中国石油大学学报（自然科学版）2017，Vol.41Issue(5)：61-68,8.DOI:10.3969/j.issn.1673-5005.2017.05.007
基于一种三维低冗余曲波变换和压缩感知理论的地震数据重建
Seismic reconstruction with 3 D low-redundancy curvelet transform and compressed sensing theory
摘要
Abstract
Sparse-transform-based seismic data reconstruction is a hot topic in seismic reconstruction, where properties of the sparse transform may influence the results of reconstruction greatly. Curvelet transform is a multi-scale, multi-directional, and local transform which has nearly the sparsest expression for seismic data. However, this transform is a highly redundant transform with redundancy about 24-32 for three dimensional data. To improve the efficiency of curvelet based reconstruc-tion, this paper proposed a low-redundancy curvelet-transform based seismic reconstruction. The new transform was intro-duced first and its merits for seismic signal processing were analyzed, followed by an iterative thresholding method for analy-sis-based L1-norm regularized models. Numerical experiments illustrate that the low-redundancy transform can reduce 60%redundancy of the original 3D curvelet transform, thus improves greatly the computational efficiency. The reconstruction com-putational efficiency based on the low redundancy transform is 4 times of the original curvelet based reconstruction, for exam-ple, even for 10% sampling ratio, this low-redundancy curvelet can get acceptable results.关键词
曲波变换/地震重建/稀疏优化/1范数Key words
curvelet transform/seismic reconstruction/sparse optimization/one-norm分类
天文与地球科学引用本文复制引用
曹静杰,王尚旭,李文斌..基于一种三维低冗余曲波变换和压缩感知理论的地震数据重建[J].中国石油大学学报（自然科学版）,2017,41(5):61-68,8.基金项目
国家自然科学基金项目( 41674114 ) （ 41674114 ）
河北省自然科学基金项目( D2017403027 ) （ D2017403027 ）
河北省高校百名优秀创新人才支持计划Ⅲ(SLRC2017024) （SLRC2017024）
中国博士后科学基金资助项目(2016M600171,2017T100137) （2016M600171,2017T100137）
