Uranium ore in-situ leaching solute transport regulation and control method and system based on three-dimensional geological modeling

Abstract

The invention provides a uranium ore in-situ leaching solute transport regulation and control method and system based on three-dimensional geological modeling. According to the method, the high-frequency pressure data of the liquid injection well are obtained and combined with the three-dimensional geologic model to construct the permeability distribution field, and the abnormal high-pressure blocking coordinate set is extracted. Magnetic anomaly signals caused by iron ion concentration changes of the leaching agent are synchronously collected, the space gradient of the magnetic anomaly signals is converted into a solute transport trajectory diagram, and a solute diffusion lag map is constructed based on the trajectory diagram. And further extracting a lagging boundary coordinate set, and performing space matching with the abnormal high-voltage blocking coordinate set to generate a blocking retention incidence matrix. And dynamically adjusting a liquid injection well pressure gradient distribution strategy according to the matrix, and generating a pumping and injection flow adjusting instruction to inhibit a leaching dead angle. According to the technical scheme provided by the invention, the efficiency and precision of uranium ore in-situ leaching solute transport regulation and control can be improved.

Description

Technical Field

[0001] The present application relates to the technical field of solute transport control in uranium mine in-situ leaching, and in particular to a method and system for solute transport control in uranium mine in-situ leaching based on three-dimensional geological modeling. Background Art

[0002] In highly heterogeneous uranium ore layers, the solute front migration path is easily offset due to differences in geological structure, resulting in the formation of leaching dead zones in local areas, significantly reducing the efficiency of uranium resource recovery. In this scenario, the penetration path of the leachate in the heterogeneous medium is affected by multiple factors such as lithologic distribution, pore structure, and formation stress. It is necessary to dynamically correct the solute migration path by precisely controlling the injection parameters and the layout of the pumping and injection wells. Technical requirements focus on the real-time identification of abnormal solute front deviations, the adaptive adjustment mechanism of the injection strategy, and the coupled modeling of multi-scale geological characteristics and the leaching process to improve leaching efficiency and avoid the risk of ore blockage.

[0003] The current solution to this need is an optimization system based on a groundwater solute transport model and manual parameter adjustment. This solution deploys monitoring equipment such as injection pressure, pumping well water level, and formation permeability, and combines traditional convection and diffusion equations to construct a solute transport numerical model. The system uses groundwater simulation software to statically simulate the diffusion range of the leaching solution under different injection modes. Based on the simulation results, the injection pressure, flow rate, and well location are manually adjusted to form a phased injection strategy. Its core advantage lies in its reliance on mature groundwater dynamics theory. Based on the quantitative relationship between geological parameters and leaching laws, it can achieve a rough prediction of the solute migration path and strategy optimization, thereby reducing the formation of dead-end areas.

[0004] Although this existing solution can partially meet the needs of regulation, it still has significant limitations. The groundwater solute transport model has limited ability to depict geological heterogeneity, and it is difficult to accurately capture the dynamic impact of complex lithology distribution on the solute front, resulting in a large deviation between the simulation results and the actual migration path. The system's response capability to sudden geological disturbances is insufficient, and it is difficult to quickly correct the injection plan in the early stage of solute front misalignment. There is still a risk of expansion of local leaching dead corners. In addition, the manual adjustment strategy relies on empirical judgment and lacks a real-time feedback mechanism. It is difficult to adapt to dynamically changing ore conditions, and the model calculation is time-consuming. In on-site regulation, it may be limited by computing resource bottlenecks, affecting the timeliness of strategy adjustments. Summary of the Invention

[0005] The present application provides a method and system for regulating solute migration in uranium ore in situ leaching based on three-dimensional geological modeling, which is used to solve the problems of low efficiency and poor precision of solute migration regulation in uranium ore in situ leaching in the prior art.

[0006] In a first aspect, the present application provides a method for regulating solute transport in uranium leaching based on three-dimensional geological modeling, comprising:

[0007] obtaining high-frequency pressure data of the injection well, constructing a uranium mine permeability distribution field in combination with a three-dimensional geological model, and extracting an abnormal high-pressure blockage coordinate set from the uranium mine permeability distribution field;

[0008] collecting a magnetic anomaly signal caused by a change in iron ion concentration in the leaching agent, converting a spatial gradient of the magnetic anomaly signal into a solute transport trajectory graph representing a solute transport path of the uranium mine in-situ leaching, and constructing a solute diffusion lag atlas based on a spatial variation feature of the solute transport trajectory graph;

[0009] extracting a lag boundary coordinate set of the leaching agent in the solute diffusion lag atlas according to a diffusion lag feature of the solute diffusion lag atlas;

[0010] spatially matching the abnormal high-pressure blockage coordinate set and the lag boundary coordinate set to generate a blockage and retention association matrix of the uranium mine geological blockage point and the in-situ leaching solute retention area;

[0011] adjusting a pressure gradient distribution strategy of the injection well based on the blockage and retention association matrix to generate an injection and extraction flow adjustment instruction for inhibiting in-situ leaching dead angles.

[0012] Optionally, the spatial matching of the abnormal high-pressure blockage coordinate set and the lag boundary coordinate set to generate the blockage and retention association matrix of the uranium mine geological blockage point and the in-situ leaching solute retention area comprises:

[0013] establishing a spatial index framework of the three-dimensional geological model, spatially associating the spatial index framework with the abnormal high-pressure blockage coordinate set to generate a uranium mine geological blockage point set;

[0014] spatially integrating the lag boundary coordinate set to obtain a closed boundary region, and calculating a spatial distance between the uranium mine geological blockage point set and the closed boundary region, and taking a uranium mine geological blockage point with a spatial distance less than a preset tolerance range as an associated blockage point;

[0015] establishing a state record table reflecting a corresponding relationship between the associated blockage point and the closed boundary region, and converting the state record table into a two-dimensional relationship structure to generate a blockage and retention association matrix.

[0016] Optionally, the spatial association of the spatial index framework and the abnormal high-pressure blockage coordinate set to generate the uranium mine geological blockage point set comprises:

[0017] dividing the spatial index framework into grid regions, and mapping each coordinate point in the abnormal high-pressure blockage coordinate set to a corresponding grid region to generate a candidate blockage point set;

[0018] matching and associating the three-dimensional geological model with the three-dimensional position data of the candidate blocking point set, generating an association data table, and screening coordinate points of a preset easy-to-block lithology type in the association data table to generate an easy-to-block point set;

[0019] configuring a blocking attribute identifier for the coordinate points in the easy-to-block point set, and sorting the configured coordinate points according to the spatial order of the grid area to generate a uranium ore geological blocking point set.

[0020] Optionally, the spatial gradient of the magnetic anomaly signal is converted into a solute migration trajectory graph representing a uranium ore leaching solute migration path, including:

[0021] extracting a spatial gradient vector set of the magnetic anomaly signal, and decomposing the spatial gradient vector set into a component along the ore bed strike, a component perpendicular to the ore bed strike, and a vertical component;

[0022] performing strike correction on the component along the ore bed strike to generate an ore bed strike reference line, and simultaneously superimposing the component perpendicular to the ore bed strike and the vertical component to generate a solute migration direction set;

[0023] taking the ore bed strike reference line as a reference path, and projecting the solute migration direction set to the reference path to generate a local migration trajectory segment, and fusing and connecting each local migration trajectory segment to construct an initial solute migration trajectory network;

[0024] mapping the initial solute migration trajectory network into a coordinate system of a three-dimensional geological model to obtain a solute migration trajectory graph.

[0025] Optionally, a solute diffusion lag map is constructed based on the spatial variation characteristics of the solute migration trajectory graph, including:

[0026] dividing the solute migration trajectory graph into spatial grids, and calculating the direction change rate of the local migration trajectory segment in each spatial grid;

[0027] identifying spatial grids with a direction change rate exceeding a preset critical threshold as migration abnormal grids, and connecting each migration abnormal grid to obtain a migration abnormal region;

[0028] calculating the attenuation coefficient of the solute migration rate in the migration abnormal region, generating a solute diffusion lag coefficient field with the attenuation coefficient as the filling value, and spatially cropping the solute diffusion lag coefficient field and the three-dimensional geological model to construct a solute diffusion lag map.

[0029] Optionally, according to the diffusion lag feature of the solute diffusion lag map, a lag boundary coordinate set of the leaching agent in the solute diffusion lag map is extracted, including:

[0030] extract diffusion hysteresis features from the diffusion hysteresis atlas, and identify a gradient mutation interface in the diffusion hysteresis features;

[0031] convert the pixel coordinate point set of the gradient mutation interface into a three-dimensional coordinate point set of a three-dimensional geological model, and perform spatial connection on the converted three-dimensional coordinate point set to generate an initial boundary polyline;

[0032] close the initial boundary polyline at the beginning and the end to obtain a closed boundary ring, and combine the vertex coordinate sequences of the closed boundary ring to generate a hysteresis boundary coordinate set of the leaching agent.

[0033] Optionally, based on the blocking and retention correlation matrix, the pressure gradient distribution strategy of the injection well is adjusted to generate injection and extraction flow adjustment instructions for inhibiting leaching dead angles, including:

[0034] According to the correlation blocking points in the blocking and retention correlation matrix, corresponding injection well identifiers are identified, and according to the spatial distribution characteristics of the correlation blocking points and the permeability direction of the three-dimensional geological model, the pressure gradient adjustment amount of each injection well is determined;

[0035] The injection well identifier and the pressure gradient adjustment amount are combined correspondingly to generate a pressure gradient distribution strategy, and the flow adjustment parameter of the extraction well is calculated based on the pressure gradient distribution strategy;

[0036] The pressure gradient adjustment amount and the flow adjustment parameter are combined and superimposed to generate injection and extraction flow adjustment instructions for inhibiting leaching dead angles.

[0037] In a second aspect, the present application provides a uranium mine in-situ leaching solute transport regulation system based on three-dimensional geological modeling, including:

[0038] The acquisition module acquires high-frequency pressure data of the injection well, constructs a uranium mine permeability distribution field in combination with a three-dimensional geological model, and extracts an abnormal high-pressure blocking coordinate set from the uranium mine permeability distribution field;

[0039] The conversion module collects magnetic anomaly signals caused by changes in the concentration of iron ions in the leaching agent, and converts the spatial gradient of the magnetic anomaly signals into a solute transport trajectory graph representing the solute transport path of the uranium mine in-situ leaching, and constructs a solute diffusion hysteresis atlas based on the spatial variation characteristics of the solute transport trajectory graph;

[0040] The extraction module extracts a hysteresis boundary coordinate set of the leaching agent in the solute diffusion hysteresis atlas according to the diffusion hysteresis features of the solute diffusion hysteresis atlas;

[0041] The matching module performs spatial matching between the abnormal high-pressure blocking coordinate set and the hysteresis boundary coordinate set to generate a blocking and retention correlation matrix of uranium mine geological blocking points and in-situ leaching solute retention zones.

[0042] The generating module generates injection and production flow adjustment instructions for inhibiting leaching dead angles based on the adjustment of the pressure gradient distribution strategy of the injection well based on the blocking and retention correlation matrix.

[0043] In a third aspect, the embodiments of the present application provide a computing device, comprising a processing component and a storage component; the storage component stores one or more computer instructions; the one or more computer instructions are used to be called and executed by the processing component to implement the method for regulating uranium in-situ leaching solute transport based on three-dimensional geological modeling according to the first aspect.

[0044] In a fourth aspect, the embodiments of the present application provide a computer storage medium, which stores a computer program, and when the computer program is executed by a computer, a method for regulating uranium in-situ leaching solute transport based on three-dimensional geological modeling according to the first aspect is implemented.

[0045] In the embodiments of the present application, high-frequency pressure data of the injection well is acquired, a uranium permeability distribution field is constructed in combination with a three-dimensional geological model, and an abnormal high-pressure blocking coordinate set is extracted from the uranium permeability distribution field; a magnetic anomaly signal caused by a change in iron ion concentration in the leaching agent is collected, and a spatial gradient of the magnetic anomaly signal is converted into a solute transport trajectory graph representing a uranium in-situ leaching solute transport path, a solute diffusion lag atlas is constructed based on a spatial variation feature of the solute transport trajectory graph; a lag boundary coordinate set of the leaching agent in the solute diffusion lag atlas is extracted according to a diffusion lag feature of the solute diffusion lag atlas; the abnormal high-pressure blocking coordinate set and the lag boundary coordinate set are spatially matched to generate a blocking and retention correlation matrix of a uranium geological blocking point and an in-situ leaching solute retention area; and injection and production flow adjustment instructions for inhibiting leaching dead angles are generated based on the adjustment of the pressure gradient distribution strategy of the injection well based on the blocking and retention correlation matrix.

[0046] The technical scheme of the present application has the following beneficial effects:

[0047] The present application fuses high-frequency pressure data of the injection well with a three-dimensional geological model to realize real-time perception of a permeability abnormal area of a mineral layer. A magnetic anomaly signal induced by a change in iron ion concentration of the leaching agent is used to dynamically capture an actual solute transport trajectory to construct a visual diffusion lag atlas to present a leaching agent transport blocking state. A lag boundary coordinate set is extracted based on the atlas to clearly identify a spatial distribution boundary of a solute retention area. Finally, the pressure gradient distribution strategy of the injection well is dynamically optimized based on the matrix to generate targeted injection and production flow adjustment instructions to realize active inhibition of leaching dead angles and substantial improvement of leaching efficiency.

[0048] Further, by establishing a three-dimensional spatial index framework, the abnormal high pressure blocking points are structured and organized, and the lagging boundaries are synchronously integrated to form a closed area. Based on the spatial proximity relationship between the blocking points and the boundary area within a preset tolerance range, the blocking points with direct correlation are screened. Finally, through the conversion of the state record table to a two-dimensional relationship structure, an association matrix is constructed to quantitatively analyze the corresponding relationship between the blocking points and the retention area. The precise spatial coupling analysis of the geological blocking points and the solute retention area is realized, the non-related interference points are filtered through the distance tolerance mechanism, and the physical authenticity of the correlation relationship is ensured. The complex three-dimensional spatial relationship is converted into a calculable two-dimensional matrix structure, which provides quantifiable and traceable decision-making basis for the pressure gradient distribution strategy, and fundamentally eliminates the randomness error of the traditional method.

[0049] These aspects or other aspects of the present application will be more apparent in the following description of the embodiments. BRIEF DESCRIPTION OF DRAWINGS

[0050] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiments or the prior art description. Obviously, the drawings in the following description are some embodiments of the present application, and other drawings can also be obtained by those skilled in the art without creative labor.

[0051] Figure 1 A flow chart of a uranium in-situ leaching solute transport regulation method based on three-dimensional geological modeling provided by the present application is shown;

[0052] Figure 2 A structural schematic diagram of a uranium in-situ leaching solute transport regulation system based on three-dimensional geological modeling provided by the present application is shown;

[0053] Figure 3 A structural schematic diagram of a computing device provided by the present application is shown. DETAILED DESCRIPTION

[0054] In order to make the personnel in the technical field better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application.

[0055] In some of the flowcharts described in the specification and claims of the present application and in the above description of the drawings, a plurality of operations are included which occur in a particular order, but it should be clearly understood that the operations can be performed in an order other than that in which they appear or in parallel, and the serial numbers of the operations, such as 101, 102, etc., are only used to distinguish different operations, and the serial numbers themselves do not represent any execution order. In addition, the flowcharts can include more or fewer operations, and the operations can be executed in sequence or in parallel. It should be noted that the descriptions of "first", "second", etc. in this paper are used to distinguish different messages, devices, modules, etc., and do not represent the order and do not limit that "first" and "second" are different types.

[0056] The existing uranium ore in-situ leaching regulation method mainly relies on static groundwater solute transport model and artificial intervention mechanism, and its core limitation is the insufficient adaptability to the strong heterogeneous characteristics of the ore bed. The model is difficult to accurately depict the dynamic influence of complex lithology distribution, pore structure and formation stress change on the percolation path of leaching solution, resulting in significant deviation between simulation prediction and actual solute front migration. At the same time, the mode relying on artificial experience for stage parameter adjustment lacks the rapid response ability to sudden geological disturbance, cannot implement accurate correction in the early stage of leaching dead angle formation, and the time-consuming calculation restricts the timeliness of strategy adjustment, which overall restricts the improvement of leaching efficiency and is difficult to effectively avoid the risk of ore bed blockage.

[0057] In view of the above problems, the present application proposes a uranium ore in-situ leaching solute transport regulation method based on three-dimensional geological modeling. The method fuses high-frequency pressure data of injection wells and three-dimensional geological model to construct the permeability distribution field of the ore bed, and captures the abnormally high pressure blockage area in real time. Using the magnetic anomaly signal caused by the change of iron ion concentration in the leaching agent, the actual migration path and diffusion lag characteristics of the solute are dynamically analyzed and constructed to generate a blockage and retention correlation matrix revealing the internal correlation between the blockage points and the solute retention area. Based on this matrix, the system automatically generates a specific injection well pressure gradient distribution optimization strategy and injection and extraction flow adjustment instructions. The method realizes high-precision perception and modeling of the dynamic solute transport of heterogeneous ore bed, and establishes an adaptive regulation mechanism based on real-time data, effectively solving the problems of existing technology such as distortion, response lag and reliance on artificial intervention, significantly improving the leaching efficiency and reducing the risk of blockage.

[0058] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.

[0059] Figure 1A flowchart of a uranium in-situ leaching solute transport regulation method based on three-dimensional geological modeling is provided for the embodiments of the present application, as shown in Figure 1 The method comprises the following steps:

[0060] 101. Obtain high-frequency pressure data of the injection well, construct a uranium in-situ leaching permeability distribution field in combination with a three-dimensional geological model, and extract an abnormal high-pressure blockage coordinate set from the uranium in-situ leaching permeability distribution field.

[0061] In this step, the high-frequency pressure data refers to the hydraulic pressure fluctuation data collected at a millisecond level in the injection well, which is used to reflect the permeability state of the ore bed in real time.

[0062] The three-dimensional geological model refers to a three-dimensional gridded model of the ore bed porosity and permeability constructed based on the drilling core and seismic exploration data.

[0063] The uranium in-situ leaching permeability distribution field refers to a dynamic permeability spatial distribution map generated by coupling the pressure data and the geological model.

[0064] The abnormal high-pressure blockage coordinate set refers to a set of spatial coordinates in the permeability distribution field whose pressure value exceeds the lithology pressure resistance threshold, which is used to identify the easy blockage area.

[0065] In the embodiments of the present application, first, a high-precision pressure sensor is installed in the injection well to continuously collect millisecond-level hydraulic pressure data. After the high-frequency pressure data is input into the three-dimensional geological model, the original permeability parameters in the model are dynamically corrected by Darcy's law, and the Kriging interpolation algorithm is used to generate a uranium in-situ leaching permeability distribution field in the whole mine area. Then, a dynamic threshold based on the lithology pressure resistance strength is set, the permeability field is scanned using an adaptive sliding window, the window size is automatically adjusted according to the homogeneity of the ore bed, and the spatial coordinates of the over-limit area are extracted to form an abnormal high-pressure blockage coordinate set.

[0066] In a certain uranium in-situ leaching injection well, the pressure in the northwest area is continuously abnormally high. The system inputs the high-frequency data into the three-dimensional geological model, dynamically reconstructs the permeability field, finds that the permeability in the target area decreases, automatically marks the coordinate set in combination with the granite lithology pressure resistance threshold, and locates the hidden fault zone as the blockage source.

[0067] 102. Collect the magnetic anomaly signal caused by the change of the iron ion concentration in the leaching agent, convert the spatial gradient of the magnetic anomaly signal into a solute transport trajectory map representing the uranium in-situ leaching solute transport path, and construct a solute diffusion lag map based on the spatial variation characteristics of the solute transport trajectory map.

[0068] In this step, the magnetic anomaly signal refers to the local geomagnetic field intensity fluctuation data caused by the change of the iron ion concentration in the leaching agent.

[0069] The leaching agent refers to an acidic or alkaline uranium leaching solution containing an oxidizing agent.

[0070] Spatial gradient refers to the rate of change of magnetic signal in three-dimensional space, which is used to identify the concentration mutation boundary.

[0071] Solute transport trajectory map refers to the reconstructed uranium in-situ leaching solute transport path in the ore bed based on magnetic gradient data, that is, the actual penetration route of the leaching agent in the ore bed.

[0072] Spatial variation feature refers to the geometric abnormality of the path mutation, bifurcation or interruption in the transport trajectory map.

[0073] Solute diffusion lag map refers to a spatial distribution thermogram representing the difference between the actual transport speed and the theoretical speed of the leaching agent.

[0074] In the embodiments of the present application, a magnetometer array is arranged in the ore bed to collect magnetic anomaly signals caused by the change of iron ion concentration in the leaching agent. After spatial vector decomposition of the magnetic anomaly signals, the three-dimensional gradient field is calculated using the Sobel operator. The improved ant colony algorithm is used to track the solute front movement trajectory along the maximum value path of the gradient field, and the solute transport trajectory map is formed. The solute transport trajectory map is compared with the theoretical convective diffusion model path, the time delay is quantified by the dynamic time warping algorithm, and finally the solute diffusion lag map is generated by inverse distance weighted interpolation.

[0075] Continuing the above embodiment, the magnetometer detects abnormal decay of the magnetic field strength in the southeast, and the system identifies the solute flow path around the region after calculating the spatial gradient of the magnetic signal. Compared with the ideal model, it is found that the diffusion delay in the flow area is significant, and accordingly the lag map is generated to show that there is a diffusion retardation zone.

[0076] 103、According to the diffusion lag feature of the solute diffusion lag map, the lag boundary coordinate set of the leaching agent in the solute diffusion lag map is extracted;

[0077] In this step, the diffusion lag feature refers to the continuous area in the lag map where the delay time exceeds the process tolerance threshold.

[0078] The lag boundary coordinate set refers to the spatial coordinate set of the outer envelope line of the diffusion lag area. The closed area circled by the set is the in-situ leaching solute retention area, which represents the range of the ore bed where the leaching agent cannot effectively diffuse.

[0079] In the embodiments of the present application, first, the process delay threshold is set in the solute diffusion lag map, and the eight-neighborhood flood filling method is used to extract the over-limit connected region of the leaching agent in the map. Second, the Canny edge detection operator is used for morphological boundary extraction to obtain the initial outer envelope line. Finally, the Douglas-Peucker algorithm is used to simplify the number of boundary coordinate points and retain the curvature mutation key points to form the lag boundary coordinate set.

[0080] For the aforementioned diffusion retardation zone, the system automatically extracts the outline of the delayed excess area, obtains the coordinate set after boundary optimization, and accurately defines the solvent retention area as an elliptical area controlled by the long-axis fault zone.

[0081] 104. Spatially matching the abnormally high pressure blocking coordinate set with the hysteresis boundary coordinate set to generate a blocking and retention correlation matrix between uranium geological blocking points and in-situ leaching solute retention areas;

[0082] In this step, spatial matching refers to calculating the spatial proximity relationship between the abnormal high-pressure blocking coordinate set and the hysteresis boundary coordinate set.

[0083] The blocking and retention association matrix refers to a two-dimensional relationship table in which rows represent blocking points and columns represent retention areas. The matrix element values ​​are weighted by the inverse of the distance to calculate the association strength.

[0084] In this embodiment, a three-dimensional grid spatial index framework is first established to organize the coordinates of the blocking points. The shortest Euclidean distance from each uranium geological blocking point to the boundary of the in-situ solute retention zone is calculated, and a formation anisotropy correction factor is introduced into the distance calculation. Secondly, a preset tolerance range is dynamically set based on the lithologic permeability coefficient. When the distance is less than this range, spatial association is determined. A blocking-retention association matrix is ​​constructed with blocking points as rows and retention zones as columns. The association strength value is normalized and assigned according to the inverse of the distance.

[0085] The magnetometer detected an abnormal attenuation of magnetic field intensity in the southeast, and matched the blocking point of the fault zone with the boundary of the retention zone. Calculations showed that the distance between the blocking point in the southern section and the boundary was less than the sandstone influence radius, marking high-intensity correlations in the correlation matrix, revealing that the fault zone is the main controlling factor of retention.

[0086] 105. Adjust the pressure gradient distribution strategy of the injection well based on the blockage and retention correlation matrix, and generate an injection flow rate regulation instruction to suppress the leaching dead corner.

[0087] In this step, the pressure gradient distribution strategy refers to the operation plan of adjusting the pressure difference between injection wells to change the flow direction of the leaching fluid.

[0088] Leaching dead corners refer to irreversible blockage areas formed because the leaching agent cannot reach them for a long time. The core goal of this directive is to inhibit the formation of such dead corners.

[0089] The pumping and injection flow regulation instruction refers to the coordinated control command for controlling the injection volume of the injection well and the extraction volume of the pumping well.

[0090] In the embodiments of the present application, firstly, the principal component analysis method is used to analyze the control contribution of high-weight blocking points in the blocking retention correlation matrix to generate a pressure gradient distribution strategy, including reducing the pressure of the high-contribution blocking point corresponding to the injection well, and adding auxiliary injection points outside the retention area. Then, based on the computational fluid dynamics model, the strategy effect of the auxiliary injection point is simulated, and the particle swarm optimization algorithm is used to iteratively optimize the injection and production flow adjustment instructions until the retention area is eliminated.

[0091] For the high correlation of fault zone blocking points, the system generates instructions to reduce the pressure of the north injection well and add a new injection point on the east side. Fluid dynamics simulation shows that the new strategy can make the leaching agent bypass the fault to cover the retention area.

[0092] In summary, steps 101 to 105 achieve accurate positioning of geological blocking points through millisecond pressure monitoring and dynamic coupling with a three-dimensional geological model. The magnetic anomaly gradient analysis and migration trajectory reconstruction technology are used to capture the solute diffusion lag characteristics in real time. Based on the spatial distance matching mechanism, a quantitative correlation model of blocking points and retention areas is established. Finally, through the adaptive co-regulation of pressure gradient and injection and production flow, the leaching dead angle is actively eliminated. The whole process breaks through the limitations of traditional methods in describing distorted heterogeneous ore layers and response lag, significantly improves resource recovery rate and reduces the risk of blockage.

[0093] To solve the problem of low correlation efficiency between blocking points and retention areas, the scheme establishes a spatial indexing framework of a three-dimensional geological model, matches the abnormally high pressure blocking coordinate set with the geological model to generate a blocking point set. Further integrate the lag boundary coordinate set to form a closed area, screen the associated points with a tolerance range of spatial distance, and construct a two-dimensional relationship structure of the blocking retention correlation matrix. Through spatial matching and data mapping, the quantitative correlation between geological blocking features and solute retention areas is realized, providing structured data support for subsequent blocking regulation. In some embodiments, in step 104, the abnormally high pressure blocking coordinate set and the lag boundary coordinate set are spatially matched to generate a blocking retention correlation matrix of uranium mine geological blocking points and in-situ leaching solute retention areas, including:

[0094] 201. Establish a spatial indexing framework of a three-dimensional geological model, spatially correlate the spatial indexing framework with the abnormally high pressure blocking coordinate set to generate a set of uranium mine geological blocking points;

[0095] In step 201, the spatial indexing framework refers to a grid data organization structure constructed based on three-dimensional space division principles, used to accelerate spatial queries. The abnormally high pressure blocking coordinate set refers to a set of three-dimensional coordinates representing the location of geological blocking. The set of uranium mine geological blocking points refers to a structured blocking point data set reorganized by the spatial indexing framework, each point containing original coordinates and its spatial grid attribution information.

[0096] In this embodiment, a multi-level spatial index framework is first constructed using a spatial segmentation algorithm based on the spatial extent of the three-dimensional geological model. The grid density is dynamically adjusted based on the structural complexity of the ore body. Secondly, the coordinate set of abnormally high-pressure blockages is loaded into the spatial index framework system, and the grid location of each blockage point is calculated by mapping the coordinates to the grid cells. Finally, grid location attribute codes are added to all blockage points to form a set of uranium geological blockage points arranged in an orderly manner according to spatial proximity.

[0097] 202. Perform spatial regional integration on the lag boundary coordinate set to obtain a closed boundary region, calculate the spatial distance between the uranium geological blockage point set and the closed boundary region, and select the uranium geological blockage points whose spatial distance is less than a preset tolerance range as associated blockage points;

[0098] In step 202, spatial region integration involves surface reconstruction of discrete hysteresis boundary coordinate points to form a continuous closed surface. The closed boundary region refers to the triangular mesh surface representing the three-dimensional spatial extent of the hysteresis zone. Spatial distance refers to the shortest three-dimensional geometric distance from the blocking point to the closed surface, with a formation permeability direction correction factor incorporated into the calculation. The preset tolerance range refers to the association determination threshold dynamically set based on the lithologic characteristics of the current grid cell. Associated blocking points are those whose distance from the closed boundary region is below the tolerance threshold.

[0099] In this embodiment, a surface reconstruction algorithm is first applied to the lag boundary coordinate set to generate a closed boundary region. The set of uranium geological blockage points is then traversed, and the shortest distance from each blockage point to the closed boundary region is calculated. This distance calculation incorporates stratigraphic strike and dip parameters for anisotropy correction. A tolerance calculation module is then invoked, which outputs a dynamic tolerance value based on the lithologic permeability characteristics of the grid cell where the blockage point is located. Finally, blockage points with distances less than the tolerance are screened and marked as associated blockage points.

[0100] 203. Establish a state record table reflecting the corresponding relationship between the associated blocking points and the closed boundary areas, and convert the state record table into a two-dimensional relationship structure to generate a blocking and retention association matrix.

[0101] In step 203, the state record table refers to a structured data table that stores the corresponding relationships between associated blocking points and target retention areas. The two-dimensional relationship structure refers to a data matrix with blocking point identifiers as row indices and retention area numbers as column indices. The blocking and retention association matrix refers to a two-dimensional relationship table whose element values ​​represent association strengths, where the strengths are determined by both spatial distance and lithologic control factors.

[0102] In the embodiments of the present application, first, a state record table is created to record the unique identifier of the associated blocking point, the target retention zone number, the measured distance value and the tolerance state. Second, the table is converted into a two-dimensional matrix form, the matrix rows correspond to the blocking point identifier sequence, and the columns correspond to the retention zone number sequence. Finally, the blocking retention association matrix is calculated, and the measured distance value is converted into an association strength coefficient through normalization processing. The conversion process combines the permeability control weight factor of the rock layer where the blocking point is located for weighted calculation.

[0103] The following is a specific example:

[0104] The injection well of a certain uranium mine monitored that the pressure in the northwest area continued to abnormally rise. A multi-layer grid index framework was constructed to map the blocking points to the grid units of a specific depth level to form a structured point set. The boundary of the retention zone was executed for surface reconstruction to generate a closed area, the anisotropic distance of each blocking point to the surface was calculated, and a higher tolerance threshold was set in combination with the sandstone permeability characteristics of the current unit to screen out part of the blocking points in the southern section of the fault zone as effective associated points. After creating the state record table, the blocking points located in the fault fracture zone were given a significantly higher weight coefficient, and finally the blocking retention association matrix was generated.

[0105] In summary, steps 201 to 203 achieve efficient organization and management of blocking points through a spatial index framework, and accurately construct a three-dimensional boundary model of the retention zone based on surface reconstruction technology. The finally constructed association matrix integrates the double parameters of spatial distance and geological control factor to objectively quantify the control strength of the blocking point on the retention zone. The whole process provides decision support with clear geomechanics basis for injection strategy optimization, significantly improving the accuracy and response timeliness of eliminating leaching dead angles.

[0106] To further improve the geological relevance of blocking point identification, the scheme maps the abnormally high pressure blocking coordinate set to the local area through the grid spatial index framework to generate a candidate blocking point set. Combined with the three-dimensional geological model and lithology type screening conditions, the easy-to-block points are extracted and attributed, and finally a geologic blocking point set is generated in spatial order. Through hierarchical screening and attribute labeling, the accuracy and geological adaptability of the blocking point set are improved. In some embodiments, the spatial index framework is spatially associated with the abnormally high pressure blocking coordinate set in step 201 to generate a uranium mine geological blocking point set, including:

[0107] 301. Divide the spatial index framework into grid regions, and map each coordinate point in the abnormally high pressure blocking coordinate set to the corresponding grid region to generate a candidate blocking point set;

[0108] In step 301, the grid region refers to a three-dimensional grid unit divided by the spatial index framework for partition management of spatial data. The candidate blocking point set refers to a set of blocking points initially mapped to the grid unit, which includes the original three-dimensional coordinates and grid attribution information.

[0109] In this embodiment, the grid topology of the spatial index framework is first parsed to obtain the spatial boundary parameters of each grid area. Next, the abnormally high-voltage blockage coordinate set is traversed, and a point inclusion detection algorithm is used for each coordinate point to determine its grid area. The coordinate point is then associated with the grid number to form a data record with a location tag. Finally, all records are combined in ascending order of grid area number to generate a set of candidate blockage points.

[0110] 302. Match and associate the three-dimensional geological model with the three-dimensional position data of the candidate blocking point set to generate a correlation data table, and select coordinate points that meet a preset blocking-prone lithology type from the correlation data table to generate a blocking-prone point set;

[0111] In step 302, the associated data table refers to a structured table that stores the mapping relationship between the spatial location of candidate points and geological attributes. The prone-to-blocking lithology type refers to a preset set of low-permeability rock formation classifications. The prone-to-blocking point set refers to a set of high-blocking risk points that have been screened based on lithology conditions.

[0112] In this embodiment, the 3D coordinates of a set of candidate blocking points are first input into a 3D geological model. An inverse distance weighted interpolation algorithm is then used to extract the lithologic attributes corresponding to each coordinate point. Next, a linked data table is constructed, with fields containing coordinate point identifiers, lithologic names, and permeability values. A pre-defined library of prone-to-blocking lithologic types is then loaded, and records in the linked data table are screened for those lithologic names that fall within the library and whose permeabilities are below the corresponding threshold. Finally, coordinate points that meet the criteria are extracted to generate a set of prone-to-blocking points.

[0113] 303. Configure blocking attribute identifiers for the coordinate points in the prone blocking point set, and sort the configured coordinate points according to the spatial order of the grid area to generate a uranium geological blocking point set.

[0114] In step 303, the blocking attribute identifier refers to a classification label that characterizes the blocking degree, which is defined according to the geological control intensity classification. The uranium geological blocking point set refers to the final result set with attribute identifiers and sorted by spatial structure.

[0115] In this embodiment, the blocking intensity index of each point in the prone blocking point set is first calculated. This index is derived by normalizing the inverse of the permeability coefficient with the distance to the nearest fault. Next, the blocking levels are classified according to the intensity index intervals. Primary blocking points are assigned high-weight identifiers, while secondary blocking points are assigned medium-weight identifiers. The grid regions are then sorted by spatial hierarchy, and within the same grid, the points are sorted in descending order of blocking intensity. Finally, a set of identified, ordered points is output as the uranium geological blocking point set.

[0116] Here's a specific example:

[0117] The pressure of the northwest area of a certain uranium mine injection well is continuously abnormally high. The system divides the spatial index framework into multiple layers of grids, and through position mapping, the high-pressure points are distributed to the corresponding grid area to form a candidate set. By calling the three-dimensional geological model, the points in the candidate set located in the granite layer and with a permeability coefficient lower than the threshold are identified, and the low-risk points in the sandstone area are screened out to generate an easy-to-block point set. The blocking strength index is calculated for the points in the granite area, the points near the fault are assigned a main control blocking identifier, and the remaining points are assigned a secondary identifier. Finally, the structured blocking point set is output in the order of the shallow to deep grid.

[0118] In summary, steps 301 to 303 achieve efficient management of the blocking points by gridding the spatial index, and accurately screen the easy-to-block points with geological relevance in combination with the lithological properties of the three-dimensional geological model. The original pressure data is converted into a blocking spatial distribution model with clear geological significance, which not only eliminates non-related interference points to improve positioning accuracy, but also optimizes the subsequent matching calculation efficiency through spatial sorting, providing a decision basis for leaching regulation with both geological rationality and high calculation efficiency.

[0119] To accurately reconstruct the solute transport path of the heterogeneous ore layer, the scheme decomposes the spatial gradient vector of the magnetic anomaly signal into the strike, vertical, and vertical components of the ore layer, generates a reference path after correction, and superimposes other components to construct a transport direction set. Through trajectory segment fusion and three-dimensional coordinate mapping, a solute transport trajectory graph is generated to dynamically represent the solute migration path. Through multi-component collaborative analysis and spatial reconstruction, technical support is provided for the visualization and quantitative analysis of solute transport rules. In some embodiments, in step 102, the spatial gradient of the magnetic anomaly signal is converted into a solute transport trajectory graph representing the leaching solute transport path of the uranium mine, including:

[0120] 401、extracting a spatial gradient vector set of the magnetic anomaly signal, and decomposing the spatial gradient vector set into a strike component, a vertical strike component, and a vertical component;

[0121] In step 401, the spatial gradient vector set refers to the rate of change of the magnetic anomaly strength in three-dimensional directions, and each vector contains a size and a direction. The strike component refers to the component parallel to the main extension direction of the ore body, reflecting the tendency of solute transport along the layer. The vertical strike component refers to the component perpendicular to the main extension direction in the horizontal plane, representing lateral diffusion. The vertical component refers to the component perpendicular to the ground surface, indicating through-layer transport.

[0122] In the embodiment of the present application, firstly, the spatial gradient vector set of all sampling points is extracted from the magnetic anomaly signal. Secondly, the ore bed strike parameter stored in the three-dimensional geological model is read. Then, a local coordinate system is established with the ore bed strike as the reference. Finally, each gradient vector is decomposed into the coordinate system. The along-strike component is obtained by vector dot product calculation, the perpendicular-to-strike component is obtained by vector projection to the strike normal plane and then orthogonal decomposition, and the vertical component is directly taken as the vertical component of the local coordinate system.

[0123] 402. The along-strike component is corrected for strike to generate an ore bed strike reference line, and the perpendicular-to-strike component and the vertical component are superimposed synchronously to generate a solute migration direction set;

[0124] In step 402, the strike correction refers to eliminating the interference of terrain undulations and ore bed occurrence changes on the strike component. The ore bed strike reference line refers to a continuous curve that reflects the ideal bedding migration path after correction. The solute migration direction set refers to the actual diffusion direction vector set after superimposing the perpendicular-to-strike component and the vertical component.

[0125] In the embodiment of the present application, firstly, the along-strike component is terrain corrected to eliminate signal distortion caused by surface elevation sudden changes using the fitting method. Secondly, the occurrence correction is performed to adjust the strike component value according to the ore bed dip angle change rate revealed by the drill hole. Then, a smooth and continuous ore bed strike reference line is generated. The perpendicular-to-strike component and the vertical component are vector synthesized synchronously to calculate the horizontal azimuth angle and the vertical inclination angle of the synthesized vector. Finally, the synthesized direction vector of all sampling points is output to form the solute migration direction set.

[0126] 403. The ore bed strike reference line is taken as a reference path, and the solute migration direction set is projected to the reference path to generate local migration trajectory segments, the local migration trajectory segments are fused and connected to construct an initial solute migration trajectory network;

[0127] In step 403, the reference path refers to the discretized ore bed strike reference line point sequence. The local migration trajectory segment refers to a straight line segment with a sampling point as the starting point and extending in the migration direction. The initial solute migration trajectory network refers to the path topological structure formed by connecting all trajectory segments.

[0128] In the embodiment of the present application, firstly, the ore bed strike reference line is discretized into an equidistant reference point sequence. Secondly, for each sampling point, the direction projection angle to the nearest reference point is calculated. Then, the local migration trajectory segment is generated by extending a fixed step in the projection direction with the sampling point as the starting point. Finally, the initial solute migration trajectory network is constructed by using the Dijkstra path connection algorithm with the trajectory segment endpoint coincidence as the connection condition, and the redundant nodes are removed by topological optimization of the branch path.

[0129] 404. The initial solute migration trajectory network is mapped into the coordinate system of the three-dimensional geological model to obtain a solute migration trajectory graph.

[0130] In step 404, the coordinate system mapping refers to converting the trajectory network from the local coordinate system to the geological model geodetic coordinate system. The solute transport trajectory map refers to the uranium ore leaching solute transport path reconstructed based on the magnetic gradient data, that is, the actual penetration route of the lixiviant in the ore bed.

[0131] In the embodiments of the present application, first, the spatial reference system conversion parameters of the three-dimensional geological model are obtained. Second, a coordinate transformation matrix is constructed, and then the coordinate conversion is realized by matrix operation on the coordinates of each node of the initial solute transport trajectory network. Finally, the out-of-bound trajectory segments are cropped according to the spatial range of the model, and the solute transport trajectory map completely matched with the geological model is output.

[0132] The following is a specific example:

[0133] In the event of abnormal pressure rise in the northwest area of a certain uranium mine, the southeast magnetic anomaly signal is monitored synchronously. The magnetic gradient vector set is extracted, combined with the strike of the ore bed, and decomposed into three components. The strike component is corrected for topography and occurrence to generate a reference line, and the vertical component is superimposed to identify the transport direction of the lixiviant diffusing laterally to the downwall of the fault. The transport direction is projected to generate a local trajectory segment with the reference line as the reference, and connected to form a trajectory network showing the flow path. The network is converted to the geological model coordinate system, and the trajectory map of the lixiviant transport along the fault fracture zone is clearly presented.

[0134] In summary, steps 401 to 404 remove the interference of the ore bed occurrence by three-component decomposition, and construct an ideal transport reference line using strike correction technology. The actual transport path is accurately reconstructed based on vector synthesis and direction projection. Finally, the spatial fusion of the trajectory and the geological model is realized through coordinate system conversion. The whole process breaks through the limitations of traditional methods in reconstructing the path in strong heterogeneous ore beds, provides high-fidelity spatial path data basis for solute diffusion lag analysis, and significantly improves the accuracy of leaching dead angle cause diagnosis.

[0135] In order to accurately quantify the abnormal characteristics of solute transport, the scheme is based on the spatial grid division of the solute transport trajectory map, calculates the local trajectory direction change rate, and identifies the abnormal area. The solute diffusion lag atlas is constructed and cropped with the three-dimensional model through the attenuation coefficient field, revealing the spatial distribution characteristics of the solute lag. Through gradient analysis and parameterized modeling, data basis is provided for the identification and optimization of the solute lag mechanism in the leaching process. In some embodiments, step 102 of constructing the solute diffusion lag atlas based on the spatial variation characteristics of the solute transport trajectory map includes:

[0136] 501、divide the solute transport trajectory map into spatial grids, and calculate the direction change rate of the local transport trajectory segment in each spatial grid;

[0137] In step 501, the spatial grid refers to dividing the study area into equal-volume cubic cells. The local migration trajectory segment refers to the path line segment in the trajectory diagram located in the same grid. The direction change rate refers to the angular dispersion degree of all trajectory segment direction vectors in the grid, which is characterized by calculating the variance value of the vector distribution within the unit solid angle.

[0138] In the embodiments of the present application, first, the spatial grid size is determined according to the average pore size of the ore body. Second, all trajectory segments are distributed to the corresponding grid cells according to the spatial position by traversing the solute migration trajectory diagram. Then, the direction vectors of all trajectory segments in each grid are extracted, and the three-dimensional direction angles of these vectors are calculated. Finally, the standard deviation of the direction angle is calculated as the direction change rate by using the spherical statistical method.

[0139] 502, identify the spatial grid with a direction change rate exceeding a preset critical threshold as a migration anomaly grid, connect each migration anomaly grid to obtain a migration anomaly region;

[0140] In step 502, the preset critical threshold refers to the angle fluctuation limit value for determining the abnormal turbulence of the migration path. The migration anomaly grid refers to the grid cell with a direction change rate exceeding the critical threshold. The migration anomaly region refers to the connected abnormal grid set in three-dimensional space.

[0141] In the embodiments of the present application, first, the critical threshold is set based on the historical normal migration data statistics. Second, the direction change rate values of all grids are scanned, and the grids exceeding the threshold are marked. Then, the three-dimensional connected domain marking algorithm is used to merge the spatially adjacent migration anomaly grids into continuous regions. Finally, the morphological smoothing processing is performed on the region boundary to generate a complete migration anomaly region.

[0142] 503, calculate the attenuation coefficient of the solute migration rate in the migration anomaly region, generate a solute diffusion lag coefficient field with the attenuation coefficient as the filling value, and perform spatial clipping on the solute diffusion lag coefficient field and the three-dimensional geological model to construct a solute diffusion lag atlas.

[0143] In step 503, the attenuation coefficient refers to the percentage of the actual solute migration rate relative to the theoretical rate. The solute diffusion lag coefficient field refers to a three-dimensional scalar field with grid as the unit and attenuation coefficient as the attribute.

[0144] In the embodiments of the present application, first, the average tortuosity of the trajectory segments in each abnormal grid is calculated in the migration anomaly region. Second, the attenuation coefficient is calculated according to the physical relationship model between tortuosity and rate attenuation. Then, the coefficient value is assigned to the corresponding grid to construct a three-dimensional scalar field. Finally, the ore body boundary of the three-dimensional geological model is called to perform spatial clipping on the coefficient field to remove the data outside the model range, and output the solute diffusion lag atlas accurately matched with the geological structure.

[0145] The following is a specific example:

[0146] In the pressure anomaly event of the northwest area of a certain uranium mine, the generated solute transport trajectory diagram shows that there is path bending in the hanging wall of the fault. By dividing the trajectory diagram into grids, it is found that the grid direction change rate of the fault zone is significantly higher. According to the preset threshold, the abnormal grid is marked, and the abnormal area covering the hanging wall of the fault is formed by connection. The trajectory bending of the area causes the transport rate to decay, and the coefficient field showing the strong hysteresis characteristics is generated, which clearly presents the diffusion hysteresis pattern controlled by the fault after being cut by the geological model.

[0147] In summary, steps 501 to 503 objectively quantify the degree of solute transport disorder through grid direction fluctuation analysis, accurately locate the diffusion abnormal area based on three-dimensional connected domain recognition technology, and finally build the hysteresis pattern. The hysteresis pattern breaks through the limitations of traditional methods relying on concentration monitoring for hysteresis judgment, directly reveals the dynamic interference mechanism of geological structure on solute transport, provides quantitative basis with clear spatial orientation for injection strategy adjustment, and significantly improves the accuracy of leaching dead angle prediction and elimination.

[0148] In order to accurately define the boundary of the solute retention area, the scheme extracts the gradient mutation interface from the solute diffusion hysteresis pattern and converts it into a three-dimensional coordinate point set, and generates the hysteresis boundary coordinate set by spatial connection and closure. Through interface recognition and geometric reconstruction, the boundary range of the leaching agent retention is accurately located, providing spatial positioning basis for subsequent blockage regulation and flow distribution. In some embodiments, step 103 extracts the hysteresis boundary coordinate set of the leaching agent in the solute diffusion hysteresis pattern according to the diffusion hysteresis characteristics of the solute diffusion hysteresis pattern, including:

[0149] 601. Extract the diffusion hysteresis characteristics from the solute diffusion hysteresis pattern, and identify the gradient mutation interface in the diffusion hysteresis characteristics;

[0150] In step 601, the diffusion hysteresis characteristics refer to the spatial distribution characteristics in the pattern that represent the delay degree of solute transport. The gradient mutation interface refers to the transition region interface where the hysteresis coefficient value changes sharply in three-dimensional space, which is located by the spatial derivative extreme point of the hysteresis coefficient.

[0151] In the embodiments of the present application, first, the gradient vector field of the solute diffusion hysteresis pattern at each spatial position is calculated. Second, the spatial points with gradient vector module length exceeding the set sensitivity are identified. Then, the non-maximum suppression algorithm is used to screen the local extreme points in the gradient direction. Finally, the extreme point set is taken as the gradient mutation interface.

[0152] 602. Convert the pixel coordinate point set of the gradient mutation interface into a three-dimensional coordinate point set of the three-dimensional geological model, and perform spatial connection on the converted three-dimensional coordinate point set to generate an initial boundary polyline;

[0153] In step 602, the pixel coordinate point set refers to the two-dimensional position set of the gradient abrupt interface points in the atlas image coordinate system. The three-dimensional coordinate point set refers to the actual position set in the corresponding geological space. The initial boundary polyline refers to the unclosed spatial polyline formed by sequentially connecting the three-dimensional coordinate points.

[0154] In this embodiment, the spatial transformation parameters from the atlas pixel coordinate system to the 3D geological model are first obtained. Next, an affine transformation matrix is ​​applied to each pixel coordinate point to calculate a 3D coordinate point set. The 3D coordinate point set is then sorted according to its original adjacency relationship, and finally, adjacent points are sequentially connected to generate an initial boundary polyline.

[0155] 603. Close the initial boundary polyline at both ends to obtain a closed boundary loop, and combine the vertex coordinate sequences of the closed boundary loop to generate a lag boundary coordinate set of the leachate.

[0156] In step 603, the closed boundary loop refers to a continuous space closed curve connected end to end. The lag boundary coordinate set refers to a three-dimensional coordinate sequence of vertices constituting the closed loop.

[0157] In this embodiment, the spatial distance between the initial boundary polyline's start and end points is first detected. If the polyline is not closed, connecting line segments are added. The Douglas-Peucker algorithm is then used to simplify the polyline's vertices, preserving key points of sudden curvature changes. The simplified polyline is then smoothed using spline processing. Finally, a coordinate sequence is output in the order in which the vertices are connected, forming the lagging boundary coordinate set.

[0158] Here's a specific example:

[0159] During an abnormal pressure event at a liquid injection well in the northwest region of a uranium mine, a diffusion hysteresis map revealed a strong hysteresis zone on the fault's hanging wall. The map's gradient field was calculated to identify the interface where the hysteresis coefficient changes sharply from high to low. The pixel coordinates of this interface were converted to geological space and connected to form a polyline defining the fault's hanging wall boundary. After closing the polyline and simplifying and smoothing it, a closed coordinate set was generated to precisely delineate the hysteresis zone.

[0160] In summary, steps 601 to 603 accurately capture the solute diffusion hysteresis boundary through gradient mutation detection, accurately locate it from image space to geological space using coordinate mapping technology, and generate a structurally concise closed boundary using a broken line optimization algorithm. This entire process overcomes the limitations of traditional threshold segmentation methods, resulting in rough boundaries. It provides a high-precision spatial reference for subsequent blocking point matching, significantly improving the accuracy of lag zone demarcation and the spatial relevance of regulatory strategies.

[0161] In order to optimize the physical pertinence of the leaching control strategy, the solution determines the pressure gradient adjustment amount of the injection well based on the blockage and retention correlation matrix, and calculates the flow control parameters in combination with the permeability direction. The pumping flow control instructions are generated by combining the pressure gradient and flow parameters to optimize the distribution of leaching solutes and suppress leaching dead corners. Through multi-parameter linkage control, dynamic intervention and systematic optimization of solute migration under complex geological conditions are achieved. In some embodiments, in step 105, the pressure gradient distribution strategy of the injection well is adjusted based on the blockage and retention correlation matrix to generate a pumping flow control instruction that suppresses leaching dead corners, including:

[0162] 701. Identify corresponding injection well identifiers based on associated blockage points in the blockage and retention association matrix, and determine pressure gradient adjustment amounts for each injection well based on spatial distribution characteristics of the associated blockage points and permeability directions of a three-dimensional geological model.

[0163] In step 701, the associated blockage point refers to the valid blockage point marked in the blockage retention association matrix. The injection well identifier refers to the injection well number associated with the hydrogeological unit where the blockage point is located. The spatial distribution characteristics refer to the three-dimensional clustering and directionality of the blockage point set. The pressure gradient adjustment value refers to the pressure change required to adjust the injection well, with a positive value indicating increased pressure and a negative value indicating decreased pressure.

[0164] In this embodiment, the row data of the blockage retention correlation matrix is ​​first analyzed to extract blockage points whose correlation strength exceeds the activation threshold. Next, the injection-production well network topology of the 3D geological model is queried based on the coordinates of the blockage points to determine the nearest injection well. The spatial distribution of the blockage points is then analyzed, and the direction and magnitude of pressure adjustment are calculated based on the dominant permeability direction of the geological model. Finally, the pressure gradient adjustment is calculated by weighting the number and strength of the associated blockage points for each well.

[0165] 702. Combine the injection well identifier and the pressure gradient adjustment amount to generate a pressure gradient allocation strategy, and calculate the flow rate adjustment parameter of the pumping well based on the pressure gradient allocation strategy;

[0166] In step 702, the pressure gradient allocation strategy refers to the allocation scheme of the pressure adjustment amount of each injection well. The flow rate adjustment parameter refers to the change value of the extraction rate that needs to be adjusted in the extraction well.

[0167] In this embodiment, a mapping table between injection well identifiers and pressure gradient adjustment values ​​is first established. A pressure gradient allocation strategy is then generated based on this mapping table, and changes in the flow direction of the leachate are simulated using a groundwater flow numerical model. The required flow rate increase for the pumping well is then calculated based on the solute removal efficiency in the retention zone from the simulation results. Finally, the flow rate adjustment parameters for the pumping well are output.

[0168] 703、combine the pressure gradient adjustment amount and the flow adjustment parameter to generate injection and extraction flow adjustment instructions for eliminating leaching dead angles.

[0169] In step 703, the spatiotemporal coordination of the pressure and flow parameters is combined and superimposed. The injection and extraction flow adjustment instructions refer to a specific set of operation commands that can be executed by the device control.

[0170] In the embodiments of the present application, first, the pressure gradient adjustment amount is grouped according to the implementation time sequence. Second, each group of pressure adjustment is bound with the corresponding liquid extraction well flow parameter. Then, safety constraints are added to the binding results. Finally, the injection and extraction flow adjustment instructions with timestamps are generated in steps.

[0171] The following is a specific example:

[0172] In the pressure anomaly event in the northwest area of a certain uranium mine, the correlation matrix shows a strong correlation between the south section of the fault zone and the southeast retention area. The set of blocking points is identified to be linearly distributed, and it is determined that the adjacent injection wells need to be depressurized. The pressure reduction amount is calculated in combination with the permeation direction. The flow of the east extraction well is calculated by the water flow model. The pressure reduction operation and the flow increase operation are bound to generate instructions. In the first phase, the target injection well is implemented in steps to reduce pressure, and the extraction well flow is increased in time periods.

[0173] In summary, steps 701 to 703 accurately locate the injection well nodes that need to be controlled through the correlation matrix, calculate the physically reasonable pressure adjustment amount based on the spatial distribution of the blocking points and the characteristics of the permeation direction. The final step generates a step-by-step instruction that takes into account the control efficiency and engineering safety. The geological correlation analysis is converted into an operational engineering instruction, significantly improving the timeliness and resource recovery efficiency of eliminating leaching dead angles.

[0174] Figure 2 A structural diagram of a uranium in-situ leaching solute transport control system based on three-dimensional geological modeling is provided for the embodiments of the present application, as shown in Figure 2 The system comprises:

[0175] The acquisition module 21 acquires high-frequency pressure data of the injection well, constructs a uranium mine permeability distribution field in combination with the three-dimensional geological model, and extracts an abnormal high-pressure blocking coordinate set from the uranium mine permeability distribution field;

[0176] The conversion module 22 collects the magnetic anomaly signal caused by the change of iron ion concentration in the leaching agent, and converts the spatial gradient of the magnetic anomaly signal into a solute transport trajectory graph representing the uranium in-situ leaching solute transport path. The solute diffusion lag atlas is constructed based on the spatial variation characteristics of the solute transport trajectory graph;

[0177] The extraction module 23 extracts the lag boundary coordinate set of the leaching agent in the solute diffusion lag atlas according to the diffusion lag characteristics of the solute diffusion lag atlas;

[0178] The matching module 24 performs spatial matching between the abnormal high-pressure blocking coordinate set and the hysteresis boundary coordinate set, to generate a blocking-hysteresis correlation matrix of the uranium ore geology blocking point and the in-situ leaching solute hysteresis area;

[0179] The generating module 25 adjusts the pressure gradient distribution strategy of the injection well based on the blocking-hysteresis correlation matrix, to generate an injection and extraction flow adjustment instruction for inhibiting the leaching dead angle.

[0180] Figure 2 The uranium in-situ leaching solute transport regulation system based on three-dimensional geological modeling can perform Figure 1 The uranium in-situ leaching solute transport regulation method based on three-dimensional geological modeling has the implementation principle and technical effects which will not be repeated. For the specific operation manner of each module and unit of the uranium in-situ leaching solute transport regulation system based on three-dimensional geological modeling in the above embodiment, the detailed description has been made in the embodiment related to the method, which will not be described in detail here.

[0181] In one possible design, Figure 2 The uranium in-situ leaching solute transport regulation system based on three-dimensional geological modeling can be implemented as a computing device, such as Figure 3 As shown, the computing device can include a storage component 31 and a processing component 32.

[0182] The storage component 31 stores one or more computer instructions, wherein the one or more computer instructions are called and executed by the processing component 32.

[0183] The processing component 32 is configured to perform the above Figure 1 The uranium in-situ leaching solute transport regulation method based on three-dimensional geological modeling.

[0184] The processing component 32 can include one or more processors to execute the computer instructions to complete all or part of the steps in the above method. Of course, the processing component can also be one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors or other electronic elements, for executing the above method.

[0185] The storage component 31 is configured to store various types of data to support the operation of the terminal. The storage component can be implemented by any type of volatile or nonvolatile storage devices or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, a magnetic disk, or an optical disk.

[0186] Of course, the computing device can also necessarily include other components, such as an input / output interface, a display component, a communication component, etc.

[0187] The input / output interface provides an interface between the processing component and peripheral interface modules, which can be output devices, input devices, etc.

[0188] The communication component is configured to facilitate wired or wireless communication between the computing device and other devices, etc.

[0189] The computing device can be a physical device or an elastic computing host provided by a cloud computing platform, and the computing device can be a cloud server, and the processing component, the storage component, etc. can be basic server resources rented or purchased from the cloud computing platform.

[0190] The embodiment of the application further provides a computer storage medium, which stores a computer program, and the computer program can implement the above-mentioned Figure 1 The embodiment shown in the figure is a uranium mine in-situ leaching solute transport regulation method based on three-dimensional geological modeling.

[0191] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the above-described system, device and unit can refer to the corresponding process in the foregoing method embodiment, which will not be described here.

[0192] The device embodiment described above is only schematic, wherein the units described as separate components can or can not be physically separated, and the components displayed as units can or can not be physical units, that is, they can be located in one place, or distributed on multiple network units. According to actual needs, part or all of the modules can be selected to achieve the purpose of the embodiment scheme. Those skilled in the art can understand and implement without creative labor.

[0193] Those skilled in the art can clearly understand the implementation of the various embodiments by means of software and necessary general hardware platforms through the description of the above embodiments, and of course, the implementation can also be through hardware. Based on such understanding, the above technical solutions, essentially or in other words, the part of the prior art that makes a contribution, can be embodied in the form of a software product, which can be stored in a computer readable storage medium, such as a ROM / RAM, a magnetic disk, an optical disk, etc., and includes a number of instructions to make a computer device (which can be a personal computer, a server, or a network device, etc.) execute the methods described in the various embodiments or some parts of the embodiments.

[0194] Finally, it should be noted that: the above examples are only used to illustrate the technical solutions of the present application, and not to limit them; although the present application has been described in detail with reference to the foregoing examples, those skilled in the art should understand that: it can still modify the technical solutions recorded in the foregoing examples, or make equivalent replacement for some technical features thereof; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the various embodiments of the present application.

Claims

1. A method for regulating solute transport in uranium leaching based on three-dimensional geological modeling, characterized in that: include: Acquire high-frequency pressure data of the injection well, construct a uranium permeability distribution field in combination with a three-dimensional geological model, and extract an abnormally high-pressure blocking coordinate set from the uranium permeability distribution field; The method collects magnetic anomaly signals caused by changes in the iron ion concentration in the leaching agent, converts the spatial gradient of the magnetic anomaly signals into a solute migration trajectory diagram that characterizes the solute migration path of the uranium ore in-situ leaching, and constructs a solute diffusion hysteresis map based on the spatial variation characteristics of the solute migration trajectory diagram; extracting a hysteresis boundary coordinate set of the leachate in the solute diffusion hysteresis map according to the diffusion hysteresis characteristics of the solute diffusion hysteresis map; Spatially matching the abnormally high pressure blocking coordinate set with the hysteresis boundary coordinate set to generate a blocking and retention correlation matrix between uranium ore geological blocking points and in-situ leaching solute retention areas; The pressure gradient distribution strategy of the injection well is adjusted based on the blockage and retention correlation matrix, and an injection flow rate regulation instruction is generated to suppress the leaching dead corner.

2. The method according to claim 1, characterized in that The abnormally high pressure blocking coordinate set is spatially matched with the hysteresis boundary coordinate set to generate a blocking and retention correlation matrix between uranium geological blocking points and in-situ leaching solute retention areas, including: Establishing a spatial index framework of a three-dimensional geological model, spatially associating the spatial index framework with the abnormally high-pressure blocking coordinate set to generate a uranium geological blocking point set; Performing spatial regional integration on the lag boundary coordinate set to obtain a closed boundary region, calculating the spatial distance between the uranium geological blockage point set and the closed boundary region, and taking the uranium geological blockage points whose spatial distance is less than a preset tolerance range as associated blockage points; A state record table reflecting the corresponding relationship between the associated blocking points and the closed boundary area is established, and the state record table is converted into a two-dimensional relationship structure to generate a blocking retention association matrix.

3. The method according to claim 2, characterized in that The spatial index framework is spatially associated with the abnormally high-pressure blocking coordinate set to generate a uranium geological blocking point set, including: Dividing the spatial index framework into grid areas, and mapping each coordinate point in the abnormally high-pressure blocking coordinate set to a corresponding grid area to generate a candidate blocking point set; Matching and associating the three-dimensional geological model with the three-dimensional position data of the candidate blocking point set to generate a correlation data table, and screening the coordinate points that meet the preset blocking-prone lithology type in the correlation data table to generate a blocking-prone point set; The coordinate points in the easy-to-block point set are configured with blocking attribute identifiers, and the configured coordinate points are sorted according to the spatial order of the grid area to generate a uranium geological blocking point set.

4. The method according to claim 1, wherein Converting the spatial gradient of the magnetic anomaly signal into a solute migration trajectory diagram representing the solute migration path of uranium ore in-situ leaching, including: Extracting a spatial gradient vector set of the magnetic anomaly signal, and decomposing the spatial gradient vector set into a component along the strike of the ore seam, a component perpendicular to the strike of the ore seam, and a vertical component; Performing strike correction on the component along the ore seam strike to generate an ore seam strike baseline, and simultaneously superimposing the component perpendicular to the ore seam strike with the vertical component to generate a solute migration direction set; The ore seam strike baseline is used as a reference path, and the solute migration direction set is projected onto the reference path to generate local migration trajectory segments, and each local migration trajectory segment is fused and connected to construct an initial solute migration trajectory network; The initial solute migration trajectory network is mapped to the coordinate system of the three-dimensional geological model to obtain a solute migration trajectory map.

5. The method according to claim 1, wherein Constructing a solute diffusion hysteresis map based on the spatial variation characteristics of the solute migration trajectory map, including: Dividing the solute migration trajectory diagram into spatial grids, and calculating the directional change rate of the local migration trajectory segment in each spatial grid; Identify the spatial grids whose directional change rate exceeds a preset critical threshold as migration anomaly grids, and connect the migration anomaly grids to obtain a migration anomaly area; The attenuation coefficient of the solute migration rate in the migration anomaly area is calculated, and a solute diffusion hysteresis coefficient field is generated using the attenuation coefficient as a filling value. The solute diffusion hysteresis coefficient field and the three-dimensional geological model are spatially clipped to construct a solute diffusion hysteresis map.

6. The method according to claim 1, characterized in that Extracting a hysteresis boundary coordinate set of the leachate in the solute diffusion hysteresis map according to the diffusion hysteresis characteristics of the solute diffusion hysteresis map includes: Extracting diffusion hysteresis features from the solute diffusion hysteresis map, and identifying gradient mutation interfaces in the diffusion hysteresis features; Converting the pixel coordinate point set of the gradient mutation interface into a three-dimensional coordinate point set of a three-dimensional geological model, and spatially connecting the converted three-dimensional coordinate point set to generate an initial boundary polyline; The initial boundary polyline is closed at both ends to obtain a closed boundary loop, and the coordinate sequences of each vertex of the closed boundary loop are combined to generate a lag boundary coordinate set of the leachate.

7. The method according to claim 1, characterized in that Adjusting the pressure gradient distribution strategy of the injection well based on the blockage and retention correlation matrix to generate an injection flow rate adjustment instruction for suppressing leaching dead corners includes: Identifying corresponding injection well identifiers according to associated blocking points in the blocking and retention association matrix, and determining pressure gradient adjustment amounts for each injection well according to spatial distribution characteristics of the associated blocking points and permeability directions of a three-dimensional geological model; The injection well identifier and the pressure gradient adjustment amount are correspondingly combined to generate a pressure gradient allocation strategy, and the flow rate regulation parameter of the pumping well is calculated based on the pressure gradient allocation strategy; The pressure gradient adjustment amount and the flow rate adjustment parameter are combined and superimposed to generate an injection flow rate adjustment instruction for suppressing leaching dead corners.

8. A uranium mine in-situ leaching solute transport control system based on three-dimensional geological modeling, characterized in that: include: an acquisition module for acquiring high-frequency pressure data of the injection well, constructing a uranium permeability distribution field in combination with a three-dimensional geological model, and extracting an abnormally high-pressure blocking coordinate set from the uranium permeability distribution field; a conversion module that collects magnetic anomaly signals caused by changes in the iron ion concentration in the leachate, converts the spatial gradient of the magnetic anomaly signals into a solute migration trajectory diagram that characterizes the solute migration path in uranium leaching, and constructs a solute diffusion hysteresis map based on the spatial variation characteristics of the solute migration trajectory diagram; an extraction module, extracting a hysteresis boundary coordinate set of the leachate in the solute diffusion hysteresis map according to the diffusion hysteresis characteristics of the solute diffusion hysteresis map; a matching module for spatially matching the abnormally high pressure blocking coordinate set with the hysteresis boundary coordinate set to generate a blocking and retention correlation matrix between uranium geological blocking points and in-situ leaching solute retention areas; A generation module adjusts the pressure gradient distribution strategy of the injection well based on the blockage and retention correlation matrix, and generates an injection flow rate regulation instruction for suppressing leaching dead corners.

9. A computing device, characterized in that The method comprises a processing component and a storage component; the storage component stores one or more computer instructions; the one or more computer instructions are used to be called and executed by the processing component to implement a method for regulating solute migration in uranium leaching based on three-dimensional geological modeling as described in any one of claims 1 to 7.

10. A computer storage medium, characterized in that A computer program is stored, and when the computer program is executed by a computer, the method for controlling solute migration in uranium leaching based on three-dimensional geological modeling according to any one of claims 1 to 7 is implemented.

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