bluuebunny/crossref_metadata_2025_split huggingface dataset:
Surface wave imaging with stationary-phase noise sources based on ultrashort traffic-induced data: An application in karst cave detection
Authors: Ning Ling , Dai Tianyu , Liu Ya , Zhang Hao , Xi Chaoqiang 
Published: December 2024

Abstract
In urban environments, abundant traffic-induced noise data are analyzed through crosscorrelation to retrieve high-frequency (> 1 Hz) surface waves, providing a cost-effective technique for detecting near-surface structures. The isotropic noise source distribution is an essential prerequisite for the correct reconstruction of the Green’s function. The azimuth of traffic noise sources, however, can change with human activities in highly populated urban areas, resulting in non-random distributions in time and space. Due to the uneven distribution of traffic noise sources, spurious signals are generated in the noise crosscorrelation functions and phase velocities calculated from the retrieved surface waves are overestimated, leading to incorrect S-wave velocity profiles. By analyzing the noise source distribution of each segment, we selected the stationary-phase segments to improve the retrieval of surface waves. We processed approximately one-day ultrashort continuous recordings to obtain virtual shot gathers with larger multichannel-coherency coefficients and dispersion images with more surface-wave dispersion data. S-wave velocity profiles for different arrays, including a 3D S-wave velocity model, were produced by inverting the surface-wave dispersion data to reveal the distribution of karst caves beneath the surface. The results demonstrate the effectiveness of the strategy of the stationary-phase segment selection and the great potential of traffic-induced surface waves in monitoring subsurface changes in urban areas.
Comparative analysis of distributed acoustic sensing responses across different optical fiber types for engineering geological exploration
Authors: Li Zhongzhi , Liu Bin , Fang Gang , Cao Hongyi , Zhao Yang , Chen Lei 
Published: December 2024

Abstract
Distributed Acoustic Sensing (DAS) has emerged as a revolutionary technology in seismic exploration, offering a novel approach to data acquisition. Despite its widespread adoption, the deployment of DAS in surface engineering exploration faces significant challenges, particularly concerning signal-to-noise ratio limitations and spatial resolution constraints. We conduct a comparative analysis of DAS responses using various types of optical fibers commonly employed for sensing purposes. We evaluate fibers of type A (tight-buffered fiber and strain-sensitive fiber) and type B (communication optical fiber, loose tube optical fiber, and temperature measurement optical fiber), as well as fibers in a helical configuration with different armoring materials. The deployment of optical fibers for this comparison includes both surface layouts and borehole integrations. Conventional geophones and hydrophones serve as benchmarks to contextualize the analysis and validate the performance of the DAS system data. This comparative approach highlights the utility of DAS for engineering seismic prospecting.
Research on density effects of interaction between River water-Groundwater by temperature tracer method based on sand tank test
Authors: Wei Wenhao , Sun Yunzhi , Lin Jingjing 
Published: December 2024

Abstract
In this study, four sets of control tests of groundwater recharge river steady flow were designed using the indoor two-dimensional sand tank model to evaluate the density effect caused by temperature change and evaluate the error of temperature tracer method in calculating groundwater velocity. The test results show that the density effect caused by temperature difference can affect the velocity and direction of groundwater flow. The calculation results of the temperature profile from the bed to the bottom of the trough show that the higher the depth, the smaller the vertical component velocity of groundwater, and the less effective the temperature tracer method is in interpreting the velocity. When the temperature gradient reaches 0.33°C/cm, local free convection has formed in the lower part of the characteristics profile, and the error of the groundwater velocity calculated by the temperature tracer method is about 200%, which is much higher than the error of Darcy’s solution 175%. The influence of density effect driven by temperature difference on the analytical results should be evaluated in the study of using temperature tracer method to estimate the exchange capacity of surface water and groundwater.
Design and implementation of seismic and electric joint detection system
Authors: Wei H , Zheng J , Cheng J , Sun Y , He D 
Published: December 2024

Abstract
Single geophysical method faces challenges in accurately depicting water-bearing anomalies due to complex factors in underground spaces. In response to this issue, our design innovatively proposes a combined approach, integrating seismic exploration with parallel electrical method. We have developed a complete joint acquisition instrument for seismic and parallel electrical method using a multi-channel acquisition board based on INTEL and FPGA. This instrument enables simultaneous data collection for both methods within the same timeframe. With high integration, it allows convenient deployment and can be controlled through visualization software on the upper computer. Laboratory tests confirm its ability to meet the basic design requirements. Once fully implemented, it is poised to offer innovative and effective technical support for the development of urban underground spaces, demonstrating broad application potential.
Radio-magnetotelluric transmitter in full-bridge resonance inverter
Authors: Guo Tao , Xi Zhenzhu , Liu Wei , Liu Qingbin 
Published: December 2024

Abstract
Radio-magnetotelluric (RMT) is a widely used method for shallow subsurface electromagnetic exploration, employing magnetic sources (coils) for signal transmission. A common challenge is the low frequency and unstable current of the instrumentation. To address this, a full-bridge resonant inverter circuit is designed for signal transmission.
Simulation Study on Broadband Hive Receiving Coil for Small-Loop Transient Electromagnetic Detection
Authors: Wang Shengjie , Su Guoying , Sun Yishu , Jia Wenfeng , Wang Weicheng , Wang Qingshan 
Published: December 2024

Abstract
The multi-turn small-loop transient electromagnetic (TEM) receiving coils can be used for urban underground space survey and mine detection because of their versatility and adaptability to complex environments. However, reducing the size of the receiving coil increases the parasitic parameters while narrowing the frequency band, resulting in the loss of high-frequency signals that contains shallow geological information. We propose a hive-receiving coil, and use finite element simulation to compare multi-turn hive coils with circular receiving coils in the same size. It is proved that the hive coil has lower parasitic parameters and wider passband, which can meet the detection requirements of small-loop TEM.
Feasibility study of applying GPR to leakage prediction of urban landfill
Authors: Luo Y 
Published: December 2024

Abstract
The urban waste pollution caused by the rapid industrialization development has become increasingly serious. The main way of dealing with municipal waste in China is still landfill, which is convenient, but often lead to the waste leakage because of the immature anti-seepage system. Therefore, how to quickly investigate the landfill leakage to take necessary remedial measures for the subsequent leakage has become a hot issue. This study discusses the feasibility of GPR in urban landfill leakage prediction by discussing the GPR response of two types of landfill leakage models. The synthetic model experiment shows that GPR can effectively identify the anomalies caused by pollutant leakage in the landfill.
A new low-cost nodal rotary seismometer
Authors: Jia Song , He Zhanxiang , Wang Caixia , Yang Hui , Yao Yongchao 
Published: December 2024

Abstract
Rotational seismometers can measure the rotational component to improve the gradient information of the seismic wavefield, which, when combined with the translational component, provides a complete and detailed measurement of the seismic wavefield. Nowadays, field seismic signal acquisition pays more and more attention to the measurement of rotational components, and the gyroscope can achieve the measurement of angular velocity. Considering the economy and convenience of the instrument, the rotary seismometer designed based on Micro Electromechanical Systems (MEMS)technology not only achieves the measurement of rotational components but also reduces the cost and volume to realize the instrument’s low cost and node type of the instrument.
Three-Component Time-Domain Electromagnetic Method for Far Detection in Boreholes
Authors: Xiao Zhanshan , Hu Haitao , Qi Chao , Zhao Yunlong , Zhao Jianbin , Fang Chaoqiang , Zhang Yonghao , Yan Junjie , Wei Bo 
Published: December 2024

Abstract
Time-domain electromagnetic measurement technology in boreholes enables geological exploration on a reservoir scale using short-distance detectors. This technology overcomes the limitations of conventional frequency-domain instruments, which require long-distance detection by reducing frequency and increasing source distance. It provides panoramic, forward, and deep borehole perspectives. Time-domain electromagnetic logging provides timely information on the distance to the formation interface ahead of the detector. This introduces a novel method for borehole measurements, useful for geological boundary detection, fracture effect evaluation, and identifying the water drive front. Research the response characteristics of time-domain electromagnetic waves in boreholes under various scenarios using time-domain finite element numerical simulation. Pilot experiments demonstrate the promising potential of time-domain electromagnetic remote detection technology for borehole exploration.
Research on the Influence of Surface Wave Dispersion Curve in Anisotropic Viscoelastic Media
Authors: Zhang Chengang , Li Jing , Liu Hui , Su Ronghua 
Published: December 2024

Abstract
Surface-wave dispersion curve inversion of S-wave velocity structure is one of the primary methods for revealing near-surface structures. However, near-surface structures have large anisotropy and strong attenuation characteristics. Previous studies have investigated that surface anisotropy and sediment attenuation parameters significantly impact the extraction of dispersive information. Quantitatively assessing the sensitivity of different parameters can provide a reference for accurate inversion of S-wave velocity. In this abstract, we utilize a 2-D VTI viscoelastic finite-difference method to simulate the propagation characteristics and dispersion features of Rayleigh wave in anisotropic and viscoelastic media. Then, we use the typical synthetic model to analyze the sensitivity of Rayleigh wave dispersion curves to viscoelastic and anisotropic parameters. The conclusion is that the anisotropic and attenuation parameters cause significant changes in the surface-wave phase velocity, and the viscoelasticity can cause the amplitude attenuation of the Rayleigh wave. The sensitivity of dispersion curves to anisotropic parameters is greater than that of viscoelastic parameters.
AMT denoising via double sparse dictionary learning
Authors: Zhang Liang , Tang Jingtian 
Published: December 2024

Abstract
Audio magnetotellurics (AMT) is commonly employed in the exploration of resources. However, the energy of AMT signals is relatively weak, making them susceptible to various artificial sources of interference, thus being submerged in intense noise. This poses a significant disadvantage for the identification of various resources. Sparse representation is a commonly used method for AMT denoising, but under strong noise interference, conventional sparse representation methods often fail to effectively remove noise due to the inadequate performance of the sparse basis. To enhance the performance of the sparse basis and achieve more accurate AMT denoising results, we propose a double sparse dictionary (DSD), which is formed by the cascading of wavelet transform and data-driven tight frame (DDTF) dictionaries. The wavelet transform compensates for the drawbacks introduced by DDTF, such as the introduction of new noise, while DDTF addresses the challenge of adaptive sparse representation of noise encountered by wavelet transform. Experimental results demonstrate that our proposed method achieves more precise denoising results compared to conventional sparse representation methods.
Research on Automatic Identification of Drainage Network Defects based on Transformer and CNN
Authors: Sun Quan , Yin Hongyi , Guo Linsong , Zeng Zhaocai , Xiong Youliang 
Published: December 2024

Abstract
In order to achieve the governance of urban water environment systems and ensure the normal operation of urban drainage systems, it is necessary to regularly inspect the drainage pipe network to detect and identify defects. Traditional methods of manually identifying defects in Close Circuit Television (CCTV) data and annotating them are labor-intensive and inefficient. To address this issue, a method for automatic identification of pipe network defects based on convolutional neural network (CNN) and transformer is proposed. The model is named RFCBAM-CGA-RTDETR and has been applied to detect 13 types of pipe network defects. Experimental results indicate an evaluation accuracy of 61.8%, demonstrating its effectiveness and reliability. This model outperforms RT-DETR and YOLOv8 models by 6.6% and 10%, respectively, providing a novel approach for drainage pipe network defect detection.
USCNet: Seismic P-wave arrival time pickup based on deep learning
Authors: Xu Lei , Shen Tong , Jiang Xuan 
Published: December 2024

Abstract
The accurate pickup of seismic P-waves has important application value for real-time seismic data processing such as earthquake activity monitoring and earthquake disaster warning. However, existing low signal-to-noise ratio seismic data pickup algorithms often face problems of low accuracy and poor robustness. To address these issues, we designed a seismic P-wave picking network called USCNet. This network combines the advantages of U-Net and SegNet networks. The U-Net network performs well in picking accuracy, but requires a large number of learning parameters; SegNet networks are trained with fewer learning parameters, but have lower picking accuracy. The USCNet network integrates the CBAM attention mechanism, which can deeply extract key information from seismic data, thereby significantly improving the picking accuracy. We use the Stanford Earthquake Dataset (STEAD) as the data source. The experimental results show that USCNet performs significantly better than U-Net and SegNet networks on this dataset, with significant improvements in metrics such as Mean (μ), Variance (δ), Precision (P), and Recall (R), as well as significantly improved picking performance.
A new inversion scheme for time-lapse electrical resistivity tomography based on a full-gradient Jacobian matrix
Authors: Yan Jiahe , Zeng Zhaofa , Zhou Shuai , Zhao Jianwei 
Published: December 2024

Abstract
Time-lapse electrical resistivity tomography (ERT) has been proved to be a useful method for monitoring subsurface changes. Four-dimensional (4D) inversion scheme is one of the most common inversion schemes used to obtain subsurface resistivity at different moments. However, it uses the cross-time term to regulate the models at neighbouring moments and still needs to be improved. Therefore, we proposed a full-gradient difference (FGD) inversion scheme based on the 4D inversion scheme. The numerical experiment shows that the FGD inversion scheme has good imaging and anti-noise capability, which can be used in ERT monitoring.
Physical simulation study of fracturing monitoring of hot dry rock by borehole-surface electromagnetic method in frequency domain
Authors: Xiaoqiang Chen , Xiaoli Mi , Hui Cao 
Published: December 2024

Abstract
The Chinese mainland has abundant hot-dry-rock (HDR) resources. However, large-scale application is significantly challenged by the fracturing and stimulation of HDR reservoirs, making monitoring HDR fracturing essential. The borehole-surface electromagnetic method, which involves borehole excitation and surface collection of electromagnetic signals, captures stronger secondary field signals, aiding in assessing and guiding the fracturing effects in HDR reservoirs. Despite its potential, research on this method for HDR fracturing monitoring is limited. To explore and validate the effectiveness and mechanism of the frequency-domain borehole-surface electromagnetic method for HDR fracturing monitoring, this study conducts physical simulation experiments. The experiments use water to simulate HDR caprock, a mixture of water and sand for the HDR layer, and a graphite-cement anomaly model for the HDR fractured zone. Results indicate significant differences in electric field response amplitudes before fracturing, during fracturing, and after fracturing. When excited below and at the center of the anomaly model, the Ey response amplitude decreases with lower model resistivity, and when excited at the center, the Ey response amplitude similarly decreases with reduced resistivity. These findings demonstrate that the borehole-surface electromagnetic method effectively reflects changes in resistivity within the fracturing anomaly model, making it a suitable electromagnetic exploration method for monitoring HDR fracturing.
3-D inversion of gravity and magnetic data and its application in the study on the characteristics of magmatic rocks in the Yin’e Basin and adjacent areas
Authors: Weiheng Yuan , Xiaoqiang Chen , Chang’an Guo , Chutong Chen , Lingxiao Zhang 
Published: December 2024

Abstract
Magmatic rocks are crucial in studies of tectonic evolution and hydrocarbon generation and reservoir formation. To elucidate the distribution characteristics of subsurface rocks in the Yin’e Basin, the study utilizes the method of the weighted physical property inversion of random subdomains to conduct a three-dimensional inversion analysis of gravity and magnetic data. The findings indicate that magmatic rocks are predominantly located in the western and southeastern regions. Regional faults significantly influence the distribution of magnetic rocks in the Yin’e Basin. In the eastern part, magmatic rocks are generally larger and predominantly aligned in a northeast-southwest direction, whereas in the western part, they are oriented northwest-southeast, aligning with the tectonic framework of the study area. Intermediate-basic rocks are primarily distributed along fault belts and uplift zones, while acidic rocks are concentrated in depression zones. These results provide substantial insights into the distribution patterns of magmatic rocks and hold significant implications for oil and gas geological exploration in the Yin’e Basin.
Deep mantle evolution of the South China Sea and its interaction with surrounding subduction systems
Authors: Tian Hao , Zhou Zhiyuan , Lin Jian , Luo Yiming , Zhang Fan 
Published: December 2024

Abstract
As one of the largest marginal seas in the Western Pacific Ocean, the South China Sea (SCS) has garnered significant attention due to its origin and tectonic evolution. Nevertheless, our understanding of the deep mantle evolution in the SCS and its interaction with adjacent subduction systems remains limited. This paper examines the interaction between subduction zone systems within and around the SCS by combining geophysical observations with 3-D geodynamic simulations. The geophysical observations reveal multiple subduction zones surrounding the SCS, suggesting a close relationship between its tectonic evolution and these neighboring subduction systems. This study presents a comprehensive three-dimensional geodynamic model that illustrates mantle evolution in the SCS, showing how mantle upwelling in its northern regions is connected to nearby subduction systems. Overall, the findings from the geophysical observations and geodynamic simulations indicate that the surrounding subduction zones significantly influence the deep structure of the SCS.
Structure-guided impedance inversion based on MTV regularization
Authors: Li Hao , Cui Yian , Wang Pu 
Published: December 2024

Abstract
Seismic impedance inversion is a reliable technique for estimating subsurface rock attributes from poststack data. However, the efficacy of inversion results is often compromised by data noise, initial model, and model constraints. Traditional single trace inversions typically generate the inversion results with spatial discontinuities, especially when the noise level is high, due to the lack of geometric constraints. To enhance the imaging quality, we introduce the structural constraints into the modified total variation (MTV) regularization scheme, developing the Structure-Guided MTV (SGMTV) regularization inversion method. Numerical examples demonstrate that the proposed SGMTV inversion method can effectively reconstruct multitrace impedance parameters simultaneously, with enhanced structural features and less model noise.
The impact of grid partitioning on the convergence efficiency of tree-based Bayesian inversion
Authors: Tian Shengqi , Guo Rongwen , Liu Jianxin 
Published: December 2024

Abstract
Bayesian inversion commonly employs the rj-MCMC sampling algorithm for global search, but it is known for its low efficiency. To enhance sampling efficiency in multidimensional subspaces, advanced model parameterization methods are required. Hawkins proposed a tree-based model parameterization using wavelet basis functions, which leverages the tree structure to subdivide the subsurface model. This paper examines the impact of logarithmic interval subdivision of the subsurface and a combination of shallow uniform subdivision with deep logarithmic interval subdivision on sampling efficiency. The results indicate that the combined approach of shallow uniform subdivision and deep logarithmic interval subdivision leads to faster convergence in the inversion process.
Optimization of new energy control parameters based on the atomic orbital search algorithm
Authors: Cao Xiaoyu , Chen Yajie , Zhao Zhibin , Tian Xiaoyu , Jiao Chaoqun 
Published: December 2024

Abstract
In order to mitigate the issues of power angle stability and transient overvoltage resulting from the integration of large-scale new energy sources into the centralized grid and the introduction of high-voltage direct current into the delivery system, a novel control parameter optimization method based on the Atomic Orbital Search (AOS) algorithm is proposed. This paper analyzes the influence of key control parameters on power angle stability and transient overvoltage during new energy Low Voltage Ride Through LVRT, constructs an optimization model considering the power angle stability and transient voltage rise, and solves the problem by using the AOS algorithm. The results of a regional power grid simulation demonstrate that optimized new energy LVRT control parameters can effectively mitigate transient overvoltage at the delivery end system, thereby ensuring the safe of the AC and DC-sending power grid.