Magnetotelluric Time Series Denoising Using Encoder-Decoder Consisted of LSTM Cells
文献类型：期刊论文
| 作者 | Wang,Sihao2,3,4; He,Lanfang2,3,4; Wang,Xuben1; Li,Liang2,3,4 |
| 刊名 | Journal of Physics: Conference Series
 |
| 出版日期 | 2023-12-01 |
| 卷号 | 2651期号:1 |
| ISSN号 | 1742-6588 |
| 关键词 | LSTM Magnetotelluric Denoising Encoder-Decoder Time Series |
| DOI | 10.1088/1742-6596/2651/1/012123 |
| 英文摘要 | Abstract Electromagnetic signals in geophysics are frequently disturbed by various interference in field data acquisition. Denoising for passive electromagnetic methods such as magnetotelluric (MT) or audio magnetotelluric (AMT) data is significant to improve data quality and finally imaging to the geoelectrical structure. Conventionally, most denoising methods are employed in frequency domain and few of them are applied in time domain. However, a great number of irregular noise in the electromagnetic time series prove difficulty to be removed. We propose a denoising method, using Encoder-Decoder consisted of Long Short-Term Memory cells (ED-LSTM), to reduce the effect of the step noise and the random-impulsive noise. Supervised learning and transductive learning are used for the denoising of the step noise and the random-impulsive noise, respectively. Our results indicate that the step and random-impulsive noise could be successfully removed from the raw time series. The result indicate that ED-LSTM could potentially to be wildly used in the electromagnetic time series denoising and then improve data quality. |
| 语种 | 英语 |
| 出版者 | IOP Publishing |
| WOS记录号 | IOP:JPCS_2651_1_012123 |
| 源URL | [http://ir.iggcas.ac.cn/handle/132A11/111668]  |
| 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 |
| 作者单位 | 1.State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation, Chengdu University of Technology, Chengdu 610059, China 2.Key Laboratory of Mineral Resources, Institute of Geology and Geophysics, Chinese Academy of Sciences, Beijing 100029, China. 3.College of Earth and Planetary Sciences, University of Chinese Academy of Sciences, Beijing 100049, China 4.Innovation Academy for Earth Science, Chinese Academy of Sciences, Beijing, China |
| 推荐引用方式 GB/T 7714 | Wang,Sihao,He,Lanfang,Wang,Xuben,et al. Magnetotelluric Time Series Denoising Using Encoder-Decoder Consisted of LSTM Cells[J]. Journal of Physics: Conference Series,2023,2651(1). |
| APA | Wang,Sihao,He,Lanfang,Wang,Xuben,&Li,Liang.(2023).Magnetotelluric Time Series Denoising Using Encoder-Decoder Consisted of LSTM Cells.Journal of Physics: Conference Series,2651(1). |
| MLA | Wang,Sihao,et al."Magnetotelluric Time Series Denoising Using Encoder-Decoder Consisted of LSTM Cells".Journal of Physics: Conference Series 2651.1(2023). |
入库方式： OAI收割
来源：地质与地球物理研究所
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