Liao et al., 2013), which is a typical feature of strike-slip faults (Christie-Blick and Biddle, 1985; Harding, 1985); and (2) the relatively small vertical throw (∼80 m [∼260 ft]) is in contrast to the large fault length of 32 km (105 ft or 20 mi) and vertical extent of at least 900 m (3000 ft) (Figure 4).
Figure 4. Seismic amplitude and coherence across section maps normal to the El Reno fault (ERF) in the study area. (A) and (B) are amplitude maps of sections C2 and C8, respectively (Figure 3). Red rectangles indicate the fault area corresponding to the area of low coherence value in (C) and (D).
The structure of the ERF at its intersection with the top of the Woodford Shale is displayed by the coherence map (Figure 3). The structure includes a system of folds and flexures that are most intense within a zone around the primary fault zone (Liao et al., 2017). We interpret this structure as the damage zone of the ERF, and evaluate its thickness in 11 horizontal, fault-normal sections of coherence. These sections are spaced at approximately 1500-m (∼5000-ft) intervals along the ERF (marked “C” in Figure 3). The seismic amplitude and coherence section samples are presented in Figure 4, and the coherence profiles are displayed in Figure 5.
Figure 5. Profiles of the coherence values across the El Reno fault at the Woodford Shale level. Profile locations in Figure 3. Note the inverse scale of the coherence. Zones of coherence values below background coherence are interpreted as damage zones. Coherence reduction intensity is shown in the following colors: pink, intense; and gray, gentle. (A) Damage zones along the type 1 segment of the El Reno fault are characterized by Riedel shear subfaults (C1–C7 sections in Figure 3B). (B) Damage zones along the type 2 segment of the El Reno fault characterized by a pull-apart basin (C6–C11 sections in Figure 3B).
It has been shown that between the Rayleigh limit and distinctive seismic response scale, seismic attributes could be interpreted to track structure details by an image-processing procedure (Liao et al., 2013; Iacopini et al., 2016). Figure 4 displays vertical sections of amplitude (Figure 4A, B) and coherence (Figure 4C, D) along line C2 and C8 (defined in Figure 3), which are perpendicular to the ERF. These sections reveal a few discrete vertical zones, with the ERF (red, dashed box) as the most prominent zone. The amplitude signals are strongly disturbed around the vertical fault zones, which is enhanced by the low coherence maps. The vertical fault zones are comprised of several vertical segments that become wider with depth. These seismic disturbance zones are analyzed here as the seismic damage zone of two structural types (type 1, Figure 4A, C; type 2, Figure 4B, D) along the strike-slip fault. The internal character of these structural types is discussed below.
The profiles display three general zones of coherence intensity (Figure 5; note inverted scale of the coherence): (1) zones of high coherence, greater than 0.9, observed away from the ERF; (2) zones of intermediate coherence, 0.8–0.9, within the ERF zone (gray in Figure 5); and (3) a zone of low coherence, 0.4–0.8, within the ERF (pink in Figure 5). The coherence levels in 3-D-seismic analysis indicate the intensity of structural disturbance and discontinuities (Chopra, 2009). Because fracturing and faulting disturb the continuity of geologic features, we regard the three coherence zones of Figure 5 as indicating three levels of damage intensity. The high coherence zone is the protolith zone away from the fault, the intermediate level zone is the damage zone, and the low coherence level zone is the fault core that is most intensely damaged, which is defined here as the “seismic fault core.” We apply this interpreted zonation in the synthesis below.
We further explored the validity of the above interpretation of damage zones by plotting the root mean square (RMS) of the seismic amplitude along the same profiles of Figure 5. We regard the amplitude RMS as a proxy for the reduction of the seismic intensity because of the damage and found that the amplitude RMS at the Woodford Formation horizon corresponds well to the coherency plots of Figure 5. Yet, although the coherency sections revealed both fault core (pink) and damage zone (gray), the amplitude RMS plots did not display the core (Figure 6).
Figure 6. Profiles of the root-mean-square (RMS) amplitude values across the El Reno fault at the Woodford Shale level. Profiles locations in Figure 3. Zones of abnormal low values (in gray) are interpreted as damage zones. (A) Damage zones along the type 1 segment of the El Reno fault (C1–C7 sections in Figure 3B). (B) Damage zones along the type 2 segment of the El Reno fault (C6–C11 sections in Figure 3B).
We noted that the width of the damage zone (gray in Figure 5) is asymmetric with respect to the seismic core zone (pink in Figure 5), and based on this asymmetry, we separated the coherence profiles into two types. Type 1, which includes profiles C1–C7 (Figure 5A), displays a strong asymmetry in which the damage zone is approximately 1100 m (∼3600 ft) wide in the western block of the ERF and only approximately 75 m (∼250 ft) wide in the eastern block. A core zone (pink), of an approximate 400-m (∼1312-ft) width, separates the two blocks. Type 2, which includes profiles C6–C11 (Figure 5B), has an approximately 1600-m (∼5400-ft)-thick damage zone (coherence <0.9), which includes a central core zone of an approximate 500-m (1600-ft) width. This type displays a gentler asymmetry with a western damage zone of an approximate 760-m (∼2500-ft) width and an eastern damage zone of an approximate 380-m (∼1200-ft) width. These types correspond to different structural styles that were recognized by Liao et al. (2017). Type 1 corresponds to the ERF segments with multiple subsidiary Riedel faults trending at 15°–30°, with respect to the main trend (red dash lines illustrated R faults in Figure 3A; Liao et al., 2017). Type 2, in contrast, is associated with segments of the ERF with pull-apart basin (e.g., area between profiles C8–C9 in Figure 3).
The dimensions and shapes of the identified coherence zones (Figure 5), which we interpret as damage zones, can be compared with equivalent features of exposed damage zones. First, both types displayed asymmetry of damage zone width with respect to the seismic fault core (Figure 5), and similar asymmetry has been observed in field cases and derived in theoretical models. Dor et al. (2006) found a systematic asymmetry of damage and pulverization distribution along multiple fault segments of the southern part of the San Andreas system in California. The pulverized rocks along these faults were typically associated with fault segments that separate rock bodies of different elastic properties. This association suggests that the asymmetric damage is related to preferential rupture propagation during earthquakes (Ben-Zion and Shi, 2005; Xu et al., 2012; Ampuero and Mao, 2017). It was modeled in rupture simulations of bimaterial faults that this preferred propagation direction would lead to strong strain asymmetry between the two sides of the fault (Cochard and Rice, 2000; Shi and Ben-Zion, 2006; Dalguer and Day, 2009; Ampuero and Mao, 2017).
To examine depth variations of the damage zones, we plotted a sequence of coherence profiles at 50-ms time intervals that are similar to the single-depth sections of Figure 5. The damage zones, marked gray in Figure 7 for type 1 (Figure 7A) and type 2 (Figure 7B), are wider (>1000 m [>3280 ft]) within the central part of the fault (e.g., intervals 1950–2000 ms in Figure 7A) and are thinner upward and downward (e.g., 1800 or 2150 ms; Figure 7A). Similar width variations can be observed for a type 2 segment (Figure 7B). This reduction of damage zone width from fault center toward its margins fits the well-documented observation that the largest displacement along a fault which is, in general, within its central region (Walsh and Watterson, 1987; Cowie and Scholz, 1992). However, the change in damage zone width from shallow to deep could be possibly influenced by differences in the connectivity of the various strands in subsurface, which is not to be discussed in this paper.
Figure 7. Coherence damage zone variations with depth intervals from 1800 to 2500 ms. (A) Type 1 segment with Riedel shear subfaults. (B) Type 2 segment with pull-apart basin. The zone of low coherence values below background coherence indicates the damage zone (colored in gray).
We further compare the geometry of the coherence zones with damage distribution in field studies. Figure 8A shows the normalized density of fractures as a function of normalized distance from the fault zone for the aforementioned three examples using seismic data (Powers and Jordan, 2010) and outcrop data (Sagy et al., 2001; Wilson et al., 2003). The curves of normalized density fit the above exponential model (equation 1) well, with slightly different coefficients, a and b, which reflect the fault lithology and geometry. Figure 8B shows the normalized coherence of the two fault blocks in type 1 (average values of C1–C7), displaying an exponential decay of the coherence as a function of increasing distance from the core. Within a wider damage zone, the deformation consists of subsidiary faults indicated by two pulses of coherence values (Figure 8C). Similar patterns of coherence (average of C6–C11) are observed in type 2 (Figure 8D, E). Figure 8E illustrates the extreme coherence anomaly of the eastern fault block of the pull-apart basin. These two types indicate that the thickness of a damage zone covers a distance of two orders of magnitude.
Figure 8. (A) Normalized damage density (fractures or seismic events) as a function of normalized distance from the fault zone. Three examples from references Sagy et al. (2001), Wilson et al. (2003), and Powers and Jordan (2010). All data are well fitted by the model D = a e-bx, in which coefficients a and b are determined by different fault lithology and geometry. (B) Normalized coherence (average of C1–C7) as a function of normalized distance from the fault zone for right block and (C) left block of type 1 segment of the El Reno fault (ERF) with Riedel shear subfaults (shown by the two arrows). (D) Normalized coherence (average of C6–C11) as a function of normalized distance from the fault zone for right block with fault wall of type 2 segment of the ERF with pull-apart basin and (E) left block in the ERF. R2 = coefficient of determination.
The damage zone of a fault can develop by various mechanisms. For example, earthquake propagation along a fault radiates seismic waves that could damage the surrounding blocks (e.g., Andrews, 1994; Dor et al., 2006). The intensity of this damage was analyzed and simulated based on the stress distribution during rupture and fault properties (Ben-Zion and Ampuero, 2009; Xu et al., 2012), and the analyses showed that the damage zone thickness depends primarily on fault depth, pre-earthquake stresses, and the intensity of stress drop during rupture (Ampuero and Mao, 2017). For example, a 15-km (5 × 104–ft)-deep strike-slip fault is expected to generate an approximately 400-m (∼1300-ft)-thick damage zone for typical crustal conditions (Ampuero and Mao, 2017). The vertical extent of the present ERF is approximately 900 m (∼3000 ft), and thus, the expected damage zone caused by an earthquake rupture is less than 100 m (<330 ft). Because our analysis revealed a much thicker damage zone (∼1600 m [∼5000 ft]), we propose that most of the observed damage is associated with the following evolution of fault growth. First, the early stages of fault evolution is characterized by development of multiple fractures and small faults that precede the localized slip in the core zone, partly because of the merger and coalescence of these smaller structures (e.g., Reches and Lockner, 1994; Heesakkers et al., 2011a, b). A large strike-slip fault, like the present ERF, evolves over an extended time and may develop a complex damage distribution that generates a wide zone. Experimental works have shown that strike-slip faults typically initiate as a wide, simple-shear zone with multiple secondary structures (Riedel shears; P shears), which eventually merge into a complex fault zone (Naylor et al., 1986; Reches 1988; Liao et al., 2013). This process forms a wide damage zone that continues to deform internally because of the nonplanar, intersecting relation of the coalesced secondary faults. Such evolution may lead to a rough fault core (Sagy et al., 2001), and the slip along such a rough fault generates a heterogeneous stress field comparable with the scale of the roughness (Dieterich and Smith, 2009; Powers and Jordan, 2010). Figure 9 displays a model calculation of the stress distribution at the proximity of a rough strike-slip fault (Chester et al., 2005). This stress field leads to further damage by branching of multiple secondary faults and general fracturing, particularly in the more tensile area (Reches, 1988), as well as multiple short folds and flexures. The ERF, studied here, is likely to be at a mature stage of its development, and we argue that the above processes prevailed during its activity, forming the damage zones with reduced seismic coherence.
Figure 9. Schematic presentation of the fault model with (A) heterogeneous stress field over a scaling region (Dieterich and Smith, 2009; Powers and Jordan, 2010) and (B) the associated damage zones (Chester et al., 2005). The color bar indicates stress change (σ).
The present analysis of the damage zone of the ERF in Oklahoma by using seismic attributes led to the following conclusions.
- The analysis shows the effectiveness of using the 3-D seismic attribute of coherence for characterization of the structural features of large fault zones.
- The thickness variations of the damage zone of the El Reno segments fit an exponential decay with distance from the fault core. This scaled decay function agrees with field observations over different scales and may be applied to characterize damage zone dimensions in the subsurface.
- It is suggested that the pattern and scale of damage zone thickness is controlled by the secondary structures that develop during fault evolution.
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The authors would like to thank the Compagnie Générale de Géophysique for providing a license to their three-dimensional seismic data, the sponsors of the Attribute Assisted Seismic Processing and Interpretation, the University of Oklahoma, and N. Gupta for their help. Additional support funding was provided by Strategic Priority Research Program of the Chinese Academy of Sciences (XDA14010306), the National Natural Science Foundation of China (NSFC; 41604036), and NSFC for Major Projects (U1663203), and Science Foundation of China University of Petroleum, Beijing (2462014YJRC013). We would like to thank S. Laubach, AAPG Editor Barry J. Katz, D. Iacopini, T. Allwardt, F. Whitehurst, and two anonymous reviewers for their thoughtful and detailed reviews, which helped improve this manuscript.