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Magnetochemistry
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Advances in Magnetotelluric Analysis
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Advances in Magnetotelluric Analysis

A special issue of Magnetochemistry (ISSN 2312-7481). This special issue belongs to the section "Magnetic Field".

Deadline for manuscript submissions: closed (20 June 2023) | Viewed by 8863

Special Issue Editors

Dr. Octavio Castillo-Reyes

E-Mail Website
Guest Editor
Geosciences applications group, CASE department of the BSC-CNS, Centro Nacional de Supercomputación, 08034 Barcelona, Spain
Interests: geoelectromagnetic modeling; numerical simulations; high-performance computing; high-order finite elements
Dr. Guang Li

E-Mail Website
Guest Editor
School of Geophysics and Measurement-control Technology, East China University of Technology, Nanchang 330013, China
Interests: deep learning; machine learning; dictionary learning; compressed sensing; magnetotelluric data processing and application; CSEM data reconstruction

Special Issue Information

Dear Colleagues,

The magnetotelluric (MT) analysis method is now an important tool for imaging complex systems. Over recent years, many and different MT studies for several and diverse problems have been reported. However, studying EM fields behavior in the context of a realistic systems is a nontrivial task from a numerical modeling perspective. The presence of high conductivity contrasts, large-scale variations, and complex geometries arises as main challenges. Fortunately, although numerically challenging, the MT imaging of realistic setups is feasible given the numerical and computational advancements that have been achieved in the MT modeling community in recent decades. In this issue, we aim to focus on the aforementioned problems, specially targeting those with high potential for industrial applications.

Dr. Octavio Castillo-Reyes
Dr. Guang Li
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Magnetochemistry is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • numerical solutions
  • magnetotelluric modeling
  • analysis of magnetotelluric responses
  • industrial applications
  • magnetotelluric data processing
  • machine learning

Published Papers (6 papers)

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Research

17 pages, 135217 KiB  
Article
Magnetic Inversion and Regional Tectonics of the Dabie Orogen
by Liang Zhang, Guangyin Lu, Ziqiang Zhu, Shujin Cao, Yajing Mao, Xinyue Chen and Lichang Wang
Magnetochemistry 2023, 9(3), 82; https://doi.org/10.3390/magnetochemistry9030082 - 15 Mar 2023
Cited by 1 | Viewed by 933
Abstract
Physical property inversion techniques are the methods to reveal the internal structures of Earth’s lithosphere. In this study, we introduce an Occam-type inversion algorithm into a spherical coordinate system, and invert the magnetization based on the three-component magnetic anomalies. The synthetic model tests [...] Read more.
Physical property inversion techniques are the methods to reveal the internal structures of Earth’s lithosphere. In this study, we introduce an Occam-type inversion algorithm into a spherical coordinate system, and invert the magnetization based on the three-component magnetic anomalies. The synthetic model tests show that the inversion effects of the vertical components are relatively stable, while the anti-noise ability is strong. We apply the algorithm to a set of vertical component anomalies derived from the satellite magnetic field model and obtain Dabie orogen 3D magnetization distribution. Multiple magnetic sources are identified within the orogen and adjacent areas, and the related tectonic evolution processes are analyzed. The significant magnetization characteristics of the orogen can be associated with mantle upwelling caused by the Early Cretaceous lithospheric delamination, along with the partial melting of the mafic–ultramafic lower crust that had not participated in the delamination. The magnetic sources near the Mozitan–Xiaotian fault, and those located in the western Dabie area, are also restricted by Mesozoic and Jurassic–Cretaceous deep melt activities, respectively. The study provides evidence for the suture line position of the plate subduction in the deep lithosphere. Furthermore, the results display certain indications of mineralization activities in the middle–lower Yangtze Valley metallogenic belt. Full article
(This article belongs to the Special Issue Advances in Magnetotelluric Analysis)
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14 pages, 4738 KiB  
Article
A Pre-Seismic Anomaly Detection Approach Based on Earthquake Cross Partial Multi-View Data Fusion
by Yongming Huang, Kun’ao Zhu, Wen Shi, Yong Lu, Gaochuan Liu, Guobao Zhang and Yuntian Teng
Magnetochemistry 2023, 9(2), 48; https://doi.org/10.3390/magnetochemistry9020048 - 03 Feb 2023
Cited by 1 | Viewed by 2073
Abstract
It is a challenge to detect pre-seismic anomalies by using only one dataset due to the complexity of earthquakes. Therefore, it is a promising direction to use multiparameteric data. The earthquake cross partial multi-view data fusion approach (EQ-CPM) is proposed in this paper. [...] Read more.
It is a challenge to detect pre-seismic anomalies by using only one dataset due to the complexity of earthquakes. Therefore, it is a promising direction to use multiparameteric data. The earthquake cross partial multi-view data fusion approach (EQ-CPM) is proposed in this paper. By using this method, electromagnetic data and seismicity indicators are fused. This approach tolerates the absence of data and complements the missing part in fusion. First, the effectiveness of seismicity indicators and electromagnetic data was validated through two earthquake case studies. Then, four machine learning algorithms were applied to detect pre-seismic anomalies by using the fused data and two original datasets. The results show that the fused data provided better performance than the single-modal data. In the Matthews correlation coefficient index, the results of our method showed an 8% improvement compared with the latest study. Full article
(This article belongs to the Special Issue Advances in Magnetotelluric Analysis)
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13 pages, 9393 KiB  
Article
Two-Dimensional Magnetotelluric Parallel-Constrained-Inversion Using Artificial-Fish-Swarm Algorithm
by Zuzhi Hu, Yanling Shi, Xuejun Liu, Zhanxiang He, Ligui Xu, Xiaoli Mi and Juan Liu
Magnetochemistry 2023, 9(2), 34; https://doi.org/10.3390/magnetochemistry9020034 - 18 Jan 2023
Cited by 1 | Viewed by 1171
Abstract
An important way to improve the resolution of electromagnetic exploration is by using known seismic and logging data. Based on previous work, 2D magnetotelluric (MT) parallel-constrained-inversion, based on an artificial-fish-swarm algorithm is further developed. The finite-difference (FD) method with paralleling frequency is used [...] Read more.
An important way to improve the resolution of electromagnetic exploration is by using known seismic and logging data. Based on previous work, 2D magnetotelluric (MT) parallel-constrained-inversion, based on an artificial-fish-swarm algorithm is further developed. The finite-difference (FD) method with paralleling frequency is used for 2D MT-forward-modeling, to improve computational efficiency. The results of the FD and finite-element (FE) methods show that the accuracy of FD is comparable to FE in the case of suitable mesh-generation; however, the calculation speed is ten times faster than that of the FE. The artificial-fish-swarm algorithm is introduced and applied to parallel-constrained-inversion of 2D MT data. The results of the synthetic-model test show that the artificial-fish-swarm-inversion based on paralleling forward can recover the model well and effectively improve the inversion speed. The processing and interpretation results of the field data are verified by drilling, which shows that the proposed inversion-method has good practicability. Full article
(This article belongs to the Special Issue Advances in Magnetotelluric Analysis)
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21 pages, 9635 KiB  
Article
Hydrogeological Study in Tongchuan City Using the Audio-Frequency Magnetotelluric Method
by Zhimin Xu, Huicui Xin, Yuren Weng and Guang Li
Magnetochemistry 2023, 9(1), 32; https://doi.org/10.3390/magnetochemistry9010032 - 14 Jan 2023
Cited by 1 | Viewed by 1348
Abstract
Tongchuan City, located in Shaanxi Province, northwest China, has limited groundwater resources. Rational planning and exploitation of groundwater are crucial to the sustainable development of the city, for which investigating the distribution of groundwater is the premise. Traditional resistivity sounding methods are often [...] Read more.
Tongchuan City, located in Shaanxi Province, northwest China, has limited groundwater resources. Rational planning and exploitation of groundwater are crucial to the sustainable development of the city, for which investigating the distribution of groundwater is the premise. Traditional resistivity sounding methods are often used to detect groundwater; however, these methods are not applicable in the study area where thick Quaternary loess is extensively distributed. In this study, we arranged five audio-frequency magnetotelluric (AMT) profiles to detect the deep clastic rock groundwater and carbonate karst fissure groundwater in Tongchuan. Firstly, we analyzed the electromagnetic interference (EMI) noises in Tongchuan City, revealing that the main EMI is power frequency interference (PFI). We used the dictionary learning processing technology to suppress the PFI. Secondly, the two-dimensional (2D) nonlinear conjugate gradient method was employed to invert a 2D electrical structure model for the area shallower than 1 km. We analyzed the characteristics of the electrical structure and its geological significance. Lastly, the three-dimensional (3D) electrical structure model of the study area was inverted using the 3D nonlinear conjugate gradient method, and the spatial distribution characteristics of the water-bearing strata were further analyzed. The results show that the PFI in urban environment can be suppressed by the dictionary learning processing technology. In Tongchuan city, the distribution of clastic rock fissure water is controlled by folds and faults, as well as the thickness of sandstone layers, and that of the carbonate karst fissure water is mainly controlled by faults. On this basis, we infer that the water-bearing areas are in the middle east and south of the study area. Full article
(This article belongs to the Special Issue Advances in Magnetotelluric Analysis)
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17 pages, 5488 KiB  
Article
Wavelet-Based Three-Dimensional Inversion for Geomagnetic Depth Sounding
by Shiwen Li and Yunhe Liu
Magnetochemistry 2022, 8(12), 187; https://doi.org/10.3390/magnetochemistry8120187 - 12 Dec 2022
Cited by 1 | Viewed by 1287
Abstract
The complexity of Earth’s structure poses a challenge to the multiscale detection capability of geophysics. In this paper, we present a new wavelet-based three-dimensional inversion method for geomagnetic depth sounding. This method is based on wavelet functions to transfer model parameters in the [...] Read more.
The complexity of Earth’s structure poses a challenge to the multiscale detection capability of geophysics. In this paper, we present a new wavelet-based three-dimensional inversion method for geomagnetic depth sounding. This method is based on wavelet functions to transfer model parameters in the space domain into the wavelet domain. The model is represented by wavelet coefficients containing both large- and fine-scale information, enabling wavelet-based inversion to describe multiscale anomalies. L1-norm measurement is applied to measure the model roughness to accomplish the sparsity constraint in the wavelet domain. Meanwhile, a staggered-grid finite difference method in a spherical coordinate system is used to calculate the forward responses, and the limited-memory quasi-Newton method is applied to seek the solution of the inversion objective function. Inversion tests of synthetic data for multiscale models show that wavelet-based inversion is stable and has multiresolution. Although higher-order wavelets can lead to finer results, our tests present that a db6 wavelet is suitable for geomagnetic depth sounding inversion. The db6 inversion results of responses at 129 geomagnetic observatories around the world reveal a higher-resolution image of the mantle. Full article
(This article belongs to the Special Issue Advances in Magnetotelluric Analysis)
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16 pages, 19021 KiB  
Article
An Improved 3D Magnetization Inversion Based on Smoothness Constraints in Spherical Coordinates
by Liang Zhang, Guangyin Lu, Ziqiang Zhu and Shujin Cao
Magnetochemistry 2022, 8(11), 157; https://doi.org/10.3390/magnetochemistry8110157 - 14 Nov 2022
Cited by 2 | Viewed by 1344
Abstract
In the inverse problem, the traditional way to obtain a stable solution is based on the maximum smoothness criteria. However, this approach cannot generate clearer and more focused images. In this study, we propose an improved inversion method based on the smoothness constraints. [...] Read more.
In the inverse problem, the traditional way to obtain a stable solution is based on the maximum smoothness criteria. However, this approach cannot generate clearer and more focused images. In this study, we propose an improved inversion method based on the smoothness constraints. In the algorithm, the model weighting functions are updated by adding a model’s total gradient module matrix, which can effectively constrain the boundary of the recovery model in the iterative operation. We invert the 3D magnetization intensity for the three-component magnetic data in the spatial domain by spherical coordinates. The preconditional conjugate gradient algorithm is introduced to improve the efficiency of the solutions. We design two sets of synthetic examples to evaluate the inversion effects, which show that the improved method is more reliable than the smoothness constraint method. The boundary of the magnetic bodies is more precise, and the magnetization ranges are more focused. The method does not rely on the initial model and is suitable for magnetic vector data inversion. We also apply the algorithm to a set of Dabie orogen three-component magnetic data derived from a geomagnetic field model and verify the effectiveness of the inversion method. Full article
(This article belongs to the Special Issue Advances in Magnetotelluric Analysis)
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