Recursive decision directed estimation of reflection coefficients for seismic data deconvolution

Abstract

This paper concerns the problem of estimation of the location and intensity of reflections of a seismic wavelet. A recursive maximum a posteriori probability (MAP) algorithm is derived as an alternative to the maximum likelihood (ML) algorithm of Mendel and Kormylo. The MAP approach proposed here yields a suboptimal detector which is substantially different in details from the corresponding approximate ML detector of Mendel and Kormylo. Simulation studies are presented to show that the MAP detector performs as well as the ML detector and can yield comparable results with much less computational effort. A comparative study of both the MAP and ML detectors has been made via simulations which show some interesting differences in structure as well as performance.