Registration-Free Multicomponent Joint AVA Inversion Using Optimal Transport
文献类型：期刊论文
| 作者 | Luo, Cong4; Huang, Guangtan3; Chen, Xiaohong2; Chen, Yangkang1 |
| 刊名 | IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
 |
| 出版日期 | 2022 |
| 卷号 | 60页码:13 |
| 关键词 | Earth Mathematical model Convex functions Transforms Signal to noise ratio Media Linear approximation Amplitude variation with offset angle (AVO AVA) inversion joint inversion multicomponent optimal transport registration-free |
| ISSN号 | 0196-2892 |
| DOI | 10.1109/TGRS.2021.3063271 |
| 英文摘要 | Seismic multicomponent, here refers to P-P wave (PP) and P- shear wave (SV), joint inversion is an important approach to improve the accuracy of S-wave velocity and density prediction. Compared with P-P wave data, converted wave data are more sensitive to these parameters. Thus, introducing these data to the seismic inversion could improve the inversion accuracy of S-wave velocity and density. Due to the travel-time gap between the multicomponent data, multicomponent inversion usually needs to be prepared for registration processing in advance. However, registration methods often suffer from matching errors, which ultimately affect the quality of the inversion results. Based on the optimal transmission idea, a registration-free multicomponent joint amplitude variation with offset/angle (AVO/AVA) inversion algorithm is developed in this article. The proposed method adopts the Earth moverx2019;s distance between the synthetic P-SV wave and the observed P-P wave by calculating the optimal transport path. Besides norm is exploited as the penalty norm, where the regularized misfit function is minimized by the alternating direction method of multipliers (ADMM) algorithm. The synthetic data test and real seismic data application show that the proposed method can retrieve the S-wave velocity and density information better than the conventional method. The proposed method can not only effectively avoid the cumbersome registration steps, but also minimize the registration error and avoid the subsequent error accumulation. |
| 资助项目 | National Natural Science Foundation of China[42004111] ; National Natural Science Foundation of China[41704121] ; National Natural Science Foundation of China[41774129] ; China Postdoctoral Science Foundation[2020M681860] ; China Postdoctoral Science Foundation[2019M661716] |
| WOS研究方向 | Geochemistry & Geophysics ; Engineering ; Remote Sensing ; Imaging Science & Photographic Technology |
| 语种 | 英语 |
| WOS记录号 | WOS:000728266600106 |
| 出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
| 源URL | [http://119.78.100.198/handle/2S6PX9GI/30947]  |
| 专题 | 中科院武汉岩土力学所 |
| 通讯作者 | Huang, Guangtan |
| 作者单位 | 1.Zhejiang Univ, Sch Earth Sci, Key Lab Geoscience Big Data & Deep Resource Zheji, Hangzhou 310027, Peoples R China 2.China Univ Petr, State Key Lab Petr Resources & Prospecting, Beijing 102200, Peoples R China 3.Chinese Acad Sci, Inst Rock & Soil Mech, State Key Lab Geomechan & Geotechn Engn, Wuhan 430071, Peoples R China 4.Hohai Univ, Sch Earth Sci & Engn, Nanjing 211100, Peoples R China |
| 推荐引用方式 GB/T 7714 | Luo, Cong,Huang, Guangtan,Chen, Xiaohong,et al. Registration-Free Multicomponent Joint AVA Inversion Using Optimal Transport[J]. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING,2022,60:13. |
| APA | Luo, Cong,Huang, Guangtan,Chen, Xiaohong,&Chen, Yangkang.(2022).Registration-Free Multicomponent Joint AVA Inversion Using Optimal Transport.IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING,60,13. |
| MLA | Luo, Cong,et al."Registration-Free Multicomponent Joint AVA Inversion Using Optimal Transport".IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING 60(2022):13. |
入库方式： OAI收割
来源：武汉岩土力学研究所
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