The Barnett Shale is one of the first and most fully developed shale gas plays in North America. In this play, the knowledge of natural and induced fracture orientation and intensity is of great importance in the choice of drilling direction and completion program. In this study, the organic-rich Barnett Shale reservoir has been extensively hydro-fractured by high pressure to simulate production prior to the acquisition of the 3D seismic survey. The objective is to recognize gas- or water- charged induced damaged rock and to identify any bypassed pay. We migrate our seismic data using a new binning approach that sorts the data by azimuth as it is imaged in the subsurface. The motivation for this binning method is to better image lineaments as indicated by the most-positive principal curvature. We find a preferential image when structural lineaments lie perpendicular to the illumination direction. We also measure the impedance as a function of azimuth in an effort to determine the present day stress field and induced fractures in the Barnett Shale. Since velocity is anisotropic in the presence of anisotropic stress fields and/or the presence of natural or induced fractures, Pwave impedance, which is the product of density and velocity, is also anisotropic. The resultant image of the azimuth of maximum impedance and degree of impedance anisotropy correlates well with the k1 most positive principal curvature.
The Barnett Shale is an important unconventional shale gas system in the Fort Worth Basin, Texas where it serves as a source rock, seal, and trap. Since it has a very low permeability for production, Devon energy launched a program that fractured the rocks in the field in recent years by injecting high pressure fluid with 10 wells per square mile, thereby significantly improving the production rate. Accurately mapping the orientation and frequency of occurrence of fractures, and the stress field can significantly impact production from horizontal wells. Seismic data offers an indirect measure of fractures and stress field though using shear wave birefringence (Alford, 1986; Crampin, 1985; Michelena, 1995), P-wave velocity variation with azimuth (Sicking et al., 2007; Roende et al., 2008; Jenner, 2001; Treadgold et al., 2008), Amplitude vs. Azimuth (AVAz) (Ruger, 1998; Luo et al., 2004; Goodway et al., 2006), and seismic attribute analysis (Chopra et al., 2007; Chopra et al., 2008). In this study, the seismic data are migrated into different azimuth by using the new binning approach which has proven to be effective for improved illumination of faults and fractures. Next, prestack-conditioning is applied to CRP gathers to improve the signal-noise ratio. Next we corrected for velocity anisotropy by snapping the full azimuth picks to the azimuth limited picks and flattening on the base horizon. Once flattened, we fit sinusoids to the four AI volumes to obtain the maximum AI direction and degree of AI anisotropy at each sample. We hypothesize that the resulting azimuthal AI anomalies are due to a combination of hydraulically-induced fluid-filled fractures and azimuthal variation in the horizontal stress.
