中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
首页 机构 成果 学者
  
  1. CAS IR Grid
  2. 地质与地球物理研究所
  3. 中国科学院地质与地球物理研究所
  4. 中国科学院油气资源研究重点实验室
Improving the least-squares image by using angle information to avoid cycle skipping

文献类型：期刊论文

作者He, Bin1,2; Liu, Yike1; Zhang, Yanbao1,2
刊名GEOPHYSICS
出版日期2019-11-01
卷号84期号:6页码:S581-S598
ISSN号0016-8033
DOI10.1190/GEO2018-0816.1
英文摘要In 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.
WOS关键词REVERSE TIME MIGRATION ; FREE-SURFACE MULTIPLES ; VELOCITY ANALYSIS ; BACKGROUND VELOCITY ; GATHERS ; INVERSION ; VECTOR ; STRATEGY
资助项目National Nature Science Foundation of China[41730425] ; National Nature Science Foundation of China[41430321] ; National Oil and Gas Major Project of China[2017ZX05008-007]
WOS研究方向Geochemistry & Geophysics
语种英语
WOS记录号WOS:000501594400045
出版者SOC EXPLORATION GEOPHYSICISTS
资助机构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 ; 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
源URL[http://ir.iggcas.ac.cn/handle/132A11/95820]  
专题地质与地球物理研究所_中国科学院油气资源研究重点实验室
通讯作者He, Bin
作者单位1.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
推荐引用方式
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.

入库方式： OAI收割

来源：地质与地球物理研究所

浏览0
下载0
收藏0
其他版本

除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。