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《Oil Geophysical Prospecting》 2015-04
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3D seismic random noise suppression with sparse and redundant representation

Zhang Guangzhi;Chang Dekuan;Wang Yihui;Li Zhenzhen;Zhao Yang;Yin Xingyao;School of Geosciences,China University of Petroleum (East China);Northwest Branch of Petroleum Research Institute of Exploration and Development,PetroChina;Geophysical Exploration Research Institute,Huabei Oilfield Company,PetroChina;  
Conventional methods to suppress random noise work very well for 2Dseismic data,but not for 3Dseismic data.Therefore we present in this paper a new method to remove random noise from3 Dseismic data,which is driven by sparse and redundant representation algorithm.Under Bayesian framework,this method uses 3D overcomplete DCT dictionary to sparsely and redundantly represent seismic data.Using orthogonal matching pursuit(OMP)and K-singular value decomposition(K-SVD)continuously to update 3Dsparse matrix and 3D overcomplete DCT dictionary,random noise of 3Dseismic data can be significantly suppressed.We apply this proposed method to both3 Dtheoretical and real seismic data together with conventional f-x deconvolution method and K-L transform method.Application results show that the proposed method can improve signal to noiseratio and protect seismic signals,and slice continuity and smoothness,and the resolution of complicated structures are also improved.
【Fund】: 国家“973”项目(2014CB239201 2013CB228604);; 国家油气重大专项(2011ZX05014-001-010HZ)资助
【CateGory Index】: P631.44
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