A Refinement of the Generalized Blind Deconvolution Method Based on the Gaussian Mixture and its Application

 

Abstract

A two-channel blind deconvolution method is developed and clearly shown to be capable of recovering the unknown reflectivity sequences from two observation data sets. The blind deconvolution technique, based on the Gaussian mixture model for the reflectivity sequence, had previously been developed, but it has one shortcoming which is that the order of the inverse filter could not be determined, thus preventing the removal of the source wavelet from the observation data. Here, this imperfection is overcome by using a technique that identifies the optimum order by using two time sequences along with the cost function. Two synthetic seismograms are used to examine the technique, and very good results are obtained. We, therefore, apply the method to analyze seismic exploration data and determine the location of the reflective signal where the reflectivity of each channel is consistent. This clearly indicates that this enhanced method is, indeed, effective for determining the true layering effect when it is applied to seismic exploration data.

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