This study developed a geogas prospecting technology suitable for concealed sandstone-type uranium deposits in desert areas. This prospecting technology consisted primarily of three parts: A geogas information collection device and sampling method tailored to desert, a method for geogas information preprocessing using the detector and material composition tests, and a method for data processing and anomaly inference and interpretation. This technology was developed based on the mechanisms behind geogas material migration and utilized a desert-specific, dust pollution-resistant geogas material sampling device equipped with a detector made of low-background polyurethane foam. Through cumulative sampling for around 45 d, this technology can effectively capture the content of U, rare earths, and associated (paragenetic) elements in concealed sandstone-type uranium deposits within desert-covered exploration areas and delineate deep uranium enrichment zones, thus achieving the goal of ore prospecting. The world's first geogas exploration section for sandstone-type uranium deposits in a desert area has been completed in an exploration area in Xinjiang, demonstrating the effectiveness of the geogas prospecting technology developed in this study.

Experiments on prospecting for concealed sandstone-type uranium deposits using the dynamic geogas method were conducted in a gobi desert region by deploying a survey line in each known sandstone-type uranium deposit and uranium ore occurrence. The results indicate that the dynamic geogas sampling technology with adjustable efficiency detected geogas anomaly zones above all known concealed sandstone-type uranium deposits. These zones were characterized by multiple adjacent anomaly peaks composed primarily of uranium (U) and multiple associated (paragenetic) elements, with widths approaching those of the surface projections in a range from the ore bodies with a burial depth of approximately 50 m to the boundaries of the ore bodies' overturning ends. Therefore, the geogas anomaly zones and their widths serve as important ore-prospecting indicators for concealed sandstone-type uranium deposits. The relationships of captured geogas anomalies with factors such as the depths and grades of ore bodies in the experimental area confirm that the dynamic geogas method with adjustable efficiency can detect concealed sandstone-type uranium deposits at depths exceeding 756.4 m. The relationships also reveal that the amplitude of U geogas anomalies increases with the ore body grade and that the spacing between geogas detection points on the profile for sandstone-type uranium deposits should not exceed 50 m. The experiment corroborates that the geogas method is feasible and effective in detecting concealed sandstone-type uranium deposits in a gobi desert region.

The Weihe Basin boasts abundant helium resources.Vigorously exploiting these resources is significant for national development and social progress.However,the complex geographical and geological conditions in the basin pose great challenges in seismic image processing and interpretation,severely hindering the identification of helium-rich natural gas traps and reservoir prediction.This study delved into the difficulties and challenges in processing the seismic data from the Huazhou-Huayin area.Based on the seismic exploration objectives,an effective seismic data processing workflow was developed,along with targeted technical solutions,to address the difficulties in seismic data processing.The results of this study demonstrate that the quality of seismic data processing can be effectively improved using techniques,such as pseudo-3D tomographic static correction,global optimization residual static correction,multi-domain and multi-method serial denoising,multiple amplitude compensation and wavelet correction,and prestack time migration.These improvements provide critical technical support for the exploration and production of helium-rich natural gas in the exploration area,and valuable insights for seismic data processing for other regions within the basin.

To clarify the occurrence characteristics of geothermal resources in the Nangong geothermal field,this study revealed the subsurface strata and structures in the geothermal field using the magnetotelluric(MT) method in combination with drilling and geologic data.Furthermore,this study systematically analyzed the distributions of shallow and deep geothermal resources and elucidated the heat source mechanisms.Finally,this study constructed the geological model of the Nangong geothermal field.The results show that within a depth of 4000 m,the strata in the Nangong geothermal field comprise the Quaternary,Neogene,Paleogene,Permian,Carboniferous,Ordovician,and Cambrian strata from top to bottom.On the east side of the urban area of Nangong City, there are two concealed NE-trending normal faults(i.e.,F₁ and F₂),exhibiting a NW dip direction and steep dip angles.The fault-affected zone displays well-developed tectonic fractures and high water abundance.The Nangong geothermal field presents a dual geothermal reservoir system,comprising shallow porous sandstone reservoirs in the Neogene Minghuazhen(lower portion) and Guantao formations,and deep fissured-karstic bedrock reservoirs in the Paleozoic Cambrian-Ordovician strata.These reservoirs host significant geothermal resources in the Nangong area.The Nangong geothermal field belongs to a heat conduction-type geothermal system within a sedimentary basin.Specifically,the heat of shallow geothermal reservoirs(temperatures:30 ℃ to 63 ℃) is sourced from the vertical conduction of regionally high terrestrial heat flow,whereas the heat of deep geothermal reservoirs(temperatures:60 ℃ to 78 ℃) originates primarily from hydrothermal convection ascending through tectonic fractures along F₁ and F₂,and heat transfer from surrounding rocks.The geological model for geothermal reservoirs constructed in this study demonstrates that the deep fissured-karstic bedrock reservoirs in the Nangong geothermal field are characterized by high connectivity,deep circulation,considerable thickness,extensive karst fissure development,and high permeability.Therefore,deep geothermal reservoirs in the karst fissure zone along F₂ are recommended for prioritized exploitation.

The Jinchanshan gold deposit, identified as a magmatic-hydrothermal vein-type gold deposit associated with Yanshanian magmatism, is located in the Chifeng-Chaoyang gold ore concentration area within Harqin Banner, Inner Mongolia. The ore bodies in the deposit primarily occur in the fault structural zone of the Anjiayingzi pluton. This study conducted a systematic analysis of the structural superimposed halo anomalies of the Dawa and Limazigou ore sections from south to north in the eastern mineralized zone in the Jinchanshan gold deposit. Results indicate that the axial zoning and characteristic parameters of primary haloes in Jinchanshan gold deposit differ from the typical high-, medium-, and low-temperature element axial zoning sequence in hydrothermal deposits. The overlapping of high-temperature and low-temperature elements, suggests multi-stage and multi-phase mineralization processes. For the first time, this study analyzed the correlation between elements using element correlation curves at varying elevations. F and Ba were identified as front halo elements, Au, Cu, and Ag as near-ore halo elements, and Co, Ti, and V as tail halo elements. By establishing a structural superimposed halo model, this study determined prospecting target areas. Mining validation indicates that the identified ore-discovery middle section aligns with the predicted target area.

Compared to shallow coal seams, deep coal seams have gradually transitioned into a complex geologic environment characterized by high temperatures, pressures, and in situ stresses, and low permeability. Temperature and other conditions result in enhanced negative adsorption effects, leading to free gas production. Free gas saturation serves as a typical parameter for predicting reserves and guiding the optimal design of production and drainage plans, rendering its accurate determination highly significant. This study investigated the coalbed methane in the Jurassic Kezilenuer Formation in the tectonic zone north of the Kuqa depression within the Tarim Basin. It calculated the free gas saturation in the target layer based on adsorption isotherms, field analysis, inversion, the element-modified bulk modulus method, and the Archie, Gassmann-Wood, and Gassmann-Brie equations. Furthermore, it comparatively analyzed the results derived from these calculation methods combined with two-dimensional nuclear magnetic resonance data. The results indicate that the element-modified bulk modulus method and the Gassmann-Wood and Gassmann-Brie equations are more appropriate calculation methods for the study area. Overall, the results of this study provide a valuable reference for calculating free gas saturation in deep coal seams in the study area, further guiding and advancing the exploration and production of deep coalbed methane.

This study aims to determine the development of dissolution pores and fractures in the target bedrock reservoir space in the Kun 2 block in the Kunteyi gas field within the Qaidam Basin. The seismic data were classified into 12 attributes in five major categories for fracture prediction and comparative analysis of bedrock reservoirs. The results show that the maximum likelihood attribute aligned highly with the well data, with high vertical and horizontal resolution, superior to curvature, coherence, discontinuity, and similarity attributes. Moreover, the favorable areas for the distribution of bedrock reservoirs were effectively predicted using the dissolution pore-fracture overlay analysis method, providing a basis for subsequent exploitation well deployment.

With the wide application of oil-based drilling fluids in the Xihu Sag, the log response characteristics of reservoirs have changed. This increases the difficulty in identifying complex fluids, rendering fluid assessment methods based on water-based drilling fluids unapplicable. Therefore, this study developed a complex fluid identification method suitable for oil-based drilling fluids based on differences in the gas logging composition, the geochemical characteristic parameters of light hydrocarbons, and spectral morphologies between condensate gas and light oil reservoirs. The results are as follows: (1) Based on the data processing and the selection of optimal sensitive parameters, Pearson correlation analysis was conducted on 10 gas logging-derived parameters. Then, chart boards were developed using sensitive parameters Hc and Hb, allowing for qualitative distinguishment between condensate gas and light oil; (2) Through the fitting of Hc, the parameter with the highest correlation with the gas/oil ratio, to the pump sampling and stratigraphic test data, this study established a quantitative calculation model for the gas/oil ratio, yielding a correlation coefficient exceeding 0.98. Therefore, the model can be used to quantitatively predict the gas/oil ratio while drilling; (3) Significant differences can be observed in the morphological characteristics of geochemical light hydrocarbon spectra between condensate gas and light oil reservoirs. Specifically, the condensate gas reservoirs exhibited high nC1 to nC4 contents, an absence of normal alkanes beyond nC5, and incomplete and low peaks of iso-alkane and aromatic hydrocarbons due to small detection ranges. In contrast, the light oil reservoirs displayed complete n-alkanes components from nC1 to nC9, along with higher peaks of iso-alkanes and aromatics hydrocarbons. (4) Based on the differences in light hydrocarbon ratios between condensate gas and light oil reservoirs, gas index Ig and oil index Io were selected to establish chart boards, which can effectively distinguish both fluids. The combination of gas logging and geochemical light hydrocarbon analysis can effectively overcome the challenge of fluid identification under the condition of oil-based drilling fluids in the Xihu Sag, deserving wide application.

This study conducted a profile spectrum survey in the southern Anhui Province using a portable gamma-ray spectrometer. Based on the differences in types and quantities of natural radioactive elements present in geological bodies, this study compared the stack plots of the characteristic parameters of U, Th, and K with geologic-topographic maps to further delineate the occurrence locations of ore bodies. Additionally, this study investigated the applicability of gamma-ray spectra to the exploration of fluorite deposits and provided empirical suggestions for parameter surveys and anomaly determination. The experimental results indicate that gamma-ray energy spectroscopy applies the exploration of fluorite minerals. Notably, Th can be used as a primary indicator, exhibiting low-amplitude anomalies, which correspond well with ore bodies. Besides, this element is applicable to other surrounding rock conditions. The analysis and verification from the perspective of environmental protection revealed that the gamma-ray radiation dose rates induced by fluorite vein ore bodies are far lower than their background values and can be used as a preliminary basis for ore prospecting.

Ground resistance is a significant factor affecting the accuracy of audio-frequency magnetotelluric (AMT) measurements. Hence, reducing the interference from ground resistance is critical for enhancing the reliability and interpretation accuracy of AMT data. By delving into the impacts of ground resistance on the measured electric field, apparent resistivity, and impedance phase, this study proposed a numerical correction method for reducing the impacts of ground resistance to a negligible level. As indicated by the theoretical calculation results, too high ground resistance can reduce the apparent resistivity in high-frequency bands to a quarter of the original value and shift the impedance phase by a maximum of 20°. The correction results of measured data demonstrate that the proposed method can enhance the accuracy of the AMT method in detecting shallow information by effectively reducing the interference from ground resistance. Therefore, this study holds critical significance for improving the application of the AMT method in engineering exploration.

The ratio of compressional to shear wave velocities(hereafter referred to as the P-to-S-wave velocity ratio) is an essential parameter for lithology discrimination,reservoir characterization,and gas reservoir identification.Direct inversion of PP-wave seismic data to derive the P- and S-wave velocities has been a well-established technique.However,calculating the P-to-S-wave velocity ratio using the P- and S-wave velocities obtained through individual inversion may lead to cumulative errors.In contrast,since PS-wave data inherently contain S-wave velocity information,the joint inversion of PS-wave data can significantly improve the accuracy of the P-to-S-wave velocity ratio.This study employed the L_1-2 norm to enhance the resolution of inversion results.Compared to the L₁ and L₂ norms,the L_1-2 norm yielded sparser solutions with higher resolution.First,this study derived and assessed the accuracy of linearized forward modeling approximate formulas for PP- and PS-waves.Second,based on Bayesian theory,this study incorporated the L_1-2 norm to construct an objective function for the direct inversion of the P-to-S-wave velocity ratio.Third,the objective function was solved to obtain the inversion result for the P-to-S-wave velocity ratio.The quantitative comparison of the correlation coefficients demonstrates that the inversion results based on the L_1-2 norm outperform those based on the L₁ or L₂ norm,direct inversion is superior to indirect inversion,and joint inversion provides better results than individual inversion.Finally, the effectiveness and feasibility of the proposed method in this study were validated through inversions of synthetic and field data.

Three-dimensional (3D) geological modeling is regarded as an effective technical method for locating deep-seated minerals. However, its application in deep metallogenic prediction of sandstone-type uranium deposits remains limited. Focusing on the Hadatu-Saihan Gaobi area in the Erlian Basin, this study developed a 3D geological model for deep metallogenic prediction by integrating geological, geophysical, and remote sensing data. Given the characteristics of multivariate geoscience information, this study proposed a layered 3D implicit modeling method. Specifically, for modeling at depths less than 1 000 m, geological and drilling data, along with ground electromagnetic survey results, were primarily used. In contrast, for modeling at depths exceeding 1 000 m, the results from 3D joint gravity and magnetic inversion were utilized. The resulting 3D geological model reveals that primary strata in the study area include the Neogene-Paleogene, Lower Cretaceous, Permian, Carboniferous, and Neoproterozoic strata, with prominent rock masses comprising granites and intermediate-basic rocks. The elevated and slightly elevated fields of aeroradiometric uranium content around the known uranium deposit are associated with the migration, deposition, and enrichment of uranium-bearing materials, as well as fault-related tectonic movements. Through three-dimensional metallogenic prediction based on metallogenic condition analysis, three metallogenic prospect areas with geological characteristics similar to the known uranium deposit were identified. This study provides a novel philosophy for the interpretation of aeroradiometric data and the exploration of deep uranium deposits in basins.

Since no targeted seismic inversion techniques are available for the prediction of complex sandstone-mudstone reservoirs, conventional inversion methods struggle to provide accurate sand body predictions in the presence of sandstone-mudstone interbeds or horizontal fractures. Hence, this study selected Poisson's impedance as the sensitive parameter for reservoir prediction based on the petrophysical parameter cross plots using log data from the study area. Considering the characteristics of fracture development in the reservoirs, this study derived the equation of anisotropic reflection coefficients in vertical transverse isotropy (VTI) media, incorporating Poisson's impedance. Furthermore, this study designed a forward modeling operator using a non-stationary convolution model to improve the strong attenuation characteristics of seismic waves generated by sandstone-mudstone interbeds and protect the reflection characteristics of deep thin reservoirs. Finally, this study proposed a high-resolution direct inversion of Poisson's impedance and fracture parameters using prestack seismic anisotropy data, providing a novel approach for high-resolution characterization of the distribution of sandstone-mudstone reservoirs and the assessment of fracture-bearing properties. Both model and field data tests validate the feasibility and adaptability of the proposed method.

Multisource technology has significantly improved the acquisition efficiency of seismic data.However,the acquired data often suffer from severe aliasing and channel missing,necessitating effective reconstruction of missing channels during data separation.Since an individual separation and reconstruction algorithm cannot improve accuracy and computational efficiency simultaneously,this study proposed a method combining the iterative shrinkage-thresholding algorithm(ISTA) and the accelerated linearized Bregman method(ALBM) to leverage ISTA's high post-processing accuracy and ALBM's fast convergence speed for simultaneous separation and reconstruction of multisource data.The simultaneous separation and reconstruction process employed curvelet transform(as a sparse basis),hard threshold function,exponential threshold and acceleration factors,and a novel exponential weighting factor.Finally,the single-source data were separated and reconstructed.The results obtained from the combined method were compared with those obtained using ISTA and ALBM,respectively.Additionally,the noise robustness and denoising capability of the combined method were examined.Both theoretical simulation and practical application demonstrate that the combined method achieves higher accuracy and faster computational efficiency in separating and reconstructing complete single-source signals.

Supervised deep learning inversion relies on labels of subsurface media for training. However, the measured data from electrical resistivity tomography usually lack such labels. Supervised learning based on significant synthetic data generated through forward modeling fails to obtain reliable inversion results for complex data outside the training set. This study proposed a semi-supervised learning inversion method based on forward modeling constraints, combining with labeled and unlabeled data for training, to enhance the inversion accuracy and the capability to characterize complex geological structures. The inversion results of synthetic data demonstrate the strong generalization capability of the proposed method. The inversion results of measured data indicate that compared to conventional least-squares inversion, semi-supervised inversion provides higher resolution and particularly more accurate characterization of vertical lithological boundaries. Overall, the proposed method offers a novel approach for the inversion of the data derived from high-resolution electrical resistivity tomography.

The resistive and capacitive properties of induced polarization(IP) medium can be characterized by complex resistivity parameters that vary with frequency. To accurately and efficiently simulate the electromagnetic responses of IP media when excited by artificial sources, this study establishes a three-dimensional forward modeling framework for complex resistivity method based on the frequency-domain Maxwell's equations. The equation takes into account the impact of electromagnetic effects and is discretized using the staggered grid finite difference method. The complex globally convergent quasi-minimum residual (QMR) method is employed to solve the discretized complex linear equation system. Initially, the accuracy of the calculations is verified through a semi-analytical solution of a simple layered model. Then, Models of large-scale and deep-seated metal ore deposits and smaller-scale and shallow-buried organic matter leakage are then established, and the electric field responses of the two induced polarization models are computed at low frequency (1 Hz), medium frequency (10 Hz), and high frequency (100 Hz). The results at different frequencies for both models indicate rapid convergence of the residual norms with iteration numbers, validating the applicability and effectiveness of the algorithm. Finally, based on the computational results, the influence of capacitive characteristics of the induced polarization medium on the electric field amplitude and phase is analyzed. It is concluded that capacitive characteristics have a minimal impact on the electric field amplitude but a significant effect on the phase, and the stronger the induced polarization effect, the more pronounced the impact on the phase.

The ground-airborne frequency-domain electromagnetic (GAFDEM) method exhibits high efficiency and low cost compared to conventional ground electromagnetic methods. It is applicable to electromagnetic sounding in complex topographic and geomorphic settings, demonstrating promising application potential. Despite the development and preliminary application of GAFDEM-related instrumentation and equipment, the interpretation methods for GAFDEM data remain under-studied. By investigating the resistivity-varying patterns of three components of the magnetic field in a homogeneous half-space, this study proposed an iterative method based on Taylor series expansion to calculate the global apparent resistivity. Through the calculation of a typical stratigraphic model, this study analyzed the characteristics of global apparent resistivity under different components, frequency domains, flight altitudes, and offsets. The results demonstrate that the definition method of global apparent resistivity in this study, subjected to minimal impacts from parameters like receiver-transmitter distance and flight altitude, can effectively reflect the variations of formation resistivity. Therefore, this study provides a theoretical guide for the processing and interpretation of GAFDEM data.

This study aims to investigate the geochemical background and baseline values of heavy metals in soils in the Xiangjiang River basin. Focusing on nine indicators, i.e., As, Cd, Cr, Cu, Hg, Pb, Zn, Ni, and pH, in both surface and subsurface soils and using methods such as iterative calculations, boxplot-based outlier removal, and content-area fractal analysis, this study investigated the background values in the soil environment within the basin' areas where multi-target geochemical survey had been conducted. Accordingly, the study discussed the factors influencing the geochemical background and baseline values of various stratigraphic units and soil types. The results indicate minimal differences in the results derived using these calculation methods. All methods consistently indicate that the background values of eight heavy metals exceed national averages, with those of Hg and Cd approaching twice the national background levels. This suggests that the Xiangjiang River basin has high geochemical background values of Hg and Cd. The background values of heavy metals in soils within the basin are closely related to parent rock types, with element enrichment levels and the number of elements enriched in soils generally increasing with a decrease in the age of strata, specifically for Cd. Across different soil types within the Xiangjiang River Basin, the geochemical background values of heavy metals are generally higher than their baseline values.The research results of this study provide an important basis for the ecological environment assessment and land planning of the Xiangjiang River Basin.

Maqin County, an important county of animal husbandry in Qinghai Province, hosts more than 13 million mu of naturally available grassland and rich forage resources. In 2022, a 1∶250 000 land (grassland) quality geochemical survey was carried out in the eastern part of Maqin County. This survey represents the first large-scale land quality survey of grassland in the Qingnan region of Qinghai Province, setting a model exemplary role. Based on nutrient content in plants from the surface soil in the survey area, this study assessed the abundance and deficiency of various nutrient elements. The results indicate that soils in the survey area are dominated by first- and second-grade soils in terms of comprehensive geochemical grades of soil nutrients, accounting for 91.68% of the total area. In contrast, third- and fourth-grade soils collectively represent 8.33%, with no fifth-grade soils identified. The generally rich nutrients in the soils provide a solid foundation for the development of plateau-specific agriculture and animal husbandry. The results of this study provide essential foundational information for the planning and utilization of local grasslands, the development of agriculture and animal husbandry with local features, and the restoration of degraded pastures.

It shows that atmospheric deposition is one of the main sources of soil heavy metal pollution. In order to find out the effects of atmospheric wet and dry deposition on farmland soil, the accumulation of heavy metals in farmland soil was analysed by monitoring the dry and wet deposition in the study area and testing the heavy metal content, estimating the dry and wet deposition flux, heavy metal change rate and potential ecological risk assessment. The results showed that the heavy metal content of dry and wet sediment exceeded the content of Cd, Pb and Zn in the surrounding soil, and Cd and Zn exceeded the soil pollution screening value of agricultural land by 2.25 times and 1.09 times;The annual flux of heavy metal elements in the dry and wet precipitation of the atmosphere is smaller than the national average, and the sedimentation flux order is Zn>Cr>Pb>Cu>Ni>As>Cd>Hg, the annual sedimentation flux of Zn is the highest, and the sedimentation flux of Cd is low. The geo-accumulation index showed that in the atmospheric dust, Cd reached extremely high pollution level, followed by Hg, Pb, there was no As and Ni pollution. The heavy metals with the most significant impact of atmospheric dry and wet sediment on soil were Cd and Zn, with an increase of 0.421 mg/kg and 104.653 mg/kg after one year, and the annual change rates reached 0.138% and 0.146%, which indicated that the atmospheric deposition was one of the most important sources of the heavy metal Cd and Zn in the farmland soil. The sedimentation flux of Cd is low, but its content exceeded the standard the most, and caused the most significant changes in the soil environment, which needs to be paid attention to.

Soils and water emerge as important natural resources for plant growth and development. Understanding the responses of vegetation to water and soil characteristics is crucial to the scientific management of agricultural production. However, there is a lack of studies on the quantification of coupling characteristics of these factors. To reveal the coupling characteristics and responses among water, soils, and vegetation, this study investigated the farming areas in Huachuan, Jixian, and Youyi counties in the hinterland of the Sanjiang Plain. Using a survey of vegetation and the analysis of soil and water samples, this study established an index system for the assessment of the water-soil-vegetation coupling. The weights of the assessment indices were determined using principal component analysis, and a water-soil-vegetation coupling coordination model was constructed for the farming areas. Additionally, the primary factors influencing plant growth were analyzed using gray correlation analysis. Results indicate that vegetation, water, and soils in the farming areas are strongly coupled. Primary factors influencing vegetation growth and development include soil bulk density; sand content; zinc, boron, and copper contents, and the calcium ion concentration and hardness of water bodies. Notably, the coupling coordination degree is not consistent with the coupling degree. Specifically, water, soils, and vegetation in the farming areas exhibit strong coupling, characterized mainly by sound coordination. In contrast, some areas of Huachuan and Jixian counties exhibit poor coupling among water, soils, and vegetation. This is primarily due to water pollution, soil texture, and deficiencies in trace elements. Therefore, it is necessary to improve the groundwater ecosystem and implement protective farming of cultivated land. The coupling model of water, soil and vegetation established in this paper provides and important basis for ecological environment protection and restoration.

This study focuses on the application of microwave-absorbing materials in the design of time-domain pulsed ground-penetrating radar(GPR) antennae.First,this study analyzed the propagation mechanisms of electromagnetic waves inside and at the medium interface of microwave-absorbing materials.Second,this study applied multi-layer foam composite microwave-absorbing materials to antennae in various loading configurations.Third,based on the CST electromagnetic simulation software,this study compared parameters like waveform fidelity,antenna gain,and voltage standing wave ratio(VSWR) for antennae with different loading configurations.Fourth,this study performed systematic modeling and simulation for the transmitting antenna,receiving antenna,stratified ground,and subsurface targets in combination with a real-world application scenario.By examining the characteristics of the target echo signal under various loading configurations for antennae,this study determined the optimal loading configuration of multi-layer foam composite microwave-absorbing materials for GPR antennae.Using the optimal loading configuration, this study designed and fabricated a flat dipole antenna with a shielding shell.Finally,this study conducted field tests using the LTD-2600 GPR with this flat dipole antenna on the ground surface and at an elevated position,clearly revealing abnormal stratigraphic signals at a depth of 5.6 m.Therefore,this study can effectively guide the design and engineering applications of GPR antennae.

Rapid,convenient,and reliable acquisition of shallow urban underground structures in densely populated areas with intense anthropogenic noise is significant for promoting the digital transparency and safe development of urban underground spaces.With the advancement of nodal seismometers,passive-source seismic imaging methods have been widely applied to image underground structures at various scales,successfully demonstrating the detection of shallow underground structures in urban underground spaces.Under the constraints imposed by urban roads and narrow spaces,linear dense arrays show high adaptability among various passive-source array deployment patterns.In a test area with known underground pipeline anomalies,this study designed three linear array arrangement patterns with spacings of 1 m,3 m,and 5 m for 1 h continuous observation of noise data.This study employed the extended spatial autocorrelation(ESPAC) method to extract surface-wave frequency dispersion data for shear-wave velocity inversion.Moreover,by comprehensively analyzing the raw data,frequency dispersion curves,and the shear-wave velocity profile obtained through inversion,this study provided a scientific understanding and basis for the parameter selection of the closely spaced linear dense array observation system for passive-source seismic detection of urban underground spaces.Finally,based on the experimental results,this study selected a scientifically reasonable observation system for detection in a real-world urban underground space construction and exploration project,revealing the complete stratigraphic structure and water-conducting structures like fracture zones at the construction area.Therefore,closely spaced linear dense arrays can yield higher resolution and accuracy in detecting urban underground spaces,showing higher adaptability in areas with severe anthropogenic interference.

The Dafengding tunnel is an extra-long deep tunnel in the seismically active mountainous region characterized by exceptionally complex geologic and hydrogeologic conditions in Southwest China. The primary challenges in the tunnel investigation arise from complex geological conditions and unfavorable exploration environments. Moreover, developing effective seismic mitigation measures necessitates precisely determining the fragmentation and water-bearing characteristics of rock masses at the tunnel site. Hence, based on the initial classification of regional lithologies using geologic data, this study conducted integrated geophysical exploration at the tunnel site by combining the audio-frequency magnetotelluric method with high-resolution electrical resistivity tomography. The results indicate that the integrated geophysical exploration effectively revealed the overall variation in apparent resistivity at the tunnel site and the shallow apparent resistivity distribution, particularly the characteristics of the electric field near the tunnel portal. These findings enabled the inference of the fragmentation and water-bearing characteristics of rock masses at the tunnel site. Moreover, the borehole data effectively validated the effectiveness of the integrated geophysical exploration, demonstrating that the integrated geophysical exploration can provide a valuable reference for the investigation and construction of extra-long deep tunnels in seismically active regions.