Evaluating the performance of Minimum Weighted Norm Interpolation in case of random and regular sampling

Abstract

In seismic data processing, we often need to interpolate and extrapolate missing data at spatial locations. The reconstruction problem can be posed as an inverse problem where from inadequate and incomplete data we attempt to reconstruct the seismic wavefield at locations where measurements were not acquired. This study presents a wavefield reconstruction scheme called minimum weighted norm interpolation (MWNI) for spatially band limited signals. The method entails the solution of an inverse problem where wavenumber domain regularization term is included. The regularization term is not only used to constrain the solution to be spatially band limited but also to impose apriori spectral shape. In this paper we tested Minimum weight Norm Interpolation method on both regularly and randomly sampled seismic data set with linear and nonlinear events.