Journal of Applied Geophysics最新文献

英文中文

Tensor ratio small subdomain filtering technique for edge detection

IF 2.2 3区地球科学 Q2 GEOSCIENCES, MULTIDISCIPLINARY

Journal of Applied Geophysics

Pub Date : 2025-02-01 DOI: 10.1016/j.jappgeo.2025.105635

Zhenhua Tai, Yuanhao Wang, Guohua Zhang, Xiangwen Li, Dezhi Huang

Edge detection is an important processing method for potential field data, used to determine the horizontal location of the edges of causative sources. We proposed an edge detection filtering based on a gradient tensor ratio and improved the small subdomain filtering technique, and merged them into a tensor ratio small subdomain filtering technique. The proposed detection filter utilizes numerical differentiation and Laplace equation to compute gradient tensors. To weaken the interference of random noise on the small subdomain filtering and the irregular bending of contour lines in its result, we replace the original data at the center with a weighted average of the data within the window, where the weighting factors are determined by the distance of each data point to the center point and the standard deviation between equidistant data points. Final filtering output is the weighted average of the data within the subdomain that has the minimum standard deviation, wherein tighten gradient belts are utilized as indicators for detecting the edges of causative sources. Test results on synthetic data show that the proposed method has higher detection accuracy and stability compared to previous methods, and can enhance local anomalies. We also apply them to a real gravity data, and the obtain results indicate that the proposed method can effectively detect fault locations and highlight the residual density characteristics of causative sources.

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引用次数: 0

Progress of the pseudoseismic imaging technology for transient electromagnetic method

IF 2.2 3区地球科学 Q2 GEOSCIENCES, MULTIDISCIPLINARY

Journal of Applied Geophysics

Pub Date : 2025-02-01 DOI: 10.1016/j.jappgeo.2024.105600

Junjie Xue , Kerui Fan , Xin Wu , Wenhan Li , Quanhui Guo

The transient electromagnetic method (TEM) has been widely applied in metal mineral detection and engineering geology investigation. While mapping the resistivity distribution through the inversion of the TEM data, the subsurface structure of conductivity can be revealed by converting TEM data to the pseudo wavefield. The wavefield transform method is consequently an effective way to highlight the geoelectric structure. However, this field inversion belongs to a first-class Fredholm integral, which is a typical ill-posed problem. So, the key problem of wavefield transform is how to get a pseudo wavefield with proper resolution and stability. This paper first analyzes some traditional TEM imaging algorithms, including aspects such as time-frequency equivalent conversion, wavefield transform, and the Kirchhoff integral imaging and swept time transformation algorithms. Then, this paper concludes with some methods that can improve the inversion results resolution of wavefield transform. To obtain high-quality electromagnetic pseudo wavefield profiles, additional technical methods, such as Born approximation imaging, pulse spectrum inversion and full waveform inversion, are used in the inversion interpretation of electromagnetic field.

{"title":"Progress of the pseudoseismic imaging technology for transient electromagnetic method","authors":"Junjie Xue , Kerui Fan , Xin Wu , Wenhan Li , Quanhui Guo","doi":"10.1016/j.jappgeo.2024.105600","DOIUrl":"10.1016/j.jappgeo.2024.105600","url":null,"abstract":"<div><div>The transient electromagnetic method (TEM) has been widely applied in metal mineral detection and engineering geology investigation. While mapping the resistivity distribution through the inversion of the TEM data, the subsurface structure of conductivity can be revealed by converting TEM data to the pseudo wavefield. The wavefield transform method is consequently an effective way to highlight the geoelectric structure. However, this field inversion belongs to a first-class Fredholm integral, which is a typical ill-posed problem. So, the key problem of wavefield transform is how to get a pseudo wavefield with proper resolution and stability. This paper first analyzes some traditional TEM imaging algorithms, including aspects such as time-frequency equivalent conversion, wavefield transform, and the Kirchhoff integral imaging and swept time transformation algorithms. Then, this paper concludes with some methods that can improve the inversion results resolution of wavefield transform. To obtain high-quality electromagnetic pseudo wavefield profiles, additional technical methods, such as Born approximation imaging, pulse spectrum inversion and full waveform inversion, are used in the inversion interpretation of electromagnetic field.</div></div>","PeriodicalId":54882,"journal":{"name":"Journal of Applied Geophysics","volume":"233 ","pages":"Article 105600"},"PeriodicalIF":2.2,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143096563","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Semi-supervised intelligent inversion from prestack seismic attributes guided by geophysical prior knowledge

IF 2.2 3区地球科学 Q2 GEOSCIENCES, MULTIDISCIPLINARY

Journal of Applied Geophysics

Pub Date : 2025-02-01 DOI: 10.1016/j.jappgeo.2025.105620

Lei Zhu , Fanchang Zhang , Shunan Zhang , Ji-an Wu

Supervised deep learning methods currently used for prestack parameter prediction are suffered from the problem of limited training samples. The lack of clear physical meanings for deep learning models also makes prediction results unreliable. To address these issues, we proposed a geophysical prior knowledge guided semi-supervised (GPKGS) deep learning framework for amplitude-versus-angle (AVA) inversion. Based on prior physical knowledge, the prestack seismic data are decoupled into prestack seismic attribute data of the elastic parameters. Meanwhile, according to the prestack seismic attribute data, constructing the new forward models corresponding to each elastic parameter. The intelligent inversion framework is built based on the constructed forward models. This reduces the dependence of the framework on training data. This GPKGS framework preserves the physical procedure of AVA inversion, making intelligent inversion results reliable. The framework contains three branch networks for each elastic parameter. Each branch network contains an inversion neural network (INN) and a forward neural network (FNN). The INN can invert the prestack seismic attribute data into elastic parameters, which corresponding to inversion process. The FNN convert the obtained elastic parameters into synthetic prestack seismic attribute data, which corresponding to forward process. To ensure a reliable training process, the difference between the prestack seismic attribute data and the synthetic data are used to train the framework supervised by well log data. In addition, to obtain more stable results, at prediction stage, the prior information is introduced to help the FNN update the elastic parameters output by INN. The Marmousi2 model and a deep carbonate data are used to test the proposed framework. We find that the intelligent inversion results of the proposed network perform well at the situation of few training data.

{"title":"Semi-supervised intelligent inversion from prestack seismic attributes guided by geophysical prior knowledge","authors":"Lei Zhu , Fanchang Zhang , Shunan Zhang , Ji-an Wu","doi":"10.1016/j.jappgeo.2025.105620","DOIUrl":"10.1016/j.jappgeo.2025.105620","url":null,"abstract":"<div><div>Supervised deep learning methods currently used for prestack parameter prediction are suffered from the problem of limited training samples. The lack of clear physical meanings for deep learning models also makes prediction results unreliable. To address these issues, we proposed a geophysical prior knowledge guided semi-supervised (GPKGS) deep learning framework for amplitude-versus-angle (AVA) inversion. Based on prior physical knowledge, the prestack seismic data are decoupled into prestack seismic attribute data of the elastic parameters. Meanwhile, according to the prestack seismic attribute data, constructing the new forward models corresponding to each elastic parameter. The intelligent inversion framework is built based on the constructed forward models. This reduces the dependence of the framework on training data. This GPKGS framework preserves the physical procedure of AVA inversion, making intelligent inversion results reliable. The framework contains three branch networks for each elastic parameter. Each branch network contains an inversion neural network (INN) and a forward neural network (FNN). The INN can invert the prestack seismic attribute data into elastic parameters, which corresponding to inversion process. The FNN convert the obtained elastic parameters into synthetic prestack seismic attribute data, which corresponding to forward process. To ensure a reliable training process, the difference between the prestack seismic attribute data and the synthetic data are used to train the framework supervised by well log data. In addition, to obtain more stable results, at prediction stage, the prior information is introduced to help the FNN update the elastic parameters output by INN. The Marmousi2 model and a deep carbonate data are used to test the proposed framework. We find that the intelligent inversion results of the proposed network perform well at the situation of few training data.</div></div>","PeriodicalId":54882,"journal":{"name":"Journal of Applied Geophysics","volume":"233 ","pages":"Article 105620"},"PeriodicalIF":2.2,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143092047","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Suppressing short time marine ambient noise based on deep complex unet to enhance the vessel radiation signal in LOFAR spectrogram

IF 2.2 3区地球科学 Q2 GEOSCIENCES, MULTIDISCIPLINARY

Journal of Applied Geophysics

Pub Date : 2025-02-01 DOI: 10.1016/j.jappgeo.2024.105611

Yuzhe Wang , Shijie Qiu , Guoqing Hu , Bin Wu , Yi Yu

UNet-type networks have demonstrated good performance in the field of denoising. In this paper, we applied a DCUNet network specifically for denoising underwater acoustic signals, which are characterized by their nonlinear, non-smooth and non-Gaussian features. The process involves transforming noisy data into LOFAR spectrograms for input into DCUnet, redesigning the network structure based on the features of underwater acoustic signals. Subsequently, a Noise2Noise training method was employed to reconstruct the underwater background noise through the end-to-end architecture. The effectiveness of the algorithm was validated on publicly available datasets after augmentation. Extensive experimental results show that our method achieves an SNR improvement of over 10 dB and is capable of restoring signals with an initial SNR of −20 dB, demonstrating better performance compared to traditional denoising algorithms. In addition, the method is verified using the public datasets and long-distance single-frequency experiments. In conclusion, the DCUNet model exhibit effectiveness in underwater acoustic noise suppression and robustness in different data.

{"title":"Suppressing short time marine ambient noise based on deep complex unet to enhance the vessel radiation signal in LOFAR spectrogram","authors":"Yuzhe Wang , Shijie Qiu , Guoqing Hu , Bin Wu , Yi Yu","doi":"10.1016/j.jappgeo.2024.105611","DOIUrl":"10.1016/j.jappgeo.2024.105611","url":null,"abstract":"<div><div>UNet-type networks have demonstrated good performance in the field of denoising. In this paper, we applied a DCUNet network specifically for denoising underwater acoustic signals, which are characterized by their nonlinear, non-smooth and non-Gaussian features. The process involves transforming noisy data into LOFAR spectrograms for input into DCUnet, redesigning the network structure based on the features of underwater acoustic signals. Subsequently, a Noise2Noise training method was employed to reconstruct the underwater background noise through the end-to-end architecture. The effectiveness of the algorithm was validated on publicly available datasets after augmentation. Extensive experimental results show that our method achieves an SNR improvement of over 10 dB and is capable of restoring signals with an initial SNR of −20 dB, demonstrating better performance compared to traditional denoising algorithms. In addition, the method is verified using the public datasets and long-distance single-frequency experiments. In conclusion, the DCUNet model exhibit effectiveness in underwater acoustic noise suppression and robustness in different data<em>.</em></div></div>","PeriodicalId":54882,"journal":{"name":"Journal of Applied Geophysics","volume":"233 ","pages":"Article 105611"},"PeriodicalIF":2.2,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143096557","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Enhancing traffic monitoring with noise-robust distributed acoustic sensing and deep learning

IF 2.2 3区地球科学 Q2 GEOSCIENCES, MULTIDISCIPLINARY

Journal of Applied Geophysics

Pub Date : 2025-02-01 DOI: 10.1016/j.jappgeo.2024.105616

Zheng Wang , Taiyin Zhang , Huiliang Chen , Cheng-Cheng Zhang , Bin Shi

Traffic monitoring provides crucial data for intelligent transportation systems (ITS) but traditional sensors are expensive to deploy and maintain at scale. This study explores distributed acoustic sensing (DAS) using existing fiber-optic infrastructure as a cost-effective solution for traffic monitoring. While DAS offers advantages, vehicle detection signals are susceptible to noise. To address this, we propose a novel approach combining DAS with deep learning object detection using YOLOv8. Pre-processed and labeled DAS data collected over two weeks on a highway during a COVID-19 lockdown were used to train the YOLOv8 network, achieving 92 % classification accuracy. Applying the trained model revealed detailed hourly traffic patterns and vehicle compositions, demonstrating the potential of DAS for robust and cost-effective ITS. These findings highlight the effectiveness of combining DAS and deep learning for noise mitigation in traffic monitoring and provide valuable insights into traffic dynamics during the pandemic.

引用次数: 0

Coupling effect of moisture desorption and matrix contraction on resistivity of water-bearing coal under high geothermal environment

IF 2.2 3区地球科学 Q2 GEOSCIENCES, MULTIDISCIPLINARY

Journal of Applied Geophysics

Pub Date : 2025-02-01 DOI: 10.1016/j.jappgeo.2024.105604

Junjun Feng , Yuanfang Qu , Shigeng Li , Chuanhua Xu , Yankun Ma , Qisong Huang , Long Dang

Resistivity is a key method for geophysical exploration of underground coal seams. However, the deep, high geothermal environment poses significant challenges to this approach, mainly due to moisture desorption and matrix contraction effects induced by high temperatures. In this study, experiments were conducted to assess the resistivity of water-bearing coal at varying temperatures between 30 °C and 70 °C. In addition, Nuclear Magnetic Resonance (NMR) technology was used to analyze the moisture distribution within the coal under high temperature conditions. The results indicate that moisture desorption in coal at elevated temperatures occurs in two distinct stages: a rapid desorption stage from seepage pores and a slower desorption stage from adsorption pores. As the temperature increased from 30 °C to 70 °C, the amount of moisture desorbed increased by 117 %, while the matrix contraction strain increased by 130 %. Furthermore, the variation of coal resistivity under high temperature conditions can be categorized into three stages: a transient decreasing stage due to the Soret effect, a significant increasing stage caused by moisture desorption, and a continuous decreasing stage due to coal matrix contraction. Finally, a theoretical model was developed to characterize the coupled effects of moisture desorption and matrix contraction on coal resistivity. This model provides a basis for the application of resistivity methods in deep, high-geothermal environments.

{"title":"Coupling effect of moisture desorption and matrix contraction on resistivity of water-bearing coal under high geothermal environment","authors":"Junjun Feng , Yuanfang Qu , Shigeng Li , Chuanhua Xu , Yankun Ma , Qisong Huang , Long Dang","doi":"10.1016/j.jappgeo.2024.105604","DOIUrl":"10.1016/j.jappgeo.2024.105604","url":null,"abstract":"<div><div>Resistivity is a key method for geophysical exploration of underground coal seams. However, the deep, high geothermal environment poses significant challenges to this approach, mainly due to moisture desorption and matrix contraction effects induced by high temperatures. In this study, experiments were conducted to assess the resistivity of water-bearing coal at varying temperatures between 30 °C and 70 °C. In addition, Nuclear Magnetic Resonance (NMR) technology was used to analyze the moisture distribution within the coal under high temperature conditions. The results indicate that moisture desorption in coal at elevated temperatures occurs in two distinct stages: a rapid desorption stage from seepage pores and a slower desorption stage from adsorption pores. As the temperature increased from 30 °C to 70 °C, the amount of moisture desorbed increased by 117 %, while the matrix contraction strain increased by 130 %. Furthermore, the variation of coal resistivity under high temperature conditions can be categorized into three stages: a transient decreasing stage due to the Soret effect, a significant increasing stage caused by moisture desorption, and a continuous decreasing stage due to coal matrix contraction. Finally, a theoretical model was developed to characterize the coupled effects of moisture desorption and matrix contraction on coal resistivity. This model provides a basis for the application of resistivity methods in deep, high-geothermal environments.</div></div>","PeriodicalId":54882,"journal":{"name":"Journal of Applied Geophysics","volume":"233 ","pages":"Article 105604"},"PeriodicalIF":2.2,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143096566","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Feasibility study of telluric magnetic field frequency selection method in groundwater exploration

IF 2.2 3区地球科学 Q2 GEOSCIENCES, MULTIDISCIPLINARY

Journal of Applied Geophysics

Pub Date : 2025-02-01 DOI: 10.1016/j.jappgeo.2024.105608

Tianchun Yang , Debing Zhu , Yawar Hussain , Rui Huang , Qilang Yu , Qijun Ding

Over the years, scholars have made significant contributions in the development of various electric pulse of a natural field methods, collectively referred to as frequency selection method (FSM). The methods still lacking the satisfactory exploratory theoretical studies for interpreting the results effectively. In a previous study, authors concluded that results obtained at several frequencies with both telluric electrical field frequency selection method (TEFSM) and telluric magnetic field frequency selection method (TMFSM) are affected by static shift effects. The present study is dedicated to the feasibility of the methods in groundwater exploration of karst aquifer applying two-dimensional forward simulations and field measurements. In the first stage, utilizing the magnetotellurics (MT) 2D forward modeling theory, authors computed the surface horizontal electric E_x and magnetic H_x field components along the survey line in both telluric magnetic (TM) and telluric electric (TE) polarization modes. Secondly, TEFSM was used where the measured curves of electric field at different frequencies were found well synchronized in depicting the abnormal position. Further, the field testing of audio-frequency magnetotellurics (AMT) conducted with V8 electric acquisition system considerably suppressed the interferences from anthropogenic noise sources. The synchronicity of magnetic field component curves at different frequencies was worse than that of electric field component. The simulation results indicated that the component E_x exhibited significantly high-value anomalies over high resistance bodies, whereas E_y and H_x components did not show clear anomalies. All three components displayed apparent anomalies for conductive bodies. Theoretically, TMFSM is a feasible approach for exploring shallow conductive abnormal bodies, although the component H_x is susceptible to external interference in practical applications. Therefore, designing specialized magnetic sensors with strong anti-interference capability and high-accuracy is a significant step towards achieving the satisfactory results.

{"title":"Feasibility study of telluric magnetic field frequency selection method in groundwater exploration","authors":"Tianchun Yang , Debing Zhu , Yawar Hussain , Rui Huang , Qilang Yu , Qijun Ding","doi":"10.1016/j.jappgeo.2024.105608","DOIUrl":"10.1016/j.jappgeo.2024.105608","url":null,"abstract":"<div><div>Over the years, scholars have made significant contributions in the development of various electric pulse of a natural field methods, collectively referred to as frequency selection method (FSM). The methods still lacking the satisfactory exploratory theoretical studies for interpreting the results effectively. In a previous study, authors concluded that results obtained at several frequencies with both telluric electrical field frequency selection method (TEFSM) and telluric magnetic field frequency selection method (TMFSM) are affected by static shift effects. The present study is dedicated to the feasibility of the methods in groundwater exploration of karst aquifer applying two-dimensional forward simulations and field measurements. In the first stage, utilizing the magnetotellurics (MT) 2D forward modeling theory, authors computed the surface horizontal electric <em>E</em><sub><em>x</em></sub> and magnetic <em>H</em><sub><em>x</em></sub> field components along the survey line in both telluric magnetic (TM) and telluric electric (TE) polarization modes. Secondly, TEFSM was used where the measured curves of electric field at different frequencies were found well synchronized in depicting the abnormal position. Further, the field testing of audio-frequency magnetotellurics (AMT) conducted with V8 electric acquisition system considerably suppressed the interferences from anthropogenic noise sources. The synchronicity of magnetic field component curves at different frequencies was worse than that of electric field component. The simulation results indicated that the component <em>E</em><sub><em>x</em></sub> exhibited significantly high-value anomalies over high resistance bodies, whereas <em>E</em><sub><em>y</em></sub> and <em>H</em><sub><em>x</em></sub> components did not show clear anomalies. All three components displayed apparent anomalies for conductive bodies. Theoretically, TMFSM is a feasible approach for exploring shallow conductive abnormal bodies, although the component <em>H</em><sub><em>x</em></sub> is susceptible to external interference in practical applications. Therefore, designing specialized magnetic sensors with strong anti-interference capability and high-accuracy is a significant step towards achieving the satisfactory results.</div></div>","PeriodicalId":54882,"journal":{"name":"Journal of Applied Geophysics","volume":"233 ","pages":"Article 105608"},"PeriodicalIF":2.2,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143135603","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Analysis of 3D induced polarization effects of SOTEM

IF 2.2 3区地球科学 Q2 GEOSCIENCES, MULTIDISCIPLINARY

Journal of Applied Geophysics

Pub Date : 2025-02-01 DOI: 10.1016/j.jappgeo.2024.105613

Wanting Song , Wen Chen , Yanbo Wang , Weiying Chen

The short-offset grounded-wire transient electromagnetic method (SOTEM) is characterized by observations conducted in the near-source region. When a polarizable medium is present, significant polarization field responses can be detected. Existing studies have been limited to 1D models, which have not elucidated the characteristics of polarization and induction fields for 3D polarization bodies. This paper employs the Comsol platform to construct and solve a 3D model in the frequency domain. The frequency-domain response is then transformed into a time-domain step response, achieving 3D finite element forward modeling of SOTEM with induced polarization (IP) effects. The accuracy of the 3D simulation is validated. We calculated basic 3D models containing polarized layers as well as typical high- and low-resistivity polarization bodies, analyzing the impact of IP effects on the SOTEM horizontal electric field Ex and vertical magnetic field Hz responses. It was found that the sign of the total field formed by the induced current and the polarization current determines the sign reversal phenomenon. Both the Ex and Hz components respond well to low-resistivity polarization bodies, while the Ex component demonstrates significantly better detection capabilities for high-resistivity polarization bodies. This paper provides a method for time-domain electromagnetic 3D simulation considering IP effects, offering valuable insights for advancing the application of SOTEM with IP effects in the exploration of metallic mineral resources and groundwater.

{"title":"Analysis of 3D induced polarization effects of SOTEM","authors":"Wanting Song , Wen Chen , Yanbo Wang , Weiying Chen","doi":"10.1016/j.jappgeo.2024.105613","DOIUrl":"10.1016/j.jappgeo.2024.105613","url":null,"abstract":"<div><div>The short-offset grounded-wire transient electromagnetic method (SOTEM) is characterized by observations conducted in the near-source region. When a polarizable medium is present, significant polarization field responses can be detected. Existing studies have been limited to 1D models, which have not elucidated the characteristics of polarization and induction fields for 3D polarization bodies. This paper employs the Comsol platform to construct and solve a 3D model in the frequency domain. The frequency-domain response is then transformed into a time-domain step response, achieving 3D finite element forward modeling of SOTEM with induced polarization (IP) effects. The accuracy of the 3D simulation is validated. We calculated basic 3D models containing polarized layers as well as typical high- and low-resistivity polarization bodies, analyzing the impact of IP effects on the SOTEM horizontal electric field Ex and vertical magnetic field Hz responses. It was found that the sign of the total field formed by the induced current and the polarization current determines the sign reversal phenomenon. Both the Ex and Hz components respond well to low-resistivity polarization bodies, while the Ex component demonstrates significantly better detection capabilities for high-resistivity polarization bodies. This paper provides a method for time-domain electromagnetic 3D simulation considering IP effects, offering valuable insights for advancing the application of SOTEM with IP effects in the exploration of metallic mineral resources and groundwater.</div></div>","PeriodicalId":54882,"journal":{"name":"Journal of Applied Geophysics","volume":"233 ","pages":"Article 105613"},"PeriodicalIF":2.2,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143136392","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Non-destructive GPR signal processing technique for thickness estimation of pavement, coal and ice layers: A review

IF 2.2 3区地球科学 Q2 GEOSCIENCES, MULTIDISCIPLINARY

Journal of Applied Geophysics

Pub Date : 2025-02-01 DOI: 10.1016/j.jappgeo.2024.105601

Shweta B. Thomas , Sangeetha Subbaraj , Deepika Rani Sona , Benedict Thomas

In recent years, there has been a significant surge in the utilization of Ground Penetrating Radar (GPR) for measuring the thickness of subsurface layers, and researchers in this field have paid close attention to it. GPR enables users to achieve greater precision in evaluating the quality and condition of underground materials. The traditional methods used to measure the thickness of underground layers are time-consuming, hard to conduct and not economical. GPR is one of the most recommended non-destructive geophysical methods for routine subsurface inspections. This article is intended to highlight the application of GPR for thickness estimation of distinct materials such as, pavement, ice and coal layers and novel non-destructive testing (NDT) techniques adopted recently for thickness estimation. This article presents an overview of Ground Penetrating Radar (GPR) methodologies for layer thickness estimation, encompassing their advantages, disadvantages, and recent research findings. By synthesizing existing literature, the potential applications of GPR while addressing its inherent limitations are illustrated here. Furthermore, practical recommendations are provided to enhance the effectiveness of GPR-based layer thickness estimation techniques.

{"title":"Non-destructive GPR signal processing technique for thickness estimation of pavement, coal and ice layers: A review","authors":"Shweta B. Thomas , Sangeetha Subbaraj , Deepika Rani Sona , Benedict Thomas","doi":"10.1016/j.jappgeo.2024.105601","DOIUrl":"10.1016/j.jappgeo.2024.105601","url":null,"abstract":"<div><div>In recent years, there has been a significant surge in the utilization of Ground Penetrating Radar (GPR) for measuring the thickness of subsurface layers, and researchers in this field have paid close attention to it. GPR enables users to achieve greater precision in evaluating the quality and condition of underground materials. The traditional methods used to measure the thickness of underground layers are time-consuming, hard to conduct and not economical. GPR is one of the most recommended non-destructive geophysical methods for routine subsurface inspections. This article is intended to highlight the application of GPR for thickness estimation of distinct materials such as, pavement, ice and coal layers and novel non-destructive testing (NDT) techniques adopted recently for thickness estimation. This article presents an overview of Ground Penetrating Radar (GPR) methodologies for layer thickness estimation, encompassing their advantages, disadvantages, and recent research findings. By synthesizing existing literature, the potential applications of GPR while addressing its inherent limitations are illustrated here. Furthermore, practical recommendations are provided to enhance the effectiveness of GPR-based layer thickness estimation techniques.</div></div>","PeriodicalId":54882,"journal":{"name":"Journal of Applied Geophysics","volume":"233 ","pages":"Article 105601"},"PeriodicalIF":2.2,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143097303","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Influence of grounded source geometry and terrain on the semi-airborne transient electromagnetic response from 3D simulation data

IF 2.2 3区地球科学 Q2 GEOSCIENCES, MULTIDISCIPLINARY

Journal of Applied Geophysics

Pub Date : 2025-02-01 DOI: 10.1016/j.jappgeo.2024.105619

Jinjing Shi , Xin Wu , Yanbo Wang , Yang Zhao

The Semi-Airborne Transient Electromagnetic (SATEM) method utilizes a grounded source and airborne receivers, making it well-suited for high-precision, rapid, and deep electromagnetic surveying in complex terrain. Typically, the grounded source is assumed to be a simple linear form in existing inversions. However, in practice, the long grounded source can be bent or undulating due to the influence of terrain, resulting in significant deviations from the idealized straight-line model. Prior studies have investigated the effects of source bending in the horizontal plane or undulation in the vertical elevation separately. This paper provides a comprehensive analysis of the combined influence of complex terrain on the spatial deployment of the grounded source. Through a thorough examination of the superposition effects of multiple unfavorable factors, the study clarifies the spatio-temporal distribution of the complex source deployment pattern on the SATEM response. The findings provide a basis for confirming the reliability of inversion results and offer suggestions for improving field survey specifications for the SATEM method.

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