Special Issue "Electromagnetic Exploration: Theory, Methods and Applications"

A special issue of Minerals (ISSN 2075-163X). This special issue belongs to the section "Mineral Exploration Methods and Applications".

Deadline for manuscript submissions: closed (30 June 2022) | Viewed by 8111

Special Issue Editors

Dr. Binzhong Zhou
E-Mail Website
Guest Editor
CSIRO Mineral Resources, PO Box 883, Kenmore, QLD 4069, Australia
Interests: seismic method; borehole logging; georadar; electromagnetics; electrical resistivity imaging; mine scale geophysics
Dr. Changchun Yin
E-Mail Website
Guest Editor
College of Geo-Exploration Sciences and Technology, Jilin University, Changchun 130026, China
Interests: land-based electromagnetic method; airborne and marine electromagnetic methods; 3D forward modeling; joint and constrained inversions; artificial intelligence and its application in geophysics
Dr. Zhengyong Ren
E-Mail Website
Guest Editor
School of Geoscience and Info-Physics, Central South University, Changsha 410083, China
Interests: electromagnetic methods; gravity methods; magnetic methods; new forward solvers; new inversion solvers
Dr. Xuben Wang
E-Mail Website
Guest Editor
Key Lab of Earth Exploration&Information Techniques of Ministry of Education, Chengdu University of Technology, Chengdu 610059, China
Interests: magnetotelluric sounding; electromagnetic methods; airborne transient electromagnetic methods; mineral and engineering geophysics

Special Issue Information

Dear Colleagues,

Electromagnetic (EM) methods, both airborne and ground, are one of the most widely used geophysical techniques in mineral exploration, in which natural or controlled sources are used to transmit EM waves into the Earth and measure the returned EM fields. The EM methods include the transient electromagnetic (TEM) method, radio imaging method (RIM), ground-penetrating radar (GPR), borehole radar (BHR), magnetotelluric (MT) method, audio-magnetotelluric (AMT) and controlled-source audio-magnetotelluric (CSAMT) method. They are used not only for the discovery of mineral deposits and extension of reserves of existing mines, but also for structural mapping of the Earth, oil and gas exploration, environment and engineering, and groundwater investigation. The ability of these methods to explore deep Earth has improved significantly in recent decades with advances in sensors, space- and drone-based observation platforms, electronics, data processing and inversion techniques, and application of machine learning. All these have improved the resolution and detectability of EM methods. In this Special Issue, we seek contributions from the EM geophysical community with the latest innovation on EM equipment developments, data processing, forward modeling and inversion, and especially applications to mineral explorations. We also welcome papers on review and case studies of EM technologies.

We look forward to receiving your contributions to this Special Issue.

Dr. Binzhong Zhou
Dr. Changchun Yin
Dr. Zhengyong Ren
Dr. Xuben Wang
Guest Editors

Manuscript Submission Information

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2000 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

  •  Electromagnetic method
  •  TEM method
  •  Radio imaging method
  •  GPR
  •  Borehole radar
  •  MT methods
  •  AMT method
  •  CSAMT method
  •  Apparent resistivity
  •  Mineral deposits
  •  Orebody delineation
  •  Groundwater
  •  Environment and engineering

Published Papers (14 papers)

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Research

Article
Deep Learning Optimized Dictionary Learning and Its Application in Eliminating Strong Magnetotelluric Noise
Minerals 2022, 12(8), 1012; https://doi.org/10.3390/min12081012 - 12 Aug 2022
Viewed by 209
Abstract
The noise suppression method based on dictionary learning has shown great potential in magnetotelluric (MT) data processing. However, the constraints used in the existing algorithm’s method need to set manually, which significantly limits its application. To solve this problem, we propose a deep [...] Read more.
The noise suppression method based on dictionary learning has shown great potential in magnetotelluric (MT) data processing. However, the constraints used in the existing algorithm’s method need to set manually, which significantly limits its application. To solve this problem, we propose a deep learning optimized dictionary learning denoising method. We use a deep convolutional network to learn the characteristic parameters of high-quality MT data independently and then use them as the constraints for dictionary learning so as to achieve fully adaptive sparse decomposition. The method uses unified parameters for all data and completely eliminates subjective bias, which makes it possible to batch-process MT data using sparse decomposition. The processing results of simulated and field data examples show that the new method has good adaptability and can achieve recognition with high accuracy. After processing with our method, the apparent resistivity and phase curves became smoother and more continuous, and the results were validated by the remote reference method. Our method can be an effective alternative method when no remote reference station is set up or the remote reference processing is not effective. Full article
(This article belongs to the Special Issue Electromagnetic Exploration: Theory, Methods and Applications)
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Article
Magnetotelluric Responses of an Anisotropic 1-D Earth with a Layer of Exponentially Varying Conductivity
Minerals 2022, 12(7), 915; https://doi.org/10.3390/min12070915 - 21 Jul 2022
Viewed by 232
Abstract
The magnetotelluric (MT) sounding of a layered Earth model involving a transitional layer has been widely studied, and MT responses of the model with dipping anisotropic conductivity have also been treated. However, a model incorporating both a transitional layer and dipping anisotropy has [...] Read more.
The magnetotelluric (MT) sounding of a layered Earth model involving a transitional layer has been widely studied, and MT responses of the model with dipping anisotropic conductivity have also been treated. However, a model incorporating both a transitional layer and dipping anisotropy has seldom been considered. The analytical solution of such a geoelectrical model including three layers was derived in this study. The middle layer was a transitional layer with conductivity exponentially varying with depth, which was covered by a homogeneous layer and underlaid by a dipping anisotropic half-space. The electromagnetic (EM) fields in the transitional layer were explicitly solved with modified Bessel functions. The surface impedance was calculated recursively. The dependence of the apparent resistivity and impedance phase as well as the EM fields on different model parameters were investigated in detail. We believe that our analytical solution provides a useful complement to the theory of the one-dimensional (1D) inversion and interpretation based on the layered model with fixed conductivity. Full article
(This article belongs to the Special Issue Electromagnetic Exploration: Theory, Methods and Applications)
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Article
Prospective Evaluation of Geothermal Resources in the Shangqiu Uplift of the Southern North China Basin with Magnetotelluric Detection
Minerals 2022, 12(7), 811; https://doi.org/10.3390/min12070811 - 25 Jun 2022
Viewed by 376
Abstract
The magnetotelluric sounding (MT) method is used to detect and study the deep stratigraphic structure and hidden faults in the Shangqiu Uplift. A total of 4 MT profiles are arranged, and 97 stations are collected. The nonlinear conjugate gradient (NLCG) two-dimensional inversion method [...] Read more.
The magnetotelluric sounding (MT) method is used to detect and study the deep stratigraphic structure and hidden faults in the Shangqiu Uplift. A total of 4 MT profiles are arranged, and 97 stations are collected. The nonlinear conjugate gradient (NLCG) two-dimensional inversion method is used to jointly invert data from both the TE and TM modes after a dimensionality analysis and impedance tensor decomposition; reliable two-dimensional resistivity models are produced since the data quality is excellent. Three-dimensional inversion is carried out to full impedance tensor as well to produce a three-dimensional resistivity model of the study area, which shows good consistency with the two-dimensional models. The results show that the electrical structure of the Shangqiu Uplift has typical layered characteristics, which can be divided into three layers from top to bottom, namely low-, medium-to-high-, and high-resistivity layers. According to the resistivity models and in combination with the gravity, aeromagnetic, seismic, and regional geological data of the study area, a geological map of the basement rock of the Shangqiu Uplift is produced. Two prospective geothermal anomaly areas are proposed according to the distribution of the high-resistivity anomaly formed by the basement uplift, which has a good corresponding relationship with the high-value area of the regional geothermal field. A geothermal exploration well (SR-1) is constructed in one of the inferred prospective geothermal anomaly areas. The well is 1702 m deep, with a water output of 1500 m3/day and a wellhead water temperature of 51.5 °C. This is the geothermal well with the largest water yield in the Shangqiu area at present, which provides a new basis for future geothermal exploration, development, and utilization. Full article
(This article belongs to the Special Issue Electromagnetic Exploration: Theory, Methods and Applications)
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Article
Joint Inversion with Borehole and Semi-Airborne TEM Data Based on Equivalent Filament Approximation
Minerals 2022, 12(7), 803; https://doi.org/10.3390/min12070803 - 24 Jun 2022
Viewed by 304
Abstract
The borehole transient electromagnetic (TEM) method can be useful in deep mineral exploration to detect blind ore bodies beside or below the borehole, and is especially adapted to finding small-scale, deep, rich ore bodies. In this method a transmitting loop is deployed on [...] Read more.
The borehole transient electromagnetic (TEM) method can be useful in deep mineral exploration to detect blind ore bodies beside or below the borehole, and is especially adapted to finding small-scale, deep, rich ore bodies. In this method a transmitting loop is deployed on the top surface of the Earth, while a receiving coil is moved down the borehole. As the borehole TEM method is limited by the borehole’s location and depth, so its exploration scope is limited. The surface to airborne TEM method is a semi-airborne TEM configuration that transmits on the surface and receives TEM response in air. The two systems are combined into one system in this study, sharing the transmission loop deployed on the surface. With this combined system, the TEM response in the borehole and in the air can be observed at the same time. This paper employs a joint interpretation method based on the equivalent filament, which is introduced to obtain more reliable geometric information for the target with both borehole and aerial TEM data. The eddy currents induced in a thin confined conductor can be represented by equivalent current filaments, and the distribution of filaments can reflect the position and geometry of the conductor. Therefore, geometric parameters of targets can be obtained by filament inversion, and the joint inversion can be more accurate with both borehole and aerial response. Numerical modeling results show that the joint inversion based on the equivalent filament results can reliably obtain the geometric parameters of the thin conductive plate embedded in half space. Full article
(This article belongs to the Special Issue Electromagnetic Exploration: Theory, Methods and Applications)
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Article
Comprehensive Physical Properties and Exploration Potential of the Permian Igneous Rocks in the Southwestern Sichuan Basin
Minerals 2022, 12(7), 789; https://doi.org/10.3390/min12070789 - 21 Jun 2022
Viewed by 379
Abstract
The Permian igneous rocks in the Sichuan Basin represent a major breakthrough, opening up a new prospect for oil and gas exploration, and igneous reservoirs have become a new field of oil and gas exploration. Gravity-magnetic-electric exploration is an effective means of identifying [...] Read more.
The Permian igneous rocks in the Sichuan Basin represent a major breakthrough, opening up a new prospect for oil and gas exploration, and igneous reservoirs have become a new field of oil and gas exploration. Gravity-magnetic-electric exploration is an effective means of identifying igneous rocks and helps in reducing the multiplicity of the prediction results. However, the lithology of igneous rocks is quite different, and the exploration theory and evaluation techniques need urgently to be improved. In order to deeply study the response characteristics of the gravity-magnetic-electric and physical properties of the Permian igneous rocks in the Sichuan Basin and their relationships with the reservoir parameters, physical property testing was carried out on outcrop samples of the Permian igneous rocks in southwestern Sichuan. The comprehensive physical properties of the samples with different lithologies, including basalt, tuff, and volcanic breccia, were analyzed and studied. Based on the geological characteristics of the igneous rocks, such as the mineral composition, microstructure, and reservoir properties, a multi-parameter intersection relationship model for the resistivity, polarizability, density, magnetic susceptibility, and their relationships with the reservoir parameters was established, and effective parameters favorable for igneous rock identification and reservoir evaluation were identified. The results of this study provide a physical basis and technical support for non-seismic exploration of igneous oil and gas reservoirs in the Sichuan Basin. Full article
(This article belongs to the Special Issue Electromagnetic Exploration: Theory, Methods and Applications)
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Article
Identification and Suppression of Magnetotelluric Noise via a Deep Residual Network
Minerals 2022, 12(6), 766; https://doi.org/10.3390/min12060766 - 16 Jun 2022
Viewed by 530
Abstract
The magnetotelluric (MT) method is widely applied in petroleum, mining, and deep Earth structure exploration but suffers from cultural noise. This noise will distort apparent resistivity and phase, leading to false geological interpretation. Therefore, denoising is indispensable for MT signal processing. The sparse [...] Read more.
The magnetotelluric (MT) method is widely applied in petroleum, mining, and deep Earth structure exploration but suffers from cultural noise. This noise will distort apparent resistivity and phase, leading to false geological interpretation. Therefore, denoising is indispensable for MT signal processing. The sparse representation method acts as a critical role in MT denoising. However, this method depends on the sparse assumption leading to inadequate denoising results in some cases. We propose an alternative MT denoising approach, which can achieve accurate denoising without assumptions on datasets. We first design a residual network (ResNet), which has an excellent fitting ability owing to its deep architecture. In addition, the ResNet network contains skip-connection blocks to guarantee the robustness of network degradation. As for the number of training, validation, and test datasets, we use 10,000,000; 10,000; and 100 field data, respectively, and apply the gradual shrinkage learning rate to ensure the ResNet’s generalization. In the noise identification stage, we use a small-time window to scan the MT time series, after which the gramian angular field (GAF) is applied to help identify noise and divide the MT time series into noise-free and noise data. We keep the noise-free data section in the denoising stage, and the noise data section is fed into our network. In our experiments, we test the performances of different time window sizes for noise identification and suppression and record corresponding time consumption. Then, we compare our approach with sparse representation methods. Testing results show that our approach can obtain the desired denoising results. The accuracy and loss curves show that our approach can well suppress the MT noise, and our network has a good generalization. To further validate our approach’s effectiveness, we show the apparent resistivity, phase, and polarization direction of test datasets. Our approach can adjust the distortion of apparent resistivity and phase and randomize the polarization direction distribution. Although our approach requires the high quality of the training dataset, it achieves accurate MT denoising after training and can be meaningful in cases of a severe MT noisy environment. Full article
(This article belongs to the Special Issue Electromagnetic Exploration: Theory, Methods and Applications)
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Article
Three-Dimensional Magnetotelluric Inversion for Triaxial Anisotropic Medium in Data Space
Minerals 2022, 12(6), 734; https://doi.org/10.3390/min12060734 - 08 Jun 2022
Viewed by 487
Abstract
The interpretation of three-dimensional (3-D) magnetotelluric (MT) data is usually based on the isotropic assumption of the subsurface structures, and this assumption could lead to erroneous interpretation in the area with considerable electrical anisotropy. Although arbitrary anisotropy is much closer to the ground [...] Read more.
The interpretation of three-dimensional (3-D) magnetotelluric (MT) data is usually based on the isotropic assumption of the subsurface structures, and this assumption could lead to erroneous interpretation in the area with considerable electrical anisotropy. Although arbitrary anisotropy is much closer to the ground truth, it is generally more challenging to recover full anisotropy parameters from 3-D inversion. In this paper, we present a 3-D triaxial anisotropic inversion framework using the edge-based finite element method with a tetrahedral mesh. The 3-D inverse problem is solved by the Gauss-Newton (GN) method which shows fast convergence behavior. The computation cost of the data-space method depends on the size of data, which is usually smaller than the size of model; therefore, we transform the inversion algorithm from the model space to the data space for memory efficiency. We validate the effectiveness and applicability of the developed algorithm using several synthetic model studies. Full article
(This article belongs to the Special Issue Electromagnetic Exploration: Theory, Methods and Applications)
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Article
Denoising Marine Controlled Source Electromagnetic Data Based on Dictionary Learning
Minerals 2022, 12(6), 682; https://doi.org/10.3390/min12060682 - 28 May 2022
Viewed by 474
Abstract
Marine controlled source electromagnetic (CSEM) is an efficient method to explore ocean resources. The amplitudes of marine CSEM signals decay rapidly with the measuring offsets. The signal is easily contaminated by various kinds of noise when the offset is large. These noise include [...] Read more.
Marine controlled source electromagnetic (CSEM) is an efficient method to explore ocean resources. The amplitudes of marine CSEM signals decay rapidly with the measuring offsets. The signal is easily contaminated by various kinds of noise when the offset is large. These noise include instrument internal noise, dipole vibration noise, seawater motion noise and environmental noise Suppressing noise is the key to improve data quality and interpretation accuracy. Sparse representation based denoising method has been used for denoising for a long time. provides a new way to remove noise. Under the framework of sparse representation, the denoising effect is closely related to the chosen transform matrix. This matrix is called dictionary and its column named atom. In general, the stronger the correlation between signal and dictionary is, the sparser representation will be, and further the better the denoising effect will be. In this article, a new method based on dictionary learning is proposed for marine CSEM denoising. Firstly, the signal segments suffering little from noise are captured to compose the training set. Then the learned dictionary is trained from the training set via K-singular value decomposition (K-SVD) algorithm. Finally, the learned dictionary is used to sparsely represent the contaminated signal and reconstruct the filtered one. The effectiveness of the proposed approach is verified by a synthetic data denoising experiment, in which windowed-Fourier-transform (WFT) and wavelet-transform (WT) denoising methods and three dictionaries (discrete-sine-transform (DST) dictionary, DST-wavelet merged dictionary and the learned dictionary) under a sparse representation framework are tested. The results demonstrate the superiority of the proposed dictionary-learning-based denoising method. Finally, the proposed approach is applied to field data denoising process, coupled with DST and DST-wavelet dictionaries based denoising methods. The outcomes further proves that the propsoed approach is effective and superior for marine CSEM data denoising. Full article
(This article belongs to the Special Issue Electromagnetic Exploration: Theory, Methods and Applications)
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Article
Natural Source Electromagnetic Component Exploration of Coalbed Methane Reservoirs
Minerals 2022, 12(6), 680; https://doi.org/10.3390/min12060680 - 28 May 2022
Viewed by 411
Abstract
As an environmentally friendly and high-calorific natural gas, coalbed methane (CBM) has become one of the world’s most crucial unconventional energy sources. Undoubtedly, it is necessary to conduct in-depth research on reservoir exploration methods to ensure high and stable CBM production in the [...] Read more.
As an environmentally friendly and high-calorific natural gas, coalbed methane (CBM) has become one of the world’s most crucial unconventional energy sources. Undoubtedly, it is necessary to conduct in-depth research on reservoir exploration methods to ensure high and stable CBM production in the development stage. However, current methods have disadvantages such as high cost, complex devices, and poor terrain adaptability, and therefore they are unsuitable for reasonable monitoring of CBM reservoirs. In contrast, electromagnetic prospecting methods are increasingly widely employed in the rapid delineation of conductive distributions, contributing a lot to in-situ reservoir interpretation. Furthermore, a natural source Super-Low Frequency electromagnetic component method (i.e., the SLF method for short) has been proposed and applied with high potential in a CBM enrichment area, Qinshui Basin, China. In this paper, this method is thoroughly discussed. The magnetic component responses of the SLF method can be used as the characteristic responses of subsurface layers, and the forward modeling algorithms using the finite element method have been successfully developed and verified. On this basis, the direct depth transformation and one-dimensional nonlinear regularization inversion algorithms of the magnetic component responses are proposed for geo-object interpretation. With the help of the empirical mode decomposition (EMD), an SLF data processing workflow is demonstrated theoretically and practically, which is integrated into a portable instrument. The instrument’s ability to identify the low-resistivity reservoirs and their surrounding rocks has been proved by field survey. The extraction of electromagnetic radiation (EMR) anomalies also helps to refine the reservoir interpretation with higher accuracy. A joint comparative inversion test between the SLF method and the audio-magnetotelluric method (AMT) is also addressed, demonstrating that the SLF method is reliably applicable in the field survey of CBM reservoirs. A preliminary statistical analysis shows that the depth resolution of CBM reservoirs can reach the order of tens of meters. Therefore, the SLF method is expected to become one of the most potential options for in-situ CBM exploration with a cost-effective interpretation capability. Full article
(This article belongs to the Special Issue Electromagnetic Exploration: Theory, Methods and Applications)
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Article
A Feasibility Study of CSEM in Geological Advance Forecast with Horizontal Casing Well
Minerals 2022, 12(5), 638; https://doi.org/10.3390/min12050638 - 18 May 2022
Viewed by 435
Abstract
With the rapid exploitation of deep mines by digging new tunnels, the advance forecast of water inrush has become increasingly important. The land-based controlled source electromagnetic method (CSEM) is commonly used to detect water-bearing structures. To increase its sensitivity, we propose a new [...] Read more.
With the rapid exploitation of deep mines by digging new tunnels, the advance forecast of water inrush has become increasingly important. The land-based controlled source electromagnetic method (CSEM) is commonly used to detect water-bearing structures. To increase its sensitivity, we propose a new measuring configuration for CSEM by placing EM sensors in an underground steel-cased well. The numerical modeling is conducted by COMSOL to overcome the difficulties of investigating the feasibility of the measuring configuration. The current distribution and electromagnetic field along an in-seam horizontal casing are investigated based on a synthesis three-layered model. The results illustrate that the casing can be treated as antennas that enhance the electric fields at large depths. The water-bearing structures can be observed by a magnetic field (with a perpendicularly horizontal electric dipole (HED) source) rather than an electric field (with a parallelly HED source). Numerical simulations demonstrate that the proposed method is a feasible and effective technique for the detection of water-bearing structures during deep mineral exploration. Full article
(This article belongs to the Special Issue Electromagnetic Exploration: Theory, Methods and Applications)
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Article
Natural Field Airborne Electromagnetics—History of Development and Current Exploration Capabilities
Minerals 2022, 12(5), 583; https://doi.org/10.3390/min12050583 - 05 May 2022
Viewed by 431
Abstract
The mineral resources exploration industry continuously expands the efficiency requirements for geophysical technologies. Due to their relatively inexpensive nature, coupled with the ability to rapidly acquire data over large areas, airborne electromagnetic technologies have been used for decades in subsurface exploration. Limitations on [...] Read more.
The mineral resources exploration industry continuously expands the efficiency requirements for geophysical technologies. Due to their relatively inexpensive nature, coupled with the ability to rapidly acquire data over large areas, airborne electromagnetic technologies have been used for decades in subsurface exploration. Limitations on the depth of investigation of airborne platforms with controlled primary field sources is the main obstacle for using these systems in many geoelectrical conditions and geographical terrains. In addition, systems based on the time-domain principle are limited in applications requiring differentiations in a high resistivity range of the mapping parameter and suffer from parasitic electromagnetic non inductive natural effects in specific near surface conditions. Methods exploiting natural electromagnetic fields in the audio frequency range significantly increase depth of investigation and sensitivity to a wide range of resistivity contrasts including in the range of thousands of ohm-ms. A brief history of the development of the natural field airborne technology is provided accompanied by a comparison of the systems technical specifications. Field examples from the latest development in the airborne electromagnetic natural fields’ domain, MobileMT, demonstrate its exploration capabilities in both conductive and resistive environments, sensitivity to any direction of geoelectrical boundary, and detectability of near-surface discrete targets along with deeper structures. Full article
(This article belongs to the Special Issue Electromagnetic Exploration: Theory, Methods and Applications)
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Article
3D Inversion of Magnetic Gradient Tensor Data Based on Convolutional Neural Networks
Minerals 2022, 12(5), 566; https://doi.org/10.3390/min12050566 - 30 Apr 2022
Viewed by 547
Abstract
High-precision vector magnetic field detection has been widely used in the fields of celestial magnetic field detection, aeromagnetic detection, marine magnetic field detection and geomagnetic navigation. Due to the large amount of data, the 3D inversion of high-precision magnetic gradient vector data often [...] Read more.
High-precision vector magnetic field detection has been widely used in the fields of celestial magnetic field detection, aeromagnetic detection, marine magnetic field detection and geomagnetic navigation. Due to the large amount of data, the 3D inversion of high-precision magnetic gradient vector data often involves a large number of computational requirements and is very time-consuming. In this paper, a 3D magnetic gradient tensor (MGT) inversion method is developed, based on using a convolutional neural network (CNN) to automatically predict physical parameters from the 2D images of MGT. The information of geometry, depth and parameters such as magnetic inclination (I), magnetic declination (D) and magnetization susceptibility of magnetic anomalies is extracted, and a 3D model is obtained by comprehensive analysis. The method first obtains sufficient MGT data samples by forward modeling of different magnetic anomalies. Then, we use an improved CNN with shear layers to achieve the prediction of each magnetic parameter. The reliability of the algorithm is verified by numerical simulations of synthetic models of multiple magnetic anomalies. MGT data of the Tallawang magnetite diorite deposit in Australia are also predicted by using this method to obtain a slab model that matches the known geological information. The effects of sample size and noise level on the prediction accuracy are discussed. Compared with single-component prediction, the results of multi-component joint prediction are more reliable. From the numerical model study and the field data validation, we demonstrate the capability of using CNNs for inversing MGT data. Full article
(This article belongs to the Special Issue Electromagnetic Exploration: Theory, Methods and Applications)
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Article
Historic Underground Silver Mine Workings Detection Using 2D Electrical Resistivity Imaging (Durango, Mexico)
Minerals 2022, 12(4), 491; https://doi.org/10.3390/min12040491 - 17 Apr 2022
Viewed by 739
Abstract
This paper presents an underground silver mining operation outside Gomez Palacio, Durango, Mexico, terminated around the 1930s, of which previous knowledge of its operations was poor. Durango’s current silver exploration campaigns are likely to overlook historic silver mining sites due to interest in [...] Read more.
This paper presents an underground silver mining operation outside Gomez Palacio, Durango, Mexico, terminated around the 1930s, of which previous knowledge of its operations was poor. Durango’s current silver exploration campaigns are likely to overlook historic silver mining sites due to interest in specific prospect regions. A two-dimensional (2D) Electrical Resistivity Imaging (ERI) survey coupled with reconnaissance of the area was performed at this historic silver mining site. The exploration campaign aimed to find the abandoned mineshaft, map its subsurface extent, and explore the occurrence of mineralization zones (silver ore). The ERI survey comprised five profiles measured with the extended dipole-dipole array with a consistent electrode spacing of 5 m. The smooth, robust, and damped least-squares inversion methods were used to invert the 2D data. Our field observations and ERI survey results collectively reveal the following findings: (a) reconnaissance reveals mining infrastructure consistent with historical mining activity; the infrastructure includes a complex of habitational rooms, an ore-processing pit near a concrete slab next to a dirt road, and two limestone-wall structures interpreted as the entrance of abandoned backfilled mineshafts named Mesquite and Lechuguilla; (b) high-resistivity anomalies suggest vestiges of shallow, underground mine workings including backfilled mineshafts that connect a mine gallery complex, and (c) various low-resistivity anomalies, juxtaposed against mine galleries, suggestive of unmined shallow vein-type and manto-type mineralization of hydrothermal origin. The imaging depth is estimated at ~65 m. Underground silver mining moved southwards and was limited to ~40 m depth. Full article
(This article belongs to the Special Issue Electromagnetic Exploration: Theory, Methods and Applications)
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Article
An Effective Algorithm for 2D Marine CSEM Modeling in Anisotropic Media Using a Wavelet Galerkin Method
Minerals 2022, 12(2), 124; https://doi.org/10.3390/min12020124 - 21 Jan 2022
Viewed by 721
Abstract
The marine controlled-source electromagnetic method (MCSEM) has attracted considerable attention as an approach to explore marine oil and gas resources and geological structures. This study presents a new wavelet Galerkin method (WGM) to solve the forward modeling problem of 2D MCSEM data incorporating [...] Read more.
The marine controlled-source electromagnetic method (MCSEM) has attracted considerable attention as an approach to explore marine oil and gas resources and geological structures. This study presents a new wavelet Galerkin method (WGM) to solve the forward modeling problem of 2D MCSEM data incorporating conductivity anisotropy. The method uses Daubechies wavelets that may be differentiated based on the need to solve the governing field equations of MCSEM. A quasi-minimal residual method was adopted by combining an incomplete LU preconditioner to solve the WGM equations. The numerical results were compared with the analytical solution and those obtained by the finite difference and element methods. The results show that the proposed WGM is superior to the finite element and difference methods in terms of computing time and memory requirements. This algorithm can be applied to solve the forward modeling problem of MCSEM. The conductivity anisotropy of the background medium affects the MCSEM response more than the reservoir anisotropy. The match between the modeled results and measured data for the simplified real model demonstrates the necessity for using the anisotropic model to interpret data. Although this study used the proposed algorithm for 2D models, it may also be used for 3D models. Full article
(This article belongs to the Special Issue Electromagnetic Exploration: Theory, Methods and Applications)
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