Journal of Applied Geophysics最新文献_第4页

Research on the response of different flight modes under concave and convex terrain by Semi-Airborne Transient Electromagnetic Method (SATEM)

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.2024.105576

Bin Xie, Yingying Zhang, Xinyu Wu, Wenyu Wu

With the development and utilization of various mineral resources in horizontal terrain areas gradually becoming saturated, the study of transient electromagnetic method has gradually shifted from flat terrain areas to complex fluctuating and high altitude areas. Due to the characteristics of transmitting source on the ground and receiving point in the air, the Semi-Airborne transient electromagnetic method (SATEM) has advantages such as superior working efficiency, large exploration depth and higher signal-to-noise ratio of collected signals. At present, there are few researches on the influence of the flight mode of the UAV on the collected data. In this paper, the concave terrain and convex terrain are described by using unstructured tetrahedral mesh, and the response of terrain model is calculated. Then the terrain response under different flight modes has been researched and analyzed systematically. The corresponding relative error graph is obtained and compared to summarize the law. Through simulation with different influence parameters, it is found that when the flight mode of the UAV is the same altitude, the SATEM response is less affected by the fluctuating terrain, and when the flight mode of the UAV is along the terrain, the SATEM response is more affected by the fluctuating terrain. The study of the response of UAV to the undulating terrain under different flight modes can provide a reference for the processing and interpretation of SATEM data in the undulating terrain region.

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引用次数: 0

FDTD analysis of ballast fouling status using PFC with discrete random medium model

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.2024.105605

Bo Li , Linyan Guo , Zhan Peng , Shilei Wang , Guixian Liu , Yaonan Li

Numerical simulation techniques for ground penetrating radar (GPR) railway ballast inspection offer significant advantages, including the avoidance of extensive field surveys and excavation work. This helps minimize construction challenges and costs while providing crucial technical support and insights for railway maintenance. Nevertheless, the intricate nature of ballast particles and bed structures, combined with the challenges in discerning their patterns, present formidable obstacles to achieving high-precision modeling. This paper employs the Particle Flow Code (PFC2D) to extract and project 2D natural ballast particles from laser scanning, generating a clean ballast physical model considering mechanical interactions. As fouling arises from fine particles smaller than 25 mm, the discrete random medium theory is applied to validate the heavy ballast fouling. This involves filling the voids in the clean ballast to simulate and analyze the electromagnetic properties of the ballast fouling. The generated ballast physical model is converted into HDF5 files and simulated using a 2.0 GHz Rayleigh wave excitation through the Finite Difference Time Domain (FDTD) method. Through S-transform and Hilbert energy results, it becomes feasible to accurately differentiate the ballast fouling. The study reveals that highly fouling ballast predominantly exhibits frequency energy concentrated within the 1.0–3.0 GHz range. As depth increases, the energy experiences faster attenuation, and the distribution of Hilbert energy becomes denser and stronger. Field tests conducted on a specific railway line in southern China validate the method's effectiveness, making it a valuable tool for guiding GPR-based ballast fouling detection projects and providing a scientific basis for railway infrastructure maintenance.

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引用次数: 0

Seismic prediction of fracture-cavity reservoirs using a rock physics model

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.2024.105607

Jianlong Su , Junxing Cao , Qiaomu Qi , Zuqing Chen , Yong Pu , Zhiwei Liu , Yuedong Li , Xiaojing Liu

Seismic prediction of fracture-cavity reservoirs is one of the vital tasks in oil and gas exploration. To enhance the accuracy of predicting fracture-cavity reservoirs controlled by faults, we propose an efficient prediction method for fracture-cavity reservoir based on a rock physics model. Firstly, we analyze the rock physics characteristics of fracture-cavity reservoirs and introduce fracture-cavity density parameters while simplifying the expressions of azimuthal anisotropy. We have derived a new azimuthal seismic reflection coefficient equation utilizing the fracture-cavity density parameter, which can accurately characterize the anisotropic characteristics of fracture-cavity reservoirs. Secondly, to improve the prediction accuracy of fracture-cavity reservoirs, we convert the seismic reflection coefficient equation into an azimuthal elastic impedance equation and perform Fourier series expansion. The second-order Fourier coefficients accurately represent the fracture-cavity density, allowing for the prediction of the distribution range of fracture-cavity reservoirs. The novel fracture-cavity reservoir prediction method effectively reduces the dimensionality of the azimuthal elastic impedance equation, enhances the stability of solving the objective function, and improves computational efficiency. Lastly, through model testing and inversion of actual data using the new method, we have successfully predicted the distribution range of fault-controlled karst fracture-cavity reservoirs in the Maokou Formation in the southern Sichuan Basin. The inversion results indicate that the fracture-cavity reservoirs coexist with faults, exhibiting vertical structural characteristics, rapid lateral variations, and strong heterogeneity. The fracture-cavity reservoirs predicted by the new method are consistent with the geological principles of fault-controlled karst in the Maokou Formation, providing support for exploration efforts in the fracture-cavity reservoir domain of the study area.

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引用次数: 0

Experimental and numerical investigation on the tensile behaviour of rocks using the Brazilian disc 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.2025.105629

Yulong Chen , Xuwen Zhang , Honghui Yuan , Junwen Zhang

Characterizing engineering properties of rock especially associated with tension is crucial for stability assessment of rock structures. This study integrates physical and numerical experiments to investigate the electromagnetic radiation (EMR) and acoustic emission (AE) responses of sandstone under Brazilian disc testing. During the Brazilian splitting process, the EMR and AE responses reflect well the cracking evolution of the disc sandstone specimen. The cracking evolution process and failure mechanism are vividly illustrated. When approaching the peak stress, massive EMR and AE activities occur abruptly. Importantly, the fractal dimension and b-value of EMR and AE switch from increase to decrease once the failure initiates. Such significant decrease in the fractal dimension and b-value of EMR and AE upon failure initiation could be applied to identify the rock failure initiation.

引用次数: 0

Seismic data denoising using convolutional sparse coding with an efficient alternating direction multipliers minimization algorithm

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.2024.105610

Bo Yang, Min Bai, Juan Wu, Zixiang Zhou, Xilin Qin, Zhaoyang Ma, Yang Zeng

During the acquisition of field seismic data, it is unavoidable to encounter random noise, and this will have an impact on the subsequent processing and interpretation of the seismic data. Lately, dictionary learning has demonstrated significant advancements in seismic data denoising. The most common method among patch-based dictionary learning algorithms is the K-singular value decomposition (K-SVD) method, which is a learning method based on patching schemes and processes data on overlapping patches without considering the complete data and the global features. In order to optimize these problems, we use convolutional sparse coding (CSC) for seismic data denoising, which can process the global data and capture the correlation between local neighborhoods. We propose the convolutional sparse coding based on an efficient alternating direction multipliers minimization (ADMM) for noise attenuation in seismic data. This CSC with efficient ADMM algorithm is capable of effectively addressing the subproblem of convolutional least-squares fitting, which reduces the complexity of the algorithm and converges to a valid solution. We accomplish the seismic data denoising using the learned filters and the corresponding sparse feature maps. The numerical experimental results on synthetic data and field data demonstrate that in comparison to fast and flexible convolutional sparse coding (FF-CSC) and K-SVD, the proposed method has more advantages in denoising performance and computational efficiency.

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引用次数: 0

A multistage algorithm to generate a predictive porphyry intrusion evidential map with low uncertainty for mineral prospectivity mapping, case study in Pariz Area, Iran

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.2025.105637

Gholam-Reza Elyasi, Abbas Bahroudi, Maysam Abedi

The quest for creating more reliable evidential maps with elevated prediction accuracy and minimal uncertainty remains a formidable challenge in mineral prospectivity mapping (MPM), particularly in the case of covered or concealed deposits. This study introduces a multistage algorithm to generate a predictive porphyry intrusion evidential map using magnetic data. Rooted in the formation model of porphyry copper deposits (PCDs), the algorithm encompasses several key steps: (1) initiating with a radial symmetry transformation to detect circular geological features (i.e., porphyry intrusions), (2) none-minimum suppression of circularity responses and thresholding to identify the center of these features, (3) amplitude contrast transformation to highlight the extent of the features, and finally (4) employing the active contour algorithm to determine the size and geometry of probable porphyry targets. Implemented on aeromagnetic data from the Pariz region in southeastern Iran, the results were evaluated by location of previously known PCDs and 3D Cu isoshells derived from exploratory boreholes. Remarkably, all six known deposits in the area were identified, alongside the discovery of a new porphyry copper deposit, boasting 2847 MT with a copper grade of 0.42 %. Additionally, five new prospective targets that may serve as fertile environments for porphyry mineralization were proposed for further exploration. The results demonstrated that the proposed algorithm significantly enhances MPM of PCDs by effectively narrowing the exploration search space, delineating 20 % (126 of 629 km²) of the study area as prospective targets. Furthermore, the findings indicate that the magnetic signatures of PCDs on the generated map are notably sharper than those on the original reduction to pole map, affirming the algorithm's efficacy in delineating buried porphyry copper deposits.

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引用次数: 0

An efficient footprint-guided finite domain algorithm for common offset ground penetrating radar forward modeling

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.2024.105617

Deshan Feng , Zhengyang Fang , Xun Wang , Siyuan Ding

Ground penetrating radar (GPR) is a widely applied shallow geophysical exploration method. However, the huge amounts of collected data from high efficiency and sampling rate are extremely time-consuming and high-cost to interpret. As the basis of full waveform inversion (FWI) and reverse time migration (RTM), the numerical simulation of GPR directly affects the accuracy and speed of the data interpretation. Besides, calculating 3D large-scale models on the personal computer (PC) is still difficult with limited memory. Therefore, an efficient and low-cost forward algorithm is required urgently. Inspired by the footprint of the airborne electromagnetic method (AEM), we propose a GPR moving finite domain (MFD) forward algorithm based on the attenuation characteristic of GPR high frequency electromagnetic waves to avoid excessive computation by limiting the calculation to the finite domain. We explore the relation between speedup and precision, summarize the optimal range of the parameter and constrain the MFD to further ensure the acceleration according to the time window. The error source and factors affecting the algorithm's speedup are explored and discussed to demonstrate its performance fully. The extensive numerical experiments emphasize that the algorithm could improve speed efficiently with ignorable loss of accuracy. Finally, the forward modeling of a large 3D model is carried out with the memory decreased by 78 % and the speed increased by 33.88 times on the PC, which is impossible through the conventional FDTD. The reduction of costs lessens the requirements for computer equipment, which is expected to promote the practical process of FWI and RTM.

{"title":"An efficient footprint-guided finite domain algorithm for common offset ground penetrating radar forward modeling","authors":"Deshan Feng , Zhengyang Fang , Xun Wang , Siyuan Ding","doi":"10.1016/j.jappgeo.2024.105617","DOIUrl":"10.1016/j.jappgeo.2024.105617","url":null,"abstract":"<div><div>Ground penetrating radar (GPR) is a widely applied shallow geophysical exploration method. However, the huge amounts of collected data from high efficiency and sampling rate are extremely time-consuming and high-cost to interpret. As the basis of full waveform inversion (FWI) and reverse time migration (RTM), the numerical simulation of GPR directly affects the accuracy and speed of the data interpretation. Besides, calculating 3D large-scale models on the personal computer (PC) is still difficult with limited memory. Therefore, an efficient and low-cost forward algorithm is required urgently. Inspired by the footprint of the airborne electromagnetic method (AEM), we propose a GPR moving finite domain (MFD) forward algorithm based on the attenuation characteristic of GPR high frequency electromagnetic waves to avoid excessive computation by limiting the calculation to the finite domain. We explore the relation between speedup and precision, summarize the optimal range of the parameter and constrain the MFD to further ensure the acceleration according to the time window. The error source and factors affecting the algorithm's speedup are explored and discussed to demonstrate its performance fully. The extensive numerical experiments emphasize that the algorithm could improve speed efficiently with ignorable loss of accuracy. Finally, the forward modeling of a large 3D model is carried out with the memory decreased by 78 % and the speed increased by 33.88 times on the PC, which is impossible through the conventional FDTD. The reduction of costs lessens the requirements for computer equipment, which is expected to promote the practical process of FWI and RTM.</div></div>","PeriodicalId":54882,"journal":{"name":"Journal of Applied Geophysics","volume":"233 ","pages":"Article 105617"},"PeriodicalIF":2.2,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143096560","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

Automatic picking of surface-wave dispersion curves with an image segmentation 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.2024.105615

Mengyuan Hu , Yudi Pan , Tianxiang Wang , Yiming Wang

The surface-wave method is a widely used technique for shallow subsurface exploration, and the extraction of the dispersion curve is one of the most important steps in the surface-wave method. Traditionally, this extraction of surface-wave dispersion curves heavily relies on manual or semi-manual picking, which is both time-consuming and prone to human error, especially when dealing with large datasets. Recent developments in machine learning algorithms have provided a promising way for the automated extraction of surface-wave dispersion curves. We present a random forest (RF) algorithm designed for the automatic extraction of surface-wave dispersion curves. In this approach, the extraction task is conceptualized as an image segmentation problem, enabling a rapid and accurate extraction of dispersion curves from dispersion energy images. We generate a dataset of 1800 models and their corresponding dispersion images. The proposed method is tested on both the noise-free and noisy datasets contaminated by Gaussian noise. Synthetic results demonstrate that our proposed method achieves relatively high accuracy and efficiency in the automatic extraction of surface-wave dispersion curves. We further analyze the impact of tuning parameters, including the number and depth of random-forest trees in the proposed algorithm on its performance and choose the best parameters in our study. Finally, the trained RF model is applied to two field datasets, which confirms the validity of our proposed RF method.

{"title":"Automatic picking of surface-wave dispersion curves with an image segmentation method","authors":"Mengyuan Hu , Yudi Pan , Tianxiang Wang , Yiming Wang","doi":"10.1016/j.jappgeo.2024.105615","DOIUrl":"10.1016/j.jappgeo.2024.105615","url":null,"abstract":"<div><div>The surface-wave method is a widely used technique for shallow subsurface exploration, and the extraction of the dispersion curve is one of the most important steps in the surface-wave method. Traditionally, this extraction of surface-wave dispersion curves heavily relies on manual or semi-manual picking, which is both time-consuming and prone to human error, especially when dealing with large datasets. Recent developments in machine learning algorithms have provided a promising way for the automated extraction of surface-wave dispersion curves. We present a random forest (RF) algorithm designed for the automatic extraction of surface-wave dispersion curves. In this approach, the extraction task is conceptualized as an image segmentation problem, enabling a rapid and accurate extraction of dispersion curves from dispersion energy images. We generate a dataset of 1800 models and their corresponding dispersion images. The proposed method is tested on both the noise-free and noisy datasets contaminated by Gaussian noise. Synthetic results demonstrate that our proposed method achieves relatively high accuracy and efficiency in the automatic extraction of surface-wave dispersion curves. We further analyze the impact of tuning parameters, including the number and depth of random-forest trees in the proposed algorithm on its performance and choose the best parameters in our study. Finally, the trained RF model is applied to two field datasets, which confirms the validity of our proposed RF method.</div></div>","PeriodicalId":54882,"journal":{"name":"Journal of Applied Geophysics","volume":"233 ","pages":"Article 105615"},"PeriodicalIF":2.2,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143096561","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

Template-matching-based data selection for passive seismic surface wave tomography

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.2024.105606

Deng Pan , Ji Gao , Haijiang Zhang

Ambient noise tomography (ANT) has been widely used to determine near surface shear-wave velocity (V_S) model. To fulfill the randomization requirement of the stationary source distribution for ANT, temporal averaging over a sufficiently long period of time is needed. However, in small-scale passive surface wave tomography, it is difficult to realize long-time observation and as a result non-stationary sources could affect the quality of the stacked dispersion measurements. In this study, we proposed a template-matching-based data selection method to obtain high-quality cross-correlation functions for dispersion analysis by only selecting time segments that are associated with similar cross-correlation functions with the template. One simple way to create the template is by stacking cross-correlations for all time segments. Two synthetic tests have demonstrated the strength of the proposed technique on recovering accurate dispersion curves. Field data analysis further proves the applicability of the proposed technique in selecting high-quality data segments with bin-stacked template. These tests show that the proposed method offers an efficient data processing method for passive surface-wave tomography.

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引用次数: 0

New Technologies for transient electromagnetic measurement with high performance

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.2025.105627

Xin Wu , Qihui Zhen , Weiying Chen , Fei Teng , Junjie Xue , Yanbo Wang

Theoretically, grounded-wire source electromagnetic methods can be categorized into far-source methods and near-source methods. The former have been used worldwide for many years, and the key technologies used in its equipment are mainly high-power transmitter and low-noise sensors. Due to its relatively narrow working bandwidth, its resolution capability is weak. In recent years, with the breakthrough of Short-Offset Transient Electromagnetic Method (SOTEM) in detection theory, its advantages of strong signal and wide bandwidth have been increasingly valued. For the research and development of specialized detection equipment for SOTEM, we first conducted system design by studying the characteristics of signals at different offset distances, and analyzed the technical difficulties that urgently need to be overcome. On this basis, a system with a high-bandwidth, high-current broadband transmitter and low-noise broadband receiver has been designed, the key technologies of which are ultra-high stabilized clamping voltage, low-noise hybrid amplifier, and adaptive variable damping. The performance and field tests have shown that the overall operating bandwidth of the system has increased by 2.5 times compared to existing mainstream equipment, significantly improving detection accuracy. The newly developed SOTEM equipment can provide strong support for near-source, great-depth, and high-resolution surveys.

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引用次数: 0