71st EAGE Conference and Exhibition Incorporating SPE EUROPEC 2009 2009
DOI: 10.3997/2214-4609.201400160
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A Regularization Workflow for the Processing of Cross-spread COV Data

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Cited by 4 publications
(4 citation statements)
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“…After this step, the best possible input is obtained for further analysis, such as azimuthal anisotropy analysis (Section 2.6.11). Poole et al (2009) provide more details on this regularization technique. Plasterie et al (2009) apply this technique for regularization in pseudo-COV gathers and obtain better shallow images with OVT processing than with conventional absolute offset processing.…”
Section: Interpolation and Regularizationmentioning
confidence: 99%
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“…After this step, the best possible input is obtained for further analysis, such as azimuthal anisotropy analysis (Section 2.6.11). Poole et al (2009) provide more details on this regularization technique. Plasterie et al (2009) apply this technique for regularization in pseudo-COV gathers and obtain better shallow images with OVT processing than with conventional absolute offset processing.…”
Section: Interpolation and Regularizationmentioning
confidence: 99%
“…In a regular WAZ geometry, inline offset and crossline offset should be regularly distributed, as in Figure 2.17a. To arrive at such a distribution from a pseudorandom geometry, there are two essential steps, similar to those described in Poole et al (2009), for irregular land data acquired with orthogonal geometry: (1) interpolate data to a regular grid of midpoints, then (2) interpolate data in each midpoint to a regular Cartesian grid or to regular polar coordinates.…”
Section: Coil Shootingmentioning
confidence: 99%
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“…Because of this, an azimuthally varying velocity field was required during the pre-processing for applications such as residual statics and 3D Radon, as well as to generate QC stacks. For the velocity model building and imaging, the data were binned, regularized and migrated using common offset vector (COV) bins (Poole et al, 2009). COV bins are cartesian common-offset bins, defined by offset-x and offset-y, that allow the acquired offset and azimuth to be honored through the imaging process.…”
Section: Data Processing and Imagingmentioning
confidence: 99%