China's complicated geological background and metallogenic environment have decided that the regional geochemical exploration can play an important role in the field of China's mineral resources prospecting. This is the strategic selection under special metallogenic conditions. The first round of regional geochemical exploration of China was carried out during mid-1950s. Since then, we carried out the second and third round of regional geochemical exploration. Until now, China's regional geochemical exploration has gone through a history of 70 years, and showed unique functions in fields of the exploration and development of nonferrous metals, precious metals as well as the rare minerals, rare earth and scattered minerals. According to incomplete statistics, during 36 years (1979~2015) of the second and third round of regional geochemical exploration, totally 182 different kinds of large to super-large scale deposits were discovered in China mainly by means of regional geochemical exploration. Of which, 61 deposits have nonferrous metals, 93 deposits have precious metals, 24 deposits have critical and scarce minerals, and 4 deposits have other kinds of minerals. On average, 5.06 large to super-large deposits were discovered each year, and one large to super-large deposit was discovered within every 37,000 square kilometers-Calculated on the basis that the second and third round of regional geochemical exploration covered 6.68 million square kilometers' area of China. Regional geochemical exploration has achieved outstanding results in the field of mineral prospecting, and made great contributions in terms of ensuring and promoting China's economic development. As our country's basic, public good and strategic geological work, regional geochemical exploration comes into the 21^st century marked by big data and earth system science. Based on high precision and good quality big data, guided by metallogenic geochemical theories, and supported by modern science and technology, the regional geochemical exploration will start a new period of development. In the future, we'll continue to carry out the high technical standard and high quality regional geochemical exploration, achieve our goal of complete covering the whole area of mainland China with regional geochemical exploration, and provide more strategic prospective areas for our country's mineral resources exploration. On the basis of high-precision big data, metallogenic theories and modern science and technology, we'll establish AI and IT application system, so as to push forward the exploration and utilization of deep minerals, buried deposits as well as the critical and scarce minerals which are difficult to identify, and achieve greater breakthroughs in the geological exploration of mineral resources. By using big data technics, China's regional geochemical exploration team will continuously solve the mineral resources exploration and evaluation problems, and in this process, our geochemical exploration system will be gradually integrated into our country's science and technology advancement.

Over the past century, electromagnetic exploration technology has evolved from direct current resistivity and induced polarization methods to a comprehensive geophysical system. Yet, in China's new mineral exploration phase, challenges like deep-mining needs, cultural noise, and weak 3D interpretation limit traditional methods. High-power-ultrahigh-power electromagnetic technology, by boosting transmission current, combats these issues. It enhances detection depth, enables 3D exploration, and drives technological and application innovation. This paper reviews the development of high-power-ultrahigh-power electromagnetic instruments and current research. It emphasizes that technologies like true 3D full-waveform IP collection and inversion, tensor CSAMT collection and inversion, and multi-parameter joint inversion of time-and frequency-domain EM methods can strengthen deep-target detection. Future research should tackle anisotropic 3D inversion, full-domain inversion with a field source, and extracting polarization and magnetization rates under complex constraints. These advances will propel electromagnetic methods toward greater depth, precision, and intelligence, supporting China's renewed mineral exploration efforts.

The method of structural superimposed halo to find blind ore is a new method to find blind ore, which is based on the study of the theory of primary halo to find blind ore-the axial zoning of primary halo, and puts forward two new theories of ‘primary superimposed halo theory’ and ‘structural superimposed halo theory’. The accuracy of blind ore prediction by superimposed halo of structure is determined by the correctness of prediction marks and indexes. Based on the summary of seven common signs of structural superimposed halos in the prediction of deep blind ore deposits in more than 100 hydrothermal deposits, four important quantitative qualitative prediction signs are upgraded to quantitative prediction indicators. The structural superimposed halo prediction signs and indicators of 17 different combinations of accurate prediction of blind ore and discrimination of ore body denudation degree in the deep and periphery of the mining area are described in detail, and a practical ideal model of structural superimposed halo for predicting blind ore and discriminating ore body denudation degree is established. The common prediction signs and indicators of the model have important guiding significance for the prediction of deep blind ore in typical hydrothermal deposits, and have achieved remarkable prospecting results in more than 100 mine applications.

The Salt Lake geothermal field in Yuncheng City, Shanxi Province, China lies beneath a densely populated urban area, posing significant challenges to further geothermal exploration and extraction. Based on the distribution of geothermal gradients in the geothermal field, which are higher in the southwest and lower in the northeast, a NE-trending microtremor survey profile was arranged in the southern part of Yuncheng City, aimed at investigating the deep geothermal reservoir structure and NW-trending structures in the geothermal field. The 2D velocity structure profile reveals a pronounced low-velocity anomaly in the eastern part, which is supposed to be induced by the fault fracture zone formed by multiple NW-striking tensional faults. Spatially, this concealed fault zone roughly corresponds to the low-geothermal gradient anomaly in the northeastern Salt Lake geothermal field, suggesting that this fault fracture zone might facilitate the rapid infiltration of cold surface water, thereby lowering the temperature of deep rocks in the northeastern part, leading to the formation of a large-scale low-temperature anomaly zone. Additionally, the faults identified by the microtremor survey can be traceable and confirmed in a controlled source reflection seismic profile in the study area, demonstrating the complementary nature of the two methods. This study further reveals the deep geothermal structures of the Salt Lake geothermal field based on previous efforts. This study provides more valuable bases and guidance for future exploration and resource evaluation of geothermal fields in the region while also demonstrating the effectiveness and superiority of the microtremor survey method in research on urban geothermal resources.

Due to dense buildings and structures and insufficient drilling surveys, the construction of shield tunnels passing through urban karst formations that host dense buildings faces significant risks of surface fracturing and subsidence caused by karst development. Hence, this study employed the microtremor survey technology with strong anti-interference capability in complex environments to address this challenge. Based on the technology, it analyzed the structural characteristics of wave velocities in underground rock formations through the inversion of the apparent shear-wave velocity profile. Combined with geological drilling data, it inferred the bedrock interface, highly weathered unconsolidated formations, and karst cave anomaly zones. Key findings are as follows: (1) The apparent shear-wave velocities in the study area gradually increased from the shallow to deep formations. Formations with wave velocities above and below 300 m/s were inferred to be limestone and Quaternary formations, respectively, with the rock-soil interface at depths approximately between 10~15 m; (2) Seven low-value anomaly zones of apparent shear-wave velocities ranging from 150~240 m/s were interpreted. They were presumed to be unconsolidated formations or karst caves at depths ranging from 8~30 m. Relying on strong anti-interference and high accuracy, the microtremor survey technology can accurately identify the shear-wave velocity structures of underground profiles, lithologic interfaces of formations, unconsolidated formations, and karst cave anomalies. Therefore, the technology is effective in the geological exploration of urban dense building areas with karst development.

Survey grid layout is a preliminary task of geophysical and geochemical exploration. The widespread use of handheld GPS has greatly facilitated navigation and positioning in small-to medium-scale geophysical and geochemical field surveys. This study, based on coordinate transformation theory, presented a method for generating large numbers of GPS waypoints for both regular and irregular survey grids for geophysical and geochemical exploration. Furthermore, an associated software program was developed. The software enjoys simple interfaces and convenient operations, enabling the quick generation of survey grids suitable for applications such as gravity, magnetic, and resistivity surveys, soil surveys, and stream sediment surveys. Therefore, this software can be used for field navigation.

As an important part of gravity investigation, the performance tests of gravimeters are required throughout field surveys. In these tests, mean squared error (MSE), accuracy, and root mean squared error (RMSE) are commonly employedto quantitatively describe the test results. The comparison of the theoretical equations for dynamic and consistency tests in specifications on geological surveys, petroleum, and measurement reveals a pronounced confusion in the usage of MSE, accuracy, and RMSE. This issue is observed in the consistent equations forconsistency testsin these specifications. Through investigations into the equations used in the dynamic and consistency tests inthe threespecifications, this study analyzed the differences between mean MSE and RMSE, elucidated the normativity of RMSE relative to MSE, and determined the applicablerange of RMSE. To avoid confusion, it is recommended that accuracy be used for qualitative expression and RMSE for quantitative expression in these specifications.

Recommendation system algorithms, having recently garnered significant attention in the field of digital Earth science, are expected to be widely applied in metallogenic prediction. Traditional metallogenic prediction studies fail to fully mine the various types of semantic information in massive geoscience data. The deep interest evolution network (DIEN), as a recommendation system algorithm, can fully mine semantic information to predict user preferences. Therefore, this study employed the DIEN model as the prediction model and the semantic information extracted from bedrock interpretation as the ore-controlling elements according to the database provided by the Western Australian government. The model was trained to perform metallogenic prediction for the study area. The prediction results indicate that 92.95% of uranium ore occurrences fell within the medium-high probability zone in the prediction map, with some unknown zones also showing high prediction probabilities. After removing known uranium ore occurrences in some zones, the retrained model still yielded medium-high prediction probabilities in these zones. The results suggest that the DIEN can effectively mine semantic information in metallogenic prediction studies, and the DIEN model exhibits strong predictive capacity for the study area, providing a novel approach for metallogenic prediction studies.

Many cities or urban residential areas in central and western China reside in alluvial plains formed from piedmont alluvial fans. Hence, revealing the stratigraphic architectures and stability of alluvial fans holds critical significance for urban construction planning and rational land use. The alluvial fan in the eastern piedmont of the Liupan Mountains hosts the urban residential areas and villages of Guyuan City, with a dense population. Moreover, the alluvial fan develops several event deposits recording the activity of the alluvial fan under tectonic movements and climatic changes. Through field geological survey, optically stimulated luminescence dating, controlled source audio-frequency magnetotellurics (CSAMT), and conventional radon measurement, this study revealed the stratigraphic architecture of the alluvial fan and its two-phase event deposits (~43.33 ka B.P. and 22.92~20.72 ka B.P) since the Late Pleistocene. As indicated by the CSAMT and conventional radon measurement results, the alluvial fan still exhibits high activity under the influence of the Haiyuan and Qingshuihe faults. The results of this study provide fundamental data for crustal stability assessment, prevention and control of geologic hazards, and engineering construction in the Liupanshan area.

This study investigated the Panxi area as an example to delineate faults and determine their current activity levels using aeromagnetic data and precise relocation results of small earthquakes. A total of 42 faults were delineated in the study area. Among them, 21 faults were inferred to be active currently, including 10 newly inferred active faults. This study examined the three-dimensional structural characteristics of some local sections of major faults in the study area. The results indicate that precise relocation results of small earthquakes can identify highly active faults and characterize their deep structures. Additionally, based on the delineation of basement faults using aeromagnetic data, the locations of active faults were constrained, and concealed active faults within the sedimentary cover were also determined. The proposed method holds certain practical significance for promoting research on the spatial distribution and activity of fault structures using aeromagnetic data.

The inversion of petrophysical data can image the microscopic fracture structures inside rocks, revealing the evolutionary patterns of fractures within rocks and soil with changes in external environments. Hence, it is an intuitive and reliable method for investigating the mechanisms of deep geotechnical disasters. This study presented a petrophysical data acquisition system and resistivity-based forward modeling and inversion algorithms. Based on the above, this study conducted numerical simulations of 2D and 3D inversion imaging of petrophysical data. As indicated by the numerical simulation results, 2D inversion imaging can characterize millimeter-scale rock fractures with high/low resistivities, whereas 3D inversion imaging can accurately locate and effectively identify millimeter-scale fractures and vugs with high/low resistivities. Moreover, data measurement and inversion imaging were conducted on rock samples subjected to microwave-induced fracturing in three states: heated sandstone before failure, sandstone heated to a molten state, and molten sandstone in a cooled state, preliminarily revealing the variation patterns of sandstone fractures under microwave heating. Overall, this study provides a novel method for exploring the mechanisms of deep geotechnical disasters.

Areas with low exploration degrees in the Tarim Basin exhibit intricate seismic-geologic conditions and extensively developed multiples.The internal multiples generated by strong reflection interfaces involving Paleozoic gypsum rocks undermine the imaging of the Ordovician stratigraphic information,resulting in vague images for Ordovician fractured-vuggy carbonate reservoirs and thus affecting stratigraphic interpretation.Accurate prediction and suppression of internal multiples in the Yubei area is challenging,thus restricting the deployment of oil and gas exploration in the area.The conventional prediction method for internal multiples is computationally intensive and ineffective.Hence,this study proposed an internal multiples suppression technique combined with the modeling method and adaptive matching subtraction.Based on the principles of internal multiples prediction and the forward modeling results,the proposed technique takes the main reflection interfaces generating internal multiples as the model layers and follows the approach of layer-by-layer prediction and suppression.Finally,it employs adaptive matching subtraction for the suppression of internal multiples.As demonstrated by the processing results of actual data,the proposed technique can effectively predict and suppress the dominant internal multiples to eliminate their interference effects.It solves the problems of layer-crossing phenomenon and flat formation occurrence,improving the imaging accuracy of formation structures,faults,and fractured-vuggy reservoirs.

This study investigated data from a 1:50,000 stream sediment survey in the Juxian-Wulian area, Shandong Province using factor analysis. By extracting eight representative factors, this study identified element assemblage types. Then, this study performed geochemical zoning based on the factor scores and discussed the relationships between various sub-zones and their geological background. Based on the geochemical zoning results, as well as geological conditions for mineralization, this study determined favorable geological bodies and prospecting targets and discovered new prospecting clues.The most significant mineralization combination in this area is Au-Cu-Ag-Mo-Bi, followed by Pb-Zn; The V-Ti-Co-Mn combination and Ni-Cr combination can serve as exploration elements, indicating that there may be favorable mineralization mechanisms in the center and deep parts of the combination anomaly zone. Finding volcanic craters and hidden explosive breccia tubes in the distribution areas of volcanic rocks in this region or area is an important direction for mineral exploration; In the area of Shichang Fangzi Village in the eastern part of the research area, there is a comprehensive zoning with a F₂-F₄-F₁ three factor combination model. The Mesozoic Buliu sequence and Weideshan sequence rock bodies are favorable geological bodies for mineralization, and the NE trending structural belt is a favorable place for mineralization, indicating the direction of prospecting.

Soil carbon pools play a significant role in regulating global carbon balance and mitigating greenhouse gases. Hence, estimating soil carbon stocks is critical for assessing the carbon cycle in terrestrial ecosystems. Based on the soil carbon data obtained from the land quality geochemical survey in the study area, this study estimated the stocks of total, organic, and inorganic carbon of various soil layers in Northwest China using the unit soil carbon amount (USCA) method. It analyzed the content characteristics of organic and inorganic carbon in soil under different soil, land use, and topographic types. The results of this study are as follows: (1) All the soil layers at depths ranging from 0 to 2 m in the study area exhibited total carbon of 10 099.4 Mt, including 1 224.8 Mt in the topsoil layer (0~0.2 m), 5 345.9 Mt in the upper soil layer (0~1.0 m), and 4 753.5 Mt in the lower soil layer (1.0~2.0 m). Inorganic carbon predominated in all the soil layers, with its proportion gradually increasing from top to bottom, whereas organic carbon was principally concentrated in the topsoil layer; (2) The high-value areas of inorganic carbon content were primarily distributed in the Huangshui Valley of Qinghai Province, and the Loess Plateau region covering the Longzhong area of Gansu Province, northern Shaanxi Province, and southern Ningxia Province. In contrast, the high-value areas of organic carbon content were chiefly distributed in the Qilian Mountains; (3) The aeolian sandy soil exhibited the lowest organic, inorganic, and total carbon contents in the topsoil and deep soil layers. The dark loessial soil and the loessal soil showed the highest inorganic carbon content in the topsoil layer. The dark felty soil and the dark loessial soil displayed the highest organic carbon contents in the topsoil and deep soil layers, respectively. Additionally, the dark felty soil had the highest total carbon content in the topsoil and deep soil layers; (4) Forests exhibited the highest organic carbon content in the topsoil and deep soil layers, and the highest total carbon content in the topsoil layer. Grasslands showed the highest inorganic and total carbon contents in the topsoil layer. Cultivated land had the highest inorganic carbon content in the deep soil layer. Bare land manifested the lowest inorganic, organic, and total carbon contents; (5) Mountains displayed the highest organic and total carbon contents in the topsoil and deep soil layers. Loess had the highest inorganic carbon content in the topsoil and deep soil layers. Plains showed intermediate carbon contents generally between those of loess and mountains. Besides, high-altitude areas manifested extremely high organic carbon content.

Traditional resistivity inversion methods tend to rely on the initial inversion model selected, get stuck in local minima, and be time-consuming. To address these issues, this study proposed a real-time resistivity inversion method based on the Res-UNet neural network. First, a significantly expanded forward response dataset was generated using the Gmsh software. Then, inversion experiments were carried out based on appropriate network parameters determined according to data characteristics. The experimental results indicate that the Res-UNet algorithm can fully dig the data characteristics and rapidly produce resistivity images that align with the electrical properties of strata. The experiments on the dataset for resistivity forward modeling yielded a mean squared error between the predicted values and the forward responses of 0.019 44, and those on the test set yielded a mean squared error of 0.075 8, suggesting improved imaging results compared to traditional inversion methods. Furthermore, the proposed method achieved encouraging results in the inversion calculations of simulation models, enabling rapid and accurate inversion of the location and morphologies of subsurface anomalies while exhibiting a strong noise resistance. This study provides a new method and philosophy for mapping the relationship between resistivity data and the actual geoelectric structures.

Despite bearing valuable recyclable elements, mine tailings pose environmental risks. However, there is a lack of studies on the geochemical characteristics of tailings in China and abroad, hindering their appropriate treatment and reuse. This study collected tailing samples from the Han-Xing Iron deposit in Hebei Province, China and conducted the analysis and tests of these samples. This study determined the concentrations and chemical speciation (i.e., exchangeable, carbonate-bound, Fe-Mn oxide-bound, organic-bound, and residual forms) of elements including Fe, Co, S, Cu, and Zn in tailing particles with varying grain sizes. Accordingly, it explored the implications for the exploitation and utilization of tailing resources, along with the assessment of environmental risks. This study provides deeper insights into the geochemical characteristics of tailings, producing positive impacts on the exploitation and utilization of tailing resources, as well as the prevention of environmental risks.

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.

Soil carbon pools constitute a crucial part of global terrestrial carbon pools. Hence, investigating soil carbon pools is critical for understanding the global carbon cycle and changes. Based on the soil carbon data obtained from a multi-purpose regional geochemical survey, this study estimated the densities and stocks of organic and inorganic carbon of soil at depths ranging from 0 to 20 cm, 0 to 100 cm, and 0 to 180 cm in oases on the northern margin of the Tarim Basin. Moreover, it delved into the spatial distribution of carbon density. The results of this study are as follows: (1) The compositions of soil carbon pools varied with the soil depth in the study area. At depths ranging from 0 to 20 cm, the organic carbon stocks accounted for 20.66% of the total carbon stocks. With an increase in soil depth, the organic carbon stocks gradually decreased, while the inorganic carbon stocks gradually increased. At depths ranging from 0 to 180 cm, the inorganic carbon stocks represented 85.73% of the total, suggesting that inorganic carbon predominated in the compositions of soil carbon pools; (2) The soil in three depth ranges exhibited organic carbon densities of 1,956.45, 7,913.37, and 119,73.19 t/km², which were all below the national average level, and inorganic carbon densities of 71,722.84, 37,605.54, and 71,914.93 t/km²; (3) The compositions of soil carbon pools varied somewhat across statistical units. In terms of soil types and land use types, the densities of organic and inorganic carbon were higher in fluvo-aquic soil, brown calcic soil, irrigation-silting soil, and solonchak but lower in aeolian sandy soil and irrigated desert soil. Cultivated land exhibited the highest densities of organic and inorganic carbon in the soil, whereas unused and construction land manifested the lowest carbon densities; (4) In terms of topography, undulating mountains manifested the highest soil organic carbon density, whereas alluvial-proluvial plains displayed relatively high inorganic carbon density; (5) The spatial distribution of soil carbon density in the study area was characterized by high organic carbon densities in the Yanqi Basin, medium organic carbon densities in part of Kashgar Delta (western and southern localities and eastern margin), and high inorganic carbon densities in the Aksu area. Overall, under the background of extreme drought, the oases on the northern margin of the Tarim Basin show high potential for inorganic carbon sink, with soil carbon sequestration significantly influenced by soil types, land use types, and geomorphologic landscapes.

Small- and micro-scale faults fractures (fractures and faults with fault throw less than 10 m) that originally developed in shale strata have a significant impact on the probability of penetration, stimulation volume, and production capacity of high-quality reservoirs in horizontal well sections. Therefore, it is critical to conduct fine-scale fault and fracture prediction. However, any single method struggles to accurately identify and predict these faults and fractures. Based on the developmental conditions of small-and micro-scale faults and fractures in the shale gas reservoirs of the Longmaxi Formation in the southern Sichuan Basin, this study conducted forward modeling, response mechanism analysis, and characterization of fracture responses, developing a prediction method integrating predicting and modeling. Furthermore, this study preferentially investigated techniques including seismic data processing, small-scale fault and fracture prediction, multi-scale fracture modeling, and fusion characterization. The results of the proposed method were highly consistent with the geological anomalies including small and micro-scale faults, lost circulation, and inter-well pressure channeling observed during the drilling of horizontal wells in the shale gas reservoirs of the Longmaxi Formation. Furthermore, these results exhibit a strong positive correlation with the single-well production capacity. All these corroborate that it is feasible to use this method to predict small- and micro-scale faults and fractures. This study can serve as a reference for predicting small-scale faults and fractures in other strata of the same type.

This study investigates the spatial distribution characteristics, temporal changes, and influencing factors of total carbon density, organic carbon density, and reserves in the farmland soils in Luoyang City based on repeated sampling data from multi-purpose regional geochemical survey points over different periods. The results indicate that in 2005, the topsoils in the multi-purpose survey area exhibited an average total carbon content of 1.57%, an average total carbon density of 44.74 t/hm², an average organic carbon content of 1.12%, and an average organic carbon density of 34.27 t/hm². With annual average increases in the total carbon density and organic carbon density of 0.709 t/hm² and 6.643 t/hm², respectively, this year witnessed increases in the total carbon and organic carbon of 41.73 kg/(hm²·a) and 390.75 kg/(hm²·a), respectively. The respective reserves of total carbon and organic carbon were 12.511 3 million tons and 8.879 59 million tons, with respective increases of 198.28 thousand tons and 1.857 8 million tons. In 2018, the topsoils in the multi-purpose survey area displayed an average total carbon content of 1.18%, an average total carbon density of 34.27 t/hm², an average organic carbon content of 1.07%, and an average organic carbon density of 30.94 t/hm². With annual average increases in the total carbon density and organic carbon density of 9.642 t/hm² and 4.727 t/hm², respectively, this year witnessed increases in the total carbon and organic carbon of -2,410.5 kg/(hm²·a) and 1,181.75 kg/(hm²·a), respectively. The respective reserves of total carbon and organic carbon were 1.963 5 million tons and 1.772 61 million tons. The total carbon reserves in topsoils in the whole study area were 14.474 81 million tons, including organic carbon reserves of 10.652 2 million tons. The total carbon reserves decreased by 552.41 thousand tons, while the organic carbon reserve increased by 270.82 thousand tons. Overall, the study area experienced a total carbon decrease of 354.13 thousand tons and an increase in the organic carbon reserves of 2.128 62 million tons. The total carbon showed significant positive correlations with the contents of organic carbon, CaO, MgO, N, and P, the organic carbon displayed significant positive correlations with the contents of total carbon, N, and P, and there was a significant positive correlation between pH and the CaO content. Fertilization led to an increase in the organic carbon and total carbon contents in farmland soils, with total carbon being significantly affected by the CaO content. In the carbonate areas, alkaline soil environments exhibited carbon sink characteristics. In the southern regions with acidified soil environments, the decomposition of carbonates in soils led to carbon loss and reduced calcium content. The results of this study provide important scientific evidence for research on peak carbon dioxide emissions and carbon neutrality of Luoyang City.

To understand the characteristics and sources of heavy metal contamination in the sediments of the Jinsha River basin, this study investigated the Qingling River basin-a primary tributary of Longchuan River on the south bank of the Jinsha River. Samples were collected from the sediments of 22 representative sections, and the concentrations of eight heavy metal elements, i.e., As, Cd, Cr, Cu, Hg, Ni, Pb, and Zn, were tested and analyzed. Statistical analysis was conducted on the distribution characteristics of these heavy metal elements in the sediments along the basin. The sources of these heavy metals were investigated using correlation analysis and principal component analysis, and the degree of heavy metal contamination in the sediments was assessed using the geo-accumulation index and the Nemero index. The results indicate that As, Cd, Cu, Hg, Ni, Pb, and Zn are primarily influenced by mining, agricultural, and industrial activities. Cr and Ni originate primarily from soil-forming parent materials. Besides natural sources, Ni is also affected by anthropogenic sources. The assessment results derived using the geo-accumulation and Nemero indices reveal that the eight heavy metal elements exhibit moderate or low contamination on average. However, partial elements, represented by Cd, Hg, Pb, and Zn, exhibit localized enrichment within the basin, primarily concentrated in the Laojiezi Au-Pb-Ag polymetallic mining area and the urban-rural junction in the lower reaches of the county.

The deep mining of geological mineral information from geochemical exploration data has been a hot research topic in mathematical geology and geological big data. Despite China's abundant regional geochemical exploration data, the deep mining of geological mineral information from these data remains limited, necessitating a scientific, efficient, simple, and feasible data processing workflow and analytical methodology. This study investigated the Gaoqiao area in Huixian County, Gansu Province, China. According to the geological background and the theories of element properties and geochemical behavior, this study processed relevant element data to mine the geological mineral information in geochemical exploration data. It established preliminary mathematical models for the boundary delineation and lithofacies classification of intermediate-acid rock masses, and the boundary delineation of mafic volcanic rocks in the Gaoqiao area to scientifically guide geological mapping. It preliminarily established the target delineation model for tectonic altered rock-hosted gold deposits. The model's effectiveness was substantiated by seven newly delineated target areas with promising prospecting potential. The mineral inspection identified five ore occurrences, including four reported for anomalies related to mineralization, with two currently under provincial geological exploration. The results of this study show that by calculating and processing data based on the geochemical properties of elements, the hidden information in regional geochemical exploration data can be further mined to effectively guide and modify geological mapping, thereby enhancing mapping efficiency and quality. High-quality anomaly information can be further extracted from geochemical exploration data to effectively guide mineral prospecting in new areas.

Seismic data processing reveals that internal multiples exhibit highly complex formation mechanisms,making their accurate identification and effective suppression a persistent challenge in geophysical exploration.Traditional methods for internal multiple suppression frequently require manual identification of subsurface reflection interfaces,making them difficult to apply to complex underground medium structures.Moreover,these methods are not only computationally cumbersome but also typically ensure only temporal and positional consistency when predicting internal multiples.The amplitude often deviates from observed values,requiring adaptive matching subtraction algorithms for effective suppression.This study developed an internal multiple suppression method based on Marchenko theory.Specifically,the wavefield relationships between the focusing function and Green’s function were constructed using the convolution and correlation reciprocity theorem of the Green’s function during data processing.The Green’s function was then solved using the focusing function,yielding either multiples or primaries constructed from the Green’s function.This method requires only the background velocity or the original data as operators during the iterative multidimensional correlation and convolution process,rendering it simple and computationally efficient. This study constructed an expression for the primary wave field using the Green’s function and the Marchenko equation.The tests using the SMAART model and actual data from the Gulf of Mexico demonstrate that the Marchenko method can effectively suppress internal multiples under the conditions of complex subsurface media.The iterative process requires no velocity information,providing significant advantages over conventional methods and great potential for application in complex underground environments where layers are difficult to distinguish.

The exploration and exploitation practices in the Sichuan Basin in recent years indicate that breakthroughs have been achieved in the Jurassic continental tight sandstones.Nevertheless,due to the low porosity and permeability of tight sandstone,conventional post-stack inversion frequently exhibits limited resolution,failing to meet the accuracy requirements for the prediction of actual exploration reservoirs.This necessitates pre-stack inversion for detailed characterization of tight sandstones,while S-wave velocity is crucial to pre-stack inversion.Based on continental exploration wells drilled in the southeastern Sichuan Basin in recent years,this study developed a petrophysical modeling technique for dense sandstones in this region.Specifically,given the low permeability of tight sandstones and the uneven mixing of fluids in the pore space,the Domenico model was preferentially employed to calculate the pore fluid modulus.Although fluid modulus and density are inevitably variable under the actual subsurface conditions,previous studies typically use constant values to conduct petrophysical modeling for tight sandstones.In this study,depth-dependent values were applied.Tight sandstones in the southeastern Sichuan Basin generally exhibit a porosity of less than 10%.Therefore,calculations using the Nur and the Krief models will yield high errors.Given this,this study preferred using the Lee-Pride model to calculate the skeleton modulus and controlled the relationship between the rock matrix and the skeleton by introducing the value of the cementation parameter.The application of the established petrophysical model of tight sandstone to an actual survey area indicates high agreement with data from actual wells.Additionally,based on log statistics,Poisson's ratio,the most sensitive parameter is used for high-precision pre-stack inversion in the proposed technique,enabling detailed characterization and prediction of the internal structure of channel sandstones.

Understanding the distribution patterns of selenium in soils and crops is critical to developing selenium-rich industries. Enshi City in Hubei Province is known for its extensive selenium-rich soils, establishing this city as a promising area for selenium-rich agriculture. This study investigated Xintang Township in Enshi. Based on the organization and analysis of the geochemical data of 2 469 soil samples and 237 crop samples of maize, potatoes, rice, radish, cabbage, and tea, this study offered a systematic summary of the selenium distribution in soils and factors influencing selenium content in crops in the study area. The results indicate that the topsoils exhibit selenium content ranging from 0.14×10^-6 to 25.74×10^-6, with a background value of 0.81×10^-6, which is 3.7 times the national background of selenium content in soils. Selenium-rich soils cover 86.23% of the total area of the study area, and two NEE-directed selenium-rich belts are found. The spatial distribution of selenium in soils is closely related to soil-forming parent materials. Soils with Permian black rock series as parent materials exhibit notably higher selenium content, with an enrichment coefficient of 3.74. In high-selenium-content areas, rice, radish, and cabbage exhibit selenium enrichment rates exceeding 65%. Except for potatoes, crops display positive correlations between their selenium content and the selenium content in their root soils, with tea showing the highest correlation (P<0.01, R=0.84). This suggests a close relationship between the selenium content in crops and their root soils. The crops in cultivated areas with Permian black rock series and Triassic carbonate rock series as soil-forming parent materials exhibit high bioconcentration factors of selenium, with soils and crops with Permian black rock series as soil-forming parent materials presenting the highest average selenium content. This highlights the significant impacts of soil-forming parent materials on crop selenium content.

The topographic factor significantly influences the 3D inversion results of magnetotelluric data. Despite extensive research results previously obtained in suppressing topographic effects, the gridding of complex terrains (with significant elevation changes) is still challenged by grid design complexity and difficulty in correcting data elevation points. Based on the mainstream 3D inversion module ModEM for magnetotelluric data, this study proposed a novel method for rapid automatic grid design and partitioning of terrains based on unsupervised learning, primarily involving the K-means++ algorithm and the assessment of clustering effects. Compared to the uniform and equal proportion-based hierarchical methods ignoring the topographic factor, the proposed method shows the following advantages: (1) The terrain grid generated by the clustering-based hierarchical method manifested higher terrain approximation, reducing the average error between the terrain grid and the actual terrain by 25%; (2) The matching calculation for terrain correction based on the digital elevation model was somewhat avoided; (3) The rapid design of terrain grids can be achieved, and the hierarchical characteristics can be referenced for gridding in other modeling software. The proposed method was employed to demonstrate the whole process of partitioning the elevation data of a complex terrain in a mining area, generating a resistivity structure model more representative of the actual terrain characteristics. Based on this model, finer-scale 3D inversion results were obtained. Theoretical and practical applications illustrate that the proposed method can significantly improve the topographic adaptability of gridding, holding critical significance for suppressing topographic effects on the 3D inversion of magnetotelluric data.

The Mianning-Dechang area in western Sichuan serves as the most important metallogenic belt of light rare earth elements (LREEs) in China. To make breakthroughs in the exploration of rare earth resources in the Dechang area, a 1:50 000 stream sediment survey was conducted in this study. The analysis of test data characteristics and the extraction of geochemical anomalies reveal that the total rare-earth oxides (REOs) in the area exhibit a pronounced enrichment pattern and that element anomalies largely overlap the spatial distribution of related geological bodies. Through comprehensive analysis using the cumulative frequency method and iterative method, this study determined the lower limits of anomalies and, accordingly, plotted element anomaly maps, with five main anomaly areas being delineated. The comprehensive evaluation of anomalies revealed four prospecting target areas: Huangjiaba, Jiaobacun, Yibasan, and Huajiaoyuan. The analysis of metallogenic geological conditions and the anomaly verification based on drilling in the Gannan area led to the discovery of three light rare earth deposits in the Huangjiaba prospecting target area, two heavy rare earth deposits in the Jiaobacun prospecting target area, two heavy rare earth deposits in the Yibasan prospecting target area, and two heavy rare earth deposits in the Huajiaoyuan prospecting target area. This study posits that the Triassic biotite moyite and biotite monzogranite in the study area are the metallogenic parent rocks of ion adsorption-type rare earth resources, with REEs primarily undergoing enrichment and mineralization in completely weathered layers. Therefore, a simple and effective prospecting pattern for "endogenous and exogenous" ion adsorption-type rare earth deposits in the Dechang area consists of analyzing the geochemical characteristics of the total REOs based on a 1:50 000 stream sediment survey, delineating metallogenic prospect areas that indicate parent rocks for REE enrichment, and selecting sections favorable for the formation and preservation of weathered crusts based on the hypergenic conditions of the enrichment areas, thus achieving the quick delineation of the prospecting target areas.

Conventional splicing methods aim to serve structural interpretation and align the reflection energy and frequency of large strata based on seismic data themselves.They adopt seismic data only from one study area in processing data of overlap zones,failing to fully utilize the effective information in seismic data of all study areas.Consequently,the resulting low-fidelity seismic data in overlap zones severely affect subsequent discrimination of reservoir connectivity and hydrocarbon-bearing properties.This study proposed a weighted fusion-based data spicing method for overlap zones,where seismic data from different study areas are fused with corresponding weights to generate a trace of seismic data.The application of the proposed method to actual seismic data shows that the processing results based on the fusion and splicing of data in overlap zones can effectively improve the quality of seismic data,with high continuity of seismic events on the profile, contributing significantly to the discrimination of the connectivity of shallow sand bodies.

Conventional inversion and forward modeling of large-scale potential field data from gravity and magnetic exploration, demanding high computer performance, exhibit low efficiency. Hence, this study defined a footprint determination method for potential fields, analyzed the influencing factors, and innovatively proposed a footprint-FFT strategy for forward modeling of potential fields. The footprint-FFT algorithm improved the forward modeling process from three aspects: (1) Kernel matrices were calculated based on the potential field-derived properties, significantly reducing their size; (2) A footprint concept for potential fields was introduced and defined, decoupling data scales from kernel matrix sizes, thus improving the kernel matrix computing efficiency and reducing the hardware cost; (3) Based on the above, the computing area was divided into subspaces, and the footprint-FFT strategy was first proposed for the batch computing of potential fields in subspaces, accelerating the forward modeling process. By reducing the computational complexity and storage of the kernel matrix, the method proposed in this study significantly improved the operational speed while ensuring computational accuracy. This method enabled the fast forward modeling of potential fields with more than 1 billion grids on a laptop computer within a few minutes. Theoretical examples demonstrate that this method has high efficiency and moderate requirements for computer configuration, manifesting considerable potential in the forward modeling and inversion of large-scale potential field data.

Based on high-precision, high-quality data on SiO₂, Al₂O₃, Fe₂O₃, and organic matter in topsoils obtained from the 1:250,000-scale multi-purpose regional geochemical survey in Fujian Province, this study assessed topsoils and, for the first time, established a geochemical method-based geochemical assessment system for desertified land in the province. Specifically, this system involves methods for calculating the silicon-aluminum-iron ratio (Saf), carbon-silicon ratio (K_Si), and their comprehensive index value (Szh_ f), which serves as the indicator for assessing the degree of land desertification. Specifically, a higher Szh_ f value indicates a higher degree of desertification, and vice versa. Furthermore, this study determined the statistics of geochemical classification parameters for desertified land in Fujian Province and delineated the distribution ranges of geochemical grades. This aims to assess the current status of desertified land in the province from the microscopic perspective of soil elements and to further ascertain the distribution characteristics of the land. The results indicate that the land with strong, moderate, slight, and very slight desertification in Fujian Province exhibits areas of 39 531 hectares (0.326%), 65,790 hectares (0.542%), 103 601 hectares (0.853%), and 360 329 hectares (2.968%), respectively, primarily distributed along the coastal zone to the south of the Minjiang River and in Changting County of Longyan City. Field verification demonstrates that this evaluation method is scientific and reliable and yields accurate classification results of desertification grades, thus objectively reflecting the distribution status of desertified land in Fujian Province.

The Tarim Basin,one of China's most significant oil exploration areas,exhibits thick sedimentary rock layers and frequent tectonic movements.These characteristics have led to the formation of abundant source,reservoir,and cap rocks,creating favorable conditions for the generation and storage of resources like petroleum.However,the high topographic relief in the area poses significant challenges to observation system arrangement and acquisition engineering design.Moreover,undulating surfaces and complex subsurface structures affect the propagation of seismic waves,impairing the quality of seismic exploration data and complicating data preprocessing,imaging,and reservoir prediction.Given the data loss of the Tarim block caused by suboptimal data collection,this study conducted high-precision reconstruction of seismic data using the compressed sensing technique,aiming to provide seismic records with high integrity,reliability,and precision for the preprocessing/superimposition phase.Compressed sensing,a novel sampling technique,plays a significant role in data reconstruction.The key to this technique is the adequate sparse representation of seismic data.However,conventional transform methods like Fourier transform and discrete cosine transform(DCT) are merely applicable to simple global structures.Considering the high complexity of the Tarim block data,this study employed the Shearlet transform as the sparse basis function for data reconstruction through compressed sensing.The technology of this study was finally applied to process the actual data of the Tarim Basin,demonstrating high accuracy and applicability for the area.

With the application of high-precision,high-density 3D seismic technology and significant improvements in acquisition efficiency,the volume of data from nodal seismic data acquisition has expanded sharply.This leads to growing demands for the quality monitoring of nodal seismic acquisition.Especially,the lag in the synthesis of common shot gather data in node data has affected the quality monitoring and processing efficiency of seismic data.Therefore,the demand for quality control technology has become increasingly prominent in nodal seismic data acquisition.By delving into technologies including the visual monitoring of pre-acquisition node states,node data synthesis,and seismic data quality monitoring,this study independently developed a quality monitoring platform for nodal seismic data acquisition,enabling quality control for the whole nodal seismic data acquisition,involving equipment status,data synthesis,and data quality control.This platform has achieved satisfactory application results in a practical seismic data acquisition project.

To improve the inversion accuracy of reservoirs in the Paleogene strata with limited wells and sedimentary and structural complexity, two key technologies were used in seismic data processing: sparse pulse inversion for primary wave estimation and anisotropic Q-pre-stack depth migration (PSDM). This contributed to improved quality of seismic gathers and imaging. Then, the pre-stack simultaneous inversion method was applied as follows: (1) Stacking velocity and layer-constrained Dix inversion were employed to obtain a low-frequency model of P-wave impedance; (2) Elastic impedance inversion was performed using angle-stacked data and well-calibrated wavelets, yielding far, medium, and near elastic impedance; (3) Initial P- and S-wave impedance, as well as initial density, were obtained through Fatti inversion; (4) Pre-stack simultaneous inversion was performed to obtain the final P- and S-wave impedance and density; (5) Lithology and physical property inversion results were used to predict the reservoir distribution range. This method, driven by three-dimensional seismic data and exhibiting low dependence on logs, can serve as a reference for reservoir prediction under similar geological settings.

Land emerges as the most fundamental resource for agricultural production, and addressing land quality-related issues is the key to ensuring high food quality. A comprehensive understanding of land quality is crucial to the scientific and sustainable utilization and development of land resources. This study conducted a 1:50,000 geochemical survey of land quality in the contiguous farmland in Dongchuan Town, Yao'an County, Yunnan Province. Accordingly, this study provided a comprehensive assessment of soil nutrients, environment, dry and wet atmospheric deposits, and agricultural irrigation water. Based on the assessment results, this study determined the production areas of green food and pollution-free agricultural products, aiming to provide a reference for the development and utilization of sustainable, green cultivated land. The results indicate that soils in the study area are nutrient-rich and enjoy a favorable environment, high-quality irrigation water, and an excellent atmospheric environment. The comprehensive grade assessment results of soil quality align with those of land quality, revealing that the first and second-grade high-quality soils account for 68.98% of the total area. A batch of production areas of pollution-free and green food were determined, and those that can be directly used to develop green, zinc- and copper-rich crops were delineated. These findings will provide geochemical data support for land use planning, food security, building agricultural products with plateau characteristics, and serving rural revitalization efforts.

Due to numerous thin interbeds in weakly elastic media,seismic excitation typically yields rapidly attenuated seismic wave energy and a narrow dominant frequency band,resulting in low-resolution seismic data.Therefore,selecting a favorable lithology plays a crucial role in improving the seismic excitation effect.This study explored the dominant factors influencing the quality of seismic data obtained from the northern Jiangsu exploration area,a region with a dense river system.Specifically,this study determined the top boundary of the high-velocity layer based on microlog surveys and the dominant lithologic member using the cone penetration test and lithologic coring.It quantitatively analyzed seismic wavelet attributes,including octave band,resolution,main-to-side lobe energy ratio,and wavelet clarity,establishing their matching relationship with the lithology for seismic excitation.By selecting a lithologic surface featuring a high seismic wave propagation velocity,a favorable elastic property,and a wide frequency band in the study area,it plotted a surface lithology map for pointwise well depth design,ensuring wide-frequency excitation.The above techniques were applied to well depth design for seismic excitation in the YA and SDX areas,achieving well-normalized single-shot frequencies and widening the dominant frequency band of the target layer in the seismic profile by over 10 Hz,with an increase of 1.5 octave bands.The results show that the excitation strategy of "selecting the dominant lithology from weakly elastic media" in regions with dense river systems can effectively enhance the seismic excitation effect in weakly elastic media,thereby improving the imaging accuracy and resolution of seismic data.

Using seismic reflection profiles and drilling data, this study determined the types and styles of inverted structures in the Tabei Sag, Erlian Basin. Accordingly, this study explored the genetic mechanisms of the inverted structures and their relationships with sandstone-hosted uranium mines. The results indicate that the eastern and western parts of the Tabei Sag experienced different degrees of normal and inverted tectonism. As a result, the eastern part exhibits typical inverted structural styles. In contrast, in the western part, the Saihan Formation on the hanging wall of inverted fault F₁ in the Bayanwula and Manglai area was uplifted and almost completely eroded, with the original geometries of inverted structures being destroyed. During the late depositional stage of the Early Cretaceous Saihan Formation (113~98.9 Ma) and from the Late Cretaceous to the Early Paleocene (66~42 Ma), the subduction direction of the Paleo-Pacific Plate shifted from NW to NWW. This change altered the stress regime in the Tabei Sag from extension to compressional inversion, leading to the formation of a series of compressional and compressional-torsional structures. Consequently, the Saihan Formation and the Upper Cretaceous strata were uplifted and eroded, resulting in the formation of regional angular unconformities. The structural inversion transformed the sedimentary system of the Saihan Formation in the Tabei Sag from lacustrine to fluvial facies. Meanwhile, it caused differential uplift and uneven erosion of the Saihan Formation and its overburden, leading to the formation of erosion windows. This facilitated the infiltration and migration of uranium- and oxygen-bearing fluids toward deep parts. These processes controlled the morphologies and development of interlayer oxidation zones, thereby promoting the enrichment of uranium deposits.

With the advancement of social economy and science and technology, the demand for oil and gas resources has been increasing in daily life and industry. Tight sandstone reservoirs have been the priority targets for the exploration and production of oil and gas resources. However, there still exist many challenges in assessing the parameters and quality of tight sandstone reservoirs. This study conducted experiments on the physical properties, pore structures, and electrical properties of rock samples from the Taiyuan Formation in the Shenmu gas field of the Ordos Basin. Based on this, it established a porosity-permeability relationship model, a capillary pressure prediction model, and a classification saturation assessment model. Besides, it obtained the relative permeability of gas and water phases, which varied point by point, from wells based on the I-Kr model. This study proposed the factors for assessing reservoir quality, which were applied to the target interval in the study area considering the physical properties, pore structures, and multiphase seepage capacity, yielding satisfactory assessment results. Therefore, the method of this study provides a reliable basis for the log-based assessment of the quality of tight sandstone reservoirs.

Marine seismic data from sparker sources exhibit strong noise interference, complex wavelet morphologies, signal distortion due to cables' feathering and undulation, and severe multiple wave interference, all of which greatly affect the imaging quality of seismic data. Based on the characteristics of marine seismic data from sparker sources, this study established a data processing workflow and elaborated on the key technologies involved, including LIFT high-fidelity noise suppression, cable drift correction, surface-consistent simulated annealing static correction, wavelet processing, and free surface multiple suppression technologies. The application to actual data indicates that this processing workflow can effectively address the challenges associated with marine seismic data from sparker sources, improve the signal-to-noise ratio, restore the wavelet bandwidth, and produce seismic sections with superior broadband imaging and clearly defined geological features. This study provides a novel technical means for the application of marine wide-azimuth seismic data.

Noise detection and suppression of oil well pumping units pose challenges in data processing for mature exploration areas.The conventional method in the industry is to identify pumping unit noise through manual interactions and then suppress it as high-amplitude interference.However,manual identification wastes manpower and yields low detection accuracy,often resulting in missed detections.Hence,based on the noise characteristics of pumping units,this study conducted noise detection on seismic data containing pumping unit noise using deep learning methods.It then estimated the bandwidth of the detected noise using mathematical morphology techniques to determine the final position and distribution pattern of the noise.This allows for adaptive parameter support for the anomalous amplitude attenuation(AAA) method to achieve automatic detection and efficient suppression of pumping unit noise.The processing results of actual seismic data reveal that the methodology used in this study enables intelligent detection of pumping unit noise,significantly reducing the manual effort required for noise identification,improving the detection accuracy,and enhancing the fidelity and robustness of the AAA method.

Traditional gridding methods struggle to balance computational accuracy and efficiency when processing irregularly distributed magnetic anomaly data. To address this issue, this study applied the classic least-squares collocation method from geodesy to the gridding of ground-based magnetic anomaly data. This application was verified through the test and analysis of the simulation data and the actual coalfield data. The results indicate that the computational accuracy of gridding based on least-squares collocation is dictated by the error estimation of discrete observational data and the selection and fitting of the covariance function. More accurate error estimation contributes to higher-accuracy interpolation. A polynomial function is a simple and effective empirical covariance function for processing magnetic anomaly data. The least-squares collocation method demonstrates more effective noise suppression compared to the Kriging, minimum curvature, and radial basis function methods. Overall, applying the least-squares collocation to the gridding of magnetic anomaly data can enhance the accuracy and efficiency of data processing.