Abandoned mine land resource recycling soil pollutant analysis system and method

Abstract

The invention provides an abandoned mine land resource recycling soil pollutant analysis system and method, and the method comprises the steps: recognizing and delineating a plurality of abnormal apparent resistivity regions caused by pollutants as suspected pollution path regions; extracting the apparent resistivity value in the spatial range of each suspected pollution path area and the characteristic pollutant concentration value in the corresponding position and the corresponding depth interval so as to obtain the physicochemical response synergy degree of each suspected pollution path area for representing the physicochemical abnormal spatial coupling degree; and determining the dominant channel index of each suspected pollution path area according to the physicochemical response synergy degree of each suspected pollution path area and the extensibility of the suspected pollution path area on the section along the potential groundwater flow direction, judging the suspected pollution path area with the highest dominant channel index as a pollutant dominant migration channel, and marking in combination with the geological section. By adopting the scheme of the invention, dominant migration path analysis can be carried out on underground pollutants from the perspective of space coupling of a physical field and a chemical field.

Description

Technical Field

[0001] This application relates to the field of soil pollutant analysis technology, and in particular to a soil pollutant analysis system and method for the reuse of abandoned mine land resources. Background Technology

[0002] With my country's increasing emphasis on ecological and environmental protection, the pollution control and safe reuse of land resources in a large number of abandoned mines left over from the past have become urgent tasks. Among them, accurately identifying the dominant migration channels of underground pollutants, such as heavy metals, acidic wastewater, and organic agents, from pollution sources to downstream soil and groundwater environments is the prerequisite and key to implementing efficient and precise monitoring and remediation projects.

[0003] Currently, exploration methods for such problems mainly rely on single technologies or simple combinations of technologies. Commonly used methods include geophysical exploration and geochemical exploration. In recent years, the industry has also attempted to combine geophysical and geochemical methods, but this usually remains at the level of "sequential work and manual comparison," that is, setting up a small number of verification boreholes in geophysical anomaly areas. This combination method lacks systematic data fusion and quantitative analysis logic, and has obvious defects, namely: first, the selection of verification points is subjective and may miss key areas; second, it is impossible to uniformly and quantitatively prioritize multiple anomaly areas; and third, it is difficult to scientifically reveal the dominant transport patterns of pollutants, resulting in insufficient targeting of subsequent remediation projects, such as the placement of monitoring wells and the construction of barrier walls, leading to resource waste and poor remediation effects. Therefore, how to analyze the dominant migration paths of underground pollutants from the perspective of the spatial coupling of physical and chemical fields, so as to provide target locations for setting up groundwater monitoring wells or implementing in-situ barrier remediation projects, has become a challenge for the industry. Summary of the Invention

[0004] Based on this, this application provides a soil pollutant analysis system and method for the reuse of abandoned mine land resources, which analyzes the dominant migration paths of underground pollutants from the perspective of spatial coupling of physical and chemical fields.

[0005] Firstly, this application provides a method for analyzing soil pollutants in the reuse of abandoned mine land resources, used to analyze the dominant migration pathways of pollutants within abandoned mines. The method includes the following steps: Based on the stratigraphic lithology data of abandoned mines, several areas of apparent resistivity anomalies caused by pollutants were identified and delineated as suspected pollution pathways. The apparent resistivity values ​​and characteristic pollutant concentration values ​​at corresponding locations and depths within the spatial range of each suspected pollution path area are extracted. The correlation between the spatial distribution trends of the two is then analyzed to obtain the physicochemical response synergy degree, which characterizes the spatial coupling degree of physicochemical anomalies in each suspected pollution path area. The dominant channel index of each suspected contamination path zone is determined based on the synergy of its physicochemical response and its extension along the potential groundwater flow direction in the profile. The suspected pollution pathway area with the highest dominant channel index is identified as the dominant migration channel for pollutants, and it is marked in conjunction with the geological profile to provide a target location for setting up groundwater monitoring wells or implementing in-situ barrier remediation projects.

[0006] In some embodiments, identifying and delineating multiple areas of apparent resistivity anomalies caused by pollutants as suspected pollution pathway areas based on stratigraphic lithology data of abandoned mines specifically includes: Obtain apparent resistivity profile data and stratigraphic lithology data of abandoned mines; Anomaly detection is performed on the apparent resistivity profile data to extract the apparent resistivity anomaly areas; Based on the stratigraphic lithology data, the extracted apparent resistivity anomaly areas are filtered for their origins, and then anomaly areas unrelated to non-contaminated geological bodies are delineated as suspected contamination pathway areas.

[0007] In some embodiments, anomaly detection of the apparent resistivity profile data and extraction of apparent resistivity anomaly regions specifically includes: Determine the background resistivity statistical characteristic value of the apparent resistivity profile data; Based on the aforementioned background resistivity statistical characteristic values, anomaly judgment thresholds for relatively high resistance and relatively low resistance are set. Based on the anomaly determination threshold, the apparent resistivity profile data is segmented to extract and delineate independent apparent resistivity anomaly regions.

[0008] In some embodiments, extracting the apparent resistivity value and the characteristic pollutant concentration value at the corresponding location and depth range within the spatial range of each suspected contamination path area specifically includes: For each suspected contamination pathway area, geochemical sampling and detection are carried out in the suspected contamination pathway area and its adjacent areas to obtain the concentration data of characteristic pollutants in the suspected contamination pathway area; The concentration data of the characteristic pollutants are registered with the apparent resistivity profile data in terms of spatial location and depth range to construct a spatially aligned chemical anomaly concentration profile. Within the spatial boundary of the suspected contamination pathway area, the registered apparent resistivity values ​​and corresponding characteristic pollutant concentration values ​​are extracted to form a set of data pairs for subsequent correlation analysis.

[0009] In some embodiments, registering the concentration data of the characteristic pollutant with the apparent resistivity profile data in terms of spatial location and depth range to construct a spatially aligned chemical anomaly concentration profile specifically includes: The spatial coordinate system and elevation datum used to unify the concentration data and apparent resistivity profile data of the aforementioned characteristic pollutants; Based on the concentration data of the characteristic pollutants in a unified spatial coordinate system, a continuous two-dimensional concentration distribution profile is reconstructed using a spatial interpolation algorithm. Align the reconstructed concentration distribution profile with the apparent resistivity profile on the grid nodes to generate the spatially aligned chemical anomaly concentration profile.

[0010] In some embodiments, analyzing the correlation between the spatial distribution trends of the two to obtain the physicochemical response synergy degree, which characterizes the spatial coupling degree of physicochemical anomalies in each suspected contamination path area, specifically includes: For each suspected contamination path region, obtain a set of apparent resistivity-concentration data pairs for that region. The apparent resistivity-concentration data in the set are subjected to rank transformation to eliminate dimensional differences and convert them into sequences suitable for nonparametric statistical analysis; Based on the transformed sequence, nonparametric statistics that can characterize the monotonic correlation between apparent resistivity values ​​and characteristic pollutant concentration values ​​are determined. The nonparametric statistics are directly used as the physicochemical response synergy degree of the suspected contamination path region.

[0011] In some embodiments, determining the dominant channel index of each suspected contamination pathway zone based on the synergy of its physicochemical response and its extension along the potential groundwater flow direction in the profile specifically includes: Determine a uniform potential groundwater flow direction within abandoned mines based on topographic and geological data; For each suspected contamination path zone, the projected length of the suspected contamination path zone along the potential groundwater flow direction on the profile is determined as a quantitative indicator of its extensibility. The physical response synergy degree and the projection length are normalized respectively to obtain the corresponding standardized evaluation values; The standardized evaluation value of the physical-chemical response synergy and the standardized evaluation value of the projection length are weighted and summed to obtain the dominant channel index of the suspected contamination path area.

[0012] Secondly, this application provides a soil pollutant analysis system for the reuse of abandoned mine land resources, the system comprising: The identification module is used to identify and delineate multiple areas of apparent resistivity anomalies caused by pollutants as suspected pollution pathway areas based on the stratigraphic lithology data of abandoned mines. The processing module is used to extract the apparent resistivity value and the characteristic pollutant concentration value of the corresponding location and depth range within the spatial range of each suspected pollution path area, and then analyze the correlation between the spatial distribution trends of the two to obtain the physicochemical response synergy degree, which characterizes the degree of spatial coupling of physicochemical anomalies in each suspected pollution path area. The processing module is also used to determine the dominant channel index of each suspected contamination path zone based on the physicochemical response synergy of each suspected contamination path zone and its extension along the potential groundwater flow direction in the profile. The execution module is used to identify the suspected pollution path area with the highest dominant channel index as the dominant migration channel of pollutants, and to mark it in conjunction with the geological profile, so as to provide the target location for setting up groundwater monitoring wells or implementing in-situ barrier remediation projects.

[0013] Thirdly, this application provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of the above-described method for analyzing soil pollutants in the reuse of abandoned mine land resources.

[0014] Fourthly, this application provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the above-described method for analyzing soil pollutants in the reuse of abandoned mine land resources.

[0015] The technical solutions provided by the embodiments disclosed in this application have the following beneficial effects: The soil pollutant analysis system and method for the reuse of abandoned mine land resources provided in this application firstly identifies and delineates multiple areas of apparent resistivity anomalies caused by pollutants as suspected pollution pathway areas based on the stratigraphic lithology data of the abandoned mine. This step can automatically and objectively screen out key target areas related to pollution from wide-area geophysical scanning, and significantly reduce interference from "false anomalies" caused by non-polluted geological bodies such as pure aquifers and clay layers through geological knowledge filtering, thereby improving the targeting and reliability of subsequent exploration work and avoiding ineffective investment. Secondly, the system extracts the soil pollutants within the spatial range of each suspected pollution pathway area. By comparing apparent resistivity values ​​with characteristic pollutant concentrations at corresponding locations and depths, and then analyzing the spatial distribution trends of these two values, the physicochemical response synergy, which characterizes the spatial coupling degree of physicochemical anomalies in each suspected pollution pathway area, is obtained. This step enables precise spatial fusion and quantitative correlation analysis of geophysical and geochemical fields. By calculating the "physicochemical response synergy," which is independent of data distribution, the spatial trend consistency of the two types of data is transformed into comparable quantitative evidence, thereby improving the objectivity and scientific rigor of pollution cause identification and overcoming the limitation of multiple interpretations of single data. Then, based on each suspected pollution pathway... The synergy of the physicochemical response of each potential contamination pathway zone and its extension along the potential groundwater flow direction in the profile are used to determine the dominant channel index for each zone. This step comprehensively evaluates potential channels from two dimensions: "abnormal coupling strength" and "hydrological function." The synergy of the physicochemical response and the extension along the groundwater flow direction are quantified and combined into a unified "dominant channel index," thereby improving the logical rationality and decision support for prioritizing multiple potential areas and making channel identification more consistent with the physical mechanisms of pollutant transport. Finally, the suspected contamination pathway zone with the highest dominant channel index is determined as the dominant contaminant transport zone. The migration pathways are identified and marked on geological profiles to provide target locations for the installation of groundwater monitoring wells or the implementation of in-situ barrier remediation projects. This step directly transforms the quantitative analysis results into intuitive and operable engineering guidance maps. By accurately marking the identified dominant migration pathways and their suggested engineering target locations on the geological profiles, the targeting accuracy, success rate, and treatment benefits of subsequent groundwater monitoring well deployment or in-situ barrier remediation projects are improved, achieving a close connection between technical detection and engineering implementation. In summary, the scheme proposed in this application can analyze the dominant migration paths of underground pollutants from the perspective of the spatial coupling of physical and chemical fields. Attached Figure Description

[0016] Figure 1 This is an exemplary flowchart of a method for analyzing soil pollutants in the reuse of abandoned mine land resources according to some embodiments of this application; Figure 2 This is a schematic diagram illustrating an application scenario of a pollutant dominant migration path analysis data processing system according to some embodiments of this application; Figure 3 This is a flowchart illustrating the determination of the degree of synergy of physical response according to some embodiments of this application; Figure 4 This is a schematic diagram of the structure of a soil pollutant analysis system for the reuse of abandoned mine land resources, as shown in some embodiments of this application; Figure 5 This is a schematic diagram of the structure of a computer device for implementing a method for analyzing soil pollutants in the reuse of abandoned mine land resources, according to some embodiments of this application. Detailed Implementation

[0017] To better understand the above technical solutions, the following will provide a detailed explanation of the technical solutions in conjunction with the accompanying drawings and specific implementation methods.

[0018] refer to Figure 1 The figure is an exemplary flowchart of a method for analyzing soil pollutants in the reuse of abandoned mine land resources according to some embodiments of this application. The method for analyzing soil pollutants in the reuse of abandoned mine land resources mainly includes the following steps: In step 101, based on the stratigraphic lithology data of the abandoned mine, multiple areas of apparent resistivity anomalies caused by pollutants are identified and delineated as suspected pollution pathway areas.

[0019] In some embodiments, identifying and delineating multiple areas of apparent resistivity anomalies caused by pollutants as suspected pollution pathways based on stratigraphic lithology data of abandoned mines can be achieved through the following steps: Obtain apparent resistivity profile data and stratigraphic lithology data of abandoned mines; Anomaly detection is performed on the apparent resistivity profile data to extract the apparent resistivity anomaly areas; Based on the stratigraphic lithology data, the extracted apparent resistivity anomaly areas are filtered for their origins, and then anomaly areas unrelated to non-contaminated geological bodies are delineated as suspected contamination pathway areas.

[0020] It should be noted that the apparent resistivity profile data in this application refers to a two-dimensional profile image dataset that systematically reflects the continuous spatial variation of the conductivity of the subsurface medium after exploration using the high-density resistivity method and inversion calculation. Its function is to provide basic geophysical field information covering the survey area and revealing the heterogeneity of the subsurface electrical structure for the entire method. The stratigraphic lithology data describes the spatial distribution and lithological characteristics of different stratigraphic units within the survey area. Its function is to provide key geological background knowledge and constraints for distinguishing the causes of geophysical anomalies. It is an important basis for judging whether anomalies may be caused by uncontaminated geological bodies, thereby conducting preliminary screening and eliminating false positives. The apparent resistivity anomaly area refers to a continuous spatial area identified from the apparent resistivity profile data whose resistivity value is significantly different from the surrounding background medium. The suspected contamination pathway area refers to a subsurface area that may contain or migrate contaminants, which is screened out after preliminary geophysical scanning and filtering by geological common sense and needs to be further verified by geochemical means.

[0021] In specific implementation, the apparent resistivity profile data and stratigraphic lithology data of abandoned mines can be obtained in the following way: A high-density resistivity survey line is laid out based on the topography and hydrogeological conditions of the abandoned mine; raw apparent resistivity data of the underground medium is collected using multi-electrode measurement; the raw apparent resistivity data is preprocessed to remove distortion points and perform topographic correction; then, a resistivity inversion algorithm, such as smooth constrained least squares inversion, is used to calculate and obtain two-dimensional apparent resistivity profile data reflecting the true electrical structure of the underground. Simultaneously, existing geological survey reports, borehole columnar sections, and hydrogeological maps of the area are collected, and stratigraphic lithology distribution maps are extracted and digitized from them to form the stratigraphic lithology data. Other methods can also be used in other embodiments, and this application does not limit this approach.

[0022] In some embodiments, anomaly detection of the apparent resistivity profile data and extraction of apparent resistivity anomaly regions can be achieved using the following steps: Determine the background resistivity statistical characteristic value of the apparent resistivity profile data; Based on the aforementioned background resistivity statistical characteristic values, anomaly judgment thresholds for relatively high resistance and relatively low resistance are set. Based on the anomaly determination threshold, the apparent resistivity profile data is segmented to extract and delineate independent apparent resistivity anomaly regions.

[0023] It should be noted that the background resistivity statistical characteristic value in this application refers to a statistical quantity used to represent the general electrical level of uncontaminated media in abandoned mines.

[0024] In specific implementation, the background resistivity statistical characteristic value of the apparent resistivity profile data can be determined in the following way: taking the resistivity values ​​of all data points in the two-dimensional apparent resistivity profile data as the overall sample, firstly, an iterative statistical method is used to remove obvious outliers. Specifically, the initial mean and standard deviation of all resistivity values ​​are calculated, and data points whose resistivity values ​​exceed the range of "initial mean plus or minus three times the standard deviation" are removed as outliers. Then, based on the remaining data points, the mean and standard deviation of the resistivity values ​​are recalculated. The recalculated mean is used as the background resistivity mean in the background resistivity statistical characteristic value, and the recalculated standard deviation is used as the background resistivity standard deviation in the background resistivity statistical characteristic value. This process aims to obtain a stable statistical quantity that can represent the general electrical characteristics of the uncontaminated medium in abandoned mines. Other methods can also be used in other embodiments, and this application does not limit them.

[0025] In specific implementation, based on the background resistivity statistical characteristic values, the abnormal judgment thresholds for relatively high resistivity and relatively low resistivity can be set in the following way: taking the average background resistivity in the background resistivity statistical characteristic values ​​as the central benchmark, the range of resistivity values ​​higher than "the average background resistivity plus twice the standard deviation of background resistivity" is defined as the judgment threshold range for relatively high resistivity anomalies; at the same time, the range of resistivity values ​​lower than "the average background resistivity minus twice the standard deviation of background resistivity" is defined as the judgment threshold range for relatively low resistivity anomalies; the multiple of "twice" can be adaptively adjusted according to the actual data variation degree and the survey accuracy requirements, for example, selected between one and three standard deviations. Other methods can also be used in other embodiments, and this application does not limit them.

[0026] In specific implementation, based on the anomaly determination threshold, image segmentation of the apparent resistivity profile data to extract and delineate independent apparent resistivity anomaly regions can be achieved in the following way: The apparent resistivity profile data is treated as a two-dimensional grayscale image, where the pixel values ​​are the resistivity values. First, according to the set anomaly determination thresholds for relative high resistivity and relative low resistivity, the image is binarized. Pixels whose resistivity values ​​fall within the high resistivity threshold range are marked as potential high-resistivity anomaly pixels, and pixels whose resistivity values ​​fall within the low resistivity threshold range are marked as potential low-resistivity anomaly pixels. Then, a connected component analysis algorithm in image processing is used to segment the pixels marked as high-resistivity and low-resistivity anomaly pixels respectively. The low-resistivity pixel set is scanned, and spatially adjacent (using four-connectivity or eight-connectivity rules) pixels of the same type are grouped together to form connected pixel clusters. Each such connected pixel cluster is identified as an independent abnormal region with a clear spatial boundary if its area (i.e., the number of pixels it contains) is greater than a preset minimum area threshold, for example, equivalent to an actual area greater than 10 square meters. This is an extracted apparent resistivity abnormal region. Finally, the spatial coordinates and boundary range of all independent apparent resistivity abnormal regions that meet the area condition are output. Other methods can be used in other embodiments, and this application does not limit them.

[0027] It should be noted that the minimum area threshold in this application needs to be set in conjunction with the accuracy of the geophysical exploration and the minimum resolvable size of the target geological body. Specifically, it can be determined in the following way: First, based on the electrode spacing and measurement depth of the high-density resistivity method, estimate the spatial resolution of the apparent resistivity profile data. Typically, this is 1-1.5 times the electrode spacing; then, the minimum area threshold is set to the minimum area on the profile that reflects a geological anomaly with a certain continuity and scale, which may constitute a pollution migration path, such as a fracture zone or a pollution plume; a practical method is to set the threshold to ,in This is an empirical coefficient, typically ranging from 4 to 10, to ensure that isolated small anomalies mainly caused by random noise or local heterogeneity are filtered out, while retaining anomaly areas with analytical value. The threshold can be used as an adjustable parameter in data processing software, adjusted according to the electrical background noise level of the actual exploration area and the exploration target. In other embodiments, automatic methods such as image morphological opening operations can also be used to remove small-area anomalies; this application does not limit this approach. In specific implementation, the extraction of apparent resistivity anomaly areas based on the stratigraphic lithology data is subjected to causal filtering, and anomaly areas unrelated to non-contaminated geological bodies are then delineated as suspected contamination pathway areas. This can be achieved in the following manner, wherein the causal filtering of the extracted apparent resistivity anomaly areas based on the stratigraphic lithology data can be determined using the following rules: a. If the apparent resistivity anomaly zone is located entirely within the thick, continuously distributed clay or silty clay layer region identified by the stratigraphic lithology data, and its resistivity exhibits a uniform low resistivity characteristic, then the anomaly is determined to be caused by a low-resistivity clay layer and is filtered out. The thickness of the thick layer is greater than a preset value, such as 2 meters, and the low resistivity characteristic is that the resistivity value is lower than the average background resistivity value minus one standard deviation. b. If the apparent resistivity anomaly zone is located entirely within the intact bedrock area and exhibits isolated high resistivity characteristics, and there are no known pollution sources or tectonic fracture zones in the surrounding area, then the anomaly is determined to be caused by a high resistivity bedrock mass and is filtered out. The intact bedrock is such as unweathered granite or limestone, and the high resistivity characteristic is that the resistivity value is higher than the average background resistivity plus one standard deviation. c. If the spatial location of the apparent resistivity anomaly zone highly overlaps with the known distribution area of ​​pure, saturated sand and gravel aquifers, and its resistivity value is within the typical low to medium resistivity range of that aquifer, then the anomaly is determined to be caused by a clean aquifer and should be filtered out. d. For apparent resistivity anomaly areas that do not meet the above rules a, b, and c, especially those located in lithologically complex areas, known goaf areas, waste rock piles, or downstream of tailings ponds, or whose resistivity anomaly morphology cannot be reasonably explained by known clean lithology, they are retained and delineated as suspected contamination pathway areas. The resistivity anomaly morphology is such as strip-shaped or funnel-shaped. In other embodiments, a more detailed electrical-lithological knowledge base can be established or machine learning models can be used for automatic genetic classification. This application does not limit this.

[0028] It should be noted that the above steps automatically and objectively screen out key target areas related to pollution from the wide-area geophysical scan, and significantly reduce the interference of "false anomalies" caused by non-polluted geological bodies such as pure aquifers and clay layers through geological knowledge filtering, thereby improving the pertinence and reliability of the starting point of subsequent exploration work and avoiding ineffective investment.

[0029] In some embodiments, reference Figure 2 As shown in the figure, this figure is a schematic diagram of the application scenario of the pollutant dominant migration path analysis data processing system shown in some embodiments of this application. The figure includes three main components: acquisition equipment, server and data storage equipment. The acquisition equipment is responsible for collecting stratigraphic lithology data of abandoned mines and sending the collected stratigraphic lithology data of abandoned mines to the server through a communication network. The pollutant dominant migration path analysis data processing system runs on the server. The server stores the processing results in the data storage equipment and visualizes them.

[0030] In step 102, the apparent resistivity value and the characteristic pollutant concentration value of the corresponding location and depth range within the spatial range of each suspected pollution path area are extracted, and then the correlation between the spatial distribution trends of the two is analyzed to obtain the physicochemical response synergy degree, which characterizes the spatial coupling degree of physicochemical anomalies in each suspected pollution path area.

[0031] In some embodiments, extracting the apparent resistivity values ​​and corresponding characteristic pollutant concentration values ​​at corresponding locations and depths within the spatial range of each suspected contamination path area can be achieved using the following steps: For each suspected contamination pathway area, geochemical sampling and detection are carried out in the suspected contamination pathway area and its adjacent areas to obtain the concentration data of characteristic pollutants in the suspected contamination pathway area; The concentration data of the characteristic pollutants are registered with the apparent resistivity profile data in terms of spatial location and depth range to construct a spatially aligned chemical anomaly concentration profile. Within the spatial boundary of the suspected contamination pathway area, the registered apparent resistivity values ​​and corresponding characteristic pollutant concentration values ​​are extracted to form a set of data pairs for subsequent correlation analysis.

[0032] It should be noted that the chemical anomaly concentration profile in this application refers to a two-dimensional continuous concentration distribution image in which the pollutant concentration data collected at discrete points are strictly aligned with the apparent resistivity profile in spatial location. Its function is to realize the spatial visualization overlay and point-by-point comparison of the geochemical field and the geophysical field. The apparent resistivity value is a physical quantity that characterizes the conductivity of the medium at a certain point underground. It is the basic data reflecting the change in electrical properties of the underground medium caused by the presence of pollutants or changes in geological structure. The characteristic pollutant concentration value is a chemical quantity that characterizes the level of a specific pollutant in the soil or groundwater.

[0033] In practice, geochemical sampling and testing are conducted in the suspected contamination pathway area and its adjacent areas to obtain the concentration data of characteristic pollutants in the suspected contamination pathway area. This can be achieved in the following way: taking the spatial boundary range of each suspected contamination pathway area delineated in the previous step as the core, soil or groundwater sampling points are arranged in a dense grid along the corresponding geophysical probe direction. The sampling points cover the background control area within and outside the anomaly area. Using lightweight drilling equipment, undisturbed soil column samples or pore water samples are collected at different depths at each sampling point. The sampling depth range should at least cover the shallow vadose zone and the water table. The sampling process involves identifying undulating zones and shallow aquifers to ensure the capture of pollutant distribution characteristics in the vertical direction. Subsequently, portable rapid detection equipment is used for real-time analysis of the samples. For common pollutant types in abandoned mines, a portable X-ray fluorescence spectrometer is used to determine the concentration of heavy metal elements such as arsenic, lead, cadmium, and zinc. A portable gas chromatography-mass spectrometry or photoionization detector is used to determine the concentration of volatile organic pollutants, thereby obtaining the concentration data of characteristic pollutants at different depths for each sampling point. In other embodiments, laboratory analysis or other on-site detection methods can also be used, which is not limited in this application.

[0034] In some embodiments, the spatial location and depth range registration of the concentration data of the characteristic pollutant with the apparent resistivity profile data to construct a spatially aligned chemical anomaly concentration profile can be achieved through the following steps: The spatial coordinate system and elevation datum used to unify the concentration data and apparent resistivity profile data of the aforementioned characteristic pollutants; Based on the concentration data of the characteristic pollutants in a unified spatial coordinate system, a continuous two-dimensional concentration distribution profile is reconstructed using a spatial interpolation algorithm. Align the reconstructed concentration distribution profile with the apparent resistivity profile on the grid nodes to generate the spatially aligned chemical anomaly concentration profile.

[0035] It should be noted that the concentration distribution profile in this application is a two-dimensional image that reflects the continuous spatial variation trend of pollutant concentration, which is initially reconstructed through spatial interpolation. It is an intermediate product generated during the construction of the chemical anomaly concentration profile.

[0036] In specific implementation, the spatial coordinate system and elevation datum used to unify the concentration data of the characteristic pollutants and the apparent resistivity profile data can be achieved in the following way: First, determine the plane coordinate system and elevation datum used in geophysical surveys. The plane coordinate system is such as the specific projection zone coordinates of the National Geodetic Coordinate System CGCS2000, and the elevation datum is such as the 1985 National Elevation Datum. Subsequently, during geochemical sampling, use a Global Navigation Satellite System (GNSS) receiver of the same model or with the same precision as the geophysical survey to perform real-time differential positioning on each sampling point, directly obtaining its coordinates in the same plane coordinate system, and using a level or combining the elevation measurement function of the GNSS to obtain its elevation in the same elevation datum. For all sampling points, their position information, including plane coordinates and elevation, is uniformly converted to a coordinate system and elevation datum that is exactly the same as that of the apparent resistivity profile data, thereby ensuring that the concentration data of the characteristic pollutants and the apparent resistivity profile data have a consistent spatial reference frame. Other methods can also be used in other embodiments, and this application does not limit them.

[0037] In specific implementation, based on the concentration data of the characteristic pollutants in a unified spatial coordinate system, the reconstruction of a continuous two-dimensional concentration distribution profile using a spatial interpolation algorithm can be achieved in the following way: First, establish a one-to-one correspondence between the characteristic pollutant concentration values ​​obtained at different depths for each sampling point and their unified three-dimensional spatial coordinates, i.e., the horizontal distance and depth along the survey line, to form a three-dimensional discrete dataset; then, for the target depth range, select a two-dimensional profile formed by the survey line direction and the vertical depth direction as the interpolation region, and use the Kriging spatial interpolation algorithm to estimate the concentration within this interpolation region. Specifically, the variation characteristics of discrete concentration data in two-dimensional space are analyzed, and the optimal semi-variogram model, such as the spherical model or the exponential model, is fitted. The corresponding range, nugget value, and sill value parameters are determined. Then, based on the model, the ordinary kriging method is used to calculate the optimal unbiased estimate of the concentration of characteristic pollutants at each regular grid node on the profile. Finally, a two-dimensional raster image reflecting the spatial distribution trend of pollutant concentration is generated, which is composed of continuous grid node values. That is, a continuous two-dimensional concentration distribution profile is reconstructed. Other methods can be used in other embodiments, and this application does not limit them.

[0038] In specific implementation, aligning the reconstructed concentration distribution profile with the apparent resistivity profile on the grid nodes to generate the spatially aligned chemical anomaly concentration profile can be achieved as follows: Obtain the grid definition parameters of the apparent resistivity profile data, including the profile start point coordinates, profile azimuth angle, horizontal grid spacing, and vertical grid layering information; using these as a standard, perform grid resampling processing on the aforementioned reconstructed concentration distribution profile. Specifically, for the center point coordinates of each grid node of the apparent resistivity profile, calculate its corresponding position in the reconstructed concentration distribution profile raster image, and use bilinear... The concentration estimate at the corresponding node position is extracted from the concentration distribution profile raster image by interpolation. After traversing and interpolating all apparent resistivity profile grid nodes, a brand new concentration profile is obtained. This brand new concentration profile has the same number of grid nodes, node spatial position, and depth layering as the apparent resistivity profile, that is, the two are spatially aligned node by node. This final concentration profile, which strictly matches the apparent resistivity profile grid, is the spatially aligned chemical anomaly concentration profile. Other methods can be used in other embodiments, and this application does not limit them.

[0039] In specific implementation, extracting the registered apparent resistivity values ​​and corresponding characteristic pollutant concentration values ​​from the spatial boundary of the suspected contamination path area to form a data pair set for subsequent correlation analysis can be achieved in the following way: For each suspected contamination path area, its delineated spatial boundary range is used as a spatial mask and applied to the spatially registered apparent resistivity profile and chemical anomaly concentration profile; at each node with the same horizontal coordinate and the same depth interval within the spatial boundary range, the data values ​​corresponding to the two profiles are read simultaneously: one value is the apparent resistivity value at that location, and the other value is the characteristic pollutant concentration value at that location; such a pair of data with a clear spatial coordinate correlation is recorded as a record, and all valid spatial nodes within the boundary of the anomaly area are traversed to finally form a data pair set of apparent resistivity-concentration specific to the suspected contamination path area; this set is the direct input data for the next step of analyzing the correlation between the spatial distribution trends of the two to calculate the physicochemical response synergy. In other embodiments, batch data export or automatic extraction by programming can also be used, which is not limited in this application.

[0040] In some embodiments, reference Figure 3 As shown in the figure, this is a flowchart illustrating the determination of physicochemical response synergy in some embodiments of this application. In this embodiment, the correlation between the spatial distribution trends of the two is analyzed, and the physicochemical response synergy, which characterizes the degree of spatial coupling of physicochemical anomalies in each suspected contamination path area, can be obtained by the following steps: In step 1031, for each suspected contamination path area, a set of apparent resistivity-concentration data pairs for the suspected contamination path area is obtained; In step 1032, the data in the apparent resistivity-concentration data set are subjected to rank transformation to eliminate dimensional differences and convert them into a sequence suitable for nonparametric statistical analysis; In step 1033, a nonparametric statistic that can characterize the monotonic correlation between apparent resistivity values ​​and characteristic pollutant concentration values ​​is determined based on the transformed sequence; In step 1034, the nonparametric statistics are directly used as the physicochemical response synergy degree of the suspected contamination path region.

[0041] It should be noted that the nonparametric statistics in this application are mathematical indicators used to measure the strength and direction of the monotonic correlation between two variable sequences. Their function is to robustly quantify the statistical correlation of the spatial trends of geophysical and geochemical data. The physicochemical response synergy is a comprehensive indicator used to quantify the degree of consistency between the distribution trends of apparent resistivity anomalies and pollutant concentration anomalies within the same spatial range. Its absolute value represents the coupling strength, and its sign represents the coupling direction (positive / negative correlation). It is a key fusion evidence for determining whether geophysical anomalies are caused by pollution.

[0042] In specific implementation, the rank transformation of the data in the apparent resistivity-concentration data set to eliminate dimensional differences and convert it into a sequence suitable for nonparametric statistical analysis can be achieved in the following way: All apparent resistivity values ​​and all characteristic pollutant concentration values ​​in the data set are sorted independently; for the apparent resistivity value sequence, all values ​​are arranged in ascending order, and the ranking position of each value is assigned to it. If the values ​​are the same, the average of the positions occupied by these identical values ​​is taken as their common rank; the characteristic pollutant concentration value sequence is processed using the same independent sorting and rank allocation rules; after this process, the original apparent resistivity values ​​and concentration values ​​with different physical units and magnitudes are converted into rank sequences that only represent their relative size and position in the current sequence, thereby eliminating the dimensional differences and non-normal distribution effects of the original data, resulting in two columns of equal length, one-to-one corresponding rank data, i.e., the converted sequence suitable for nonparametric statistical analysis. Other methods can also be used in other embodiments, and this application does not limit them.

[0043] In specific implementation, determining the nonparametric statistic that characterizes the monotonic correlation between apparent resistivity values ​​and characteristic pollutant concentration values ​​based on the transformed sequence can be achieved as follows: The Spearman rank correlation coefficient method is used to determine the nonparametric statistic. Specifically, first, the difference between each pair of apparent resistivity ranks and concentration value ranks in the transformed sequence is calculated, and then each difference is squared. Next, the squares of all differences are summed to obtain the sum of squares. Subsequently, according to the Spearman rank correlation coefficient calculation formula, the sum of squares and the total number of data pairs are used to calculate the final result. A value between -1 and 1 is the Spearman rank correlation coefficient. This Spearman rank correlation coefficient is the nonparametric statistic that can characterize monotonic correlation. Its absolute value indicates the strength of the monotonic correlation between apparent resistivity and pollutant concentration in spatial distribution trends. Its positive or negative sign indicates the direction of this correlation, i.e., positive or negative correlation. This nonparametric statistic does not require the original data to meet the assumption of normal distribution or linear relationship. It is suitable for analyzing the spatial trend correlation between geophysical and geochemical data. Other methods can be used in other embodiments, and this application does not limit them.

[0044] It should be noted that, in order to ensure the statistical reliability of the physicochemical response synergy, this application, after calculating the nonparametric statistics, also includes a step of performing a statistical significance test on the correlation coefficient. Specifically, this can be achieved by: based on the number of data pairs in the apparent resistivity-concentration data set... and the preset significance level ,For example Query the Spearman rank correlation coefficient critical value table to obtain the value at the significance level. The critical value below If the calculated If the correlation coefficient is statistically significant, then it will be determined that the correlation coefficient is statistically significant. The value is directly used as the physicochemical response synergy of the suspected contamination pathway area; if If the correlation coefficient is not statistically significant, the physical-chemical response synergy of the suspected contamination path area is assigned to zero or a preset value that represents no significant correlation. By introducing a statistical significance test, weak or false correlations caused by random data fluctuations can be effectively distinguished from true physical-chemical spatial coupling, thereby improving the credibility of the physical-chemical response synergy as evaluation evidence. In other embodiments, the t-test or other non-parametric test methods can also be used for significance judgment, which is not limited in this application.

[0045] In addition, it should be noted that the above steps achieve precise spatial fusion and quantitative correlation analysis of geophysical and geochemical fields. By calculating the "physicochemical response synergy" that is independent of data distribution, the spatial trend consistency of the two types of data is transformed into comparable quantitative evidence, thereby improving the objectivity and scientificity of pollution cause identification and overcoming the defect of strong ambiguity of single data.

[0046] In step 103, the dominant channel index of each suspected contamination path zone is determined based on the physicochemical response synergy of each suspected contamination path zone and its extension along the potential groundwater flow direction in the profile.

[0047] In some embodiments, determining the dominant channel index of each suspected contamination pathway zone based on the synergy of its physicochemical response and its extension along the potential groundwater flow direction in the profile can be achieved through the following steps: Based on topographic and geological structure data, a unified potential groundwater flow direction was determined within the abandoned mine; For each suspected contamination path zone, the projected length of the suspected contamination path zone along the potential groundwater flow direction on the profile is determined as a quantitative indicator of its extensibility. The physical response synergy degree and the projection length are normalized respectively to obtain the corresponding standardized evaluation values; The standardized evaluation value of the physical-chemical response synergy and the standardized evaluation value of the projection length are weighted and summed to obtain the dominant channel index of the suspected contamination path area.

[0048] It should be noted that the dominant pathway index in this application is a composite evaluation index that integrates the synergy of physical and chemical response and the extension along the groundwater flow direction. Its function is to prioritize all suspected areas in order to identify the pathways most likely to become the main transport routes of pollutants.

[0049] In some embodiments, determining the uniform potential groundwater flow direction within an abandoned mine based on topographic and geological structure data can be achieved through the following steps: Obtain digital elevation model data and geological structure maps of abandoned mines; Analyze the digital elevation model data to extract the confluence trend of surface water systems and the direction of terrain slope in abandoned mines; Based on the geological structure map, identify the occurrence of the main aquifer strata and the trend of the dominant structural lines in the abandoned mine; Based on the confluence trend, the topographic slope direction, the stratum occurrence, and the orientation of the dominant structural line, a unified potential groundwater flow direction within the abandoned mine is determined.

[0050] It should be noted that the confluence trend in this application refers to trend information characterizing the overall convergence and flow direction of surface water bodies, and its function is to provide macroscopic surface hydrological basis for inferring the potential groundwater flow field in a region; the topographic slope direction refers to the main direction of the overall slope of a region's surface, and its function is to serve as an important topographic factor indicating the potential trend of groundwater flow, usually related to the direction of groundwater potential energy reduction; the rock strata attitude refers to the three-dimensional spatial orientation information of underground rock strata, and its function is to reveal, from the geological structure level, the dominant direction in which the rock strata themselves may control or influence groundwater flow; the dominant structural line orientation refers to the extension orientation of the largest and longest linear geological structures such as faults and fracture zones in the survey area, and its function is to identify the direction of key geological structures that may become high-speed groundwater transport channels or control water flow boundaries.

[0051] In specific implementation, the acquisition of digital elevation model data and geological structure maps of abandoned mines can be achieved in the following ways: Digital elevation model data of abandoned mines can be obtained from national or provincial basic geographic information centers and relevant surveying and mapping departments. This digital elevation model data is usually stored in the form of a regular grid, and the accuracy can be selected according to the survey range, such as a grid resolution of 5 meters or 10 meters. At the same time, regional geological maps, hydrogeological maps and existing geological exploration reports compiled by geological and mineral departments are collected, and geological structure elements are extracted and digitized to form digital geological structure maps containing information such as stratigraphic boundaries, fault lines and rock strata attitude symbols. Other methods can also be used in other embodiments, and this application does not limit them.

[0052] In specific implementation, the analysis of the digital elevation model data to extract the confluence trend and topographic slope direction of the surface water system in abandoned mines can be achieved in the following way: The hydrological analysis tools of geographic information system software are used to process the digital elevation model data. First, depression filling is performed to eliminate data depressions. Second, a standard water flow direction algorithm, such as the D8 single-direction algorithm, is used to calculate the water flow direction of each grid cell, obtaining water flow direction data. The principle of the D8 single-direction algorithm is: for the central grid, its elevation difference with the eight surrounding adjacent grids is compared, and the water flow direction is assigned to the direction of the adjacent grid with the largest elevation difference. Subsequently, based on the obtained water flow direction data, a confluence accumulation algorithm is used for calculation, that is, starting from all grid cells, following the water flow direction, each grid cell is connected... The number of all upstream grids (including itself) is accumulated, and this accumulated value is the cumulative runoff of each grid cell, which simulates the upstream catchment area flowing through that point. Then, by setting a cumulative runoff threshold, for example, more than 500 grid cells, grids with cumulative runoff exceeding the threshold are connected to identify and extract the main surface water network. Finally, the overall structure of the surface water network is analyzed, especially the extension direction of the main stream, as the runoff trend of the surface water system. At the same time, the surface slope and aspect of the entire area are calculated using digital elevation model data, and the topographic slope direction, i.e., the main direction of the overall topographic tilt, is determined through statistical analysis (such as aspect rose diagram). Other methods can also be used in other embodiments, and this application does not limit them.

[0053] In specific implementation, based on the geological structure map, the identification of the strata attitude and dominant structural line orientation of the main aquifer in the abandoned mine can be achieved in the following way: On the digitized geological structure map, locate and identify the distribution range of the main aquifer in the abandoned mine, such as gravel layers, fractured bedrock, etc.; read the strata attitude symbols marked on the geological structure map for the main aquifer, usually represented by strike, dip, and dip angle, thereby determining its strata attitude; at the same time, identify the largest and longest fault or large fracture zone on the geological structure map, define it as the dominant structural line, and measure its extension direction on the geological map, i.e., the orientation of the dominant structural line. In other embodiments, other methods can also be used, and this application does not limit them.

[0054] In practice, determining the unified potential groundwater flow direction within an abandoned mine, based on the aforementioned confluence trend, topographic slope direction, stratum attitude, and dominant structural line orientation, can be achieved in the following way: The extracted surface water system confluence trend and topographic slope direction are used as important surface references indicating the overall flow direction of shallow groundwater; simultaneously, the stratum attitude (especially stratum dip) and dominant structural line orientation of the main aquifers are used as key underground geological factors controlling deep groundwater flow; by comprehensively comparing these four directional information, if they exhibit a high degree of consistency, such as topographic slope aspect, water system confluence direction, stratum dip, and structural orientation... If the lines generally point to the same direction, then that direction is determined as the unified potential groundwater flow direction within the abandoned mine. If there are differences, i.e., when the hydrogeological structure of the abandoned mine is complex, with multiple independent hydrogeological units or significant changes in the direction of the groundwater flow field, then according to the principles of hydrogeology, the attitude of the rock strata and the direction of the dominant structural lines that reflect the control of the underground structure are given greater weight, and combined with topographic information, a representative water flow direction for the whole area is finally determined as the unified potential groundwater flow direction in the form of angle value or direction description. Other methods can also be used in other embodiments, and this application does not limit them.

[0055] It should be noted that in some implementations, when the hydrogeological structure of abandoned mines is complex, with multiple independent hydrogeological units or significant changes in the direction of groundwater flow, the potential direction of groundwater flow can be determined by regional or profile-based methods. Specifically, this can be achieved through the following steps: Based on the digital elevation model, geological structural zoning, and borehole hydrogeological data, the entire abandoned mine study area is divided into several sub-regions with relatively uniform hydrogeological characteristics; for each sub-region, independently, the following analysis is performed: the topographic slope direction, surface water confluence trend, the occurrence of major aquifer strata, and the orientation of structural lines within the sub-region are analyzed to comprehensively determine the direction of groundwater flow within that sub-region. The potential groundwater flow direction is determined accordingly. When calculating the projected length of each suspected contaminated path zone, the potential groundwater flow direction determined by the sub-zone where the suspected contaminated path zone is located is used. If a suspected contaminated path zone spans multiple sub-zones, the direction of the sub-zone to which its center point belongs can be taken, or the weighted value of its projected length under different sub-zone directions can be calculated. This method enhances its adaptability to complex hydrogeological conditions, making the evaluation of the dominant channel index more consistent with the actual groundwater dynamic field characteristics. In other embodiments, a spatially continuous flow direction field can also be obtained through groundwater flow numerical simulation, which is not limited in this application.

[0056] In specific implementation, the projection length of the suspected contamination path zone along the potential groundwater flow direction on the cross-section can be determined as a quantitative indicator of its extensibility. This can be achieved in the following way: On a two-dimensional cross-sectional view containing all suspected contamination path zones, the two-dimensional cross-sectional view includes horizontal distance and depth coordinate axes, and an arrow indicating the unified potential groundwater flow direction is drawn. For each suspected contamination path zone, the boundary of the abnormal area already delineated on the two-dimensional cross-sectional view is projected along a direction perpendicular to the arrow line of the water flow direction, onto a straight line parallel to the arrow line of the water flow direction. The length of the line segment covered by the projection of the abnormal area on this straight line is measured. This line segment length is defined as the projection length of the corresponding suspected contamination path zone along the potential groundwater flow direction on the cross-section. This projection length quantifies the spatial distribution scale of the abnormal area corresponding to the suspected contamination path zone along the possible hydraulic migration direction. Other methods can also be used in other embodiments, and this application does not limit them.

[0057] In specific implementation, the normalization of the physical response synergy degree and the projection length to obtain the corresponding standardized evaluation value can be achieved in the following way: First, collect the physical response synergy degree values ​​of all suspected contamination path areas and find the maximum and minimum values; then, for any suspected contamination path area, subtract the minimum value of all synergy degrees from its physical response synergy degree value, and then divide by the difference between the maximum and minimum values ​​of all synergy degrees to calculate the standardized evaluation value of the physical response synergy degree of the suspected contamination path area. This standardized evaluation value will fall within the range of 0 to 1; using the same method, based on the projection length data of all suspected contamination path areas, find the maximum and minimum values ​​and calculate the standardized evaluation value of the projection length of each suspected contamination path area. Other methods can also be used in other embodiments, and this application does not limit them.

[0058] In specific implementation, the standardized evaluation value of the physical-chemical response synergy and the standardized evaluation value of the projection length are weighted and summed to obtain the dominant channel index of the suspected pollution path area. This can be achieved in the following way: based on the formation mechanism of the pollution dominant migration channel, the standardized evaluation value of the physical-chemical response synergy is used. Assign weights , which is the standardized evaluation value of the projection length. Assign weights ,in The specific weights can be determined using one of the following methods: Method 1: Empirical assignment. Based on domain knowledge, since the synergy of physical response directly characterizes the strength of evidence of pollution presence, it is usually assigned a higher weight. For example, setting... Between 0.6 and 0.7, correspondingly Between 0.3 and 0.4, Method Two employs objective weighting, based on historical case data or an evaluation matrix of multiple suspected contamination pathways within the same site, using the entropy weighting method to determine weights. Specifically, this involves constructing a weighting matrix composed of all suspected contamination pathways. and The evaluation matrix is ​​composed of two indicators. The entropy values ​​of the two indicators are calculated separately. The difference coefficients are then calculated based on the entropy values. Finally, the difference coefficients are normalized to obtain the objective weights. and For suspected contamination pathway areas, their dominant channel index According to the formula It is calculated that, in other embodiments, the analytic hierarchy process, the coefficient of variation method, or the weights can be dynamically adjusted according to specific remediation goals, such as priority blocking or priority monitoring. This application does not limit this to any particular approach.

[0059] It should be noted that the above steps comprehensively evaluate potential channels from two dimensions: "abnormal coupling strength" and "hydrological function". The physical and chemical response synergy and the extension along the groundwater flow direction are quantitatively combined into a unified "dominant channel index", thereby improving the logical rationality and decision support of prioritizing multiple suspected areas and making channel identification more consistent with the physical mechanism of pollutant transport.

[0060] In step 104, the suspected pollution path area with the highest dominant channel index is identified as the dominant migration channel of pollutants, and it is marked in conjunction with the geological profile to provide a target location for setting up groundwater monitoring wells or implementing in-situ barrier remediation projects.

[0061] In some embodiments, identifying the suspected contamination pathway area with the highest dominant channel index as the dominant migration channel for pollutants, and marking it in conjunction with geological profiles, can provide target locations for setting up groundwater monitoring wells or implementing in-situ barrier remediation projects. This can be achieved through the following steps: The dominant channel index of all suspected contamination pathway areas is sorted and screened to determine the suspected contamination pathway area with the highest dominant channel index. The suspected pollution pathways identified are determined as dominant migration channels for pollutants, and the spatial feature information of these dominant migration channels is extracted. The spatial feature information is superimposed and annotated onto the geological profile map of the abandoned mine to form a comprehensive result map to guide the implementation of the project, providing a target location for setting up groundwater monitoring wells or implementing in-situ barrier remediation projects.

[0062] In specific implementation, the dominant channel index of all suspected contamination path areas is sorted and screened to determine the suspected contamination path area with the highest dominant channel index. This can be achieved by sorting the dominant channel indices of all suspected contamination path areas in descending order of value to determine the suspected contamination path area with the highest dominant channel index. Other methods can also be used in other embodiments, and this application does not limit them.

[0063] In specific implementation, the selected suspected pollution path areas are identified as dominant pollutant migration channels, and the spatial feature information of the dominant pollutant migration channels is extracted. This can be achieved in the following way: the selected suspected pollution path areas are formally assigned the attribute label of dominant pollutant migration channels; then, for the suspected pollution path areas corresponding to the dominant pollutant migration channels, the planar distribution range and spatial location are extracted from the abnormal area boundary data delineated in step 101, the corresponding potential groundwater flow direction is extracted from the water flow direction data determined in step 104, and the specific value is extracted from the dominant channel index data calculated in step 104. These data, namely spatial location, boundary range, dominant channel index, and potential groundwater flow direction, are integrated into the spatial feature information of the dominant pollutant migration channel. In other embodiments, additional information such as the center point coordinates, area, and major axis direction can also be extracted, but this application does not limit this.

[0064] In practice, the spatial feature information is overlaid and annotated onto the geological profile of the abandoned mine to form a comprehensive result map guiding the project implementation. This map provides target locations for setting up groundwater monitoring wells or implementing in-situ barrier remediation projects. This can be achieved in the following way: First, obtain a base map of the geological profile of the abandoned mine, which includes stratigraphic boundaries, lithological symbols, and necessary scale and legend. Then, using a geographic information system or professional mapping software, the spatial feature information of the extracted dominant pollutant migration channels is overlaid onto the base map as graphic elements. Specifically, this includes: clearly outlining the boundary of each channel using closed polygons, marking its dominant channel index within or beside the polygons, and... Arrow symbols are used to indicate the potential direction of groundwater flow. Simultaneously, based on a comprehensive consideration of the boundary range, flow direction, and the location of downstream sensitive targets, prominent markings, such as asterisks or drilling rig symbols, are used to clearly indicate the preferred target locations for deploying groundwater monitoring wells or implementing in-situ vertical barrier walls within the channel boundary or at appropriate locations adjacent to the downstream. Finally, the map is refined by adding map titles, descriptions, etc., to generate a comprehensive result map that intuitively displays the spatial distribution of dominant pollutant migration channels and engineering layout recommendations. This comprehensive result map can be directly used to guide the design and construction of subsequent environmental remediation projects. In other embodiments, it can also be presented in the form of three-dimensional visualization or thematic maps; this application does not limit this.

[0065] It should be noted that the above steps directly transform the quantitative analysis results into intuitive and operable engineering guidance maps. By accurately marking the identified advantageous migration channels and their suggested engineering target locations on the geological profile, the targeting accuracy, success rate, and treatment benefits of subsequent groundwater monitoring well deployment or in-situ barrier remediation projects are improved, achieving a close connection between technical detection and engineering implementation.

[0066] In another aspect, in some embodiments, this application provides a soil pollutant analysis system for the reuse of abandoned mine land resources, with reference to... Figure 4 The figure is a schematic diagram of the structure of a soil pollutant analysis system for the reuse of abandoned mine land resources according to some embodiments of this application. The system includes an identification module 401, a processing module 402, and an execution module 403, which are described below: The identification module 401 in this application is mainly used to identify and delineate multiple areas of apparent resistivity anomalies caused by pollutants as suspected pollution pathway areas based on the stratigraphic lithology data of abandoned mines. Processing module 402 in this application is mainly used to extract the apparent resistivity value and the characteristic pollutant concentration value of the corresponding position and depth range within the spatial range of each suspected pollution path area, and then analyze the correlation between the spatial distribution trends of the two to obtain the physicochemical response synergy degree that characterizes the spatial coupling degree of physicochemical anomalies in each suspected pollution path area. The processing module 402 described in this application is further configured to determine the dominant channel index of each suspected contamination path zone based on the physicochemical response synergy of each suspected contamination path zone and its extensibility along the potential groundwater flow direction in the profile; The execution module 403 in this application is mainly used to identify the suspected pollution path area with the highest dominant channel index as the dominant migration channel of pollutants, and to mark it in conjunction with the geological profile, so as to provide a target location for setting up groundwater monitoring wells or implementing in-situ barrier remediation projects.

[0067] Each module in the aforementioned soil pollutant analysis system for the reuse of abandoned mine land resources can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device, or stored in the computer device's memory as software, so that the processor can call and execute the corresponding operations of each module.

[0068] In another embodiment, this application provides a computer device, which may be a server, and its internal structure diagram may be as follows. Figure 5As shown, the computer device includes a processor, memory, and a network interface connected via a system bus. The processor provides computational and control capabilities. The memory includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage medium. The database stores soil pollutant analysis data for the reuse of abandoned mine land resources. The network interface communicates with external terminals via a network connection. When executed by the processor, the computer program implements a method for analyzing soil pollutants in the reuse of abandoned mine land resources.

[0069] Those skilled in the art will understand that Figure 5 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0070] In one embodiment, a computer device is also provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps in the above-described embodiment of the method for analyzing soil pollutants for the reuse of abandoned mine land resources.

[0071] In one embodiment, a computer-readable storage medium is provided storing a computer program that, when executed by a processor, implements the steps in the above-described embodiment of the method for analyzing soil pollutants in the reuse of abandoned mine land resources.

[0072] In one embodiment, a computer program product or computer program is provided, comprising computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform the steps described in the embodiment of the method for analyzing soil pollutants in the reuse of abandoned mine land resources.

[0073] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the methods described above. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, or optical storage, etc. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc.

[0074] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0075] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the invention patent. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this patent application should be determined by the appended claims.

Claims

1. A method for analyzing soil pollutants in the reuse of abandoned mine land resources, used to analyze the dominant migration pathways of pollutants within abandoned mines, characterized in that... The method includes the following steps: Based on the stratigraphic lithology data of abandoned mines, several areas of apparent resistivity anomalies caused by pollutants were identified and delineated as suspected pollution pathways. The apparent resistivity values ​​and characteristic pollutant concentration values ​​at corresponding locations and depths within the spatial range of each suspected pollution path area are extracted. The correlation between the spatial distribution trends of the two is then analyzed to obtain the physicochemical response synergy degree, which characterizes the spatial coupling degree of physicochemical anomalies in each suspected pollution path area. The dominant channel index of each suspected contamination path zone is determined based on the synergy of its physicochemical response and its extension along the potential groundwater flow direction in the profile. The suspected pollution pathway area with the highest dominant channel index is identified as the dominant migration channel for pollutants, and it is marked in conjunction with the geological profile to provide a target location for setting up groundwater monitoring wells or implementing in-situ barrier remediation projects.

2. The method as described in claim 1, characterized in that, Based on the stratigraphic and lithological data of abandoned mines, several areas of apparent resistivity anomalies caused by pollutants were identified and delineated as suspected pollution pathways, including: Obtain apparent resistivity profile data and stratigraphic lithology data of abandoned mines; Anomaly detection is performed on the apparent resistivity profile data to extract the apparent resistivity anomaly areas; Based on the stratigraphic lithology data, the extracted apparent resistivity anomaly areas are filtered for their origins, and then anomaly areas unrelated to non-contaminated geological bodies are delineated as suspected contamination pathway areas.

3. The method as described in claim 2, characterized in that, Anomaly detection is performed on the apparent resistivity profile data, and the specific extraction of apparent resistivity anomaly regions includes: Determine the background resistivity statistical characteristic value of the apparent resistivity profile data; Based on the aforementioned background resistivity statistical characteristic values, anomaly judgment thresholds for relatively high resistance and relatively low resistance are set. Based on the anomaly determination threshold, the apparent resistivity profile data is segmented to extract and delineate independent apparent resistivity anomaly regions.

4. The method as described in claim 1, characterized in that, Extracting the apparent resistivity values ​​and corresponding characteristic pollutant concentration values ​​at the corresponding locations and depth ranges within each suspected contamination path area specifically includes: For each suspected contamination pathway area, geochemical sampling and detection are carried out in the suspected contamination pathway area and its adjacent areas to obtain the concentration data of characteristic pollutants in the suspected contamination pathway area; The concentration data of the characteristic pollutants are registered with the apparent resistivity profile data in terms of spatial location and depth range to construct a spatially aligned chemical anomaly concentration profile. Within the spatial boundary of the suspected contamination pathway area, the registered apparent resistivity values ​​and corresponding characteristic pollutant concentration values ​​are extracted to form a set of data pairs for subsequent correlation analysis.

5. The method as described in claim 4, characterized in that, The spatial alignment of the concentration data of the characteristic pollutants with the apparent resistivity profile data, based on spatial location and depth range, to construct a spatially aligned chemical anomaly concentration profile specifically includes: The spatial coordinate system and elevation datum used to unify the concentration data and apparent resistivity profile data of the aforementioned characteristic pollutants; Based on the concentration data of the characteristic pollutants in a unified spatial coordinate system, a continuous two-dimensional concentration distribution profile is reconstructed using a spatial interpolation algorithm. Align the reconstructed concentration distribution profile with the apparent resistivity profile on the grid nodes to generate the spatially aligned chemical anomaly concentration profile.

6. The method as described in claim 1, characterized in that, Analyzing the correlation between their spatial distribution trends, the physicochemical response synergy, which characterizes the spatial coupling degree of physicochemical anomalies in each suspected contamination pathway area, specifically includes: For each suspected contamination path region, obtain a set of apparent resistivity-concentration data pairs for that region. The apparent resistivity-concentration data in the set are subjected to rank transformation to eliminate dimensional differences and convert them into sequences suitable for nonparametric statistical analysis; Based on the transformed sequence, nonparametric statistics that can characterize the monotonic correlation between apparent resistivity values ​​and characteristic pollutant concentration values ​​are determined. The nonparametric statistics are directly used as the physicochemical response synergy degree of the suspected contamination path region.

7. The method as described in claim 1, characterized in that, The dominant pathway index for each suspected contamination pathway zone is determined based on its physicochemical response synergy and its extension along the potential groundwater flow direction in the profile. Specifically, this includes: Based on topographic and geological structure data, a unified potential groundwater flow direction was determined within the abandoned mine; For each suspected contamination path zone, the projected length of the suspected contamination path zone along the potential groundwater flow direction on the profile is determined as a quantitative indicator of its extensibility. The physical response synergy degree and the projection length are normalized respectively to obtain the corresponding standardized evaluation values; The standardized evaluation value of the physical-chemical response synergy and the standardized evaluation value of the projection length are weighted and summed to obtain the dominant channel index of the suspected contamination path area.

8. A soil pollutant analysis system for the reuse of abandoned mine land resources, characterized in that, The system includes: The identification module is used to identify and delineate multiple areas of apparent resistivity anomalies caused by pollutants as suspected pollution pathway areas based on the stratigraphic lithology data of abandoned mines. The processing module is used to extract the apparent resistivity value and the characteristic pollutant concentration value of the corresponding location and depth range within the spatial range of each suspected pollution path area, and then analyze the correlation between the spatial distribution trends of the two to obtain the physicochemical response synergy degree, which characterizes the degree of spatial coupling of physicochemical anomalies in each suspected pollution path area. The processing module is also used to determine the dominant channel index of each suspected contamination path zone based on the physicochemical response synergy of each suspected contamination path zone and its extension along the potential groundwater flow direction in the profile. The execution module is used to identify the suspected pollution path area with the highest dominant channel index as the dominant migration channel of pollutants, and to mark it in conjunction with the geological profile, so as to provide the target location for setting up groundwater monitoring wells or implementing in-situ barrier remediation projects.

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