Seismic imaging in thrust-belt environments like the foothills of the Himalayas benefits significantly from interpretive input to velocities used for time and depth migration. With low fold in the near surface, low signal-to- noise ratios on the image gathers, and complex horizon geometries, automated velocity-model-building tools fail to produce an optimum velocity model for TTI anisotropic depth imaging. In a setting with such under-constrained velocities, geologic constraints are crucial in the interpretation of our velocity model. 

 

The goal of our imaging strategy is to get the most from each algorithm: robustness from prestack time migration (PSTM) and geological accuracy from anisotropic prestack depth migration (APSDM). The delicate nature of depth imaging makes it an effective diagnostic on subsurface interpretation, but at times it can be unstable. We view PSTM and APSDM as complementary technologies, with the clearest basic image coming from the PSTM and the accuracy needed to reduce drilling risk from APSDM. 

 

Complex-structure data examples illustrate how integrating geologic data into our velocity analysis processes improves the clarity of PSTM images and accuracy of corrections for velocity heterogeneity and anisotropy effects with APSDM.