Subsalt optimal survey design with dipping scatterers

We describe a Bayesian framework for designing seismic surveys that takes into account the anisotropic nature of the radiation patterns associated with scattering from locally dipping interfaces. These interfaces are modeled as a discrete set of finite-size planar scattering elements, with the size of each element controlling the width of its radiation pattern. We show that the size of these dipping scatterers may be used to characterize the uncertainty on the dip angles that is observed on many subsalt reservoir illumination problems, thus complementing the information provided by the model-parameter uncertainties and ultimately leading to better survey designs. The benefits of the proposed method are further demonstrated with a coil survey design that aims at illuminating a complex subsalt reservoir in deep water Gulf of Mexico.