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 degrees) 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.
Original language | English |
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Pages (from-to) | 1277-1292 |
Number of pages | 16 |
Journal | Geophysics |
Volume | 64 |
Issue number | 4 |
Publication status | Published - Jul 1999 |
Keywords
- AZIMUTHAL ANISOTROPY
- ELASTIC-ANISOTROPY
- WAVE-PROPAGATION
- MEDIA
- ATTENUATION
- DIRECTIONS
- CONSTANTS
- EQUATIONS
- MOVEOUT
- CRACKS