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一种改进的基于非高斯性最大化的预测反褶积算法
引用本文:刘军,陆文凯.一种改进的基于非高斯性最大化的预测反褶积算法[J].应用地球物理,2008,5(3):189-196.
作者姓名:刘军  陆文凯
作者单位:清华大学自动化系智能技术与系统国家重点实验室
基金项目:国家高技术研究发展计划(863计划),国家自然科学基金,NCET Fund
摘    要:The predictive deconvolution algorithm (PD), which is based on second-order statistics, assumes that the primaries and the multiples are implicitly orthogonal. However, the seismic data usually do not satisfy this assumption in practice. Since the seismic data (primaries and multiples) have a non-Gaussian distribution, in this paper we present an improved predictive deconvolution algorithm (IPD) by maximizing the non-Gaussianity of the recovered primaries. Applications of the IPD method on synthetic and real seismic datasets show that the proposed method obtains promising results.

关 键 词:预定去卷积  多重稀薄化  地震数据  最大值

An improved predictive deconvolution based on maximization of non-Gaussianity
Jun?Liu,Wenkai?Lu.An improved predictive deconvolution based on maximization of non-Gaussianity[J].Applied Geophysics,2008,5(3):189-196.
Authors:Jun Liu  Wenkai Lu
Institution:State Key Laboratory of Intelligent Technology and Systems, Tsinghua National Laboratory for Information Science and Technology, Department of Automation, Tsinghua University, Beijing, 100084, China
Abstract:The predictive deconvolution algorithm(PD),which is based on second-order statistics,assumes that the primaries and the multiples are implicitly orthogonal.However, the seismic data usually do not satisfy this assumption in practice.Since the seismic data (primaries and multiples)have a non-Gaussian distribution,in this paper we present an improved predictive deconvolution algorithm(IPD)by maximizing the non-Gaussianity of the recovered primaries.Applications of the IPD method on synthetic and real seismic datasets show that the proposed method obtains promising results.
Keywords:Multiple attenuation  non-Gaussianity  predictive deconvolution
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