Regularized least-squares migration of simultaneous-source seismic data with adaptive singular spectrum analysis

Simultaneous-source acquisition has been recog- nized as an economic and efficient acquisition method, but the direct imaging of the simultaneous-source data produces migration artifacts because of the interference of adjacent sources. To overcome this problem, we propose the regularized least-squar...

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Bibliographic Details
Published in:Petroleum science 2017, Vol.14 (1), p.61-74
Main Authors: Li, Chuang, Huang, Jian-Ping, Li, Zhen-Chun, Wang, Rong-Rong
Format: Article
Language:English
Subjects:
Earth and Environmental Science
Earth Sciences
Economics and Management
Energy Policy
Imaging techniques
Industrial and Production Engineering
Industrial Chemistry/Chemical Engineering
Marmousi模型
Methods
Mineral Resources
Original Paper
Regularization
Seismic data
Spectrum analysis
偏移方法
地震资料
奇异谱分析
最小二乘
正则化
自适应
震源
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Description
Summary:Simultaneous-source acquisition has been recog- nized as an economic and efficient acquisition method, but the direct imaging of the simultaneous-source data produces migration artifacts because of the interference of adjacent sources. To overcome this problem, we propose the regularized least-squares reverse time migration method （RLSRTM） using the singular spectrum analysis technique that imposes sparseness constraints on the inverted model. Additionally, the difference spectrum theory of singular values is presented so that RLSRTM can be implemented adaptively to eliminate the migration artifacts. With numerical tests on a fiat layer model and a Marmousi model, we validate the superior imaging quality, efficiency and convergence of RLSRTM compared with LSRTM when dealing with simultaneoussource data, incomplete data and noisy data.
ISSN:1672-5107
1995-8226
DOI:10.1007/s12182-016-0134-1