This paper was prepared for presentation at the Unconventional Resources Technology Conference held in Denver, Colorado, USA, August 2013.

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1 URTeC Ambient Fracture Imaging: A New Passive Seismic Method Alfred Lacazette*, Jan Vermilye, Samuel Fereja, Charles Sicking, Global Geophysical Services Inc., Microseismic Services Division, 1625 Broadway St., Suite 1150, Denver, Colorado Copyright 2013, Unconventional Resources Technology Conference (URTeC) This paper was prepared for presentation at the Unconventional Resources Technology Conference held in Denver, Colorado, USA, August The URTeC Technical Program Committee accepted this presentation on the basis of information contained in an abstract submitted by the author(s). The contents of this paper have not been reviewed by URTeC and URTeC does not warrant the accuracy, reliability, or timeliness of any information herein. All information is the responsibility of, and, is subject to corrections by the author(s). Any person or entity that relies on any information obtained from this paper does so at their own risk. The information herein does not necessarily reflect any position of URTeC. Any reproduction, distribution, or storage of any part of this paper without the written consent of URTeC is prohibited. Summary Knowledge of discrete transmissive features such as faults or fracture zones prior to drilling offers substantial benefits for all phases of operations from exploration to development planning and hydraulic fracture design. We describe a new application of a relatively new passive-seismic method. The product is images of seismic activity produced by discrete features such as faults and fractures in the reservoir prior to drilling. We will present data acquired with passive seismic listening arrays in two unconventional reservoirs and a fractured carbonate reservoir. An extensive body of literature shows that fracture/fault zones with high resolved shear stress correlate positively with fracture transmissivity. In many cases, discontinuities with high resolved shear stress will be the most microseismically active. This method therefore allows mapping of many hydraulically transmissive zones prior to drilling or any other activity. The passive seismic method (Tomographic Fracture Imaging or TFI) directly images seismically active hydraulic fractures and natural fractures as complex surfaces and networks. Until recently, TFI has been used primarily to image hydraulic fracture treatments. We report a new application: imaging ambient seismic activity both prior to frac monitoring and by quiet-time monitoring using 3D reflection grids, i.e. by recording on a reflection grid or dedicated passive seismic grid when shooting or vibrating is not in progress. The resulting images reveal seismically active fracture and fault zones that correlate well with features illuminated by fracing or that are imaged by 3D reflection seismic attributes. The presence and hydraulic transmissivity of some of these features have been validated by independent measures including chemical tracers and pressure monitoring. This work also considers drivers of ambient seismic activity including earth tides and epeirogenic movements. Earth stress studies have established that the brittle crust is a self-organizing critical system in a state of frictional equilibrium and hence is constantly on the verge of movement. The earth s brittle crust is continually loaded by a variety of forces although tectonic movements, isostacy and isostacy-related flexure appear to dominate. It has been shown that stress or pressure changes of less than 0.01 atmospheres can stimulate seismicity. We present our work to date on quantitative correlations between earth tides and ambient seismic activity imaged on large grids. The results suggest that earth tides help stimulate release of stored elastic strain energy in the brittle crust. Introduction Natural fracture networks strongly influence the movement of hydrocarbons in the subsurface and hence the productivity of wells and entire fields. The importance of natural fractures to productivity of many unconventional reservoirs is widely recognized. Reflection seismic methods can provide bulk measures of velocity and velocity anisotropy. Although these values have proven useful in many cases for fracture detection in advance of drilling, they do not reveal the discrete fracture network directly and they do not indicate fracture systems that are likely to be hydraulically transmissive. Similarly, high-resolution reflection seismic methods can reveal larger fractures, but do not reveal the detailed network or the likelihood that the fractures will be productive. Other methods for

2 URTeC Page 2 understanding subsurface fracture networks include borehole images, open- and cased-hole production logs, chemical and radioactive frac tracers, well tests, interference tests, production data, and other methods that require drilling and completing multiple wells, thus precluding field development planning that accounts for the natural fracture network. This work describes a new passive-seismic method that images subsurface fracture networks prior to drilling that are likely to be hydraulically transmissive. The data required can be obtained inexpensively by listening to ambient seismic emissions during standard 3D reflection surveys when shooting or vibrating is not in progress. The resulting images allow potential sweet spots to be targeted first and allow field development planning to begin before starting a drilling campaign. Ambient images can also aid in planning hydraulic fracture treatments. Ambient images of natural fracture networks are less complete than images produced by hydraulic fracture monitoring, but are useful for exploration and pre-drill development planning. More complete TFIs are obtained when monitoring a fracture treatment because the fluid pressure pulse and poroelastic stress changes produced by the frac illuminate the transmissive fracture fairways over a large area and provide more energy for imaging. However, many features that are illuminated by fracture treatments appear in the ambient, pre-frac images. This paper is intended to provide a brief overview of Tomographic Fracture Imaging and a progress report and overview of our work-to-date on ambient TFI. More complete publications are in preparation. Here we summarize the imaging method, explain why it works, and provide several examples of results that were validated with independent data sets. We also present our work-to-date on correlation of bulk ambient seismicity with earth tides. Method Tomographic Fracture Imaging or TFI (Geiser et al, 2006; Geiser et al, 2012; Lacazette and Geiser, 2013; Sicking et al, 2013) is a proprietary, patented and patent-pending technology. In brief, TFI is accomplished as follows. 1. Single (vertical) or multi-component passive seismic data is recorded continuously throughout the time period of interest with a surface or shallow buried array. Uniform grid geometries are preferred, hexagonal closest-packed grids are ideal. 2. The data is processed to remove noise, make static corrections etc. similarly to standard reflection seismic processing.. 3. A velocity model of the study volume is developed using any available data such as sonic logs, stacking velocities from seismic data, or VSP surveys. The velocity model is as detailed as possible. If sufficient data are available, then a 3D spatially-varying, anisotropic velocity model is built. If data such as string or perforation shots are available, then the initial model is fine-tuned using this data. 4. The study volume is divided into voxels. Using ray-tracing, a table of one-way travel times from every voxel to every receiver is computed. 5. The traces are aligned in time for each voxel, and the semblance or other quantity (such as a measure of energy) is computed for discrete time intervals to produce a five-dimensional data volume. The dimensions of the data volume are the X, Y, Z coordinates of the voxels, the time-step, and the semblance or other measure of cumulative seismic activity in each voxel during each time-step. 6. The computed volumes are analyzed, edited, and then combined to produce a single stacked depth volume. The stacked volume may be a combination of data from minutes to hours and sometimes days. 7. The volume is clipped to eliminate low-level noise leaving sinuous clouds of high activity. 8. The Tomographic Fracture Image is generated by finding the central surfaces of the clouds. These central surfaces represent the large, seismically-active fractures. For hydraulic fracture monitoring, two slightly different proprietary workflows are used to produce two types of TFIs. Near-well TFIs show the highest energy features connected to or near the perforations, which are the induced fractures and most heavily stimulated natural fractures. Reservoir-scale TFIs show the total activity throughout the imaged volume. For ambient imaging studies only the reservoir-scale workflow is used. Other branches to this workflow include analysis of individual time steps to identify and locate microearthquake (MEQ) hypocenters or perforation shots and producing movies of cumulative activity volumes from moving-sums of time steps. The method works because:

3 URTeC Page 3 The earth s brittle crust is a self-organized critical system (e.g. Leary, 1997) in a state of frictional equilibrium due to pervasive fracturing (Zoback, 2007). Stress or pressure changes <0.01 atmospheres are sufficient to stimulate seismicity (Ziv and Rubin, 2000). Earthquake magnitude vs. frequency distributions are linear on log-log plots (magnitude is a logarithmic measure), so small earthquakes are many orders of magnitude more abundant than large ones and the distribution appears to have no lower magnitude limit (Ziv and Rubin, 2000). However, distinct earthquakes are not the only type of seismic activity. For these reasons, the brittle crust is constantly emitting seismic energy at a low level in the absence of artificial stimuli. Hydraulic fracture treatments stimulate activity both by reducing the normal stress on pre-existing natural fractures, breaking new rock, and altering the present-day stress state. Note that a pressure pulse can be transmitted through a fracture network without transmitting fluid (Lacazette and Geiser, 2013). An extensive, 18 year old body of work demonstrates that in many/most cases resolved shear stress on a fracture is correlated positively with its hydraulic transmissivity (e.g. Barton et al, 1995; Heffer et al, 1995; Morris et al, 1996; Ferrill et al, 1999; Sibson, 2000; Takatoshi and Kazuo, 2003; Tamagawa and Pollard, 2008; Heffer, 2012; Hennings et al, 2012). Higher resolved shear stress is positively correlated with seismic activity so that more microseismically active fractures are generally expected to be more hydraulically transmissive. Note that the converse is not necessarily true. Rock mechanics theory, field studies (e.g. Vermilye and Scholz, 1998) and experiment (e.g. Janssen et al, 2001) show that large fractures are embedded in clouds of smaller fractures and seismic emissions. Hence the central surfaces of high activity clouds are the loci of large fractures. TFI is extremely sensitive because it stacks total trace energy rather than simply looking for large, discrete events. Stacking total trace energy captures energy from numerous microearthquakes (MEQs) too small to discriminate as individual events and/or too small or indistinct to have separable P and S wave arrivals. These small events represent much more energy that the relatively-rare large MEQs amenable to standard seismological methods. Perhaps more importantly, stacking total trace energy captures energy from Long Period, Long Duration (LPLD) events (Das and Zoback, 2011; Zoback et al, 2012), and perhaps other as yet unclassified types of seismic activity. Stacking over extended time periods both adds tremendous sensitivity and images surfaces. Sensitivity is increased because random noise is canceled and spatially stable signal is stacked. Surfaces are imaged because activity along large fracture surfaces is episodic and extended time periods are required to fully image such surfaces. In common with other methods employing seismic emission tomography, TFI stacks energy from large numbers of traces which cancels noise and increases signal strength. The method detects only seismically active features, which leads to the following caveats: High resolved shear stress, and hence seismicity, does not always correlate positively with hydraulic transmissivity. Poroelastic stress waves induced by a hydraulic fracture treatment can cause fractures to become seismically active without a direct fluid connection to the wellbore. Weak features such as fault breccia zones may be very transmissive with little resolved shear stress or associated seismic activity because they are unable to support substantial shear stress. We find that such weak features are detected only sporadically along their length by this method and in some cases are not detected at all. The following sections provide examples of some ambient TFI results and brief discussions of independent data sets that validate the results. Drivers of ambient emissions are discussed subsequently. Example 1: Tight gas sand, southern West Virgina Figure 1 shows some passive seismic results from a detailed reservoir characterization study of stacked unconventional reservoirs carried out in the Upper Devonian section of southern West Virgina. Some aspects of this study are described in Lacazette and Geiser (2013), Geiser et al. (2012), Moos et al. (2011), Franquet et al. (2011), and Mulkern et al. (2010) and additional publications are in preparation. The TFI results were confirmed by chemical and radioactive tracer data, wellbore images and other data (Geiser et al 2012; Lacazette et al, in prep).

4 URTeC Page 4 The results show that pre-frac ambient seismic activity imaged major features revealed by frac monitoring. The zone of intense fracturing in the southwest corner of the study area is prominent and the highly transmissive area around the vertical well in the southwest corner of the diagram (west southwest of the horizontal wellhead) is identified. See Geiser et al (2012), especially Figure 6, for additional detail. This study was blind, so that well and other data was not known to personnel engaged in the TFI study until after delivery of the results. Figure 1. Depth slices of ambient activity and TFIs at the level of a horizontal well. North is up. LEFT Ambient image of four hours of cumulative seismic activity in the Berea Sandstone Fm. RIGHT TFIs from all 9 frac stages in the horizontal Berea well shown at the center of each diagram. A subsequent horizontal well (red bar in SW) confirmed that the area in the southwest is unusually heavily fractured and highly permeable. Example 2: Gas shale, Pennsylvania Figure 2 shows results from a fracture treatment of a well in an important gas shale formation. TFI and cumulative activity sums show that stage 3 of the horizontal well (A in Figure 2) immediately connected to an older vertical well (B in figure 2) through a preexisting natural fracture system. Well B was monitored for pressure and chemical tracers during the fracture treatment. Activity in the natural fracture system began immediately when stage 3 was pumped because increased fluid pressure in the fracture reduced the normal stress and hence friction along the feature thus allowing slip. During stage 4 activity was primarily confined to the area around well B. Pressure and chemical tracer anomalies were not detected in well B until commencement of stage 5. Two stages of pumping were required to move sufficient fluid to displace any preexisting fluid and account for leak-off into the rock matrix and natural fracture system. The ambient data shown at the lower right of Figure 2 is heavily contaminated by noise from a nearby factory, but some prominent features of the frac stage results were forecast by the ambient data. These features are the east-west trending feature that extends east of the wellbore (feature 1 in Figure 2) and the prominent NW-SE trending fracture zone just south of well B (feature 2 in Figure 2). Note that a fracture treatment provides much more energy than ambient emissions so that noise was much less of a problem for fracture monitoring. Had less coherent noise been present it is likely that more detail of the natural fracture network would have been resolved by the ambient data.

5 URTeC Page 5 Figure 2. Depth slices from a Tomographic Fracture Imaging study of a horizontal shale well. All slices are at the level of the wellbore. North is up. LEFT 10 minute semblance stack with horizontal treatment well (A) and offset vertical producer (B) shown in gray, Stage 3 perforation depth range in red. Stack shows the time interval shortly after breakdown when activity between the treatment well and vertical producer was declining. Blue = low cumulative seismic activity, red = high. CENTER Tomographic Fracture Image of stage 3. The fracture connecting the wells is imaged clearly. Color shows relative intensity of cumulative seismic activity (red high, blue low), as in image on left. TOP RIGHT Detailed view showing combined reservoir-scale TFIs for stages 1-5 (color). BOTTOM RIGHT Same as top right but with ambient TFI overlain in grayscale. Note that prominent features in the ambient data were later activated during the fracture treatment, especially the large fracture zones marked by 1 and 2. See text for discussion. Example 3: Carbonate anticline This section presents some highlights of an ambient imaging study performed on a carbonate anticline in the Colombian Andes. A surface array of standard 10 Hz vertical component geophones was deployed over the study area in a hexagonal closest-packed grid pattern and data was recorded continuously for four days. The array density was approximately 87 receiver points/km 2. This study was conducted blind, so that GMS personnel did not know of the well results or even the existence of these approx. 50-year-old wells prior to delivery of the passive seismic products. The study was conducted because a well-developed natural fracture system is required for production in this play. Structure in the study area is complex, as shown in Figure 3. An early thrust-fault-bend anticline, now largely inactive, is cut by wrench faults that are currently active. The current tectonic regime appears to be reactivating parts of the older thrust-fault-bend folds.

6 URTeC Page 6 Figure 3. Diagrams show the four-day cumulative seismic activity sum (stacked semblance) in relation to the geologic structure of the anticline. LEFT - Vertical section of interpreted PSDM reflection seismic data in grayscale with overlay of cumulative activity in color. RIGHT Horizon extraction of cumulative activity data overlain on a structure contour map of the horizon with fault cuts. Line of cross-section at left is shown. Hot colors represent high activity levels. Note the correspondence of activity with specific structural domains and in particular with the late, currently active wrench fault that cuts the anticline (right-hand diagram). Figure 4. Reservoir-level depth slice of the ambient TFI derived from the four-day activity sum shown in Figure 3. Symbols indicate well productivity. 0 = no production. S = some production. E = Excellent production. The role of earth tides Earth stress studies show that the earth s brittle crust is in a state of frictional equilibrium (Zoback, 2007). Recent studies that monitor slow crustal movements with permanent GPS base stations show that even relatively stable parts of the continental cratons are in constant motion and that crustal movement vectors have varying velocities and directions. The resulting vector fields can be used to produce strain maps that correlate with earthquake abundance.

7 URTeC Page 7 For examples see El-Fiky and Kato (2006), Tesauro et al (2006), and the U.S. National Geodetic Survey online toolkit (see references for link). These observations are relevant because they show that even very slow strain rates (as in Western Europe) keep the crust pervasively loaded with enough elastic strain energy to produce large earthquakes. Because earthquake size vs. frequency scales linearly on log-log plots with no apparent lower limit, subtle, widespread seismic activity is to be expected. In addition to tectonic movements, other forces including isostacy and isostacy-related flexure (e.g. Jurkowski et al, 1984) and even seasonal water loading (Davis et al, 2004) produce movements that contribute to the elastic strain energy stored in the crust. In summary, the earth s brittle crust is kept loaded with elastic strain energy from a variety of sources. What causes this pervasive strain energy to be released in the form of subtle, pervasive ambient seismicity? This question is important for commercial development of ambient seismic methods for several reasons, including the information that it may reveal about fracture system properties and perhaps determining optimum times and methods for sampling ambient activity. The answer to this question could have implications for fields beyond hydrocarbon exploitation including earthquake forecasting, the tidal energy balance of the earth-moon system, and tectonics. This section presents some of our work to date investigating the role that earth tides may play in ambient seismic emissions. Our approach is to relate bulk measures of cumulative seismic activity to earth tides. The data presented in this section are from the carbonate anticline study described here as Example 2. The volume of rock studied was km 3 (33.0 mi 3 ). We used the mean cumulative semblance value in discrete time intervals as a measure of the bulk seismic activity within the study volume and compared it to displacement variables representing the earth tide movements in the corresponding time period. Earth tide movements for the study area were computed using software available from the U.S. National Geodetic Survey (Figure 5). The north-south, east-west, and vertical components of movement have different periods and are out-of-phase because of the complex and constantly changing angular relationships between the earth, sun, and moon. Consequently, the average activity variable cannot be examined as a function of time. Instead we have compared the average activity to the earth tide displacements, linear and angular velocities and accelerations in terms of a vector that connects a point on the earth before and after a specified time period (Figure 6). We computed velocities in the north-south, east-west, and vertical directions, the angular velocities with respect to these axes, the total length of the displacement vector, the horizontal length of the displacement vector, and the horizontal angular velocity (Figure 6). Corresponding accelerations were also computed. Figure 5. Earth tides for the four-day survey period and the days before and after computed with software from the U.S. National Geodetic Survey. The north-south, east-west, and vertical movement components are shown separately. Note that the components are out-of-phase.

8 URTeC Page 8 Figure 6. LEFT Diagram illustrating the displacement variables computed from the earth tide data. The variables represent the magnitude and orientation of a vector that connects the same point on the earth at the beginning and end of a specified time period and hence represent velocities. Accelerations are also computed. RIGHT The displacement variables used for the regression shown in Figure 8 with the sensitivities, i.e. the predictive values of the variables for the regression. Experimentation with different time intervals showed that averaging over a 20 minute interval was required to reveal structure in the data (Figure 7). Simple crossplots of such moving averages (e.g. Figure 7) indicate that there is structure in the data and that multiple variables are likely required to predict bulk ambient activity from earth tide movements. Figure 7. Crossplot of the 20 minute moving averages of the absolute length of the total displacement vector (Figure 6) vs. the mean activity measure in the study volume. We performed the exploratory multivariate statistics presented here with the Transform software package ( Non-parametric, non-linear multivariate statistical analysis (regression) was performed to predict the activity variable from various combinations of the displacement variables. The results show that 40% - 50% of the variability of the mean ambient seismicity in the entire volume can be predicted by various combinations of the displacement variables. Figure 8 shows the results of a run with all of the variables shown in the table in Figure 6. Eliminating variables with low positive or negative sensitivities yields plots similar to Figure 8 but with somewhat lower R 2 values. A run with only the North, NorthAngle, Horizontal, and Total velocities explains 40% of the observed variability of the mean activity (i.e. has an R 2 of 0.4).

9 URTeC Page 9 We find these correlations remarkably high given that they represent an average of km 3 (33.0 mi 3 ) of structurally complex rock riddled with a complex fracture network (Figures 3 and 4). Furthermore, the complex polyphase structure and active deformation in the study volume must be producing a very complex stress regime within the structures. The four-day cumulative intensity of ambient activity is related clearly to distinct structural domains (e.g. fold panels, see Figure 3). It is likely that different structural domains and faults and other fractures with different orientations in each structural domain are stimulated differently by earth tide movements in different directions. We suspect that separate analysis of homogeneous structural domains will yield stronger correlations between earth tides and ambient seismic emissions. This work is ongoing. These results raise the possibility that the seismic response to earth tide displacement components could represent a measure of natural fracture orientations and other fracture network properties and perhaps even aspects of the fracture flow regime. Figure 8. Predicted mean activity (vertical axis) vs. observed mean activity (horizontal axis) in 20 minute intervals. See text for discussion. Conclusions We conclude that ambient seismic emissions can be imaged to reveal parts of hydraulically transmissive natural fracture networks whose existence can be verified by independent data sets. We tentatively conclude that earth tides measurably affect the intensity of ambient seismic emissions. Acknowledgements The authors gratefully acknowledge our clients (who choose to remain anonymous) for both permission to publish the results presented here and especially for their insight and courage to work with a radical new technology. We also acknowledge the work of the following Global Geophysical Services personnel: Gloria Eisenstadt for the structural interpretation shown in Figure 3, Sean Boerner and Rohit Singh for their work on multivariate statistical analysis of the earth tide data, and the numerous personnel of both Global and other companies who worked on the acquisition and processing of the ambient and reflection seismic data presented here. References Barton, C.A., Zoback, M.D., Moos, D., Fluid flow along potentially active faults in crystalline rock. Geology 23 (8),

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