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Anisotropy signature in reverse‐time migration extended images
Author(s) -
Sava Paul,
Alkhalifah Tariq
Publication year - 2015
Publication title -
geophysical prospecting
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.735
H-Index - 79
eISSN - 1365-2478
pISSN - 0016-8025
DOI - 10.1111/1365-2478.12189
Subject(s) - anisotropy , geology , gemology , signature (topology) , point (geometry) , economic geology , normal moveout , environmental geology , image (mathematics) , regional geology , seismic migration , residual , mineralogy , optics , geophysics , computer science , algorithm , telmatology , seismology , engineering geology , geometry , artificial intelligence , physics , tectonics , mathematics , volcanism
Reverse‐time migration can accurately image complex geologic structures in anisotropic media. Extended images at selected locations in the Earth, i.e., at common‐image‐point gathers, carry rich information to characterize the angle‐dependent illumination and to provide measurements for migration velocity analysis. However, characterizing the anisotropy influence on such extended images is a challenge. Extended common‐image‐point gathers are cheap to evaluate since they sample the image at sparse locations indicated by the presence of strong reflectors. Such gathers are also sensitive to velocity error that manifests itself through moveout as a function of space and time lags. Furthermore, inaccurate anisotropy leaves a distinctive signature in common‐image‐point gathers, which can be used to evaluate anisotropy through techniques similar to the ones used in conventional wavefield tomography. It specifically admits a V‐shaped residual moveout with the slope of the “V” flanks depending on the anisotropic parameter η regardless of the complexity of the velocity model. It reflects the fourth‐order nature of the anisotropy influence on moveout as it manifests itself in this distinct signature in extended images after handling the velocity properly in the imaging process. Synthetic and real data observations support this assertion.