Estimating subsurface stress direction and intensity from surface full azimuth land data

Roende, H.; Meeder, Charles A.; Allen, James; Peterson, Steven M.; Eubanks, Darrell; Ribeiro, Christophe

doi:10.1190/1.3054791

Cited by 13 publications

(4 citation statements)

References 4 publications

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“…Survey A was acquired in 2006 using 16 live receiver lines forming a wide-azimuth survey with a nominal 16.7 × 16.7 m (55 × 55 ft) common-depth point (CDP) bin size. The data were preprocessed and binned into six azimuths, preserving the amplitude fidelity at each step before prestack time migration (Roende et al, 2008). A 3 trace × 3 trace × 7 sample (inline axis × crossline axis × vertical axis) analysis window is used to compute coherence.…”

Section: Applicationmentioning

confidence: 99%

Multiazimuth coherence

et al. 2017

SEG Technical Program Expanded Abstracts 2017

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Since its introduction two decades ago, coherence has been widely used to map structural and stratigraphic discontinuities such as faults, cracks, karst collapse features, channels, stratigraphic edges, and unconformities. With the intent to map azimuthal variations of horizontal stress as well as to improve the signal-to-noise ratio of unconventional resource plays, wide-/ full-azimuth seismic data acquisition has become common. Migrating seismic traces into different azimuthal bins costs no more than migrating them into one bin. If the velocity anisotropy is not taken into account by the migration algorithm, subtle discontinuities and some major faults may exhibit lateral shifts, resulting in a smeared image after stacking. Based on these two issues, we evaluate a new way to compute the coherence for azimuthally limited data volumes. Like multispectral coherence, we modify the covariance matrix to be the sum of the covariance matrices, each of which belongs to an azimuthally limited volume, and then we use the summed covariance matrix to compute the coherent energy. We validate the effectiveness of our multiazimuth coherence by applying it to two seismic surveys acquired over the Fort Worth Basin, Texas. Not surprisingly, multiazimuth coherence exhibits less incoherent noise than coherence computed from azimuthally limited amplitude volumes. If the data have been migrated using an azimuthally variable velocity, multiazimuth coherence exhibits higher lateral resolution than that computed from the stacked data. In contrast, if the data have not been migrated using an appropriate azimuthally variable velocity model, the misalignment of each image results in a blurring of the multiazimuth coherence and the coherence computed from the stacked data. This suggests that our method may serve as a future tool for azimuthal velocity analysis.

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Section: Applicationmentioning

confidence: 99%

Multiazimuth coherence

et al. 2017

SEG Technical Program Expanded Abstracts 2017

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“…A 3D seismic acquisition program was undertaken in 2006 by Marathon Oil Company using 16 live receiver lines forming a wide-azimuth survey with a nominal 16 × 16 m (55 × 55 ft) CDP bin size to image the Barnett Shale at approximately 914 m (3000 ft) true vertical depth subsea (TVDSS) or 0.7 s two-way time (TWT) (Roende et al, 2008). Although data quality is excellent, minor improvements through poststack data conditioning can significantly facilitate and improve subsequent interpretation.…”

Section: Data Conditioningmentioning

confidence: 99%

Attribute expression of fault-controlled karst — Fort Worth Basin, Texas: A tutorial

Zhang

Zhou

et al. 2014

Interpretation

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Much of seismic interpretation is based on pattern recognition, such that experienced interpreters are able to extract subtle geologic features that a new interpreter may easily overlook. Seismic pattern recognition is based on the identification of changes in (1) amplitude, (2) phase, (3) frequency, (4) dip, (5) continuity, and (6) reflector configuration. Seismic attributes, which providing quantitative measures that can be subsequently used in risk analysis and data mining, partially automate the pattern recognition problem by extracting key statistical, geometric, or kinematic components of the 3D seismic volume. Early attribute analysis began with recognition of bright spots and quickly moved into the mapping of folds, faults, and channels. Although a novice interpreter may quickly recognize faults and channels on attribute time slices, karst terrains provide more complex patterns. We sought to instruct the attribute expression of a karst terrain in the western part of the Fort Worth Basin, Texas, United States of America. Karst provides a specific expression on almost every attribute. Specifically, karst in the Fort Worth Basin Ellenburger Group exhibits strong dip, negative curvature, low coherence, and a shift to lower frequencies. Geomorphologically, the inferred karst geometries seen in our study areas indicate strong structural control, whereby large-scale karst collapse is associated with faults and where karst lineaments are aligned perpendicularly to faults associated with reflector rotation anomalies.

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“…The need to better understand the fractured nature of reservoirs has encouraged the acquisition of wide azimuth data. Many 3D land surveys are being designed to have enough fold, azimuth and offset coverage for a proper azimuthal processing sequence, allowing for the estimation of subsurface stress direction and intensity as ell as other attributes (Roende et al 2008) w…”

Section: Ntroduction Imentioning

confidence: 99%