Seismic homomorphic blind deconvolution based on high order statistics constraint
Sinopec Exploration · Shiyou diqiu wuli kantan · 2013
A high order statistical method,so called,in-dependent components analysis(ICA)with constraint of seismic wavelet estimated from bispectrum of seismic traces,is introduced in this paper to improve the traditional homomorphic seismic deconvolution method.In the noise-free condition,seismic records are converted from the time domain to the complex cepstrum domain in order to transform the common seismic model to the basic ICA model.By applying FastICA algorithm,reflectivity series and the seismic wavelet can be produced in complex cepstrum domain and converted back to the time domain subsequently.Model and real seismic data numerical examples show that this method can blindly and effectively inverse the wavelet and the reflectivity at the same time without the assumptions of Gauss reflectivity white noise and wavelet minimum phase.The algorithm referred here is an updated version of homomorphic deconvolution methods for seismic signal blind deconvolution and merits more researches.