Hybrid rank-sparsity constraint model for simultaneous reconstruction and denoising of 3D seismic data

doi:10.1190/GEO2016-0557.1

CORC > 武汉植物园 > 中国科学院武汉植物园

	Hybrid rank-sparsity constraint model for simultaneous reconstruction and denoising of 3D seismic data
	Chen, Wei 3,4,5; Zhang, Dong 1; Zhou, Yatong 2; Chen, Hanming 1; Zu, Shaohuan 1; Chen, Yangkang 6,7
刊名	GEOPHYSICS
	2017-09-01
卷号	82 期号:5 页码:V351-V367
ISSN号	0016-8033
DOI	10.1190/GEO2016-0557.1
英文摘要	We have determined an approach for simultaneous reconstruction and denoising of 3D seismic data with randomly missing traces. The core in simultaneous reconstruction and denoising of 3D seismic data is the choice of constraint method. Recently, there have been two types of popular approaches to choose such a constraint: sparsity-promoting transforms using a sparsity constraint and rank reduction methods using a rank constraint. Although the sparsity-promoting transform enjoys the direct advantage of high efficiency, it lacks adaptivity to a variety of data patterns. On the other hand, the rank reduction method can be adaptively applied to different data sets, but its computational cost is quite high. We investigate multiple constraints for simultaneous seismic data reconstruction and denoising based on a novel hybrid rank-sparsity constraint (HRSC) model, which aims at combining the benefits of the sparsity-promoting transforms and rank reduction methods. Also, we design the corresponding HRSC algorithmic framework to effectively solve our new model via tightly combining a sparsity-promoting transform and a rank reduction method, which is more powerful in simultaneous reconstruction and denoising of 3D seismic data. Our HRSC framework aims at providing an extra level of constraint and, thus, can significantly improve the signal-to-noise ratio (S/N) of the reconstructed results with higher efficiency. Application of the HRSC framework on synthetic and field 3D seismic data demonstrates superior performance in terms of S/N and visual observation compared with the well-known rank reduction method, known as multichannel singular spectrum analysis.
资助项目	China Postdoctoral Science Foundation[2014M561053] ; Humanity and Social Science Foundation of Ministry of Education of China[15YJA630108] ; Hebei Province Natural Science Foundation[E2016202341] ; Sinopec Key Laboratory of Geophysics[33550006-15-FW2099-0017] ; State Key Laboratory of Geodesy and Eartha (sic)(TM)s Dynamics (Institute of Geodesy and Geophysics, CAS)[SKLGED2017-4-3-E] ; Project for Young Scientists Fund of Hubei Ministry of Education[Q20161304]
WOS研究方向	Geochemistry & Geophysics
语种	英语
出版者	SOC EXPLORATION GEOPHYSICISTS
WOS记录号	WOS:000417972900029
内容类型	期刊论文
源URL	[http://202.127.146.157/handle/2RYDP1HH/4396]
专题	中国科学院武汉植物园
通讯作者	Zhang, Dong
作者单位	1.China Univ Petr, State Key Lab Petr Resources & Prospecting, Beijing, Peoples R China 2.Hebei Univ Technol, Sch Elect & Informat Engn, Tianjin, Peoples R China 3.Yangtze Univ, Minist Educ, Key Lab Explorat Technol Oil & Gas Resources, Wuhan, Hubei, Peoples R China 4.Hubei Cooperat Innovat Ctr Unconvent Oil & Gas, Wuhan, Hubei, Peoples R China 5.Chinese Acad Sci, Inst Geodesy & Geophys, State Key Lab Geodesy & Earths Dynam, Wuhan, Hubei, Peoples R China 6.Univ Texas Austin, Bur Econ Geol, John A & Katherine G Jackson Sch Geosci, Austin, TX USA 7.Oak Ridge Natl Lab, Natl Ctr Computat Sci, Oak Ridge, TN USA
推荐引用方式 GB/T 7714	Chen, Wei,Zhang, Dong,Zhou, Yatong,et al. Hybrid rank-sparsity constraint model for simultaneous reconstruction and denoising of 3D seismic data[J]. GEOPHYSICS,2017,82(5):V351-V367.
APA	Chen, Wei,Zhang, Dong,Zhou, Yatong,Chen, Hanming,Zu, Shaohuan,&Chen, Yangkang.(2017).Hybrid rank-sparsity constraint model for simultaneous reconstruction and denoising of 3D seismic data.GEOPHYSICS,82(5),V351-V367.
MLA	Chen, Wei,et al."Hybrid rank-sparsity constraint model for simultaneous reconstruction and denoising of 3D seismic data".GEOPHYSICS 82.5(2017):V351-V367.