Seismic homomorphic blind deconvolution based on high order statistics constraint
Sun Jianye1, Gao Wei2, Liu Huaishan1, Liu Xiwu3
1. College of Marine Geosciences,Ocean University of China,Qingdao,Shandong 266100,China;
2. National Deep Sea Center of China,Qingdao,Shandong 266061,China;
3. SINOPEC Exploration & Production Research Institute,Beijing 100083,China
Abstract：A high order statistical method socalled,in-dependent components analysis(ICA)with con-straint of seismic wavelet estimated from bispec-trum of seismic traces，is introduced in this paperto improve the traditional homomorphic seismic de-convolution method.In the noise-free condition,seismic records are converted from the time domainto the complex cepstrum domain in order to trans-form the common seismic model to the basic ICAmodel.Bv applying FastICA algorithm，reflectivi-tv series and the seismic wavelet can be producedin complex cepstrum domain and converted back tothe time domain subsequently.Model and realseismic data numerical examples show that thismethod can blindly and effectively inverse thewavelet and the reflectivity at the same time with-out the assumptions of Uauss reflectivity whitenoise and wavelet minimum phase.The algorithmreferred here is an updated version of homomorphicdeconvolution methods for seismic signal blind de-convolution and merits more researches.
孙建业, 高伟, 刘怀山, 刘喜武. 基于高阶统计约束实现同态盲地震反褶积[J]. 石油地球物理勘探, 2013, 48(1): 31-36.
Sun Jianye, Gao Wei, Liu Huaishan, Liu Xiwu. Seismic homomorphic blind deconvolution based on high order statistics constraint. OGP, 2013, 48(1): 31-36.
