地震期刊库 地震书目库 龙门山专辑 英文篇名：Study on Robust Sparse Deconvolution中文刊名：工程数学学报英文刊名：Chinese Journal of Engineering Mathematics作者：高倩 ; 刘建朝 ; 常象宇英文作者：GAO Qian ; LIU Jian-chao ; CHANG Xiang-yu ; Digital Oil Field Institute ; School of Earth Science and Resource ; Chang'an University ; Institute of Information and System Science ; School of Mathematics and Statistics ; Xi'an Jiaotong University中文关键词：反褶积 ; 反射系数 ; 稳健估计 ; 稀疏性英文关键词：deconvolution ; reflection coefficient ; robust estimation ; sparsity出版日期：2015-06-15机构：长安大学地球科学与资源学院数字油田研究所;西安交通大学数学与统计学院信息与系统科学研究所;年：2015期：03出版单位：工程数学学报

A fundamental and important approach in the field of seismic signal processing is the deconvolution of seismic signals. However, seismic signal acquisition can be contaminated by outliers, and the outliers affect the performance of deconvolution results. In this paper, we follow the Bayesian deconvolution framework, which was proposed by Canadas, and propose a new robust sparse deconvolution method for overcoming the influence of outliers. The new approach properly models the heavy-tail outliers and sparse reflection coefficients simultaneously. For solving the approach, we derive a type of alternative algorithm. Finally, we demonstrate the performance of the algorithm by a series of simulations, which show that the new approach can eliminate the influence of heavy-tail outliers and recover the reflection coefficients. This further indicates the approach is valid and the algorithm is convergent.

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