Detection and analysis of naturally fractured gas reservoirs: Multiazimuth seismic surveys in the Wind River basin, Wyoming

Abstract Multiazimuth binning of 3-D P-wave reflection data is a relatively simple but robust way of characterizing the spatial distribution of gas-producing natural fractures. In our survey, data were divided into two volumes by ray azimuth (approximately perpendicular and parallel (±45° to the dominant fracture strike) and separately processed. Azimuthal differences or ratios of attributes provided a rough measure of anisotropy. Improved imaging was also attained in the more coherent fracture-parallel volume. A neural network using azimuthally dependent velocity, reflectivity, and frequency attributes identified commercial gas wells with greater than 85% success. Furthermore, we were able to interpret the physical mechanisms of most of these correlations and so better generalize the approach. The apparent velocity anisotropy was compared to that derived from other P- and S-wave methods in an inset three-component survey. Prestack determination of the azimuthal moveout ellipse will best quantify velocity anisotropy, but simple two- or four-azimuth poststack analysis can adequately identify regions of high fracture density and gas yield.