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.