Imaging in deep-water environments poses a specific set of challenges, both in data preconditioning and velocity model building. These challenges include scattered, complex 3D multiples, aliased noise, and low-velocity shallow anomalies associated with channel fills and gas hydrates. We describe an approach to tackling such problems for data from deep water off the east coast of India, concentrating our attention on iterative velocity model building, and more specifically the resolution of near-surface and other velocity anomalies. In the region under investigation, the velocity field is complicated by narrow buried canyons ([Formula: see text] wide) filled with low-velocity sediments, which give rise to severe pull-down effects; possible free-gas accumulation below an extensive gas-hydrate cap, causing dimming of the image below (perhaps as a result of absorption); and thin-channel bodies with low-velocity fill. Hybrid gridded tomography using a conjugate gradient solver (with [Formula: see text] vertical cell size) was applied to resolve small-scale velocity anomalies (with thicknesses of about [Formula: see text]). Manual picking of narrow-channel features was used to define bodies too small for the tomography to resolve. Prestack depth migration, using a velocity model built with a combination of these techniques, could resolve pull-down and other image distortion effects in the final image. The resulting velocity field shows high-resolution detail useful in identifying anomalous geobodies of potential exploration interest.
Spatial variations in the transmission properties of the overburden cause seismic amplitude attenuation, wavelet phase distortion and seismic resolution reduction on deeper horizons. This poses problems for the seismic interpretation, tying of migration images with well-log data and AVO analysis. We developed a prestack depth Q migration approach to compensate for the frequency dependent dissipation effects in the migration process. A 3D tomographic amplitude inversion approach may be used for the estimation of absorption model. Examples show that the method can mitigate these frequency dependent dissipation effects caused by transmission anomalies and should be considered as one of the processes for amplitude preserving processing that is important for AVO analysis when transmission anomalies are present.
Spatial variations in the transmission properties of the overburden cause seismic amplitude attenuation, wavelet phase distortion and seismic resolution reduction on deeper horizons. This poses problems for the seismic interpretation, tying of migration images with well-log data and AVO analysis. We developed an efficient prestack beam Q migration approach to compensate for the frequency dependent dissipation effects in the migration process. A 3D tomographic amplitude inversion approach may be used for the estimation of absorption model. Examples show that the method can mitigate these frequency dependent dissipation effects caused by transmission anomalies and should be considered as one of the processes for amplitude preserving processing that is important for AVO analysis when transmission anomalies are present.
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