A Fast Optimal Deconvolution Algorithm for Real Seismic Data Using Kalman Predictor Model

The paper is concerned with an application of a recently proposed algorithm for minimal realization of stochastic dynamic systems to the problem of deconvolution of reflection seismograms. Results of real data processing are presented in order to establish the advantages of this algorithm in terms of computational requirements and accuracy of signal estimation vis-à-vis the widely accepted algorithm of Robinson and Treitel.