The heterogeneity of subsurface media induces multipath scattering and dielectric loss in Ground Penetrating Radar (GPR) signal propagation, which results in wavefront distortion and signal attenuation. These effects degrade B-scan profiles by blurring target signatures, hindering automated feature extraction, and reducing the clarity of regions of interest (ROI). To address these issues, we propose the Adaptive Region Target Enhancement Algorithm (ARTEA), a multi-stage preprocessing framework. ARTEA integrates dynamic range compression, continuous-scale normalization guided by adaptive sigma maps, and a frequency-domain refinement step. By dynamically adjusting parameters according to local signal characteristics, ARTEA is designed to achieve an effective trade-off between artifact suppression and target preservation. Experiments on both synthetic and field GPR data demonstrate that ARTEA can enhance target contrast and structural fidelity while suppressing artifacts and preserving essential target features.

The heterogeneity of subsurface media usually complicates the identification of subsurface voids, which disrupts electromagnetic signal propagation in the Ground Penetrating Radar (GPR), leading to signal attenuation and scattering. These factors contribute to increased ambiguity in B-scan profiles (BP) and reduce the information regarding geophysical features, ultimately reducing identification accuracy. To address these challenges, we propose a novel method that integrates Multi-scale Fused GPR Instantaneous Attributes with a Convolutional Neural Network (CNN). First, the Hilbert transform is employed to extract instantaneous attributes—Instantaneous Amplitude (IA), Phase (IP), and Frequency (IF)—from GPR time series data, which enhances the precision of local signal features. In addition, we introduced a feature fusion strategy based on Dual-Tree Complex Wavelet Transform (DT-CWT), which utilizes the advantages of DT-CWT in capturing multi-scale and multi-directional features and enhances the geophysical feature information in BP by feature fusion of IA, IP, and IF. Based on our proposed method results in the creation of the fused Instantaneous Attribute Features dataset (IAF-dataset), which includes data from both normal and void conditions. Utilizing this IAF-dataset, we evaluated a CNN for subsurface void recognition and achieved higher accuracy and robustness than traditional methods. Finally, we applied our method to three field cases using real-world GPR data. The experimental results demonstrated that the CNN model, which was trained on the fused IAF-dataset, outperforms traditional methods in subsurface void recognition. The multi-scale fusion technique preserved a greater amount of information, which enabled the model to effectively identify subsurface voids, even within intricate subsurface environments.

The Ground Penetrating Radar (GPR) data interpretation of dam defects detection by manual process is a heavy task. Although the convolutional neural network (CNN) is applicable to detect road defects with the help of other auxiliary instruments and techniques, it is still a challenge for the dam defect detection by deep learning. To overcome this problem, a multi-output CNN model for GPR response recognition of dam defects is proposed. The training dataset and test dataset are produced from a large number of GPR responses with different types of dam defects forward modeling by GPRMax3.0 software. The results show that the highest recognition accuracy of the training dataset and test dataset is about 98% and 97%, respectively. To verify the effectiveness, the new proposed method is used to recognize the hidden GPR responses of dam defects in the real GPR data. The results show that the types and locations of dam defects in the real GPR data can be recognized and classified automatically, efficiently and accurately.

When the third type of boundary conditions are used for the forward modeling of resistivity method by finite element method（FEM）, a large computational domain is required to ensure the computation accuracy. The element free method（EFM） is an emerging forward modeling method in the field of geophysics, although its computation efficiency is low, the moving least squares（MLS） shape function implemented in EFM has better continuity property and higher computation accuracy compared with the shape function used by FEM. In this work, the MLS shape function is implemented for the processing of the third type of boundary conditions in the 2.5D forward modeling framework of the resistivity method with the traditional finite element method. Therefore, we call the proposed method a finite element-moving least squares（FEM-MLS） coupled forward modeling algorithm. By numerical comparisons of different models with different forward modeling methods, the validity of this method is verified, and the influences of the parameters on simulation results are discussed. The numerical tests show that when the third type of boundary conditions are used, the computation domain can be reduced with the FEM-MLS coupling method and the computation efficiency is improved with the same accuracy reached. Compared with the FEM using a large-scale computation domain, computation efficiency of FEM-MLS coupling method is accelerated by about one times. When the same small-scale computation domain is used, the average accuracy of FEM-MLS coupling method is improved by about one times.

With the development of society and the acceleration of urbanization,urban road safety has become a focal point of attention.In this study,Ground Penetrating Radar(GPR)was utilized as an efficient geophysical method to investigate the detection of road quality and defects on a large scale in urban areas.A numerical simulation software,gprMax,based on the Finite-Difference Time-Domain(FDTD)method,was employed to simulate the electromagnetic wave propagation and perform geophysical forward modeling of common road anomalies and defects in urban environments.By analyzing the generated B-scan radar profiles and visualizing the geometric models,the radar re-sponse characteristics of different anomalies and defects were studied and analyzed,providing guid-ance for the data analysis and interpretation of practical road GPR surveys.Finally,by integrating actual data collected from road GPR surveys in Nanchang city,a road quality assessment was con-ducted,and potential defect types were identified.The results indicated that this method effectively served the detection of urban road quality and defects using GPR,providing an efficient approach for improving urban road quality and defect investigations.This research holds significant importance in addressing the increasing challenges of urban road safety.

传统的数值模拟方法依赖于节点连接信息的单元,基于全局弱式的无单元Galerkin法虽然无需节点连接信息的单元剖分,但仍依赖于全局域内剖分的背景积分单元.文中基于无单元Galerkin法,利用单位分解积分法将全局域积分转化为节点局部域积分,从而不再需要全局域内剖分的背景积分单元,进一步减小了对单元的依赖,实现了更灵活和更高精度的2.5维直流电阻率无单元局部弱式法正演模拟.分别应用该算法、无单元Galerkin法及有限单元法对不同地电模型进行数值模拟及效果对比,证明了所提算法对直流电阻率正演模拟的正确性和有效性.相比于无单元Galerkin法和有限单元法,文中算法具有更强的灵活性和适应性、更高的精度.为了提高该算法对地形起伏模型的模拟精度,对地形起伏区域进行节点加密,并对地形以外的高斯点不做计算,可获得与无单元Galerkin法和有限单元法(FEM)基本一致的效果.

The resistivity anisotropy characteristic of near-tight sandstone reservoirs is important for reservoir evaluation, but it is a challenge to obtain it by using conventional logging curves in vertical boreholes. Thus, a novel evaluation scheme is established. Firstly, in the Chang 8 Formation of Zhenjing area, Ordos Basin, China, horizontal rock samples (parallel to bedding) and vertical rock samples (perpendicular to bedding) are collected for designed rock electricity experiments and analyzed to obtain the corresponding horizontal and vertical Archie's parameters. Secondly, based on the detection characteristics of acoustic logging instrument and the transformation form of the Archie's equation, an estimation method of vertical resistivity is established. Combined with the horizontal resistivity obtained from conventional deep resistivity logs in vertical boreholes, an estimation method of resistivity anisotropy coefficient is proposed. Thirdly, the relationships between resistivity anisotropy coefficients and water saturations and porosities are analyzed using experiment results, and four adjacent vertical wells in the study area are processed using the estimated method. The processed results demonstrate the feasible of the estimation method. In addition, the cross well profile of resistivity anisotropy coefficient in the target formation is characterized, which shows the target formation is slightly resistivity anisotropic and slightly heterogeneous. The relationships between the resistivity anisotropy coefficient and commonly used logs are discussed, which contribute to rapid analyze the resistivity anisotropy of the target formation. Based on the above methods and processes, the novel evaluation scheme of resistivity anisotropy is established, which contributes to quantify and qualitatively analyze the resistivity anisotropy characteristics of formations in and between vertical boreholes. The application results show that it provides an alternative scheme for continuously evaluating the resistivity anisotropy in boreholes and cross well profiles by using conventional logs and experiments.

The controlled-source electromagnetic (CSEM) forward modeling with vector and scalar potentials could provide insights into the inductive and galvanic effects. We have developed a finite-element (FE) forward modeling algorithm for the CSEM with vector and scalar potentials. The first-order vector and nodal shape functions are used for the vector and scalar potentials, respectively. To mitigate the null space and thus the nonuniqueness of the potentials caused by the curl operator, we introduce a new preconditioner constructed from an incomplete Cholesky decomposition with zero fill-ins of the Laplacian approximation to the resulted matrix after the FE discretization. We implemented a preconditioned quasiminimal residual method to iteratively solve the resulting linear system with the new preconditioner. We first verified the accuracy of the algorithm through comparison against the analytic solutions obtained for a three-layered earth model. The new iterative modeling algorithm converges much faster compared with the modeling algorithm with the preconditioner constructed from the original stiffness matrix. The efficiency and accuracy are further illustrated by comparison with the modeling scheme based on coupled potentials with explicit enforcement of the Coulomb gauge condition for the vector potential by modeling three 3D models. In addition, the accuracy of our algorithm is demonstrated via a comparison of our numerical solution for a 3D model with the numerical solution obtained from the integral equation method. We also present the inductive and galvanic components of the horizontal secondary electric field for numerical solutions obtained with direct and iterative solvers. The numerical test demonstrated that, aside from the efficiency improved with the new iterative solver, the unstable and nonuniqueness problem for the potentials is eliminated by the new preconditioner with the Laplacian approximation involved.

Abstract As a key part of water conservancy and flood control, the safe service of levee is a matter of national importance. Since the construction of early levee showing the disease phenomena such as breakage, leakage and hollowness, it has seriously threatened the safety of people’s lives and properties, and became one of the important livelihood problems that need to be solved imminently. In this paper, the network model for automatic classification of levee hazards is constructed using convolutional neural network algorithm. The data set of the ground-penetrating radar responses of different hazards types required for training is constructed by forward modeling. Then, the network model is used to predict the hazards types from the actual measured data of a levee in Jiangxi Province. The results show that the good recognition accuracy and effect of the convolutional neural network model established in this paper.

Water inrush is a common geological disaster during the tunnel construction in the broken zone of deep buried water-rich faults. In order to improve the exploring accuracy of this water-rich faults, we first design four water-rich fault models with different inclined angle (22.5°, 45°, 67.5° and 90°) in 2D Magnetotelluric (MT) forward modelling using the finite element method. The simulation results show that the contour lines of apparent resistivity and impedance phase in these four models have a sparse concave feature, which increases with the inclined angle of the water-rich fault. However, the lateral resolution for the inclined fault in TM mode is better than that of TE model. We finally arranged two MT exploring lines in rocky mountainous area of southwest China to detect the deep buried water-rich fault. The inversion results show four significant low resistivity zones in the two MT measured lines. Combine with the geological data, we found that each two low resistivity areas are coherence with the fracture fault zone. Moreover, considering the forward modelling of the faults, we infer that two fracture faults spread in our study area. One fault F1 is northwest tilt with the inclined angle ~60°, and the other fault F2 is southeast tilt with the inclined angle ~80°. All these were also confirmed by the drilling data. The detections of two tilt water rich faults can effectively avoid potential hazards at this area and the forward numerical simulation can provide abundant theoretical reference for the field measured data.

依据PBGS教学的特点,针对地球物理学专业课程展开研究,对教学质量评价体系研究设计了"3+3+X"评价模式.PBGS教学模式让学生加入教师科研项目中,以教学促科研,以科研助教学,及时获得教学反馈,提高学生的创新能力与教师的积极性,从而形成良性循环,成为新的教育改革的推动力.

The streaming potential in porous media is one of the main constituents of the self-potential. It has attracted special attention in environmental and engineering geophysics. Forward modeling of streaming potentials could be the foundation of corresponding data inversion and interpretation, and improving the application effect of the self-potential method. The traditional finite element method has a large subdivision area and computational quantity, and the artificial boundary condition is not suitable for complex models. The Helmholtz-Smoluchowski equation is introduced for evaluating the streaming potential. Then three new shape functions of the multidirectional mapping infinite elements are proposed and the finite-infinite element coupling method is deduced for reducing the subdivision scale and improving both the calculation efficiency and accuracy. The correctness and validity of the new coupled method are verified by a resistive model in homogeneous half-space. Besides, a seepage model with complex terrain and a landfill model with dynamic leakages are modeled using the improved coupled method. The results show that the accuracy of the improved coupled method is superior to the unimproved coupled method, and is better than the finite element method. Also, the coupled method has better adaptability to complex models and is suitable for the accurate simulation of dynamic multi-source seepage models.

The migration-based source location methods have been widely used due to their robustness and automatism for detecting and locating weak microseismic events. Of them, the diffraction stacking method locates the event by stacking the amplitudes of seismic traces along the diffraction travel time curve, while it needs searching the origin time. The interferometry imaging method utilizes differential arrival times obtained by the cross-correlograms, which can avoid searching the origin time. However, its location results are sensitive to the signal-to-noise ratio of data. To solve this problem, this work proposes a full-interferometry imaging method which combines cross-correlograms and auto-correlograms to improve the location accuracy. The S-P differential traveltimes obtained by auto-correlograms can reduce the location errors along the direction of source-receiver. The numerical tests on the downhole monitoring model and research on field data indicate that the full-interferometry imaging method can obtain more accurate locations compared with the interferometry imaging method, and also improve the computational efficiency compared with the diffraction stacking method.

An element-free Galerkin method (EFGM) is proposed to perform the direct current (DC) resistivity modeling problems. The advantage of this method is the absence of elements, which makes nodes free from the elemental restraint. In this method, the moving least square (MLS) approximation is employed to construct the shape function. And the cubic spline function with high continuity is used as a weight function. Then, the boundary value problem and the corresponding variation problem of DC resistivity modeling problems are discussed. The discrete equations of two and a half dimensional (2.5D) DC resistivity modeling problems are obtained by using the Galerkin weak form formulation. Thereby, a 1D multilayered geoelectric model is adopted to verify the validity of the proposed EFGM. And the further tests of complicated geoelectric models illustrate that the correctness, good adaptability and flexibility of EFGM compared with the finite element method (FEM). The EFGM can conveniently simulate the undulating terrain and improve the simulation accuracy by refining nodes in local domain. In addition, the discretization of test models shows that EFGM is easy to handle the complicated geometrical geoelectric models by using arbitrary and irregular nodes. All these tests demonstrate that the EFGM is suitable to perform forward modeling for complicated geoelectric models.

PreviousNext No AccessInternational Workshop on Gravity, Electrical & Magnetic Methods and Their Applications, Xi'an, China, 19–22 May 2019An element-free Galerkin method based on hybrid background cells for 2.5D DC resistivity modellingAuthors: Changying Ma*Jianxin LiuWenwu TangHaifei LiuRongwen GuoYian CuiZhenwei GuoChangying Ma*School of Geophysics and Measurement-Control Technology, East China University of Technology, Nanchang, ChinaSearch for more papers by this author, Jianxin LiuSchool of Geosciences and Info-Physics, Central South University, Changsha, China, and Non-ferrous Resources and Geologic Disasters Prospecting Emphases Laboratory of Hunan, Changsha, ChinaSearch for more papers by this author, Wenwu TangSchool of Geophysics and Measurement-Control Technology, East China University of Technology, Nanchang, ChinaSearch for more papers by this author, Haifei LiuSchool of Geosciences and Info-Physics, Central South University, Changsha, China, and Non-ferrous Resources and Geologic Disasters Prospecting Emphases Laboratory of Hunan, Changsha, ChinaSearch for more papers by this author, Rongwen GuoSchool of Geosciences and Info-Physics, Central South University, Changsha, China, and Non-ferrous Resources and Geologic Disasters Prospecting Emphases Laboratory of Hunan, Changsha, ChinaSearch for more papers by this author, Yian CuiSchool of Geosciences and Info-Physics, Central South University, Changsha, China, and Non-ferrous Resources and Geologic Disasters Prospecting Emphases Laboratory of Hunan, Changsha, ChinaSearch for more papers by this author, and Zhenwei GuoSchool of Geosciences and Info-Physics, Central South University, Changsha, China, and Non-ferrous Resources and Geologic Disasters Prospecting Emphases Laboratory of Hunan, Changsha, ChinaSearch for more papers by this authorhttps://doi.org/10.1190/GEM2019-067.1 SectionsAboutPDF/ePub ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinked InRedditEmail Abstract We present an element-free Galerkin method (EFGM) based on hybrid background cells for 2.5D direct current (DC) resistivity modelling. In our method, we only need nodal data, which makes it flexible for the description of arbitrary complex geoelectric models and efficient for local nodal refinement. In EFGM, the quadrature is calculated with the aid of background cells. The background cells are generated adaptively and automatically according to the nodal distribution using an adaptive background cell generation approach, proposed by authors. This approach decreases the computational cost significantly, provided that the Gauss integration points are reasonably arranged. However, the uneven background cell size in regions around the field sources may result in bad simulation accuracy. A hybrid background cell generation scheme is proposed by combining the adaptive scheme and the evenly subdivided scheme. The hybrid scheme can overcome the disadvantage of adaptive scheme. The developed algorithm is applied to solve the 2.5D DC resistivity modelling problems with a circular anomalous body model, based on the Galerkin global weak-forms to illustrate the performance of the proposed method. The results indicate the validity of developed algorithm. Keywords: resistivity, modelling, algorithmPermalink: https://doi.org/10.1190/GEM2019-067.1FiguresReferencesRelatedDetails International Workshop on Gravity, Electrical & Magnetic Methods and Their Applications, Xi'an, China, 19–22 May 2019ISSN (online):2159-6832Copyright: 2019 Pages: 471 publication data© 2019 Published in electronic format with permission by the Society of Exploration Geophysicists and the Chinese Geophysical SocietyPublisher:Society of Exploration Geophysicists HistoryPublished Online: 28 Sep 2019 CITATION INFORMATION Changying Ma*, Jianxin Liu, Wenwu Tang, Haifei Liu, Rongwen Guo, Yian Cui, and Zhenwei Guo, (2019), "An element-free Galerkin method based on hybrid background cells for 2.5D DC resistivity modelling," SEG Global Meeting Abstracts : 264-267. https://doi.org/10.1190/GEM2019-067.1 Plain-Language Summary KeywordsresistivitymodellingalgorithmPDF DownloadLoading ...

In this paper, we analyze the advantages and disadvantages of the Element-Free Galerkin Method (EFGM) and Finite Element Method (FEM) in forward simulation of Direct Current (DC) resistivity. A large enough computational domain is required when the first class boundary condition is used, which will significantly increase the computational cost of EFGM. To solve this problem, we propose a Element-Free Galerkin-Finite Element (EFG-FE) coupling method for forward modeling of DC resistivity. The FEM is used in the peripheral region of the calculation domain in the EFG-FE. In order to eliminate the difficulties in the traditional EFGM and FEM coupling method on the interface, the Radial Point Interpolation Method (RPIM) is used to construct the element-free shape function. Due to the RPIM shape function has the Kronecker delta function property, EFGM and FEM can be coupled directly without any other processing technology. EFG-FE divides the model calculation domain into a EFGM region and FEM region. In order to exert the flexibility, adaptability and high precision of EFGM, the core area of the model is calculated using EFGM, which results in the simplicity and convenience of model establishment, the adaptability of any complex geoelectric model and high precision of simulation results. In order to reduce the calculation time and expand the computational domain so that the natural boundary conditions are satisfied, a rapidly expanding FEM grid is used in the periphery of the EFGM region, which results in a small number of nodes and FEM grid cells. Finally, the simulation results of different forward modeling methods are compared. The results show that the proposed EFG-FE is feasible. And compared to the EFGM with the third kind of boundary conditions, the proposed EFG-FE method can improve the computational efficiency. In conclusion, the proposed EFG-FE has a better simulation performance.

The integral equation method (IEM) and differential equation methods have been widely applied to provide numerical solutions of the electromagnetic (EM) fields caused by inhomogeneity for the controlled-source EM method. IEM has a bounded computational domain and has been well-known for its efficiency, whereas differential equation methods are commonly used for complex geologic models. To use the advantages of the two types of approaches, a hybrid method is developed based on the combination of IEM and the edge-based finite-element method (vector FEM). In the hybrid scheme, Maxwell’s differential equations of the secondary electric fields in the frequency domain are derived for a volume with boundary placed slightly away from the inhomogeneity. The vector FEM is applied to solve Maxwell’s differential equations, and a system of linear equations for the secondary electric fields can be derived by the minimum theorem. The secondary electric fields on the boundary are represented by IEM in terms of the secondary electric fields inside the inhomogeneity. The linear equations from substituting the boundary values into the vector FEM linear equations then can be solved to obtain the secondary electric fields inside the inhomogeneity. The secondary electric fields at receivers are calculated by IEM based on the secondary electric field solutions inside the inhomogeneity. The hybrid algorithm is verified by comparison of simulated results with earlier works on canonical 3D disc models with a high accuracy. Numerical comparisons with two conventional IEMs demonstrate that the hybrid method is more accurate and efficient for high-conductivity contrast media.

We present an element-free Galerkin method (EFGM) based on adaptive background cells for 2.5D direct current (DC) resistivity modelling. In our method, we only need nodal data, which makes it flexible for the description of arbitrary complex geoelectric models and efficient for local nodal refinement. In EFGM, the quadrature is calculated with the aid of background cells. The background cells are generated adaptively and automatically according to the nodal distribution using an adaptive background cell generation approach, proposed in this paper. This approach decreases the computational cost significantly, provided that the Gauss quadrature pointsare reasonably arranged. The application of the background cell generation method makes the modeling, with arbitrary and irregular nodal distribution, flexible and convenient. The developed algorithm is applied to solvethe 2.5D DC resistivity modelling problems with A homogeneous 2D half-space model, based on the Galerkin globalweak-forms to illustrate the performance of the proposed method. The results indicate the validity of developed algorithm. Note: This paper was accepted into the Technical Program but was not presented at the 2018 SEG Annual Meeting in Anaheim, California.

We present a global weak form element free method (EFM) for simulation of direct current resistivity. EFM is a new numerical simulation method developed on the basis of the finite element method (FEM). The key point of this method is the absence of elements and the nodes free from the elemental restraint, which makes it very flexible and simple in pre-processing. It utilizes the nodes of local support domain to construct shape functions to achieve the accurate approximations of the local domain. Approximations of EFM are of high order and boundary conditions are enforced simply, because the radial point interpolation method (RPIM) is used to construct shape function. Therefore, EFM is more suitable to simulate complex models than FEM. First, the boundary value problem and the corresponding variational problem of direct current resistivity forward simulation are derived starting with the partial differential equation of current field. Second, the construction of RPIM shape function is introduced in details. Third, equations of the global weak form EFM for direct current resistivity are derived in details based on RPIM shape function. Then, a Fortran program is written according to the equations. By this program, a homogeneous half-space model was used to verify our element free approach. At the same time, we compared the solutions of EFM and FEM in details which shows that the solutions of EFM are more accurate. Furthermore, the solutions indicate the correctness and effectiveness of the EFM for direct current resistivity forward simulation. Finally, we improve the simulation accuracy successfully by refining nodes arbitrarily, and the solutions of EFM forward simulation for complex geoelectric models show that EFM has a high degree of flexibility.