A hybrid second- and higher-order statistical method for blind deconvolution of seismic data
G. Tong Zhou, Anthony Vassiliou · 2002
Successful deconvolution of the seismic traces in exploration seismology relies on accurate wavelet estimation. We model the wavelet as the impulse response of a pole-zero model and allow it to be non-casual and/or non-minimum phase. We first employ second-order statistics of the data to construct spectrally equivalent models and then find the "best" model according to a fourth-order cumulant matching criterion. Both the lower variance property of the second-order statistics and the ability of the higher-order statistics to distinguish spectrally equivalent models are taken advantage of. Numerical examples illustrate the key points of the paper.