A Simple and Robust Total Variation-Based Inversion Scheme for Transient Electromagnetic Data
文献类型：期刊论文
| 作者 | Rao, Liting2; Gao, Jianshen2; Wu, Xin1,4,5; Wang, Youcheng3; Jia, Huiqin2 |
| 刊名 | IEEE ACCESS
 |
| 出版日期 | 2020 |
| 卷号 | 8页码:16539-16549 |
| 关键词 | Reconstructing minimization approach sharp boundaries total variation transient electromagnetic inversion |
| ISSN号 | 2169-3536 |
| DOI | 10.1109/ACCESS.2020.2963917 |
| 英文摘要 | Transient electromagnetic (TEM) data are conveniently inverted to visualized underground structure with the widely used Occam & x2019;s inversion. However, in sedimentary environments, Occam & x2019;s inversion performs poorly in reproducing the sharp boundaries as it produces smoothed results of subsurface geophysical properties. Here, we develop a simple and robust total variation (TV) based inversion scheme for TEM data to preserve sharp boundaries and improve the accuracy of recovered underground structure. To solve the standard L2-TV optimization problem, we propose a reconstructing minimization (RM) approach. The TV-based inversion scheme is divided into two phases. In Phase I the misfit is brought down to a desired level utilizing Occam & x2019;s inversion. In Phase II we utilize RM approach to implement TV regularization until the convergent result is achieved. Taking advantage of the excellent stability of Occam & x2019;s inversion, the TV-based inversion scheme has the characteristics of robustness to different initial models. The switch process between Occam & x2019;s inversion and the RM approach is rather simple to realize due to their similar solution forms. The synthetic and field data examples validate the efficiency and accuracy of the proposed TV-based inversion scheme. We further present a novel analysis based on reconstruction of stabilizer to illustrate the reason for their distinctive behaviors of TV-based inversion and Occam & x2019;s inversion. |
| WOS关键词 | ALGORITHM |
| 资助项目 | National Natural Science Foundation of China[41804115] ; National Natural Science Foundation of China[61701465] ; Natural Science Basic Research Plan in Shaanxi Province of China[2018JQ4007] ; Natural Science Basic Research Plan in Shaanxi Province of China[2018JQ4008] ; Natural Science Basic Research Plan in Shaanxi Province of China[2019JZ-37] ; Natural Science Foundation of Shaanxi Provincial Department of Education[19JK0669] |
| WOS研究方向 | Computer Science ; Engineering ; Telecommunications |
| 语种 | 英语 |
| WOS记录号 | WOS:000524753200002 |
| 出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
| 资助机构 | National Natural Science Foundation of China ; National Natural Science Foundation of China ; Natural Science Basic Research Plan in Shaanxi Province of China ; Natural Science Basic Research Plan in Shaanxi Province of China ; Natural Science Foundation of Shaanxi Provincial Department of Education ; Natural Science Foundation of Shaanxi Provincial Department of Education ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; Natural Science Basic Research Plan in Shaanxi Province of China ; Natural Science Basic Research Plan in Shaanxi Province of China ; Natural Science Foundation of Shaanxi Provincial Department of Education ; Natural Science Foundation of Shaanxi Provincial Department of Education ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; Natural Science Basic Research Plan in Shaanxi Province of China ; Natural Science Basic Research Plan in Shaanxi Province of China ; Natural Science Foundation of Shaanxi Provincial Department of Education ; Natural Science Foundation of Shaanxi Provincial Department of Education ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; Natural Science Basic Research Plan in Shaanxi Province of China ; Natural Science Basic Research Plan in Shaanxi Province of China ; Natural Science Foundation of Shaanxi Provincial Department of Education ; Natural Science Foundation of Shaanxi Provincial Department of Education |
| 源URL | [http://ir.iggcas.ac.cn/handle/132A11/95561]  |
| 专题 | 地质与地球物理研究所_中国科学院矿产资源研究重点实验室 |
| 通讯作者 | Rao, Liting |
| 作者单位 | 1.Chinese Acad Sci, Inst Geol & Geophys, Key Lab Mineral Resources, Beijing 100029, Peoples R China 2.Xian Shiyou Univ, Sch Elect Engn, Xian 710065, Peoples R China 3.Sci & Technol Complex Syst Control & Intelligent, Beijing 100074, Peoples R China 4.Chinese Acad Sci, Inst Earth Sci, Beijing 100029, Peoples R China 5.Univ Chinese Acad Sci, Coll Earth & Planetary Sci, Beijing 100049, Peoples R China |
| 推荐引用方式 GB/T 7714 | Rao, Liting,Gao, Jianshen,Wu, Xin,et al. A Simple and Robust Total Variation-Based Inversion Scheme for Transient Electromagnetic Data[J]. IEEE ACCESS,2020,8:16539-16549. |
| APA | Rao, Liting,Gao, Jianshen,Wu, Xin,Wang, Youcheng,&Jia, Huiqin.(2020).A Simple and Robust Total Variation-Based Inversion Scheme for Transient Electromagnetic Data.IEEE ACCESS,8,16539-16549. |
| MLA | Rao, Liting,et al."A Simple and Robust Total Variation-Based Inversion Scheme for Transient Electromagnetic Data".IEEE ACCESS 8(2020):16539-16549. |
入库方式： OAI收割
来源：地质与地球物理研究所
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