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.

The exposed crust is the critical interface where the lithosphere interacts with the pedosphere, hydrosphere, and atmosphere. The petrogeochemical map of the exposed crust can provide essential fundamental geochemical data for investigating the distributions and cycles of elements among different spheres. However, the plotting of the large-scale petrogeochemical map of the exposed crust has been constrained by the limited data volume and mapping technology. Consequently, no such a map covering the Chinese continent is available. This study proposed an innovative mapping technology roadmap based on over 16,000 petrogeochemical data and fundamental geological information. First, the databases for petrogeochemical information, stratigraphic structure information, and spatial information of geological units were constructed. Second, the geospatial information of strata and rock masses was extracted from the basic databases. Third, the petrogeochemical information was assigned to strata and rock masses to obtain their spatial distributions and element contents. Fourth, the spatial distribution patterns of 76 elements in the exposed crust were visualized using geographical information system (GIS) technology. Additionally, this study analyzed the challenges in the mapping process, including geological information accuracy, the lack of samples for special lithologies, reliability assessment, and scope of application, finally proposing corresponding solutions. The petrogeochemical map of the exposed crust demonstrates significant application potential, providing foundational data for investigating geochemical background and rock-sediment element cycling.

The Fe-Cu-U mineralization in the Luzong area in Anhui Province occurs primarily within the syenite mass and along its contact zone with surrounding rocks. Effectively delineating the syenite mass using geophysical exploration methods is a scientific issue that needs to be addressed urgently for mineral exploration breakthroughs in the Luzong area. Therefore, based on 358 rock samples from scientific drilling borehole ZK01 at a burial depth of 2 012 m in the Luzong area, this study measured their petrophysical properties, including density, magnetism (magnetic susceptibility and remanent magnetization intensity), electrical properties (resistivity and polarizability), and elastic wave velocity. The results indicate that syenites manifested low density and weak magnetic characteristics, providing prerequisites for syenite identification through gravity and magnetic explorations in borehole ZK01 or similar geological conditions. The strata and syenite-monzonite masses in the borehole exhibited medium-to-high resistivity characteristics with nonsignificant differences, increasing the difficulties in electrical prospecting. The syenite-monzonite masses displayed lower compressional and shear wave velocities compared to the volcanic layer in the Zhuanqiao Formation, laying a foundation for distinguishing strata from rock masses through seismic exploration.

Large-area hydrogen escape anomalies were detected during the soil hydrogen geochemical survey in the Zhangbei Basin, making it urgent to apply geophysical methods to understand the basement structures that generate and transport hydrogen. For this purpose, the first gravity and magnetotelluric surveys targeting natural hydrogen were conducted in the Zhangbei Basin, with 1∶50,000 gravity and magnetotelluric surveys performed within the study area. Using the collected gravity and magnetotelluric data, a large-scale gravity-magnetotelluric profile across the study area was inverted, constrained by drilling, geological, and physical property data. The study identified a "two depressions and three uplifts" structural pattern in the basin, with a total Mesozoic-Cenozoic sedimentary thickness ranging from 0.62 to 1.9 km. Four concealed faults were revealed, among which faults F₁ and F₄ can serve as migration pathways and storage channels for natural hydrogen. The inversion results indicate that the two depressions exhibited continuous and stable stratigraphic interfaces and relatively thick sandstone-mudstone assemblage layers, which provide good sealing capacity to reduce hydrogen leakage effectively. These findings on basement structures offer valuable insights for the prospect area evaluation of natural hydrogen and subsequent exploration plans in the area. They also provide a significant basis for establishing a natural hydrogen exploration technology system and selecting optimal exploration targets.

The Laowan gold belt is located in the eastern part of the Qinling orogenic belt, between the Nanyang and Wucheng basins. It boasts super-large gold resources hosted by moderate- to low-temperature magmatic-hydrothermal gold deposits formed during the Late Yanshanian. To explore the second exploration space and achieve new prospecting breakthroughs, this study investigated the primary halo of the No.59 ore body in the Laowan gold belt. Multiple statistical methods were employed to analyze the correlations among ore-forming elements. Accordingly, reliable geochemical indicators were identified to predict deep prospecting orientations. The results show that the primary halo of the No. 59 ore body exhibits an axial zoning sequence of Sn, Ba, As, Au, Pb, Cu, Sb, Ag, Mo, Bi, W, Hg, and Zn. The front-halo element Hg appears late in sequence, positioned after ore-forming elements Au, Ag, Pb, and Cu, suggesting the presence of blind ore bodies at depth or significant extension of the known ones to a burial depth of 650 m and above. In contrast, the rear-halo element Sn appears early in the sequence, indicating that the ore body was somewhat denuded. Correlation, cluster, and factor analyses were used to investigate the affinities between ore-forming elements and other metallic elements. Strong correlations were observed among Cu, Ag, and Au, establishing them as effective prospecting indicators within the deposit area. The cumulative index ratio of front- to rear-halo elements showed an increasing trend at a burial depth of 650 m, where a well-developed and non-closed anomaly was revealed by the F2 factor score contour. This suggests promising prospecting potential at this depth and deeper parts. Based on the comprehensive analysis, this study posits that the area at and below the burial depth of 650 m in borehole ZK3041 along the exploration line 304 is an exploration target. A prediction borehole drilled north of borehole ZK3041 saw the extension of No.59 ore body at a burial depth of about 720 m. Moreover, the assessment indicators show that the ore body still holds significant prospecting potential in the deeper part.

To identify areas potentially rich in metal minerals, this study proposed a prospecting method based on tectono-geochemistry weak information extraction. After the exploration scope was determined, sampling points were arranged using a grid pattern, followed by chemical tests on the collected samples. Through static extraction, centrifugation, and dynamic extraction, weak tectono-geochemical information in the samples was extracted. Then, the distribution of metal minerals within fault zones was analyzed based on the extraction results, and thus metal mineral prospecting was completed. During the geological exploration in the Wuminggou-Baidungou area in the Wulonggou, Dulan County, Qinghai Province, the mineral structures within the exploration area were analyzed using extracted weak tectono-geochemical information. As a result, among the 17 fault zones identified, a 500 m long metal ore body was delineated in fault zone Ⅳ, six ore bodies with lengths ranging from 180 to 400 m were determined in fault zone Ⅵ, and two ore bodies with lengths ranging from 550 to 800 m were delineated in fault zone Ⅺ. The remaining ore bodies were identified as blind ore bodies. The application of tectono-geochemistry weak information extraction for metal mineral prospecting yielded significant achievements, meeting the practical needs of metal mineral exploration. This method can be widely applied to metal mineral prospecting in similar geological settings.

The Xinfang gold deposit resides in the gold polymetallic ore concentration area in eastern Liaoning Province. Based on regional metallogenic patterns and existing exploration results, the southern part of the Yalu River fault zone, where the Xinfang gold deposit is located, shows significant potential for gold resources. As exploration progresses, more gold ore bodies are expected to be discovered in the gold deposit area. However, the lack of effective deep exploration techniques limits further exploration and exploitation in the area, failing to effectively reveal the extensions of lithological boundaries and the distributions of fault structures in the area. This study presented the first application of the wide-field electromagnetic method in the area. Based on the obtained results and geological engineering information, this study delineated the electrical layers within a depth of 3 km, determining the thickness of the Neoproterozoic cap rocks and inferring several fault zones. Combined with existing geological data, this study identified the low-resistivity anomaly zone at a depth of about 1 km as an extensional structural plane caused by ductile shearing. Overall, this study provides valuable geophysical data for establishing a geological prospecting model for eastern Liaoning Province, holding significant research value for geological and mineral exploration in the area.

For regional geochemical surveys in the forest swamp landscape area, Great Xing'an Range, a variable main geological setting can lead to significant element background variations, posing challenges to anomaly extraction. After gridding the original data, this study compared the anomalies delineated by the commonly used anomaly threshold method with the anomalies obtained from the hollow micro-area method. The comparison reveals that the latter could effectively suppress the variations in the geochemical field caused by different geological settings, enabling more objective anomaly extraction. Based on a systematic summary of the area's geological and geochemical characteristics, this study conducted anomaly screening and verification, achieving satisfactory prospecting results. Finally, this study preliminarily summarized the dominant prospecting indicators and orientations for the area.

The uranium-radium (U-Ra) equilibrium coefficient is a significant correction parameter for the resource and reserve estimation of in situ leached (ISL) sandstone uranium deposits, directly influencing the accuracy and scientificity of such estimations. Employing a high-purity germanium gamma-ray spectrometer, this study determined the U and Ra contents of 1 431 samples from the Manglai uranium deposit in the Erlian Basin, yielding U-Ra equilibrium coefficients for these samples. Statistical analyses were performed on the U-Ra equilibrium coefficients in terms of frequency distribution, U content, grain size, lithology, and spatial distribution, to explore the primary factors influencing the changes in U-Ra equilibrium coefficients and their implications. The results indicate that the Manglai uranium deposit showed a U-Ra equilibrium coefficient of 0.85, suggesting that the deposit is significantly richer in U. The U-Ra equilibrium coefficient was negatively correlated with U's concent and grade. Additionally, the U-Ra equilibrium coefficient exhibited distinct vertical zoning within ore bodies. Within uranium-mineralized sand bodies, the most favorable grain sizes were observed in sandy conglomerates, coarse- and fine-grained sandstones. The presence of grayish-black and dark black mudstones contributed to uranium enrichment and mineralization in adjacent mineralized sand bodies. The block I-1 in the southern main ore body exhibits significant uranium enrichment potential and the highest U enrichment degree. The uranium deposit is overall richer in U, with almost no Ra-richer zones, indicating that the uranium deposit experienced minimal oxidative transformation after its formation. The results of this study provide a scientific basis for the subsequent construction arrangement of in situ leaching at the Manglai uranium deposit while contributing to a deeper understanding of the deposit's mineralization regularity.

The Puguang exploration area in the northeastern Sichuan Basin,China,is characterized by complex surface and subsurface conditions due to the influence of multistage tectonic movements.This dual complexity poses a challenge to precisely characterizing special geobodies like anhydrites in this area,leading to inaccurate velocity field establishment.Consequently,the seismic imaging quality is severely degraded,hindering the fine-scale exploration and production of oil and gas.To enhance velocity modeling accuracy and improve seismic modeling and imaging effects for complex structures,this study investigated the application of a joint velocity modeling method integrating full waveform inversion(FWI) for complex mountainous terrain.A depth-domain velocity modeling workflow based on FWI was developed for the Puguang exploration area.The joint inversion combining tomography and FWI,enhanced by incorporating geological constraints to improve FWI stability,results in a velocity model that effectively matches the subsurface structures.The test using actual data demonstrates that FWI can significantly improve the detail characterization accuracy of velocity models for complex transition zones.This improvement is particularly evident in the enhanced imaging of complex structures in the Dawan and Maoba blocks in the Puguang exploration area.

To address the key issues in marine geomagnetic field modeling, this paper systematically explored the theoretical basis, modeling method, and optimization strategy of the equivalent source technology. By analyzing the geometric parameters and spatial configuration strategies of equivalent sources, a terrain-following vertical hexahedral equivalent source configuration scheme was proposed, significantly enhancing the accuracy of magnetic field models. In terms of algorithm implementation, a sliding window-based coverage calculation scheme was employed, effectively overcoming the bottleneck in the high-precision processing of massive magnetic survey data. Experimental results show that maintaining an overlap rate of 15%~20% in the sliding window ensures both boundary continuity and optimal computational performance. This method provides a reliable technical support for high-precision marine geomagnetic field modeling, with its effectiveness having been verified across various geological models (with the errors less than 5%).

The thin interbedded sand bodies in the W oilfield of the South Turgay Basin,Kazakhstan,exhibit rapid lateral variation and poor connectivity.For many years,the application of conventional reservoir prediction methods has yielded unsatisfactory results,and unclear insights into the horizontal and vertical distribution characteristics of favorable reservoirs have severely constrained the oilfield's exploration and development.To address these challenges,this study adopted an integrated approach incorporating forward modeling,post-stack seismic processing,and multi-attribute fusion to develop a prediction methodology suitable for the geological conditions of the study area.Based on forward modeling that established the relationship between reservoir variation and seismic waveform changes,empirical mode decomposition and blue filtering were applied to enhance the dominant frequency and resolution of the seismic data.The multi-attribute fusion of waveform indication inversion results,root-mean-square amplitude,and instantaneous frequency ultimately delineated the distribution and thickness of the target sand bodies.The results demonstrate that this method effectively predicts the distribution and thickness of favorable sand bodies,with errors of less than 2 meters compared to drilled thicknesses across the field.The spatial distribution of reservoirs is consistent with geological understanding.This study provides valuable guidance for subsequent rolling evaluation and efficient development of the oilfield.

The gradient structure tensor (GST) serves as a common attribute to characterize the boundaries of strongly heterogeneous reservoirs, such as fracture-cavity types, playing an important role in research on carbonate reservoirs. However, due to a lack of dimensions and high difficulties in threshold determination, the accuracy of GSI directly affects the precision of reservoir delineation and reserve estimation. Given this, focusing on a fracture-cavity carbonate reservoir model, this study proposed a three-step strategy for threshold selection based on analysis of the GST attribute distribution corresponding to noisy reservoir and non-reservoir regions. First, the distribution of GST attribute values was statistically analyzed. Then, the value distribution of attribute values in the non-reservoir regions was estimated to identify their mean point, left critical point, and right critical point. Finally, the right critical point was selected as the threshold for the GST attribute of noisy reservoirs, thus delineating the boundaries of fracture-cavity bodies. Model tests and practical applications demonstrate the feasibility and effectiveness of this method. The findings provide a foundation for the application and promotion of the GST attribute in geophysics.

The Audio-frequency Magnetotelluric (AMT) sounding method is an electrical exploration technique widely used for shallow to medium-depth geological investigations. Its data quality is influenced by various factors, including cultural electromagnetic interference, electrode polarization, and grounding resistance. This study focuses on the impact of electrode polarization and grounding resistance on AMT data quality. First, the mechanisms of electrode polarization and the influence of grounding resistance on apparent resistivity and impedance phase are theoretically analyzed. Then, based on measured data, the effects of electrode polarization and grounding resistance on apparent resistivity and phase curves are investigated. Finally, a comparative analysis of 2D inversion results from field data is conducted to reveal how grounding resistance affects geological interpretation. The results indicate that electrode polarization significantly degrades data quality in the low-frequency band, though this can be mitigated through data processing techniques, while its effect on high-frequency data is negligible. Unstable grounding resistance mainly influences the high-frequency range, causing notable reductions in apparent resistivity and phase, which gradually stabilize toward the low-frequency band. Moreover, unstable grounding resistance may lead to inversion results that deviate from the true geoelectrical structure, thereby resulting in erroneous geological interpretations. The findings of this study provide important guidance for field data acquisition and processing.

The small-scale coal mines and goaves of roadways in coal mines have a significant impact on coal mine safety production.Moreover,the limited space of roadways makes geophysical exploration very difficult,calling for higher requirements on the resolution and fidelity of seismic data.In this study,a node seismograph,with a 10 Hz natural frequency of geophones,was used for the acquisition of 3D seismic data.During data interpretation,the extraction root mean square(RMS) amplitude identified the presence of a known roadway with a cross-section of 5 m×4 m.Then,by further extracting the spectral decomposition attributes and coherent energy gradients,the characteristics of the roadway anomalies were intensified,with the revealed anomaly centers aligning with the known roadway positions.In conjunction with forward modeling analysis,the 10 Hz geophone exhibited a high resolution for deep-buried coal mine roadways, and the seismic attribute technologies proved to be an effective means to highlight roadway anomalies.These findings can provide critical reference for the interpretation of small coal seams and goaf-side roadways in coal mines.

With the ongoing exploration of hydrocarbon reservoirs, conventional linear inversion methods for conventional hydrocarbon reservoirs fail to meet the accuracy requirements for tight sandstone reservoirs.In response,this study,focusing on tight sandstone reservoirs,calculated expressions for P-wave velocity,S-wave velocity,and density in saturated rocks using inclusion models.A nonlinear reflection coefficient equation was established based on the exact Zoeppritz equations.Using the L₁-norm as the inversion objective function,a high-precision amplitude variation with offset(AVO) inversion method for reservoir parameter prediction was developed using the sparrow search algorithm(SSA).Compared to the conventional least-squares inversion results with the L₂-norm as the objective function,the proposed method improves the accuracy and resolution of the inversion results.It provides more reasonable and reliable predictions of petrophysical parameters and offers an effective approach for evaluating pore development and hydrocarbon content in tight sandstone reservoirs.The validity and practicality of this method are verified through model tests and application to actual data from tight sandstone reservoirs in the Ordos Basin.

Reflection waveform inversion(RWI) provides an effective initial model for full waveform inversion(FWI) by alternately updating the low-to-intermediate and high wavenumber components in the model.However,time-domain RWI requires storing the cross-correlation between the source background wavefield and the receiver scattered wavefield over the entire time series to compute gradients,demanding substantial computational storage.Although frequency-domain RWI exhibits multi-scale properties,it also imposes high demands on computational memory.Based on the discrete Fourier transform,this study proposed a RWI method that extracts frequency-domain wavefields from corresponding time-domain wavefields for multi-scale inversion in the time-frequency domain.The proposed method requires storing only a few single-frequency wavefield snapshots,showing significantly lower storage demands compared to conventional time-domain RWI and reduced computational costs relative to frequency-domain RWI.Therefore,the proposed method effectively combines the computational efficiency of time-domain RWI with the multi-scale properties of frequency-domain RWI.Considering the frequently missing low-frequency data in actual seismic data,this study further integrated envelope-based RWI to reconstruct low-frequency information for medium-deep subsurface structures.This enables stage-wise optimization of the inversion process,reducing the dependency on low-frequency long-offset data.Finally,numerical examples validate the effectiveness of the time-frequency domain RWI method based on envelope data in recovering low-frequency information.

This study aims to demonstrate the effects of the electric-source short-offset transient electromagnetic method(SOTEM) for water hazard prevention and control in coal mines under complex topographical conditions.To this end,the detection capabilities of the H_x and E_x components were simulated and analyzed using the SOTEM method,along with field tests in a coal mine in northern Guizhou.During the tests,four profiles were arranged and the SOTEMSoft software was used for inversion, with the inversion results verified by drilling.The results show that during measurement along the equatorial direction,the H_z component exhibited a high capability to detect low-resistivity anomalies.In contrast,the E_x component exhibited a comparable capability in detecting both low-resistivity(along the equatorial direction) and high-resistivity anomalies(along the axial direction).The SOTEM technique can accurately locate the most severe water hazard areas in coal mines under complex topographical conditions.The feasibility and accuracy of the SOTEM method for water hazard prevention and control were validated through the application in coal mines in northern Guizhou.

The pre-stack anisotropic seismic inversion based on azimuthal seismic data is a key method for fracture detection and fluid identification of fractured reservoirs,which provides effective guidance for exploration and development of fractured reservoirs.However,the anisotropic inversion method under conventional constraints encounters challenges in terms of stability and reliability,with higher requirements being placed for fine characterization of exploration targets.Moreover,there exists a lack of direct inversion methods targeting the fracture density prediction and fluid identification of the fractured reservoirs with high-angle fractures in East China.Therefore,this paper first identified the sensitive factors for fluid identification using multi-well crossplots.Then,based on the poroelasticity theory and the linearized reflection coefficient equation for horizontal transverse isotropy(HTI) media,an azimuthal seismic reflection coefficient equation was deduced,which can reflect the variations of fluid factors and fracture density with the angle of incidence and azimuth angle.Finally,based on the advanced Markov Chain Monte Carlo(MCMC) algorithm,a two-step Bayesian anisotropic seismic inversion method with the L₁ norm constraint was proposed,achieving the fluid identification and accurate prediction of fracture density for reservoirs with high-angle fractures.The deduced reflection coefficient equation proved to be feasible through accuracy analysis.In addition,the method proved to be rational and reliable through synthetic seismogram testing and application in actual survey areas,offering a novel solution for the fracture density prediction and fluid identification in such reservoirs.

The non-self-oscillating optically pumped helium magnetometer is widely used in the field of geophysical exploration. The filter, as a key module for the digitization of domestic magnetometers, plays a significant role in improving the performance of the magnetometer. In view of the limits of the current filter design, this study developed and implemented a multi-stage filter design characterized by a simple structure, low FPGA resource consumption, and user-friendly operation. Specifically, the multi-stage cascaded integrator comb (CIC) filter was cascaded with the infinite impulse response (IIR) filter, which was then embedded into a lock-in amplifier, thereby enabling signal extraction and detection. Through MATLAB simulation and FPGA implementation, the performance of this newly designed filter was verified, which can realize the extraction of the first and second harmonic signals during magnetic surveys. Furthermore, an optically pumped helium magnetometer configured with such a filter exhibited a picotesla (pT) sensitivity, satisfying the requirements of the Criterion of Aeromagnetic Survey. This new design provides technical support for the miniaturization of new-generation aerial magnetometers.

Based on the analysis of the data files from the MTU series instruments, this study explored the data files from the Aether magnetotelluric system. The C# programming language was employed to write a program to decode the original time series A24 files, magnetic probe calibration apial files, and standard time series atts files, completing the development of time series split, read/write, and display modules, probe file read/write and display modules, and Fourier transform and Fourier coefficient display modules. Finally, the applicability of the program used in this study was tested by comparing the above modules with the relevant modules in the prMT processing software. The operability of the program was tested using actual field data. Overall, this study provides a certain basis and reference for delving into power spectrum estimation and interference signal processing.

The traditional Tolles-Lawson (TL) linear model suffers limitations of compensation precision in processing complex magnetic disturbance data obtained using a towed coherent population trapping (CPT)-based atomic magnetometer detection system. This study introduced neural network technology to achieve more precise nonlinear compensation. Given that conventional neural network models encounter issues such as gradient vanishment or overfitting during parameter updates, this study proposed a deep residual network-based magnetic compensation model (MCRNet) to further enhance the compensation effects of magnetic interference within a towed pod. Experimental results demonstrate that compared to the best traditional method—The Residual Backpropagation Network (ResBP), the proposed MCRNet model increased the improvement ratio (IR) to 4.826 from 4.251, increasing by 13.53%, and reduced the root mean square error (RMSE) of compensated residual magnetism to 0.171 from 0.2, representing a reduction of 14.5%. The proposed model enhances the magnetic survey accuracy of towed magnetic anomaly detection systems.

The green food industry has developed vigorously in recent years. Properly choosing green food production areas through environmental quality surveys and assessments can ensure the quality of green food and generate significant economic, social, and ecological benefits. China has obtained vast amounts of high-quality geochemical data by implementing a series of geochemical survey programs. However, there is a lack of software platforms that can translate these scientific data into a language that is easily understandable and usable by the public. To address this issue, this study conducted a systematic investigation and assessment of green land at the village and plot scale in Yongqing County. A total of 822 topsoil and deep soil samples were collected from 386 administrative villages and four agricultural science and technology industrial parks in Yongqing County. Based on these soil samples, 54 elements and indicators were analyzed, focusing on nutrient elements like nitrogen, phosphorus, and potassium closely associated with green food production areas, eight hazardous heavy metals including copper, lead, zinc, nickel, chromium, cadmium, arsenic, and mercury, and health-related elements like selenium, germanium, fluorine, and iodine. The land in the Yongqing area was categorized and rated to comprehensively analyze the distribution of the elements and systematically assess and utilize the land. Finally, unique QR codes were generated for various land plots. The survey results indicate that the Yongqing area, one of the cleanest contiguous land areas in the Beijing-Tianjin-Hebei region, holds a solid foundation for vigorously developing the green food industry. The QR code identification technology can serve the protection and utilization of green land and farmers' production and income increase. This technology assists in establishing an accurate zoning and grading system based on geochemical characteristics for the study area. The system further facilitates the formulation of targeted ecosystem conservation measures characterized by specialized strategies for specific locations, achieving precise management and efficient control of ecosystems. Moreover, based on the Chemical Earth big data platform, the first geochemical spatial big data platform for green industries can be constructed to create the database of green land in Yongqing County and generate QR codes for visual land identification, thereby facilitating the government's management, enterprises' farming and sales, and consumers' inquiries. This technology is expected to generate significant economic and social benefits in the future.

Assessing the abundance and deficiency of soil nutrient elements holds critical referential significance for guiding agricultural production, improving the planting structure, and implementing location-specific scientific fertilization. This study investigated Tangyi Town, a typical agricultural area in Liaocheng City. First, this study tested 15 nutrient indicators in 84 topsoil samples from representative cultivated land. Second, using the geographic information system (GIS) and geostatistical analysis, this study revealed the spatial distribution patterns of various geochemical elements. Third, this study conducted single-indicator and comprehensive assessments of soil nutrient geochemistry. The results show that the soils from cultivated land in Tangyi Town exhibited relatively abundant to abundant P and CaO contents, and moderate to relatively abundant K₂O content. Their S content displayed overall relatively abundant to a higher level and a non-uniform distribution, with local excess observed. Additionally, they manifested relatively deficient N and organic matter contents and generally moderate trace element content. This study identified a Se-rich soil area of approximately 2.98 km², representing about 4.76% of the total cultivated land area, with Se content ranging from 0.49×10^-6 to 2.03×10^-6. The comprehensive geochemical grades of soil nutrients in the study area are predominantly of grades Ⅱ (relatively abundant) and Ⅲ (moderate), covering areas of 54.11% and 40.47%, respectively, indicating favorable conditions for agricultural production. This study ascertained the soil nutrient status of cultivated land in the study area and identified Se-rich land resources, providing fundamental geochemical data for guiding the development and utilization of land resources and developing distinctive agriculture.

This study aims to accurately predict the organic carbon content in black soils at the county level, thereby supporting county-level agricultural production and carbon peak and neutrality goals. This study examined 427 soil samples obtained from a surface substrate survey of the black soil area in Baoqing County. Employing deterministic interpolation (inverse distance weighting, IDW), geostatistics (ordinary Kriging method, OK), and machine learning (random forest, RF), this study constructed assessment models to predict the organic carbon content in topsoils in Baoqing County and to compare their prediction accuracy and performance. The results show that the IDW, OK, and RF models yielded average organic carbon contents of 27.21×10^-3, 26.33×10^-3, and 32.05×10^-3, respectively. The RF model outperformed the other two models in terms of root mean square error (RMSE), mean absolute error (MAE), and the coefficient of determination (R²). Specifically, the RF model achieved R² values of 0.73 and 0.53 on training and validation sets, respectively, suggesting significantly higher accuracy. This superior performance demonstrates that the RF model can more fully explore potential patterns in data through the nonlinear interaction of environmental variables. Overall, the RF model, incorporating multiple environmental variables, proved to be the optimal approach for predicting the organic carbon content in topsoils in Baoqing County, demonstrating high prediction accuracy. This study provides valuable theoretical and methodological insights for assessing the spatial variations in soil organic matter relevant to county-level agricultural production and regional differences in carbon peak and neutrality goals within black soil areas.