Angle-domain common-image gathers from plane-wave least-squares reverse time migration

被引:0
作者
Li, Chuang [1 ]
Gao, Zhaoqi [1 ]
Gao, Jinghuai [1 ]
Li, Feipeng [1 ]
Yang, Tao [1 ]
机构
[1] Xi An Jiao Tong Univ, Sch Informat & Commun Engn, Natl Engn Lab Offshore Oil Explorat, Xian 710049, Peoples R China
基金
国家重点研发计划; 中国博士后科学基金; 中国国家自然科学基金;
关键词
ATTENUATION COMPENSATION; VELOCITY ANALYSIS; FORM INVERSION; IMPLEMENTATION;
D O I
10.1190/GEO2020.0511.1
中图分类号
P3 [地球物理学]; P59 [地球化学];
学科分类号
0708 ; 070902 ;
摘要
Angle-domain common-image gathers (ADCIGs) that can be used for migration velocity analysis and amplitude-versus-angle analysis are important for seismic exploration. However, because of the limited acquisition geometry and seismic frequency band, ADCIGs extracted by reverse time migration (RTM) suffer from illumination gaps, migration artifacts, and low resolution. We have developed a reflection angle-domain pseudoextended plane-wave least-squares RTM method for obtaining high-quality ADCIGs. We build the mapping relations between the ADCIGs and the plane-wave sections using an angle-domain pseudoextended Born modeling operator and an adjoint operator. based on which we formulate the extraction of ADCIGs as an inverse problem. The inverse problem is iteratively solved by a preconditioned stochastic conjugate-gradient method, allowing for reduction in computational cost by migrating only a subset instead of the whole data set and improving the image quality thanks to preconditioners. Numerical tests on synthetic and field data verify that our method can compensate for illumination gaps, suppress migration artifacts, and improve resolution of the ADCIGs and the stacked images. Therefore, compared to RTM, our method provides a more reliable input for migration velocity analysis and amplitude-versus-angle analysis. Moreover, it also provides much better stacked images for seismic interpretation.
引用
收藏
页码:S311 / S324
页数:14
相关论文
共 50 条
[31]   Least-squares reverse time migration with and without source wavelet estimation [J].
Zhang, Qingchen ;
Zhou, Hui ;
Chen, Hanming ;
Wang, Jie .
JOURNAL OF APPLIED GEOPHYSICS, 2016, 134 :1-10
[32]   Model parameterizations in the time-domain multi-parameter acoustic least-squares reverse time migration [J].
Zhang, Wei ;
Gao, Jinghuai .
ACTA GEOPHYSICA, 2021, 69 (02) :441-458
[33]   Least-squares extended reverse time migration with randomly sampled space shifts [J].
Yang, Jizhong ;
Li, Yunyue Elita ;
Liu, Yuzhu ;
Zong, Jingjing .
GEOPHYSICS, 2020, 85 (06) :S357-S369
[34]   A wavefield-separation-based elastic least-squares reverse time migration [J].
Gu, Bingluo ;
Li, Zhenchun ;
Han, Jianguang .
GEOPHYSICS, 2018, 83 (03) :S279-S297
[35]   Least-squares reverse time migration in viscoacoustic tilted transversely isotropic media [J].
Huang, Jianping ;
Mu, Xinru ;
Yang, Jidong ;
Su, Laiyuan .
GEOPHYSICS, 2025, 90 (03) :S69-S88
[36]   3D angle gathers from reverse time migration [J].
Xu, Shang ;
Zhang, Yu ;
Tang, Bing .
GEOPHYSICS, 2011, 76 (02) :S77-S92
[37]   A new scheme of wavefield decomposed elastic least-squares reverse time migration [J].
Lv, Wenhao ;
Du, Qizhen ;
Fu, Li-Yun ;
Li, Qingqing ;
Zhang, Jianlei ;
Zou, Zhen .
FRONTIERS IN EARTH SCIENCE, 2022, 10
[38]   Accelerating the multi-parameter least-squares reverse time migration using an appropriate preconditioner [J].
Farshad, Milad ;
Chauris, Herve .
COMPUTATIONAL GEOSCIENCES, 2021, 25 (06) :2071-2092
[39]   Double-plane-wave reverse time migration in the frequency domain [J].
Zhao, Zeyu ;
Sen, Mrinal K. ;
Stoffa, Paul L. .
GEOPHYSICS, 2016, 81 (05) :S367-S382
[40]   3-D Q-Compensated Image-Domain Least-Squares Reverse Time Migration Through Point Spread Functions [J].
Zhang, Wei ;
Gao, Jinghuai .
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2022, 19