The artificial source electromagnetic method is an important technique for deep resource exploration. The key challenge is to improve the depth and precision of detection through innovative technology. The detection mode of electromagnetic methods is evolving from far-field to near-field, and the study of near-source electromagnetic methods has become an international research frontier in recent years. Building on the recent advancements in wide-field electromagnetic methods and multi-channel transient electromagnetic methods, the short-offset transient electromagnetic method (SOTEM) has been further developed and proposed. The distinguishing features of SOTEM are its stronger signals and wider bandwidth, which are advantageous for achieving the detection requirements of greater depth and higher precision. This special issue presents eight articles covering the methods, techniques, software, and applications of SOTEM, providing strong support for the growing need for high-resolution subsurface detection.

The grounded-source short-offset transient electromagnetic (SOTEM) method involves many parameters in field data acquisition. The selection of these parameters is closely associated with the signal quality and detection sensitivity of measured data. Based on the relevant provisions in the organization standard, Technical specification for grounded-source short-offset transient electromagnetic method (T/CGS 002—2021), issued by the Chinese Geophysical Society, numerical emulations, and practical cases, this study analyzed and expounded the selection criteria of critical parameters like transmitting source length, transmitting fundamental frequency, offset, device type, and observation component. The insights obtained in this study are significant for guiding the field construction of the SOTEM device and leveraging its detection performance.

This study performed forward modeling for the short-offset transient electromagnetic (SOTEM) responses of a three-dimensional geoelectric model using the three-dimensional finite-difference time-domain method. The results reveal that: (1) The attenuation curves of the E_x responses from the electric field above the goaf or collapse column were above the background response curve at early times but below it at later times; (2) A shorter offset corresponded to a higher relative anomaly of ∂B_z/∂t response signals. Increasing the length of the transmitting source could enhance the signal intensity while slightly decreasing the relative anomaly; (3) In the case of survey lines close to the transmitting source, the overall ∂B_z/∂t responses of the goaf or collapse column were weaker than the background responses. For survey lines away from the transmitting source, the overall ∂B_z/∂t responses of the goaf or collapse column were stronger than the background responses. In summary, the calculation results demonstrate significant implications for understanding the ability of the SOTEM method to detect typical water-rich bodies in coal mines, laying a theoretical foundation for the parameter selection of SOTEM devices and their generalized application in the coal sector.

Owing to the successful application of grounded-source in recent years, roadway detection using the grounded-source transient electromagnetic (TEM) method has attracted significant academic interest. Using the three-dimensional finite-difference time-domain (FDTD) method, this study simulated the grounded-source TEM responses of the anomalies in the roadway floors and between roadways. The simulation results are as follows: (1) For anomalies in the roadway floors, their surfaces show violent changes in the horizontal and vertical components of the electric field subjected to the surface charge of anomalies. The horizontal electric field exhibits a strong ability to discriminate low-resistivity bodies but a weak ability to discriminate high-resistivity bodies. The vertical electric field displays opposite response signs from the low- and high-resistivity bodies. The low- and high-resistivity bodies correspond to opposite ∂B_y/∂t responses in the early and late stages. Specifically, the response signs are negative in the early stage and positive in the late stage for low-resistivity bodies, whereas the results are contrary for high-resistivity bodies; (2) For anomalies between roadways, the horizontal electric field also exhibits a strong ability to discriminate low-resistivity bodies but a weak ability to discriminate high-resistivity bodies. The ∂B_z/∂t response curves are above the background curves in the model of high-resistivity bodies but below the background curves in the model of low-resistivity bodies, suggesting the discrimination ability of the ∂B_z/∂t response for both low- and high-resistivity bodies.

The transform from transient electromagnetic (TEM) field to pseudo wavefield is the basis for using the imaging technique. The TEM field follows the diffusion equation, while the pseudo wavefield follows the wave equation. These two can be transformed into each other via the Q-transform. As the integral transformation from TEM field to pseudo wavefield is ill-posed, numerical method is used to get the desired pseudo wavefield. As a result, it is often the case that the methods and parameters are need to be optimized to get a optimal pseudo wavefield. Therefore, here in this paper, we derived the analytical solution of the pseudo wavefield from the TEM field. We start from the analytical formula of TEM field, and utilize the Laplace transform to establish the analytical solution pairs. The pairs can be used to test the accuracy and stability of the numerical method, as well as examining the features of the pseudo wavefield to get an effective imaging method.

The short-offset transient electromagnetic (SOTEM) data are typically processed using conventional inversion methods based on physical modeling, manifesting relatively low efficiency and difficulty in integrating priori information. In contrast, the data-driven inversion methods can enhance the inversion accuracy and efficiency but fail to ensure the generalization capability. To achieve high inversion accuracy and efficiency for SOTEM data and a reliable generalization capability, this study proposed an inversion method that integrates physical modeling with the data-driven approach, introducing the supervised descent method in machine learning into SOTEM data inversion. The proposed inversion method involves the offline training and online prediction stages. In the offline training stage, the prior information is flexibly integrated into the model training through a reasonable training dataset to obtain the average descent directions with implicit model features. In the online prediction stage, the physical modeling functions and the descent directions are employed to reconstruct the model parameters under the conventional inversion framework. In this study, the layered geodetic model was applied to design the training and test datasets for the 1D inversion of SOTEM data based on the supervised descent method. The inversion results were compared with those obtained using Occam's inversion algorithm, demonstrating that the proposed inversion method shows significantly enhanced inversion efficiency, higher inversion accuracy, and higher generalization capability.

Within a coal mine in Peixian County, Xuzhou City, brick-red Paleogene and Neogene strata were deposited in the faulted basin during the Cenozoic, with extensive Quaternary strata overlying various strata. The Quaternary, Jurassic, and Cretaceous strata exhibit thick overburden, up to over 500 m. This study explored the coal mine using the short-offset transient electromagnetic (SOTEM) method. Based on geoelectric conditions, reasonable observation parameters were designed to obtain the subterranean electric structure within a burial depth of 1500 m. Goafs were detected at a burial depth of 900 m, with their delineated boundaries aligning with the mining situation of the coal mine. The results of this study serve as a reference for detecting goafs with thick overburden in North China-type coalfields.

Tunnel detection in complex environments requires fine-scale detection of small unfavorable geobodies like karst caves and fissures. Hence, this study designed a tunnel construction model with a small karst cave in front of the tunnel face. A borehole was drilled at the center point of the tunnel face towards the construction direction, and then an electrical source was put into the borehole for excitation. Array data acquisition was conducted on the tunnel face. The 3D forward modeling based on transient electromagnetic data was performed using the time-domain finite element method. As indicated by the results, the electromagnetic sounding of the target was achieved through the movement of the electrical source, and the planar position of the unfavorable geobody was determined based on the distribution patterns of the electromagnetic field on the tunnel face. Therefore, electrical source excitation in a borehole can enhance the detection ability of the transient electromagnetic method on small karst caves, serving as a feasible method for improving the accuracy of tunnel seismic prediction.

Several thermal springs associated with tectonic activity occur along the Chuhe fault zone. Except for the Bantang thermal spring at the southern end, other springs along the fault zone exhibit unideal utilization of thermal energy. This affects the development of local industries. Therefore, it is necessary to delve into the geochemical characteristics and formation mechanism of typical thermal springs along the Chuhe fault zone. The purpose is to provide scientific evidence for the rational utilization and exploration methods of geothermal resources in the thermal spring groups in the future. Therefore, this study investigated thermal springs in the Bantang, Zhaoguan, and Xiangquan areas along the Chuhe fault zone, where nine samples of thermal spring water, cold well water, and surface water were collected individually. For these samples, the composition tests of 25 indices, including anions, cations, and major and trace elements, were tested, and the hydrogen and oxygen isotope values were determined. The analyses of the 25 measured indices, along with the investigation of the geothermal water source and controlling factors through hydrogen and oxygen isotope tracing, indicate that the thermal spring water in the three areas tends to be of the CaSO₄ type and is all closely related to the interactions between groundwater and surrounding rocks. The thermal spring water, cold well water, and surface water in Bantang and Zhaoguan show consanguinity, with geothermal water being directly recharged with local precipitation and surface water. In contrast, the thermal spring water, surface water, and cold well water in the Xiangquan area show weaker consanguinity, indicating different sources for the underground cold water runoff and geothermal water. This should be noted when determining the primary factors controlling the thermal spring in this area. The temperatures calculated using a chalcedony geothermometer were close to the temperatures of the hot water recovered on the surface. In contrast, the temperatures calculated using a quartz geothermometer approached the temperatures of deep geothermal reservoirs. The results of this study preliminarily reveal the geochemical characteristics, recharge relationships, and water-rock interactions of thermal spring water in the Chuhe fault zone and propose effective geochemical geothermometers for the study area. These contribute to deeper insights into the mechanisms and controlling factors of the thermal springs along the fault zone, as well as providing practical value and a methodological model for enhancing thermal spring functionality and geothermal resource exploitation and utilization in the future.

Over recent years, large-scale geochemical surveys on a scale of 1:25,000 have been conducted in the eastern Kunlun region for geological prospecting. These surveys, characterized by the rapid and accurate location of anomaly sources, have been widely applied in mineral explorations, yielding encouraging mineral prospecting results. Using 1:25,000-scale stream sediment surveys, this study delineated 12 geochemical integrated anomalies of the element associations of Cu, Co, and Ni in the Hedong area, Mangya City, eastern Kunlun. These anomalies include one integrated anomaly dominated by Co, where various element anomalies exhibit high-degree overlap, relatively large scales, high intensity, and distinct concentration zoning. The Co anomaly is closely associated with the Ordovician Qimantag Group, demonstrating a high degree of spatial consistency. The subsequent anomaly verification reveals four cobalt mineralized zones within anomalies GA16, GA26, GA11, and GA39, with three ore bodies and multiple mineralized bodies of cobalt being identified within the mineralized zones. The comprehensive analysis indicates that the eastern Kunlun region enjoys excellent metallogenic geological conditions and favorable geochemical characteristics, with promising prospecting results having been achieved. Therefore, this region has the prospecting potential of medium to large-scale cobalt deposits.

The gold ore zone in the Daduhe area of Shimian County, Sichuan Province, is located in the rare metal-precious metal-nonferrous polymetal metallogenic belt in the southern segment of the Songpan-Ganzi orogenic belt. It exhibits complex structures and steep terrains, severely restricting prospecting and exploration. Based on the geological settings, conditions, and geophysical characteristics for regional mineralization, this study investigated the typical Luoluoping gold deposit in Shimian by conducting deep geophysical exploration centered on audio-frequency magnetotellurics (AMT). Three low-resistivity anomalies (M1, M2, and M3) were identified, corresponding to the mineralized alteration zone I, the gold mineralization zone III, and the gold-copper ore body, respectively, demonstrating the effectiveness and applicability of geophysical methods for deep prospecting. Combined with geological understanding and engineering verification, this study summarized geological and geophysical prospecting markers for the typical gold deposit, establishing the geological-geophysical prospecting model for the gold ore zone in the study area. Therefore, this study provides technical support for deep prospecting in the study area.

The successful operation of geothermal wells on the eastern margin of the Yinchuan Basin suggests a new geothermal exploration orientation around the Huanghe fault and its secondary faults. To further investigate the controlling effect of the Huanghe fault on geothermal resources in the study area and pinpoint the exploration target, this study arranged four magnetotelluric (MT) lines, obtaining 71 survey points.The preprocessing and two-dimensional inversion of MT data yielded a two-dimensional electrical structure of the study area within a depth of 10 km.Based on the previous geological, gravity, microtremor, and controllable source audio magnetotellurics(CSAMT) data in the study area, this study further interpreted the strata and fault structures of the study area.It posited that the relatively-low-resistivity zone within the high-resistivity zone of the Ordovician basement reflected by the MT lines may be the secondary-fault development site at the rear edge of the Huanghe fault, which is caused by the fragmentation and water filling of Ordovician strata, showing certain exploration potential for geothermal resources.

In response to the need for large-scale exploration of radioactive minerals in high-relief areas, this study developed an airborne gamma-ray spectrometer based on small-sized NaI (Tl) crystals, which was integrated with the F-120 unmanned aerial vehicle (UAV) to form an airborne gamma-ray spectrometry (AGRS) system. The UAV-AGRS system was applied to the follow-up geochemical survey of uranium deposits in a certain area of South China. The survey results show roughly consistent locations and morphologies for high-anomaly zones with the ground gamma-ray spectrometry results. Moreover, the results of this study exhibit more detailed anomaly morphologies, and more significant responses of uranium content-related uranium channel data to known uranium occurrences in the study area, suggesting superior data. Therefore, the UAV-AGRS system shows promising potential as an effective alternative to ground gamma-ray spectrometry for the follow-up geochemical survey of uranium deposits in high-relief areas.

The Mianning-Dechang rare earth element (REE) metallogenic belt exhibits considerable resource potential. Previous prospecting was oriented to hard-rock REE deposits associated with Himalayan alkaline complexes, with ion adsorption-type REE deposits under-studied. To explore the mineralization prospect of granite weathering crusts widespread in the metallogenic belt, this study investigated the Shizishan area through multi-channel gamma-ray spectrometry, soil profile survey, and shallow drilling. One ion adsorption-type REE ore occurrence was identified in the granite weathering crust at Mosuoying. This study analyzed the radioactive response of the geological, geophysical, and geochemical profiles and ore contents, finding that the elemental contents of thorium (Th) and potassium (K) were highly indicative of REE and rare metal mineralization. Highly mineralized, industrial-scale ion adsorption-type REE deposits will likely occur when 6.25<w(Th)/w(K)<10, w(eTh)>37×10^-6, and w(eK)>4.2%. As revealed by the analysis of the response of radioactive anomalies to supergene weathering, thorium anomaly halos can effectively indicate granitic plutons while potassium anomaly halos can well delineate the extent of granite weathering crusts.

Magnetotelluric (MT) data collected from offshore areas are generally distorted due to coastal effects, posing challenges in obtaining true subterranean electrical structures. Based on the model of half-space with seawater, 2D electrical isotropy and anisotropy models, and 3D electrical isotropy model, this study analyzed the distortion patterns of MT responses under coastal effects through forward modeling. Moreover, it conducted 2D and 3D inversions of MT data with or without seawater constraints. Key findings are as follows: (1) The initial frequency points of distortion in MT apparent resistivity curves are closely correlated to the distances from survey points to seawater; (2) Compared to MT responses free from coastal effects, the high-frequency sections exhibit increased amplitudes in real induction vectors only at survey points in offshore areas and higher phase tensor ellipticity, whereas the low-frequency sections display expanded influence areas subjected to coastal effects; (3) Excluding seawater constraints, the inversion results show false anomalies in offshore areas and poor reconstruction effects on subsurface anomalies. Considering seawater constraints, the constrained inversion can effectively suppress the distortion caused by coastal effects. Overall, this study will provide a significant reference for the collection, processing, and interpretation of MT data from offshore areas.

A strong shielding layer exists between Neogene and Meso-Paleozoic strata in the South Yellow Sea Basin,hindering the downward propagation of seismic wave energy.Consequently,reflected seismic waves in deep strata manifest low energy and poor wave group characteristics,severely constraining the oil and gas exploration in Meso-Paleozoic strata.To enhance the imaging quality of Meso-Paleozoic strata under the strong shielding layer,this study proposed a method for designing a high-energy airgun source rich in low-frequency components through extensive simulation analyses at the excitation end of the source.Finally,a 6050 in³ high-energy airgun source rich in low-frequency components was designed and applied to the streamer-based seismic data acquisition in the extremely shallow water area in the western Laoshan uplift.The seismic data acquired in the deep strata under the strong shielding layer demonstrate significantly improved quality,exhibiting a higher signal-to-noise ratio,more continuous seismic events,and clearer structural characteristics.

Prolonged intense magmatic-hydrothermal activity and regional metamorphism in western Hubei Province created favorable conditions for the formation of gold deposits. As the Shuiyuesi area witnessed a thorough exploration of surface and outcrop mines, the prospecting of gold deposits in the area has shifted to overburden and deep zones in recent years. However, the prospecting in the Shuiyuesi area becomes gradually complicated due to significant topographic relief, high vegetation coverage, and severe terrain cutting. Hence, efficient prospecting approaches are urgently needed to achieve breakthroughs in ore prospecting. Through geological survey and analysis, this study statistically analyzed the alteration types intimately associated with gold mineralization in nine gold veins of the Shuiyuesi area. It extracted alteration information from Landsat8-OLI remote sensing images using methods like numerical operations, and weak anomaly information of element distribution using methods like multivariate statistical analysis and local singularity analysis. Employing the data integration technology, it integrated the alteration anomaly information from remote sensing images and the singularity anomaly information. Based on comprehensive information, such as geological settings for mineralization and metallogenic regularity, this study identified 19 metallogenic prospect areas and new anomaly clues in the Yangjiatang-Caishenmiao area. The novel approach combining singularity analysis and data integration enhanced the spatial resolution of geochemical anomalies, the spatial details of surface features, and weak anomaly information associated with gold mineralization, thus enabling rapid and efficient identification and extraction of comprehensive anomalies and prediction of metallogenic prospect areas.

Accurately identifying faults is crucial for the exploration and exploitation of oil and gas fields,and further fault extraction based on this holds critical significance for later comprehensive research.At present,the commonly used fault extraction techniques primarily include automatic fault tracking,fault slice interpretation,and manual interpretation.However,these fault extraction techniques and their application in practical exploration and exploitation often face the following challenges.Automatic fault tracking based on an attribute volume often extracts faults with low accuracy and poor continuity,whereas fault slice interpretation and conventional manual interpretation require long work cycles.Hence,this study proposed a fault extraction technique based on structure-oriented filtering.First,the original poststack seismic data were processed through structure-oriented filtering to improve the quality of fundamental data and enhance the fault boundary features.Then,a relative isochronous model was established based on the filtered data volume,with sensitive attributes that can characterize faults extracted.Finally,based on the analysis of fault combination relationships,a comprehensive interpretation method combining plane and profile views was employed to extract faults.The technique proposed in this study has been successfully applied to a certain block of SB.As indicated by the application results,the proposed technique exhibits higher reliability,accuracy,and efficiency compared to the three commonly used fault extraction techniques, thus demonstrating high applicability.

The extended spatial autocorrelation (ESPAC)-based microtremor exploration(natural-source surface wave exploration) technology has been extensively used in shallow formation exploration owing to its simplicity,efficiency,and accuracy.However,the imaging effect of dispersion energy extracted based on the ESPAC method is unsatisfactory in practical applications.In particular,different observation array arrangements influence the extraction of dispersion curves from collected data.By investigating the imaging principle of the ESPAC method,this study conducted the simulation experiment of natural-source microtremor recording through ambient noise simulation.It compared the differences in dispersion energy under various dominant frequency distributions of wavelets.Moreover,it quantitatively analyzed the influence of different station arrangements and acquisition durations on the imaging quality of dispersion energy.The comparative study reveals the imaging patterns of the ESPAC method in shallow surface exploration.The ESPAC method can maximize the imaging quality of dispersion energy in the fundamental mode while considering both efficiency and exploration costs.The results of this study were applied to engineering application cases to further verify the simulation results.

Surface-related multiple elimination(SRME) is vital in processing seismic data.At present,the SRME method most commonly used for processing marine data can effectively predict surface-related multiple models,achieving multiple elimination through matching and subtraction.However,this method requires full wave field information,thus placing higher demands on observation systems.The irregular land data acquisition makes it difficult to apply this method for processing land data.Hence,this study presented an improved SRME method,which performs moveout correction on adjacent channels for multiple prediction by constructing the minimum error constraint function,thus enhancing the adaptability to complex observation systems.The improved SRME method was applied to process the actual seismic data of land.Its effectiveness was validated by comparing the gathers,velocity spectra,prestack time migration profiles,and synthetic seismograms before and after SRME.

Tight sandstones serve as significant oil and gas reservoirs.Their lithofacies identification can assist in further understanding the developmental characteristics of reservoirs.Combining core observations with log data processing,this study analyzed the lithofacies and sedimentary microfacies characteristics of tight sandstones in the Xinchang area and the internal relationships between lithofacies and sedimentary microfacies.Moreover,it constructed a random forest classification model with geological implications through data mining of sedimentary microfacies characteristics.The results show that:(1)Tight sandstones in the Xinchang area can be classified into seven typical lithofacies,including mudstone,siltstone with ripple lamination,massive fine sandstone,fine sandstone with parallel bedding,massive medium- to coarse-grained sandstone,and medium- to coarse-grained sandstone with parallel/cross bedding;(2)The sedimentary microfacies in the Xinchang area consist primarily of subaqueous distributary channel,subaqueous distributary bay,river-mouth bar,and prodeltaic mud,which are closely associated with the sedimentation of lithofacies;(3)In the classification model,the relative centroid(RM),root mean square deviation(GS),average median(AM),and average slope(M) of the gamma ray(GR) curve can be used as the characteristic parameters of sedimentary microfacies to increase the number of characteristics in the dataset;(4)Considering the characteristics of sedimentary microfacies,especially the energy and turbulence of water bodies,can significantly enhance the performance of the random forest classification model.Overall,the results of this study provide a novel approach for lithofacies identification using machine learning methods and a significant reference for oil and gas exploration in tight sandstones.

This study converted the frequency-domain electromagnetic diffusion equation into the wave equation in the fictitious domain based on the transformation relationship between the diffusion field and the fictitious wave field,achieving the numerical calculation of the electromagnetic field in the fictitious wave field.By introducing the complex frequency shifted perfectly matched layer(CFPML) boundary condition,the storage capacity of the computer memory decreased.Furthermore,by encompassing the air layer in the calculation domain,the complex processing of the ground-air interfaces was avoided.Compared to the uniform half-space analytical solution,the algorithm proposed in this study had relative errors of less than 3.5% and thus is effective and correct.Finally,the numerical simulation of a typical geoelectric model indicated that the 3D electromagnetic responses of multiple frequencies can be obtained through single forward modeling,suggesting an elevated calculation efficiency.The numerical simulation results also exhibit that the apparent resistivity calculated based on the fictitious wave field is insensitive to the field source effect and thus can effectively identify anomaly boundaries.

A variogram serves as a crucial tool for quantifying spatial correlations. However, existing variogram fitting methods often yield unstable results. This study proposed an automatic variogram fitting method based on deep learning, aiming to enhance the precision and stability of automatic fitting. The fitting of the experimental variogram is essentially a nonlinear optimization problem, which involves optimizing the matching between the experimental and theoretical variograms. The proposed method generated substantial training datasets using several sets of theoretical variograms with varying parameter values for training and learning in deep neural networks. The trained model was then used for the automatic fitting of the experimental variogram. Multiple sets of experimental results demonstrate that based on the robust fitting capability of deep neural networks, the proposed method manifested superior fitting stability and computational efficiency compared to the least squares method, providing a novel approach for automatic variogram fitting in geostatistics.

Black soil layer thicknesses, anessential attribute of black soil,serves as a significant indicator for measuring the fertility and erosion degree of black soil. Their spatial prediction holds critical significance for supporting China's black land conservation and ensuring food security.Considering the diagnostic characteristics of black soil layers in soil system classification, this study regarded soil layers with organic carbon content higher than 6×10^-3 of soil parent materials as black soil layers.Moreover, it derived the calculation formula for the thicknesses of black soil layers relying on the exponential distribution pattern of organic carbon in the vertical soil profile. Based on the 62 896 topsoil and 15 687 deepsoil organic carbon data obtained from the multi-purpose regional geochemical survey, this study conducted detailed spatial prediction of the thicknesses of black soil layers in the Songliao Plain and analyzed their relationship with soil types and climate factors. Key findings are as follows:(1) The thicknesses of black soil layers in the Songliao Plain range from 0 to 165 cm, with a median of 23.33 cm;(2) The spatial distribution of black soil layers exhibits significant heterogeneity, characterized by thin southwestern and thick northeastern portions;(3) The black soil layers of swampy soil and peat soil manifest the largest average thicknesses between 60 and 80 cm, followed by those of typical black soil (average thickness: 56 cm) and those of albic soil and meadow soil (average thickness: 40~50 cm);(4) The spatial distributions of the thicknesses of black soil layers are closely associated with climatic conditions, primarily showing a significant negative correlation with temperature and a positive correlation with rainfall;(5) The mean annual temperature of 0 ℃ is a significant temperature threshold for the development of thick black soil layers.Above this temperature, the average thickness of black soil layers exceeds 80 cm and no longer changes with temperature. With global warming, the southward shift of this 0 ℃ is otherm may significantly influence the thicknesses of black soil layers.

This study examined 121 sets of surface sediments collected from Qinzhou Bay, Guangxi, China, determining their grain sizes and macroelement contents and analyzing the characteristics, spatial distribution patterns, and sources of microelement assemblages. The results indicate the presence of eight types of surface sediments in Qinzhou Bay, which are dominated by sands and silty sands in terms of grain size. The surface sediments featured a stable macroelement composition,with SiO₂, Al₂O₃, Fe₂O₃, and CaO accounting for about 95.54% of the total sediments. Of these, SiO₂ and Al₂O₃ exhibited the highest contents, averaging 73.23% and 8.71%, respectively. Compared to the upper continental crust (UCC), these surface sediments are enriched in SiO₂, MnO, and TiO₂ but depleted in other elements. These sediments displayed similar spatial distribution patterns of Al₂O₃, MgO, TiO₂, K₂O, and Na₂O. The significant positive correlations between these oxides indicate similar factors governing their distributions. Using Al as a reference,the enrichment factors (EFs) of nine macroelements in the study area were calculated. The results indicate that these elements largely originated from the UCC, with those from some sites being potentially affected by other factors. A comprehensive analysis of correlation and R factors shows that the ten types of macroelements in the study area can be divided into three categories. The first category consists of SiO₂, Al₂O₃, Fe₂O₃, MgO, MnO, TiO₂, K₂O, and Na₂O, suggesting a source of terrigenous clastic sediments. The second category is CaO, principally representinga marine biological source. The third type comprises P₂O₅, representinga mariculture source. The analysis of these sediment sources using the PCA-MLR model reveals that the three sources exhibit relative contribution rates of 46.14%, 15%, and 38.86%, respectively.

The Zhangye Basin in Gansu Province serves as a national modern agriculture demonstration area in China. The 1990s was the only period that witnessed both agricultural soil surveys and regional geochemical surveys in the area. This study aims to provide data support for investigating the evolution of the regional soil environment in the area. It gathered geochemical survey data of rocks, deep topsoil, and stream sediments, which were sampled by Gansu geophysical and geochemical exploration teams in the Zhangye Basin and its surrounding mountains in the 1990s. Using these data, this study calculated the background values of elements in various geological units as per the Pauta criterion and sampling media. Focusing on heavy metals, it compared their regional background values in deep topsoil with the nationalsoil background values and the coetaneous averages of farming soil elements surveyed by the agricultural sector, as well as the soil background values of Quaternary sediments with the regional background values. Moreover, it combined geochemical hybrid models with geographical factors. Finally, it explored the distribution characteristics and material sources of heavy metals in deep topsoil of the Zhangye Basin in the 1990s. Compared to the national soil background values, the deep topsoil was enriched in Cu and Cd but depleted in Zn. Contrasting with contemporaneous farming soil, the deep topsoil was significantly enriched in Cr but prominently depleted in Cu, Zn, Pb, and As. In terms of sources, heavy metals Zn, Cd, and As were principally derived from the northern Qilian Mountains, Pb originated from the Longshou Mountains, and Hg and Cr might be primarily associated with human activities. The abnormal H3 potential ecological risk index of the deep topsoil resulted from the combined effect of northwest and southeast winds. The enrichment of heavy metals in deep topsoil was positively correlated with human activity intensity but negatively correlated with neotectonic movement intensity.

Soil fertility is a significant indicator that measures the ability of soil to provide various nutrients required by vegetation and reflects the crop producing power of soil. To ascertain the soil fertility of different forest stand types in the Nanshan forest farm of Jiyuan City, this study investigated the soil of four forest stand types: Platycladus orientalis, Robinia pseudoacacia, Quercus variabilis, and walnut trees. It analyzed the soil nutrients of the forest stand types by determining the pH, organic matter, total nutrients (TN,TP,TK), and available nutrients (AN,AP,AK) of soil at different depths (0~40 cm). Moreover, it assessed the comprehensive soil fertility using the improved Nemerow comprehensive index method. The results show that: (1) Except pH, the physicochemical factors of the soil of the forest stand types in the study area exhibited moderate variations, and the soil TP, TK, AP, AK, and pH manifested significant differences; (2) With an increase in soil depth, the soil in the study area showed increased pH and bulk density, decreased organic matter, TN, and available nutrients, and almost unchanged TP and TK; (3) The assessment of soil nutrient abundance indicated that the TN, TP, and available nutrients were relatively poor in the soil of the study area; (4) Based on a comprehensive assessment, the soil fertility of four forest stand types at different depths decreased in the order of Robinia pseudoacacia, Quercus variabilis, Platycladus orientalis, and walnut trees. Their soil fertility was generally at an average level, with low values observed at depths ranging from 20 to 40 cm. The comprehensive analysis indicates that TN, TP, and available nutrients are deficient in the study area. Therefore, applying appropriate organic fertilizers, nitrogen, and phosphorus is recommended for the study area.

Hidden disaster-causing factors in coal minesdenote the geological structures and unfavorable geobodies that are concealed in coal seams and surrounding rocks and may cause mine disasters during mining. Methane and radon are common harmful gases in coal mines, and their abnormal release is often accompanied by hidden disasters like unfavorable structures of coal seams and gas accumulation. With the Xinyuan coal mine in Yangquan City as the study area, this study selected two geochemical indices based on the microseepage mechanism:Methane and radon, which are highly sensitive to hidden disaster-causing geological factors. Building on the dynamic monitoring data of methane and radon in free hydrocarbons at 408 points, and the area survey data of methane in free and acid-hydrolyzed hydrocarbons at 416 points and soil radon at 651 points, this study obtained the geochemical characteristics reflecting the distributions of disaster-causing factors like the underlying water-bearing fracture zones, coal bed methane see page zones, microstructural fracture zones, and collapse column surround zones. Moreover, this study conducted joint exploration and analysis combined with the wide-field electromagnetic method, completing the verification and identification of hidden disaster-causing factors related to structures and gas accumulation in coal mines. Furthermore, it delineated the distribution sections of potential disaster-causing factors in the study area. This study demonstrates the applicability and practicability of the hydrocarbon microseepage theory in the exploration of hidden disaster-causing factors in coal mines. It also lays a foundation for the extensive application of methane-radon geochemical indices in the survey and exploration of hidden disaster-causing factors in coal mines, thus holding critical significance for enhancing the safety of coal mine production.

Unfavorable geobodies such as Karsts, weak soil, and water-rich areas are extensively distributed in China. Under heavy rainfall, they are prone to geologic hazards like collapse. A severe geological collapse occurred in Xiacun Town, Yushui District, Xinyu City, near the Shanghai-Kunming high-speed railway. The space around the collapsed foundation pit was limited, with many interference sources like underground pipelines. With early signals subjected to the mutual inductance effects of receiver and transmitter coils, the conventional transient electromagnetic method exhibited low detection accuracy and anti-interference ability, encountering significant shallow blind zones. To locate unfavorable geobodies in the study area and provide suggestions for the prevention and control of geologic hazards, this study innovatively applied the opposing-coils transient electromagnetic method (OCTEM), supplemented by borehole-based verification. The results show that: (1) The OCTEM exhibited high accuracy, as demonstrated by the high consistency between the geophysical exploration results and the drilling results of the study area; (2) The low-resistivity zone spread across the study area, and the low-resistivity anomalies revealed by geophysical exploration were caused by groundwater according to borehole-based verification; (3) The strata from top to bottom were composed of soft plastic silty clay, hard plastic silty clay, soft plastic silty clay, and moderately weathered limestones; (4) The subsurface micro-confined water in the collapse area surged upward, gradually eroding the soft plastic silty clay layer around the area. The static water level in the collapsed foundation pit manifested an elevation of 55.60 m, located approximately 1.4 m below the surface; (5) A groundwater channel existed under the collapse area, with soil caves formed in the limestone layer under the prolonged erosion effect of water flow; (6) Long-term groundwater extraction may expand the underground seepage zone; (7) The administrative department in charge must promptly contain groundwater in the collapse area to prevent it from further eroding the surrounding unconsolidated soil layer.