Extraction of Multiple Electrical Parameters From IP-Affected Transient Electromagnetic Data Based on LSTM-ResNet
文献类型：期刊论文
| 作者 | Zhang, Shun1,2,3; Zhou, Nannan1,2,3 |
| 刊名 | IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
 |
| 出版日期 | 2023 |
| 卷号 | 61页码:14 |
| ISSN号 | 0196-2892 |
| 关键词 | Conductivity Electric fields IP networks Distortion measurement Neural networks Magnetic fields Data mining Chargeability induced polarization (IP) long short-term memory-residual network (LSTM-ResNet) sign reversal transient electromagnetic (TEM) method |
| DOI | 10.1109/TGRS.2023.3266258 |
| 英文摘要 | The induced polarization (IP) effect due to a polarizable body distorts transient electromagnetic (TEM) data, thereby potentially triggering sign reversal phenomena in the measured response. The measured horizontal electric field associated with a grounded-wire TEM is more strongly affected by IP effects than the measured vertical field, meaning that data inversion is more problematic for its component. The traditional inversion method, which assumes a frequency-independent resistivity, is complex to extract the chargeability. Yet, the chargeability provides critical information, so it is important to extract the chargeability in addition to the resistivity from IP-affected TEM data. Thus, we proposed a data-driven method based on deep learning (DL) to recover the resistivity and chargeability of IP-affected horizontal electric fields. This method, named LSTM-ResNet, combines long short-term memory (LSTM) and a residual network (ResNet) to estimate subsurface electrical properties. Synthetic tests showed that LSTM-ResNet is computationally efficient and accurate for inversion problems. Based on the inverse results with data added noise, we found that a well-trained neural network was not sensitive to noise. A case study was performed by applying LSTM-ResNet to field data collected by a grounded-wire TEM survey at the Kalatongke copper-nickel ore deposit. LSTM-ResNet recovered the simultaneous resistivity and chargeability distributions of subsurface structures from the IP-affected horizontal electric TEM field. The results show a high-chargeability and low-resistivity layer, which was consistent with the lithologic profiles based on drilling cores, indicating the accuracy and robustness of the proposed framework for multiparameter inversion. |
| WOS关键词 | RECURRENT NEURAL-NETWORKS ; INDUCED-POLARIZATION ; INVERSION ; DISCRIMINATION ; FIELDS |
| 资助项目 | Natural Science Foundation of China[41874162] ; Youth Innovation Promotion Association, CAS[2020070] ; National Key Research and Development Program of China[2017YFC0601204] ; Ministry of Science and Technology National Key Research and Development Program of China[2022YFC2903505] ; Key Research Program of the Institute of Geology and Geophysics, CAS[IGGCAS-201902] |
| WOS研究方向 | Geochemistry & Geophysics ; Engineering ; Remote Sensing ; Imaging Science & Photographic Technology |
| 语种 | 英语 |
| 出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
| WOS记录号 | WOS:000979605400015 |
| 资助机构 | Natural Science Foundation of China ; Natural Science Foundation of China ; Natural Science Foundation of China ; Natural Science Foundation of China ; Youth Innovation Promotion Association, CAS ; Youth Innovation Promotion Association, CAS ; Youth Innovation Promotion Association, CAS ; Youth Innovation Promotion Association, CAS ; National Key Research and Development Program of China ; National Key Research and Development Program of China ; National Key Research and Development Program of China ; National Key Research and Development Program of China ; Ministry of Science and Technology National Key Research and Development Program of China ; Ministry of Science and Technology National Key Research and Development Program of China ; Ministry of Science and Technology National Key Research and Development Program of China ; Ministry of Science and Technology National Key Research and Development Program of China ; Key Research Program of the Institute of Geology and Geophysics, CAS ; Key Research Program of the Institute of Geology and Geophysics, CAS ; Key Research Program of the Institute of Geology and Geophysics, CAS ; Key Research Program of the Institute of Geology and Geophysics, CAS ; Natural Science Foundation of China ; Natural Science Foundation of China ; Natural Science Foundation of China ; Natural Science Foundation of China ; Youth Innovation Promotion Association, CAS ; Youth Innovation Promotion Association, CAS ; Youth Innovation Promotion Association, CAS ; Youth Innovation Promotion Association, CAS ; National Key Research and Development Program of China ; National Key Research and Development Program of China ; National Key Research and Development Program of China ; National Key Research and Development Program of China ; Ministry of Science and Technology National Key Research and Development Program of China ; Ministry of Science and Technology National Key Research and Development Program of China ; Ministry of Science and Technology National Key Research and Development Program of China ; Ministry of Science and Technology National Key Research and Development Program of China ; Key Research Program of the Institute of Geology and Geophysics, CAS ; Key Research Program of the Institute of Geology and Geophysics, CAS ; Key Research Program of the Institute of Geology and Geophysics, CAS ; Key Research Program of the Institute of Geology and Geophysics, CAS ; Natural Science Foundation of China ; Natural Science Foundation of China ; Natural Science Foundation of China ; Natural Science Foundation of China ; Youth Innovation Promotion Association, CAS ; Youth Innovation Promotion Association, CAS ; Youth Innovation Promotion Association, CAS ; Youth Innovation Promotion Association, CAS ; National Key Research and Development Program of China ; National Key Research and Development Program of China ; National Key Research and Development Program of China ; National Key Research and Development Program of China ; Ministry of Science and Technology National Key Research and Development Program of China ; Ministry of Science and Technology National Key Research and Development Program of China ; Ministry of Science and Technology National Key Research and Development Program of China ; Ministry of Science and Technology National Key Research and Development Program of China ; Key Research Program of the Institute of Geology and Geophysics, CAS ; Key Research Program of the Institute of Geology and Geophysics, CAS ; Key Research Program of the Institute of Geology and Geophysics, CAS ; Key Research Program of the Institute of Geology and Geophysics, CAS ; Natural Science Foundation of China ; Natural Science Foundation of China ; Natural Science Foundation of China ; Natural Science Foundation of China ; Youth Innovation Promotion Association, CAS ; Youth Innovation Promotion Association, CAS ; Youth Innovation Promotion Association, CAS ; Youth Innovation Promotion Association, CAS ; National Key Research and Development Program of China ; National Key Research and Development Program of China ; National Key Research and Development Program of China ; National Key Research and Development Program of China ; Ministry of Science and Technology National Key Research and Development Program of China ; Ministry of Science and Technology National Key Research and Development Program of China ; Ministry of Science and Technology National Key Research and Development Program of China ; Ministry of Science and Technology National Key Research and Development Program of China ; Key Research Program of the Institute of Geology and Geophysics, CAS ; Key Research Program of the Institute of Geology and Geophysics, CAS ; Key Research Program of the Institute of Geology and Geophysics, CAS ; Key Research Program of the Institute of Geology and Geophysics, CAS |
| 源URL | [http://ir.iggcas.ac.cn/handle/132A11/110945]  |
| 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 | Zhou, Nannan |
| 作者单位 | 1.Univ Chinese Acad Sci, Coll Earth & Planetary Sci, Beijing 100049, Peoples R China 2.Chinese Acad Sci, Inst Geol & Geophys, Key Lab Mineral Resources, Beijing 100029, Peoples R China 3.Chinese Acad Sci, Innovat Acad Earth Sci, Beijing 100029, Peoples R China |
| 推荐引用方式 GB/T 7714 | Zhang, Shun,Zhou, Nannan. Extraction of Multiple Electrical Parameters From IP-Affected Transient Electromagnetic Data Based on LSTM-ResNet[J]. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING,2023,61:14. |
| APA | Zhang, Shun,&Zhou, Nannan.(2023).Extraction of Multiple Electrical Parameters From IP-Affected Transient Electromagnetic Data Based on LSTM-ResNet.IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING,61,14. |
| MLA | Zhang, Shun,et al."Extraction of Multiple Electrical Parameters From IP-Affected Transient Electromagnetic Data Based on LSTM-ResNet".IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING 61(2023):14. |
入库方式： OAI收割
来源：地质与地球物理研究所
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