Synthesizing magnetotelluric time series based on forward modeling
The validity of magnetotelluric time-series processing methods has been lacking reasonable testing criteria. Since the time series synthesized by existing techniques are not fully derived from a given model, they are not reliable. In this paper, we present a novel approach to synthesize magnetotellu...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2023-02-01
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| Series: | Frontiers in Earth Science |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/feart.2023.1086749/full |
| _version_ | 1811168356078714880 |
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| author | Peijie Wang Xiaobin Chen Yunyun Zhang |
| author_facet | Peijie Wang Xiaobin Chen Yunyun Zhang |
| author_sort | Peijie Wang |
| collection | DOAJ |
| description | The validity of magnetotelluric time-series processing methods has been lacking reasonable testing criteria. Since the time series synthesized by existing techniques are not fully derived from a given model, they are not reliable. In this paper, we present a novel approach to synthesize magnetotelluric time series based on forward modeling and the correspondence between frequency and time domain electromagnetic fields. In this approach, we obtain the electromagnetic response of two orthogonal polarization sources for a given model by magnetotelluric forward modeling, and simulate the randomness of the polarization of the natural field source by a linear combination of the two polarization sources. Based on the correspondence between the frequency and time domain electromagnetic fields, the electromagnetic fields obtained by forward modeling in the frequency domain are transformed into the time domain, and finally the time series are synthesized. The test results on 1D and 3D models validate the effectiveness of the proposed method and the correctness of the procedure. After adding noise to the synthesized time series, we can test the performance of each method by comparing the results of the time series processing methods with the response of the given model. Therefore, the method presented in this paper can be used to construct standard magnetotelluric time series, which can be used as a carrier to construct synthetic data satisfying various noise distributions, and for the study of related methods. This method can also be used to synthesize time series of other frequency-domain electromagnetic methods. |
| first_indexed | 2024-04-10T16:26:00Z |
| format | Article |
| id | doaj.art-98b9a3ac01da4eb88db6fef0a57096de |
| institution | Directory Open Access Journal |
| issn | 2296-6463 |
| language | English |
| last_indexed | 2024-04-10T16:26:00Z |
| publishDate | 2023-02-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Earth Science |
| spelling | doaj.art-98b9a3ac01da4eb88db6fef0a57096de2023-02-09T06:49:52ZengFrontiers Media S.A.Frontiers in Earth Science2296-64632023-02-011110.3389/feart.2023.10867491086749Synthesizing magnetotelluric time series based on forward modelingPeijie Wang0Xiaobin Chen1Yunyun Zhang2State Key Laboratory of Earthquake Dynamics, Institute of Geology, China Earthquake Administration, Beijing, ChinaNational Institute of Natural Hazards, Ministry of Emergency Management of China, Beijing, ChinaNational Institute of Natural Hazards, Ministry of Emergency Management of China, Beijing, ChinaThe validity of magnetotelluric time-series processing methods has been lacking reasonable testing criteria. Since the time series synthesized by existing techniques are not fully derived from a given model, they are not reliable. In this paper, we present a novel approach to synthesize magnetotelluric time series based on forward modeling and the correspondence between frequency and time domain electromagnetic fields. In this approach, we obtain the electromagnetic response of two orthogonal polarization sources for a given model by magnetotelluric forward modeling, and simulate the randomness of the polarization of the natural field source by a linear combination of the two polarization sources. Based on the correspondence between the frequency and time domain electromagnetic fields, the electromagnetic fields obtained by forward modeling in the frequency domain are transformed into the time domain, and finally the time series are synthesized. The test results on 1D and 3D models validate the effectiveness of the proposed method and the correctness of the procedure. After adding noise to the synthesized time series, we can test the performance of each method by comparing the results of the time series processing methods with the response of the given model. Therefore, the method presented in this paper can be used to construct standard magnetotelluric time series, which can be used as a carrier to construct synthetic data satisfying various noise distributions, and for the study of related methods. This method can also be used to synthesize time series of other frequency-domain electromagnetic methods.https://www.frontiersin.org/articles/10.3389/feart.2023.1086749/fullmagnetotelluricelectromagnetic theoryforward modelingsynthesize time seriesdata processing |
| spellingShingle | Peijie Wang Xiaobin Chen Yunyun Zhang Synthesizing magnetotelluric time series based on forward modeling Frontiers in Earth Science magnetotelluric electromagnetic theory forward modeling synthesize time series data processing |
| title | Synthesizing magnetotelluric time series based on forward modeling |
| title_full | Synthesizing magnetotelluric time series based on forward modeling |
| title_fullStr | Synthesizing magnetotelluric time series based on forward modeling |
| title_full_unstemmed | Synthesizing magnetotelluric time series based on forward modeling |
| title_short | Synthesizing magnetotelluric time series based on forward modeling |
| title_sort | synthesizing magnetotelluric time series based on forward modeling |
| topic | magnetotelluric electromagnetic theory forward modeling synthesize time series data processing |
| url | https://www.frontiersin.org/articles/10.3389/feart.2023.1086749/full |
| work_keys_str_mv | AT peijiewang synthesizingmagnetotellurictimeseriesbasedonforwardmodeling AT xiaobinchen synthesizingmagnetotellurictimeseriesbasedonforwardmodeling AT yunyunzhang synthesizingmagnetotellurictimeseriesbasedonforwardmodeling |