Normalized shaping regularization for robust separation of blended data

doi:10.1190/GEO2018-0557.1

	Normalized shaping regularization for robust separation of blended data
	Zhao, Qiang 4,5; Du, Qizhen 4,5; Gong, Xufei 4,5; Li, Xiangyang 3; Fu, Liyun 2,5; Chen, Yangkang 1
刊名	GEOPHYSICS
	2019-09-01
卷号	84 期号:5 页码:V281-V293
ISSN号	0016-8033
DOI	10.1190/GEO2018-0557.1
英文摘要	Simultaneous source acquisition has attracted more and more attention from geophysicists because of its cost savings, whereas it also brings some challenges that have never been addressed before. Deblending of simultaneous source data is usually considered as an underdetermined inverse problem, which can be effectively solved with a least-squares (LS) iterative procedure between data consistency (l(2)-norm) and regularization (l(0)-norm or l(1)-norm). However, when it comes to abnormal noise that follows non-Gaussian distribution and possesses high-amplitude features (e.g., erratic noise, swell noise, and power line noise), the l(2)-norm is a nonrobust statistic that can easily lead to suboptimal deblended results. Although abnormal noise can be attenuated in the common source domain at first, it is still challenging to apply a coherency-based filter due to the sparse receiver or crossline sampling, e.g., that commonly found in ocean bottom node (OBN) acquisition. To address this problem, we have developed a normalized shaping regularization to make the inversion-based deblending approach robust for the separation of blended data when abnormal noise exists. Its robustness comes from the normalized shaping operator defined by the confidence interval of normal distribution, which minimizes the abnormal risk to a normal level to satisfy the assumption of LS shaping regularization. In special cases, the proposed approach will revert to the classic LS shaping regularization once the normalized coefficient is large enough. Experimental results on synthetic and field data indicate that the proposed method can effectively restore the separated records from blended data at essentially the same convergence rate as the LS shaping regularization for the abnormal noise-free scenario, but it can obtain better deblending performance and less energy leakage when abnormal noise exists.
资助项目	National Key Research & Development Programs of China[2017YFB0202903] ; National Science Foundation of China[41574125] ; National Science Foundation of China[41774139] ; National Science & Technology Major Projects of China[2017ZX05018-005] ; China National "111" Foreign Experts Introduction Plan for Tight Oil & Gas Geology and Exploration
WOS关键词	ACQUISITION ; MIGRATION ; INVERSION
WOS研究方向	Geochemistry & Geophysics
语种	英语
出版者	SOC EXPLORATION GEOPHYSICISTS
WOS记录号	WOS:000490236900032
资助机构	National Key Research & Development Programs of China ; National Key Research & Development Programs of China ; National Science Foundation of China ; National Science Foundation of China ; National Science & Technology Major Projects of China ; National Science & Technology Major Projects of China ; China National "111" Foreign Experts Introduction Plan for Tight Oil & Gas Geology and Exploration ; China National "111" Foreign Experts Introduction Plan for Tight Oil & Gas Geology and Exploration ; National Key Research & Development Programs of China ; National Key Research & Development Programs of China ; National Science Foundation of China ; National Science Foundation of China ; National Science & Technology Major Projects of China ; National Science & Technology Major Projects of China ; China National "111" Foreign Experts Introduction Plan for Tight Oil & Gas Geology and Exploration ; China National "111" Foreign Experts Introduction Plan for Tight Oil & Gas Geology and Exploration ; National Key Research & Development Programs of China ; National Key Research & Development Programs of China ; National Science Foundation of China ; National Science Foundation of China ; National Science & Technology Major Projects of China ; National Science & Technology Major Projects of China ; China National "111" Foreign Experts Introduction Plan for Tight Oil & Gas Geology and Exploration ; China National "111" Foreign Experts Introduction Plan for Tight Oil & Gas Geology and Exploration ; National Key Research & Development Programs of China ; National Key Research & Development Programs of China ; National Science Foundation of China ; National Science Foundation of China ; National Science & Technology Major Projects of China ; National Science & Technology Major Projects of China ; China National "111" Foreign Experts Introduction Plan for Tight Oil & Gas Geology and Exploration ; China National "111" Foreign Experts Introduction Plan for Tight Oil & Gas Geology and Exploration
内容类型	期刊论文
源URL	[http://ir.iggcas.ac.cn/handle/132A11/93880]
专题	中国科学院地质与地球物理研究所
通讯作者	Gong, Xufei
作者单位	1.Zhejiang Univ, Sch Earth Sci, Hangzhou, Zhejiang, Peoples R China 2.Chinese Acad Sci, Inst Geol & Geophys, Beijing 100029, Peoples R China 3.China Univ Petr, Beijing 102200, Peoples R China 4.Qingdao Natl Lab Marine Sci & Technol, Lab Marine Mineral Resources, Qingdao 266071, Shandong, Peoples R China 5.China Univ Petr East China, Key Lab Deep Oil & Gas, Changjiang West Rd 66th, Qingdao 266580, Shandong, Peoples R China
推荐引用方式 GB/T 7714	Zhao, Qiang,Du, Qizhen,Gong, Xufei,et al. Normalized shaping regularization for robust separation of blended data[J]. GEOPHYSICS,2019,84(5):V281-V293.
APA	Zhao, Qiang,Du, Qizhen,Gong, Xufei,Li, Xiangyang,Fu, Liyun,&Chen, Yangkang.(2019).Normalized shaping regularization for robust separation of blended data.GEOPHYSICS,84(5),V281-V293.
MLA	Zhao, Qiang,et al."Normalized shaping regularization for robust separation of blended data".GEOPHYSICS 84.5(2019):V281-V293.