Non-Gaussian modeling is used to generalize Wiener-Levinson (WL) deconvolution and to obtain a procedure that is more robust to nonstationarities in the reflectivity and to correlated noise. This generalization can lead to up to a 60% reduction in the dynamic range of the residual wavelet's amplitude response and in the rms error of phase estimates. In addition, it reduces to WL deconvolution when the reflectivity is Gaussian or when noise masks the nonstationary features of the reflectivity.

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