Adaptive Deconvolution of Seismic Signals

Seismic signals are often modeled as the convolution of a wavelet with the earth reflectivity function. Deconvolution, for the purpose of obtaining the reflectivity function, can be done using state space estimation methods. Such methods are hampered, however, by lack of precise modeling information. The deconvolution problem then becomes an adaptive estimation problem. In this paper the correct model is assumed to be one of a finite set of candidate models, and adaptive deconvolution is accomplished using estimation algorithms developed for this type of model uncertainty.