Internal multiple prediction on Hussar synthetics

Pan (Penny) Pan, Kristopher A. Innanen

The inverse scattering series internal multiple prediction algorithm is often called upon due to its unique ability to predict internal multiples with no subsurface information and without compromising the primaries. This technology does not require velocity information from the subsurface or any advance knowledge of the multiple generators, and it predicts first-order internal multiples that are generated by all possible generators below the free surface. In this paper, we employ the 1.5D internal multiple prediction algorithm on Hussar synthetics. The synthetics are acquired by blocking the well 12-27 with different depth steps. We find that it can successfully predict internal multiples generated by the relatively thin layers of the Hussar geology (provided the interval between two primaries is larger than the optimal value). By extending the synthetic in offset, we see that certain prediction artifacts can be tied to land apertures.