bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Numerical Output Technique for Voxler’s ObliqueImages and Its Application
Authors: Liu Haitao , Peng Jun , Hu Jun , Xiong Youliang , Li Huan 
Published: December 2023

Abstract
In geophysical surveys, there will be no measured data at some location where it is inaccessible for placement of survey points or lines. The interpolation data of those locations can be obtained and displayed by using three-dimensional (3D) mapping platform. Based on the study of the file format of ObliqueImage output in Voxler platform, this paper presents a technique for extracting spatial coordinates and physical parameter values of each point in the ObliqueImage. This numerical output technique is used to map the profiled slice across the tunnel axis where boreholes can not be arranged in the electromagnetic wave CT investigation section in a dedicated karst survey of an underwater tunnel in Wuhan, rendering the karst development on the profile across the tunnel axis; after further extension, the point cloud data of bedrock surface and karst caves for building 3D geological model are extracted from isosurface files, which provides data basis for tunnel design and construction digitization.
The Application of Rayleigh Wave Method in the Underground Void Area Exploration
Authors: An Yin , Du Lizhi , Zhang Guoqiang , Wang Yong 
Published: December 2023

Abstract
Underground voiding refers to the phenomenon that abnormal looseness, plate breakage, increase in porosity of underground medium lead to the formation of voids that decrease the stability of stratum and weaken the physical and mechanical properties. For example, road underground voiding will seriously affect the comfort and safety of vehicle driving. At present, the engineering geophysical prospecting technology is mainly used to detect the void area. In this paper, the elastic wave simulation method is used to study the response of the Rayleigh wave method to the underground void of the pavement. The response regularity is explored by adjusting the model parameters. The outdoor experiment is carried out according to the law parameters, and the effectiveness of the elastic wave for the detection of shallow surface voids is verified.
Application of OCTEM in The Detection of Hidden Faults in Urban Underground Space Investigation
Authors: Zhou Chao , Liu Yi , Zhao Siwei 
Published: December 2023

Abstract
At present, the geological survey of urban underground space is currently being carried out in many cities across the country. Choosing appropriate survey methods will make this work more effective. OCTEM is a new exploration method that has emerged in engineering geophysical prospecting in recent years. It has the advantages of portable facilities and strong anti-interference ability, and is suitable for urban geological survey work. In this paper, OCTEM is applied to the hidden fault detection work in underground space survey in Chengdu. The results show that this method can effectively identify the fault fracture zone in the strong interference urban environment. At the same time, the OCTEM results are compared with the application results of the other 2 geophysical methods. The analysis further proves the adaptability and superiority of this method. It provides an effective new method for urban underground space survey work.
Surface-Wave Imaging with Nonrandom Traffic Noise Sources
Authors: Mi Binbin , Xia Jianghai 
Published: December 2023

Abstract
We analyze the influence of nonrandom traffic noise sources on surface wave imaging. With nonrandom traffic noise sources in time (correlated sources), spurious signals are produced in the crosscorrelation functions. With nonrandom traffic noise sources in space (directional sources), phase velocities are overestimated from the retrieved surface waves. The retrieval of surface waves can be improved by stationary-phase segment selection, cross-coherence and stacking of the results from multiple traffic noise sources. Synthetic results demonstrate that cross-coherence and stacking of multiple traffic noise sources makes the source tend to be random distribution in time and suppresses the spurious signals in the crosscorrelation functions. Enhancing the stationary-phase contribution makes more accurate estimation of surface wave phase velocities.
Effect Analysis on Field Acquisition Parameters of Surface Wave Survey - Case Study on The Gobi Desert Field
Authors: Ren Quanchao , Li Zhongsheng , Liu Sitong , Tian Awei , Li Yongxin , Xiao Weiguo , Lu Qiang , Su Wuque , Li Xingwang 
Published: December 2023

Abstract
In this paper, the Gobi Desert landform is used as a test site to analysis the results on surface wave survey. The body wave exploration methods are used to determined velocity structure of the site as a reference standard firstly. Subsequently, different acquisition parameters for surface wave are tested. After comparing the results, the optimal parameters are selected by using the surface wave multi-channel analysis method (MASW). Meanwhile, several theoretical equations for estimating minimum offset, optimum offset, geophone spread length, and resolution of dispersion are demonstrated as the guidelines to organize the real-world data acquisition. Finally, the selected optimal parameters are applied to the data acquisition of total 69 surface wave recorders. The final two-dimensional inversion profile is in good agreement with the known background. It means the method of MASW is feasible in geological surveys on Gobi Desert landform.
Trans-Dimensional Bayesian Inversion of Rayleigh Wave Dispersion Curves for Shallow Surface Two-Dimensional Imaging
Authors: Liu Haonan , Zhang Zhifu , Ma Zhenning , Zhang Jinyung 
Published: December 2023

Abstract
In this study, we achieve 2-D spatial structure directly from dispersion measurements using the reversible jump Markov chain Monte Carlo (rj-McMC) algorithm with a fully 2-D model parameterization. New parsimonious parameterization with low dimensional representation is introduced, which enable us to accurately reproduce the wave velocity field and the associated uncertainties. Field data test demonstrates that the proposed method estimates directly the shear-wave velocity profile with better lateral resolution. The associated uncertainties provide directly interpretable uncertainty on structures of interest.
Modified Frequency-Bessel Transform Method for Dispersion Imaging of Surface Wave from Six-Component Ambient Noise Recordings
Authors: Xi Chaoqiang , Liu Ya , Wu Haibo , Ning Ling , Zhang Hao , Guan Bo 
Published: December 2023

Abstract
Surface wave analysis methods based on ambient noise have attracted considerable attention within the geophysical and civil engineering communities, particularly in light of the limitations associated with traditional seismic surveys in densely populated urban areas. Conventionally, translational seismic sensors have been employed for the observation of ambient noise. Nevertheless, recent advancements in rotational sensor technology have facilitated the direct measurement of ground motion induced by seismic waves in a rotational manner. Through the integration of these rotational sensors with traditional inertial seismometers, a novel six-component seismic sensor has been developed. This innovative sensor enables the local observation of six degrees of freedom pertaining to ground motion, encompassing three orthogonal components of translational motion and three orthogonal components of rotational motion. In order to demonstrate the seismological significance of rotational ground-motion data, we applied the modified frequency-Bessel transform method (MFJ) to six-component ambient noise recordings for surface wave analysis. To underscore the practical utility of the MFJ method, a real-world case study is presented, illustrating its effectiveness in quantifying Rayleigh and Love wave dispersion from six-component ambient noise recordings.
Application of Deep Learning in Rayleigh Dispersion Curves Inversion
Authors: Ye Zhihu , Xie Xiaoguo , Zhang Zhihou , Zhao Minghao , Zhang Tianyi , Wang Hu 
Published: December 2023

Abstract
The inversion of the Rayleigh wave dispersion curve is a fundamental step in determining the shear wave velocity profile. However, existing inversion methods, such as linear and nonlinear approaches, have inherent limitations. In order to overcome these challenges and enhance the speed and accuracy of the inversion, this paper proposes a novel deep learning-based approach. We establish a method to construct sample data that ensures ergodicity and evolutive orderliness of the near-surface velocity profile using a constrained Markov decision process to address these limitations. We then design a deep learning model to capture the nonlinear mapping relationship between the dispersion sequence data and velocity structure. Training the model on the generated sample data accurately predicts the subsurface velocity profile based on the dispersion curve. The proposed method is evaluated through theoretical model experiments, demonstrating high computational accuracy.
Application of Variational Mode decomposition in GPR Detection of Oil Contaminated Soil
Authors: Lu Qi , Guo Shilong , Zeng Zhaofa , Liu Sixin , Liu Kexin , Li Xiaolong 
Published: December 2023

Abstract
In this article, Ground penetrating radar (GPR) is used to investigate the contaminated soil by oil pollutants in oilfield operation area. Time frequency analysis method is applied to GPR data to reveal the changes of GPR signal frequency components with time variation, which is very important for data interpretation. We use variational mode decomposition (VMD) for time frequency analysis. It can decompose radar signal into several quasi-orthogonal intrinsic mode functions (IMFs) with limited bandwidth, and has strong robustness and local decomposition ability. We apply the VMD on field data acquired in the area with waste liquid contaminated soil in oilfield. The decomposed IMFs from GPR data shows that the signals from the contaminated soil is characterized by the strong energy and low frequency. Then the instantaneous attribute analysis of the IMF is carried out to delineate the scope and thickness of contaminated soil. The experimental results show that the limited bandwidth IMF with specific sparsity obtained by VMD method is more conducive to the processing and interpretation of GPR data.
Near-field Focusing in Ground Penetrating Radar Based on Phase Compensation Algorithm
Authors: Zhang Qifei , Guo Linyan , Chen Lianfeng , Zhang Qisheng 
Published: December 2023

Abstract
Underground energy intensity and electromagnetic wave penetration depth are important parameters to characterize the detection performance of Ground Penetrating Radar (GPR). Near-field focusing (NFF) is an effective means to improve the electromagnetic energy fed into the ground by the antennas. In this paper, the phase compensation algorithm considering underground media is derived. In order to verify the effectiveness of the algorithm, the NFF antenna array is proposed. By changing the phase of the NFF array, the focus distance can be adjusted in the range of 400 mm – 800 mm. The maximum field enhancement coefficient in the focal region can achieve 19.2 dB. This shows that NFF array based on phase compensation algorithm has potential application prospects in increasing GPR detection performance.
Removal of Diagonal Strip Noise in Airborne Ice Penetrating Radar Data
Authors: Luo Kun , Liu Sixin , Tang Xueyuan , Li Lin 
Published: December 2023

Abstract
Airborne ice-penetrating radar (IPR) is a powerful geophysical method for detecting ice thickness, subglacial topography and internal layers in the vast and frigid Antarctic ice sheet. Data processing is an essential step in improving the signal-to-noise ratio (SNR). In order to eliminate the diagonal strip noise mainly present in airborne IPR data of the Amery ice shelf and Grove Mountain regions, traditional ground penetrating radar processing methods such as F-K (frequency-wavenumber domain) filtering and F-K migration are applied. The validity of the data processing methods is proved by the quantitative index of image quality evaluation. It provides a reference for subsequent airborne radar data processing and application.
Research on GPR Response Recognition of Levee Hazards Based on Convolutional Neural Network
Authors: Zhao Wenxue , Ma Changying , Yan Lingling , Ding Wenqiang , Zhong Weichen , Xie Song 
Published: December 2023

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.
Application Research of 3D Geological Radar Detection Technology in Urban Road Disease Survey
Authors: Tan Shunjia , Qian Peng , RuixueWang  
Published: December 2023

Abstract
With the comprehensive detection and risk assessment industry of urban road underground diseases taking shape and the long-term development of new technologies, new methods and new equipment, this paper introduces the important breakthrough of 3D geological radar detection technology. Such nondestructive testing site acquisition can achieve high-density seamless detection, qualitative accuracy of data interpretation, accurate determination of road disease scope, detection data has long-term preservation and application research value.
Breakthrough and Practice of Ground Penetrating Radar Detection Technology in Baiyangdian Lake
Authors: Wang Chunhui , Pu Yuantian , Guo Shujun , Sun Sheng 
Published: December 2023

Abstract
In order to investigate the stratum structure of the lake bottom in the Baiyangdian Lake area, implement the test of the water-based ground penetrating radar detection system, explore the working mode of the water-based radar detection, compare the water exploration capabilities of different hardware devices, analyze the electromagnetic wave propagation characteristics in the Baiyangdian Lake area, and interpret the geophysical response of the native strata at the bottom of the lake. The stratum structure data in the 15m depth range of the bottom of the lake was obtained to provide a basis for the establishment of a three-dimensional geological model of the Dian District. This technical achievement can strongly promote the construction of a lake and wetland water-land integrated technical method system.
AVO Attribute Characteristics of Ground Penetrating Radar
Authors: Yuan Lei , Jiang Zhihai , Liu Shucai , Li Maofei 
Published: December 2023

Abstract
As a non-destructive and high-efficiency electromagnetic wave exploration method, the conventional fixed-offset GPR detection has been able to solve some practical problems. However, in the case of complex formation conditions and variable physical parameters, the effect is not too ideal. In reference to earthquakes, AVO processing technology can be used to enhance the detection of lithologic parameters. This paper introduces the application of AVO in GPR by numerical simulation. By controlling variables and changing the parameters of the model, the response characteristics under different offsets and different relative dielectric constants are analyzed, and the application of AVO technology in radar processing and the identification of lithologic parameters of the lower interface are verified.
Effect Analysis of Random-weighted Equipoise Multi-channel Adaptive Matched Filtering on Regular Interference Removal
Authors: Li Yongxin , Li Zhongsheng , Xiao Weiguo , Lu Qiang , Wang Zhongsheng , Su Wuque , Ren Quanchao , Li Xingwang , Hu Jing 
Published: December 2023

Abstract
Equipoise multi-channel adaptive matched filtering is an effective method to remove regular interference signals from the original seismic records. In order to weaken the dependence of data on orthogonality restrictions, some channels around the target are usually selected as equipoise channels. In order to accurately extract the wavelet shape, the selected equipoise channels need to be as few as possible. The fewer equipoise channels, however, will lead to unsatisfactory filtering effect because of data non-orthogonality. In view of this defect, we develop conventional equipoise multi-channel adaptive matching via randomly selecting channels away from the target as the equipoise channels and assigning different weight factors to different equipoise channels simultaneously. This method may weaken the data non-orthogonality and reduce the influence related to the number of equipoise channels. In order to verify the effectiveness of this method, numerical experiments and analysis of different models have been carried out. The results show that in the case of a small number of matching channels, the effects of the random or random-weighted equipoise multi-channel adaptive matched filtering are better than the conventional one. The random-weighted has the best effect.
The Strain State Analysis of 4-component Borehole Strainmeter Observations in Sichuan-Yunnan Region
Authors: Tang Lei , Ye Qing , Fan Junyi 
Published: December 2023

Abstract
Analysis of nearly a decade of crustal strain changes state after the Ms8.0 Wenchuan earthquake by using 4-component borehole strain observation data, and combined with the tectonic stress field, this paper studied the regional stress and strain variation characteristics and dynamics. The results show that the main compressive strain direction of the 4-component borehole strain observation is approximately the same as that of tectonic stress field. However, there are also some regional inconsistencies, which should be related to regional structural features.
MTAINV3D: A Three-dimensional Adaptive Magnetotelluric Inversion Tool Using Unstructured Grids
Authors: Chen Huang , Ren Zhengyong , Tang Jingtian 
Published: December 2023

Abstract
Currently, 3D magnetotelluric inversion often uses a fixed inversion grid. Too sparse inversion grids cannot approximate the complex subsurface conductivity distribution, and may also lead to inversion results failing to converge. Too dense inversion grids will increase not only the computational cost, but also the non-uniqueness of the inversion. Aiming at the above problems, we have developed a three-dimensional magnetotelluric adaptive inversion strategy with unstructured finite element and limited memory BFGS (L-BFGS) algorithms. Firstly, based on the unstructured finite element method, the high accuracy forward responses of the 3D geo-electric model with arbitrary complex terrain and conductivity distributions can be obtained. Then, the forward and inversion meshes are decoupled by using the nested forward and inversion tetrahedral meshes. The Thikhonov regularization objective function with smooth constraints is established and minimized by L-BFGS optimization algorithm with inexact line search procedure, where the gradient of the objective function is solved by using the adjoint principle. Most importantly, an inversion grid adjustment strategy based on the dual constraints of sensitivity matrix and model gradient is proposed, which are used to guide the automatic refinement of inversion grid in the optimization process. Finally, a topographic model is used to validate and test the performance of the proposed adaptive inversion algorithm.
Using High-speed Train Induced Signal to Estimate High-Speed Train Acceleration
Authors: Wang Hailin , Wang Xiaokai , Chen Wenchao , Liu Zhaodan 
Published: December 2023

Abstract
A moving high-speed train (HST) stimulates various seismic waves near a high-speed railroad (HSR). Thus, the HST has been treated as a combined and moving seismic source. Moreover, the speed and acceleration of HST are typical moving parameters for this HST seismic source. Certain devices, such as GPS, Doppler radar, and cameras, can be used to estimate the HST’s speed. However, they are inconvenient or can be affected by the obstacles. The geophone near an HSR continuously receives the seismic signal induced by the moving HST. This work focuses on the HST acceleration estimation using only one geophone near the HSR and proposes an acceleration estimation method based on the time-frequency spectrum. The experimental field result for a viaduct situation shows the proposed method’s ability to estimate a passing HST’s acceleration, which is verified by acceleration estimation results based on a 14-geophones array along the HSR.
A Rapid Forward for Grounded Long Wire Source Transient Electromagnetic Method
Authors: Yang Yunjian , Sun Weibin , Mi Xiaoli , Zhu Yongshan , Chai Yanning 
Published: December 2023

Abstract
Aiming at enhancing the forward and inversion efficiency of grounded long wire source TEM (Transient ElectroMagnetic method), a new rapid layered medium forward method is proposed in the paper. This forward method is based on two points, one is to approximate the vertical magnetic component in frequency domain of a grounded long wire source by the response of several circular loops, and the other is to introduce the technique of "flow through" into the digital filtering calculation of sinusoidal transformation. The result of model tests shows that the calculation efficiency of proposed method is improved greatly (dozens of times) compared with that of the conventional method.
Application of Electromagnetic Wave Computerized Tomography in Metro Tunnel Detection in Karst Area
Authors: Sun Jianxin , Wang Hui 
Published: December 2023

Abstract
When tunnelling in karst areas, a series of geological hazards caused by karst are often encountered, resulting in huge economic losses as well as human casualties. In order to ensure the safety of tunnel construction, risk assessment and early warning of karst-related geological hazards, it is necessary to use geophysical methods to find out the location, size, shape and filling of karst, and to provide necessary reference information for traffic route planning and tunnel construction planning. Based on theoretical model research, the construction plan of electromagnetic wave CT method was designed for data acquisition in an underground tunnel detection project in a city of Jiangsu province based on existing geological data, and the inverse interpretation of the measured data was carried out in combination with borehole core data to study the feasibility, effectiveness and accuracy of the electromagnetic wave CT method for karst detection in urban underground space.
3D Forward and Inversion Research on Frequency Domain Electromagnetic Tipper Data
Authors: Gao Wenlong , Wang Xuben , Mao Lifeng , Luo Wei 
Published: December 2023

Abstract
The tipper is one of the main parameters of the electromagnetic exploration data in the frequency domain and has an important role and significant advantage in the exploration under complex geological conditions. In this paper, the 3D forward modeling is carried out based on the staggered grid finite difference method, and the analytical solution of the layered medium is used to verify its correctness; the L-BFGS algorithm is used to perform the 3D inversion of the tipper data. Through the three-dimensional complex model, the forward response characteristics and spatial distribution of the tipper are analyzed. The inversion results show that the inversion using the inversion data has less influence on static displacement and better inversion results.