3‐D converted‐wave processing: Wind river basin case history

Dok, Richard R. Van; Gaiser, James; Jackson, Alexander; Lynn, Heloise B.

doi:10.1190/1.1885613

Cited by 4 publications

(2 citation statements)

References 5 publications

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“…The use of positive and negative source-receiver offsets can help with improved velocity analysis and imaging (Dai et al, 2000). Van Dok et al (1997) outline a 3C-3D processing flow for data acquired in the Wind River Basin, Wyoming. Key steps in their sequence are full P-P processing of the vertical geophone data (especially for source statics and velocities to be used with the P-S data), edits of the horizontal components, coherent noise filtering, surface-consistent statics, deconvolution, CCP binning, Alford rotation, anisotropic layer stripping, P-S NMO, stack, and 3-D f -k migration.…”

Section: P-s Data Processingmentioning

confidence: 99%

Converted‐wave seismic exploration: Methods

Gaiser²,

et al. 2002

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Multicomponent seismic recording (measurement with vertical-and horizontal-component geophones and possibly a hydrophone or microphone) captures the seismic wavefield more completely than conventional single-element techniques. In the last several years, multicomponent surveying has developed rapidly, allowing creation of converted-wave or P-S images. These make use of downgoing P-waves that convert on reflection at their deepest point of penetration to upcoming S-waves. Survey design for acquiring P-S data is similar to that for P-waves, but must take into account subsurface V P /V S values and the asymmetric P-S ray path. P-S surveys use conventional sources, but require several times more recording channels per receiving location. Some special processes for P-S analysis include anisotropic rotations, S-wave receiver statics, asymmetric and anisotropic binning, nonhyperbolic velocity analysis and NMO correction, P-S to P-P time transformation, P-S dip moveout, prestack migration with two velocities and wavefields, and stacking velocity and reflectivity inversion for S-wave velocities.Current P-S sections are approaching (and in some cases exceeding) the quality of conventional P-P seismic data. Interpretation of P-S sections uses full elastic ray tracing, synthetic seismograms, correlation with P-wave sections, and depth migration. Development of the P-S method has taken about 20 years, but has now become commercially viable.

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Section: P-s Data Processingmentioning

confidence: 99%

Converted‐wave seismic exploration: Methods

Gaiser²,

et al. 2002

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“…After processing and analysing the data, they find indications of fracture direction from their calculated anisotropy. Gaiser (1999) and Van Dok et al (1997) show analyses of a full 3C-3D seismic survey from the Madden field in the Wind River Basin, Wyoming. This analyses uses 4-component Alford (1986) rotations and layer stripping (Winsterstein and Meadows, 1991a) to calculate the fast shear-wave (P-S 1 ) polarization direction and the associated percent anisotropy.…”

Section: Anisotropy and Fracture Analysismentioning

confidence: 99%

Converted‐wave seismic exploration: Applications

Gaiser²,

et al. 2003

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Converted seismic waves (P-to-S on reflection) are being increasingly used to explore for subsurface targets. Rapid advancements in multicomponent acquisition methods and processing techniques have led to numerous applications for P-S images. Uses that have arisen include sand/shale differentiation, carbonate identification, definition of interfaces with low P-wave contrast, anisotropy analysis, imaging through gas zones, shallow high-resolution imaging, and reservoir monitoring. Marine converted-wave analysis using 4-C recordings (a three-component geophone plus a hydrophone) has generated some remarkable images. BACKGROUND

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

et al. 1999

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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 fractureparallel 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 Pand 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.

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3‐D converted‐wave processing: Wind river basin case history

Cited by 4 publications

References 5 publications

Converted‐wave seismic exploration: Methods

Converted‐wave seismic exploration: Methods

Converted‐wave seismic exploration: Applications

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

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