Blind deconvolution of seismic data based on Kagan divergences

We proposes a new approach to the seismic blind deconvolution problem in the case of band-limited seismic data with a low dominant frequency and short data records, based on the Csiszár's f-divergence. In order to model the probability density function of the deconvolved data, and obtain the closed form formula of Kagan divergence, mixture Jones' family of distributions (MJ) is introduced, by which a new criterion for blind deconvolution is constructed. By applying N. S. Neidell's wavelet model to the inverse filter, we then make the optimization program for multivariate reduce to univariate case. Examples are provided showing the good performance of the method even in low SNR.