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Improving the least-squares image by using angle information to avoid cycle skipping
He, Bin1,2; Liu, Yike1; Zhang, Yanbao1,2
2019-11-01
Source PublicationGEOPHYSICS
ISSN0016-8033
Volume84Issue:6Pages:S581-S598
AbstractIn the past few decades, the least-squares reverse time migration (LSRTM) algorithm has been widely used to enhance images of complex subsurface structures by minimizing the data misfit function between the predicted and observed seismic data. However, this algorithm is sensitive to the accuracy of the migration velocity model, which, in the case of real data applications (generally obtained via tomography), always deviates from the true velocity model. Therefore, conventional LSRTM faces a cycle-skipping problem caused by a smeared image when using an inaccurate migration velocity model. To address the cycle-skipping problem, we have introduced an angle-domain LSRTM algorithm. Unlike the conventional LSRTM algorithm, our method updates the common source-propagation angle image gathers rather than the stacked image. An extended Born modeling operator in the common source-propagation angle domain is was derived, which reproduced kinematically accurate data in the presence of velocity errors. Our method can provide more focused images with high resolution as well as angle-domain common-image gathers (ADCIGs) with enhanced resolution and balanced amplitudes. However, because the velocity model is not updated, the provided image can have errors in depth. Synthetic and field examples are used to verify that our method can robustly improve the quality of the ADCIGs and the finally stacked images with affordable computational costs in the presence of velocity errors.
DOI10.1190/GEO2018-0816.1
Funding OrganizationNational Nature Science Foundation of China ; National Nature Science Foundation of China ; National Nature Science Foundation of China ; National Nature Science Foundation of China ; National Oil and Gas Major Project of China ; National Oil and Gas Major Project of China ; National Oil and Gas Major Project of China ; National Oil and Gas Major Project of China ; National Nature Science Foundation of China ; National Nature Science Foundation of China ; National Nature Science Foundation of China ; National Nature Science Foundation of China ; National Oil and Gas Major Project of China ; National Oil and Gas Major Project of China ; National Oil and Gas Major Project of China ; National Oil and Gas Major Project of China ; National Nature Science Foundation of China ; National Nature Science Foundation of China ; National Nature Science Foundation of China ; National Nature Science Foundation of China ; National Oil and Gas Major Project of China ; National Oil and Gas Major Project of China ; National Oil and Gas Major Project of China ; National Oil and Gas Major Project of China ; National Nature Science Foundation of China ; National Nature Science Foundation of China ; National Nature Science Foundation of China ; National Nature Science Foundation of China ; National Oil and Gas Major Project of China ; National Oil and Gas Major Project of China ; National Oil and Gas Major Project of China ; National Oil and Gas Major Project of China
WOS KeywordREVERSE TIME MIGRATION ; FREE-SURFACE MULTIPLES ; VELOCITY ANALYSIS ; BACKGROUND VELOCITY ; GATHERS ; INVERSION ; VECTOR ; STRATEGY
Language英语
Funding ProjectNational Nature Science Foundation of China[41730425] ; National Nature Science Foundation of China[41430321] ; National Oil and Gas Major Project of China[2017ZX05008-007]
Funding OrganizationNational Nature Science Foundation of China ; National Nature Science Foundation of China ; National Nature Science Foundation of China ; National Nature Science Foundation of China ; National Oil and Gas Major Project of China ; National Oil and Gas Major Project of China ; National Oil and Gas Major Project of China ; National Oil and Gas Major Project of China ; National Nature Science Foundation of China ; National Nature Science Foundation of China ; National Nature Science Foundation of China ; National Nature Science Foundation of China ; National Oil and Gas Major Project of China ; National Oil and Gas Major Project of China ; National Oil and Gas Major Project of China ; National Oil and Gas Major Project of China ; National Nature Science Foundation of China ; National Nature Science Foundation of China ; National Nature Science Foundation of China ; National Nature Science Foundation of China ; National Oil and Gas Major Project of China ; National Oil and Gas Major Project of China ; National Oil and Gas Major Project of China ; National Oil and Gas Major Project of China ; National Nature Science Foundation of China ; National Nature Science Foundation of China ; National Nature Science Foundation of China ; National Nature Science Foundation of China ; National Oil and Gas Major Project of China ; National Oil and Gas Major Project of China ; National Oil and Gas Major Project of China ; National Oil and Gas Major Project of China
WOS Research AreaGeochemistry & Geophysics
WOS SubjectGeochemistry & Geophysics
WOS IDWOS:000501594400045
PublisherSOC EXPLORATION GEOPHYSICISTS
Citation statistics
Document Type期刊论文
Identifierhttp://ir.iggcas.ac.cn/handle/132A11/95820
Collection油气资源研究院重点实验室
Corresponding AuthorHe, Bin
Affiliation1.Chinese Acad Sci, Inst Geol & Geophys, Key Lab Petr Resource Res, Beijing 100029, Peoples R China
2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
First Author AffilicationInstitute of Geology and Geophysics, Chinese Academy of Sciences
Corresponding Author AffilicationInstitute of Geology and Geophysics, Chinese Academy of Sciences
Recommended Citation
GB/T 7714
He, Bin,Liu, Yike,Zhang, Yanbao. Improving the least-squares image by using angle information to avoid cycle skipping[J]. GEOPHYSICS,2019,84(6):S581-S598.
APA He, Bin,Liu, Yike,&Zhang, Yanbao.(2019).Improving the least-squares image by using angle information to avoid cycle skipping.GEOPHYSICS,84(6),S581-S598.
MLA He, Bin,et al."Improving the least-squares image by using angle information to avoid cycle skipping".GEOPHYSICS 84.6(2019):S581-S598.
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