In many areas, available seismic acquisition data may not be optimal, and purely data-driven velocity modeling methods are inadequate to resolve specific imaging problems. In this case study to image beneath a fault shadow offshore in the Gulf of Mexico, limitations of the available data were the original motivation to incorporate various interpretation-derived constraints in conjunction with data-driven tomographic velocity updates to improve the overall velocity modeling process. Automated tomographic modeling is increasingly relied upon to produce high-quality models in cases of robust data input. However, in the case of sub-optimal acquisition that limits illumination, and noise and multiples that affect the ability to pick residual moveout, interpretation constraints can enhance data-driven modeling. Strategies incorporated here include "manually seeded" velocity analysis, explicit interpretation-guided pick weighting, and implicit geologic steering filters based on dip fields. The goal of the study is to highlight effective strategies for interpretationconstrained modeling to complement data-driven modeling in an effective holistic workflow.

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The goal of repeat imaging (detailed studies of prospects as new information is available) using PSDM is to generate new locations for both development and exploration targets. We present two case studies of repeat imaging and grid tomography in the Gulf of Mexico acreage. The first field (field H) consists of angular beddings truncating at the base of a thick salt. The second field (field T) consists of sediments under a salt of unknown thickness where well control shows only thin salt penetration. The up dip potential of the pay sands for both prospects had not been shown clearly in the previous depth processing. A careful model building approach with automated residual moveout estimation and 3-D grid tomography in the supra-salt area enabled us to estimate the sediment velocity properly. This helped us to reinterpret the top salt and base salt and enhance the sub-salt reflections. We provide two examples of the velocity model building and depth imaging in this area.

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Obtaining an accurate velocity model is fundamental to successfully imaging complex salt bodies in the deep Gulf of Mexico. With the introduction of faster, full volume wavefield solutions that output finely-sampled angle gathers, velocity models can be constructed allowing the full potential of the wavefield method to be applied to our most complex subsurface problems. We present a case history of building a high-resolution velocity model in the Gulf of Mexico, using multiple iterations of wave-equation migration and angle common image gathers (ACIG). We show how in certain instances picking in depth slices can build more detail in the velocity model, and how we integrated well log information and other stratigraphic geological information into the velocity model in collaboration with the interpreter team, to produce an optimal depth migrated image.