Regularized inversion for imaging: Effect on the data space

Marie L. Clapp

marie@sep.Stanford.EDU

ABSTRACT

Imaging in areas of complex subsurfaces is difficult due to poor illumination. This poor illumination is partially caused by seismic energy being directed outside of the survey bounds. Imaging in areas with poor illumination can be improved by using Regularized Inversion with model Preconditioning (RIP). RIP helps compensate for poor illumination by regularizing amplitudes in the image. By compensating for the lost energy, RIP in essence expands the data space.