In-situ leaching uranium mining extraction and injection well flow decision determination method and system

Abstract

The invention provides an in-situ leaching uranium mining extraction and injection well flow decision determination method and system, and relates to the technical field of in-situ leaching uranium mining, and the method comprises the steps: obtaining measurement data and geological data information of a uranium mining well to be decided; sending the measurement data and geological data information of the uranium mining well to be decided to preset modeling software for three-dimensional modeling, and marking the preset flow field operation parameters of the uranium mining well to be decided into a three-dimensional model obtained by modeling; all preset liquid pumping well flow schemes and all preset liquid injection well flow schemes are sent to Matlab software to be marked, and a three-dimensional model after flow marking is obtained; and performing simulation optimization operation on the three-dimensional model marked with the flow based on a preset multi-objective optimization model, and selecting to obtain an optimal decision scheme of all uranium mining wells to be decided. According to the method, accurate numerical simulation can be carried out on a complex in-situ leaching uranium mining system, and an optimal management strategy meeting constraint conditions can be provided for a management decision maker.

Description

Technical Field

[0001] The present invention relates to the technical field of in-situ leaching uranium, and in particular to a method and system for determining flow rate of an in-situ leaching uranium injection well. Background Art

[0002] In-situ uranium leaching is the main method of natural uranium production in my country. In the production process, chemical agents need to be injected into underground mineral-bearing aquifers through injection wells to dissolve the uranium in the ore layer, and then the uranium-containing solution is extracted to the surface through extraction wells to extract uranium. In the actual in-situ uranium leaching, the decision on the operation parameters of extraction and injection needs to weigh many factors, such as leaching cost, time and effective leaching range. Among them, the defects of the existing technology include the individual acceptance of the flow rate of each well and the limited number of selected schemes, and the inability to differentiate the flow rate of each well under each scheme. The individual acceptance of the flow rate of each well cannot calculate the actual flow rate under the working conditions of the group of wells when the entire well field is operating stably, and there are certain errors in human judgment.

[0003] Therefore, a method and system for determining flow rate decision of in-situ leaching uranium injection wells are needed to improve the above-mentioned problems. Summary of the invention

[0004] The purpose of the present invention is to provide a method and system for determining flow rate of in-situ leaching uranium injection wells to improve the above problems. In order to achieve the above purpose, the technical solution adopted by the present invention is as follows:

[0005] In a first aspect, the present application provides a method for determining flow rate decision of an in-situ leaching uranium injection well, comprising:

[0006] Acquire measurement data and geological data information of the uranium mining well to be decided, wherein the measurement data includes basic hydrogeological parameter data of the uranium mining well to be decided, and the geological data information includes spatial distribution information of the ore layer and stratum distribution characteristic information of the uranium mining well to be decided;

[0007] Sending the measurement data and geological data information of the uranium mining well to be decided to a preset modeling software for three-dimensional modeling, and marking the preset flow field operation parameters of the uranium mining well to be decided into the three-dimensional model obtained by modeling;

[0008] Send all preset pumping well flow plans and injection well flow plans to Matlab software, and mark the pumping well flow and injection well flow of each uranium mining well to be decided in the three-dimensional model based on Matlab software to obtain a three-dimensional model with marked flow;

[0009] Based on the preset multi-objective optimization model, the three-dimensional model with marked flow is simulated and optimized to select the optimal decision-making plan for all uranium mining wells to be decided.

[0010] In a second aspect, the present application also provides a flow rate decision determination system for in-situ leaching uranium injection wells, comprising:

[0011] An acquisition unit, used to acquire measurement data and geological data information of the uranium mining well to be decided, wherein the measurement data includes basic hydrogeological parameter data of the uranium mining well to be decided, and the geological data information includes spatial distribution information of the ore layer and stratum distribution characteristic information of the uranium mining well to be decided;

[0012] A modeling unit, used for sending the measurement data and geological data information of the uranium mining well to be decided to a preset modeling software for three-dimensional modeling, and marking the preset flow field operation parameters of the uranium mining well to be decided into the three-dimensional model obtained by modeling;

[0013] A marking unit is used to send all preset pumping well flow plans and injection well flow plans to Matlab software, and mark the pumping well flow and injection well flow of each uranium mining well to be decided in the three-dimensional model based on Matlab software to obtain a three-dimensional model with marked flow;

[0014] The selection unit is used to perform simulation optimization calculation on the three-dimensional model after the flow is marked based on a preset multi-objective optimization model, and select the optimal decision plan for all uranium mining wells to be decided.

[0015] The beneficial effects of the present invention are:

[0016] The present invention can not only perform accurate numerical simulation on complex in-situ uranium leaching systems, but also provide management decision makers with optimal management strategies that meet constraint conditions. The flexibility and adaptability of the method allow decision makers to adjust flow plans according to different geological environments and economic conditions, helping decision makers to make more intelligent flow settings and adjustment plans, thereby reducing costs while improving the efficiency of in-situ uranium leaching.

[0017] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or be understood by implementing the embodiments of the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the written description, claims, and drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for use in the embodiments are briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without creative work.

[0019] Figure 1 It is a flow chart of a method for determining flow rate of an in-situ leaching uranium injection well described in an embodiment of the present invention;

[0020] Figure 2 It is a schematic diagram of the structure of the flow rate decision-making and determination system for in-situ leaching uranium injection wells described in an embodiment of the present invention.

[0021] In the figure: 701, acquisition unit; 702, modeling unit; 703, marking unit; 704, selection unit; 705, calculation unit; 706, adjustment unit; 7021, first modeling subunit; 7022, second modeling subunit; 7023, third modeling subunit; 7024, fourth modeling subunit; 7041, first processing subunit; 7042, first calculation subunit; 7043, second calculation subunit; 70421, third calculation subunit; 70422, second processing subunit; 70423, fourth calculation subunit; 70424, third processing subunit; 70431, fifth calculation subunit; 70432, fourth processing subunit. DETAILED DESCRIPTION

[0022] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all of the embodiments. The components of the embodiments of the present invention generally described and shown in the drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present invention provided in the drawings is not intended to limit the scope of the claimed invention, but merely represents selected embodiments of the present invention. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0023] It should be noted that similar reference numerals and letters represent similar items in the following drawings, so once an item is defined in one drawing, it does not need to be further defined and explained in the subsequent drawings. At the same time, in the description of the present invention, the terms "first", "second", etc. are only used to distinguish the description and cannot be understood as indicating or implying relative importance.

[0024] Embodiment 1:

[0025] This embodiment provides a method for determining flow rate decision of an in-situ leaching uranium injection well.

[0026] See also Figure 1 , the figure shows that the method includes step S1, step S2, step S3, and step S4.

[0027] Step S1, obtaining measurement data and geological data information of the uranium mining well to be decided, wherein the measurement data includes basic hydrogeological parameter data of the uranium mining well to be decided, and the geological data information includes spatial distribution information of the ore layer and stratum distribution characteristic information of the uranium mining well to be decided;

[0028] It is understandable that this step can provide accurate basic data for subsequent three-dimensional modeling by obtaining detailed measurement data and geological data information, so that the three-dimensional model can truly reflect the underground geological conditions and hydrogeological characteristics. This is of great significance for simulating the fluid flow and leaching range in the uranium mining process, which helps to improve the accuracy and scientificity of flow rate decisions, and ultimately optimize the uranium mining effect and reduce operating costs. Among them, the hydrogeological basic parameter data obtained through field measurements, laboratory tests and historical data analysis reflects the hydrogeological characteristics of the area where the uranium mining well is located, including groundwater level, permeability, porosity, hydraulic gradient and other parameters. The spatial distribution information of the ore layer and the stratigraphic distribution characteristics information obtained through drilling data and geophysical exploration data describe the specific location and distribution of the ore layer underground.

[0029] Step S2, sending the measurement data and geological data information of the uranium mining well to be decided to a preset modeling software for three-dimensional modeling, and marking the preset flow field operation parameters of the uranium mining well to be decided into the three-dimensional model obtained by modeling;

[0030] It is understandable that in this step, by using the preset modeling software to perform three-dimensional modeling and marking the flow field operation parameters into the three-dimensional model, a three-dimensional model that accurately reflects the underground hydrogeological characteristics and stratigraphic structure can be obtained. This model can provide a reliable data basis in the subsequent simulation and optimization process, thereby improving the accuracy and scientificity of flow decision-making, helping to optimize the flow configuration of the pumping and injection wells, improving the uranium mining effect and reducing costs. In this step, step S2 includes step S21, step S22, step S23, and step S24.

[0031] Step S21, converting the measurement data and geological data information of the uranium mining well to be decided, performing XOY plane frame selection processing on the contour map in the converted geological data to obtain a selected terrain contour map;

[0032] It can be understood that this step can ensure the consistency and accuracy of the data by converting the format of the measurement data and geological data information and selecting the contour map, and provide a reliable data basis for subsequent three-dimensional modeling. In particular, the terrain contour map after the selection can accurately reflect the terrain characteristics of the area where the uranium mining well to be decided is located, so that the three-dimensional model can more realistically reflect the actual terrain conditions, which helps to improve the accuracy of modeling and optimization results.

[0033] Step S22, sending the discrete elevation data in the geological data information and the selected terrain elevation line map to the three-dimensional modeling software for processing to obtain a three-dimensional model of the surface;

[0034] It can be understood that in this step, by sending the discrete elevation data and the selected terrain contour map to the 3D modeling software for processing, the constructed surface 3D model can accurately reflect the actual terrain characteristics. This provides an accurate surface foundation for the subsequent construction of the underground geological model, helps to improve the accuracy and reliability of the overall 3D model, and thus improves the accuracy and scientificity of flow decision-making.

[0035] Step S23, taking the measurement point of the measurement data of the uranium mining well to be decided as the coordinate origin, sending the spatial distribution information of the ore layer and the stratum distribution characteristic information in the geological data information to the surface three-dimensional model for coupling processing, and obtaining at least one three-dimensional geological unit model, wherein the three-dimensional geological unit model is a three-dimensional model including the stratum information above the surface of each measurement point;

[0036] It can be understood that this step can generate a three-dimensional geological unit model that accurately reflects the underground geological structure by coupling the spatial distribution information of the ore layer and the stratigraphic distribution characteristics information into the surface three-dimensional model by taking the measurement point as the coordinate origin. These models can describe the location of each uranium mining well and the stratigraphic characteristics around it in detail, provide a reliable geological basis for the subsequent optimization of the flow rate of the pumping and injection wells, and help improve the accuracy and scientificity of the optimization results.

[0037] Step S24, discretize the three-dimensional geological unit model to obtain at least one three-dimensional geological columnar unit, and perform linear interpolation processing on each of the three-dimensional geological columnar units based on the linear interpolation method to obtain a three-dimensional geological model, wherein the three-dimensional geological model is a three-dimensional model that includes the hydrogeological basic parameter data of the uranium mining well locations above the surface and the uranium mining wells below the surface.

[0038] It can be understood that this step can generate a three-dimensional geological model containing detailed geological and hydrogeological parameters by discretizing and linearly interpolating the three-dimensional geological unit model. This model not only accurately reflects the surface and underground geological characteristics, but also provides reliable basic data for optimizing uranium well flow decisions, thereby improving the scientificity and accuracy of decision-making.

[0039] Step S3, sending all preset pumping well flow plans and injection well flow plans to Matlab software, and marking the pumping well flow and injection well flow of each uranium mining well to be decided in the three-dimensional model based on Matlab software, to obtain a three-dimensional model with marked flow;

[0040] It can be understood that this step uses software such as Matlab or Python to call the source program in the three-dimensional model, inputs a series of pumping well flow rates and injection well flow rates in Matlab according to the code for simulation calculations, and marks the pumping well flow rates and injection well flow rates, thereby preparing for the subsequent simulation optimization calculations of the pumping and injection volumes using multi-objective optimization methods in software such as Matlab or Python.

[0041] Step S4: Based on a preset multi-objective optimization model, a simulation optimization operation is performed on the three-dimensional model after the flow is marked, and the optimal decision plan for all the uranium mining wells to be decided is selected.

[0042] It can be understood that this step can comprehensively consider multiple objectives such as operating costs and effective leaching range by simulating and optimizing the three-dimensional model after marking the flow rate based on the multi-objective optimization model to find the optimal decision-making solution. This method not only improves the scientificity and accuracy of decision-making, but also can effectively reduce operating costs and improve uranium mining efficiency. This step includes step S41, step S42 and step S43.

[0043] Step S41, taking the pumping well flow rate and injection well flow rate of all schemes in the three-dimensional model as decision variables;

[0044] It can be understood that in this step, by taking the pumping well flow rate and injection well flow rate of all schemes in the three-dimensional model as decision variables, the optimization model can perform simulation calculations based on these variables, evaluate the effects of different schemes, and find the optimal scheme. This method can ensure that the optimization process comprehensively considers multiple objectives and constraints, and improves the scientificity and accuracy of decision-making.

[0045] Step S42: constructing the objective function and constraint conditions of the multi-objective optimization model based on the decision variables, and calculating the solution set corresponding to the flow rate of the pumping well and the flow rate of the injection well of all schemes;

[0046] In this step, step S42 includes step S421, step S422, step S423 and step S424.

[0047] Step S421, performing cost calculation based on the pumping well flow rate, injection well flow rate and preset operation cost calculation formula of all schemes to obtain the operation cost corresponding to each scheme;

[0048] It can be understood that the operating cost calculation formula in this step is as follows:

[0049] E=Jc+Dc+Rc

[0050] Among them, E represents the operating cost corresponding to each scheme, Jc represents the leaching agent cost, Dc represents the electricity cost, and Rc represents the labor cost.

[0051] Step S422, calculating the effective leaching range corresponding to each scheme based on the particle tracing simulation method, wherein during the simulation, a preset number of neutral particles are set to be injected into each injection well, and all neutral particles captured by the pumping wells within a preset simulation time are counted, and the sum of the grid volumes through which the neutral particles flow is taken as the effective leaching range corresponding to each scheme;

[0052] It can be understood that in this step, the flow of particles in the formation follows the seepage field equation, which is as follows:

[0053]

[0054] Among them, K x , K y , K z is the permeability coefficient along the X, Y, and Z directions in the main infiltration direction; h is the height of the groundwater level; W is the source-sink term; Ss is the storage coefficient; and t is time.

[0055] Step S423, constructing an objective function and constraint conditions based on the operation cost corresponding to each scheme and the effective leaching range corresponding to each scheme, and solving the objective function while satisfying the constraint conditions to obtain the Pareto optimal solution corresponding to all the pumping well flow rates and injection well flow rates in each scheme;

[0056] It can be understood that the calculation formula of the objective function in this step is as follows:

[0057] maxf1=V i

[0058] minf2=PC

[0059] Among them, f1 and f2 are the objective functions of the multi-objective optimization model, V i represents the leaching range under the i-th extraction volume, and PC represents the production cost.

[0060] It can be understood that the constraints in this step are as follows:

[0061] Q 注min ≤Q m,注 ≤Q 注max

[0062] Q 抽min ≤Q n,抽 ≤Q 抽max

[0063] Q 注 ≤Q 抽 ≤1.03Q 注

[0064] Among them, Q注max Indicates the maximum total flow rate of a single horizontal injection well, Q 注min Indicates the minimum injection flow rate of a single horizontal injection well, Q n,抽 represents the total flow rate of the nth vertical pumping well, Q 抽max Indicates the maximum total flow rate of a single vertical pumping well, Q 抽min Indicates the minimum total flow rate of a single vertical pumping well, Q 注 Indicates the total injection volume of the vertical injection well in the block, Q 抽 Indicates the total injection volume of the vertical pumping well, Q m,注 Represents the total flow rate of the mth horizontal injection well.

[0065] Step S424: construct a set of all Pareto optimal solutions in each scheme to obtain a solution set corresponding to the pumping well flow rate and the injection well flow rate of all schemes.

[0066] Step S43: Select a preset number of solutions from the solution set and calculate the solution scores according to a preset weight ratio, and use the solution with the highest score as the optimal decision solution for the uranium mining well to be decided.

[0067] It can be understood that this step can comprehensively consider the weights of multiple optimization objectives and select the solution that best meets the decision requirements by selecting a preset number of solutions in the solution set and performing score calculation. This method can effectively balance the weights between different objectives and ensure that the final selected solution has a high optimization effect in multiple aspects. In this step, step S43 includes step S431 and step S432.

[0068] Step S431, calculating the weight distribution scheme corresponding to each weight distribution scheme number according to the preset weight distribution scheme number and the preset calculation formula;

[0069] It is understandable that the number of weight distribution schemes in this step is preset by the decision maker. After the number of recommended schemes is determined, the operating cost weight and the effective leaching range are equally divided between 0% and 100% according to the number of schemes to obtain the corresponding recommended scheme.

[0070] Step S432: Calculate the score of each weighted allocation scheme based on the preset weighted allocation scheme score calculation formula, and compare each weighted allocation scheme, and select the weighted allocation scheme with the highest score as the best decision scheme corresponding to the preset number of weighted allocation schemes.

[0071] It can be understood that in this step, the solution with the highest weight score under each weight distribution coefficient is selected as the recommended solution under the distribution coefficient, that is, the calculation formula of the weight distribution solution score is as follows:

[0072]

[0073] W=max(a1V′ i +a2PC′ i )

[0074] Among them, V′ i represents the effective leaching range after normalization, V i represents the effective leaching range corresponding to each optimal solution, V min represents the minimum effective leaching range corresponding to all optimal solutions, V max Indicates the maximum effective leaching range corresponding to all optimal solutions, PC′ i represents the normalized operating cost, PC i represents the operating cost corresponding to each optimal solution, PC min represents the minimum operating cost corresponding to all optimal solutions, PC max Represents the maximum operating cost corresponding to all optimal solutions.

[0075] It can be understood that step S4 further includes step S5 and step S6.

[0076] Step S5, calculating the coefficient of variation of all the best decision-making solutions based on a preset coefficient of variation calculation formula to obtain the coefficient of variation corresponding to the best decision-making solution;

[0077] It can be understood that the calculation formula of the coefficient of variation of the best decision-making solution is as follows:

[0078]

[0079] Among them, CV i represents the coefficient of variation of the ith decision variable, represents the i-th decision variable under the k-th decision plan, represents the mean of the i-th decision variable in the solution set, and N represents the number of optimal solutions in the solution set.

[0080] Step S6: adjust each optimal decision plan based on the coefficient of variation corresponding to the optimal decision plan, wherein, if the coefficient of variation of the optimal decision plan is greater than or equal to a preset threshold, the optimal decision plan is subjected to flow control processing to obtain the optimal decision plan after flow control.

[0081] It can be understood that when the coefficient of variation corresponding to the best decision-making scheme is greater than or equal to the preset threshold, there is an obvious trade-off between the cost and the effective leaching range of the flow rate of the best decision-making scheme, among which the flow rate change has a greater impact on the objective function. Therefore, when performing flow control to obtain a larger effective leaching range or reduce costs, the focus should be on adjusting the flow rate of this type of well, that is, performing flow control to obtain a larger effective leaching range or reduce costs.

[0082] Embodiment 2:

[0083] like Figure 2 As shown, this embodiment provides a flow rate decision determination system for in-situ leaching uranium injection wells, see Figure 2 The system shown includes an acquisition unit 701 , a modeling unit 702 , a labeling unit 703 and a selection unit 704 .

[0084] The acquisition unit 701 is used to acquire the measurement data and geological data information of the uranium mining well to be decided, wherein the measurement data includes the basic hydrogeological parameter data of the uranium mining well to be decided, and the geological data information includes the spatial distribution information of the ore layer and the stratigraphic distribution characteristic information of the uranium mining well to be decided;

[0085] The modeling unit 702 is used to send the measurement data and geological data information of the uranium mining well to be decided to the preset modeling software for three-dimensional modeling, and mark the preset flow field operation parameters of the uranium mining well to be decided into the three-dimensional model obtained by modeling;

[0086] Among them, the modeling unit 702 includes a first modeling sub-unit 7021, a second modeling sub-unit 7022, a third modeling sub-unit 7023 and a fourth modeling sub-unit 7024.

[0087] The first modeling subunit 7021 is used to convert the measurement data and geological data information of the uranium mining well to be decided, and perform XOY plane frame selection processing on the contour map in the converted geological data to obtain a selected terrain contour map;

[0088] The second modeling subunit 7022 is used to send the discrete elevation data in the geological data information and the selected terrain elevation line map to the three-dimensional modeling software for processing to obtain a three-dimensional model of the surface;

[0089] The third modeling subunit 7023 is used to use the measurement point of the measurement data of the uranium mining well to be decided as the coordinate origin, send the ore layer spatial distribution information and the stratum distribution characteristic information in the geological data information to the surface three-dimensional model for coupling processing, and obtain at least one three-dimensional geological unit model, wherein the three-dimensional geological unit model is a three-dimensional model including the stratum information above the surface of each measurement point;

[0090] The fourth modeling subunit 7024 is used to discretize the three-dimensional geological unit model to obtain at least one three-dimensional geological columnar unit, and perform linear interpolation processing on each of the three-dimensional geological columnar units based on the linear interpolation method to obtain a three-dimensional geological model, wherein the three-dimensional geological model is a three-dimensional model that includes the hydrogeological basic parameter data of the uranium mining well locations above the surface and the uranium mining wells below the surface.

[0091] The marking unit 703 is used to send all the preset pumping well flow plans and injection well flow plans to the Matlab software, and mark the pumping well flow and injection well flow of each uranium mining well to be decided in the three-dimensional model based on the Matlab software to obtain the three-dimensional model after marking the flow;

[0092] The selection unit 704 is used to perform simulation optimization calculation on the three-dimensional model after the flow is marked based on a preset multi-objective optimization model, and select the optimal decision plan for all uranium mining wells to be decided.

[0093] The selection unit 704 includes a first processing subunit 7041 , a first calculation subunit 7042 , and a second calculation subunit 7043 .

[0094] The first processing subunit 7041 is used to use the pumping well flow rate and injection well flow rate of all solutions in the three-dimensional model as decision variables;

[0095] The first calculation subunit 7042 is used to construct the objective function and constraint conditions of the multi-objective optimization model based on the decision variables, and calculate the solution set corresponding to the flow rate of the pumping well and the flow rate of the injection well of all schemes;

[0096] The first calculation subunit 7042 includes a third calculation subunit 70421 , a second processing subunit 70422 , a fourth calculation subunit 70423 and a third processing subunit 70424 .

[0097] The third calculation subunit 70421 is used to perform cost calculation based on the pumping well flow rate, injection well flow rate and preset operation cost calculation formula of all schemes to obtain the operation cost corresponding to each scheme;

[0098] The second processing subunit 70422 is used to calculate the effective leaching range corresponding to each scheme based on the particle tracing simulation method, wherein during the simulation, a preset number of neutral particles are set to be injected into each injection well, and all neutral particles captured by the pumping wells within a preset simulation time are counted, and the sum of the grid volumes through which the neutral particles flow is taken as the effective leaching range corresponding to each scheme;

[0099] The fourth calculation subunit 70423 is used to construct an objective function and a constraint condition based on the operation cost corresponding to each scheme and the effective leaching range corresponding to each scheme, and solve the objective function under the condition of satisfying the constraint condition to obtain the Pareto optimal solution corresponding to all the pumping well flow rates and injection well flow rates in each scheme;

[0100] The third processing subunit 70424 is used to construct a set of all Pareto optimal solutions in each scheme to obtain a solution set corresponding to the flow rate of the pumping well and the flow rate of the injection well of all schemes.

[0101] The second calculation subunit 7043 is used to select a preset number of solutions from the solution set and calculate the solution scores according to a preset weight ratio, and use the solution with the highest score as the optimal decision solution for the uranium mining well to be decided.

[0102] The second calculation subunit 7043 includes a fifth calculation subunit 70431 and a fourth processing subunit 70432 .

[0103] The fifth calculation subunit 70431 is used to calculate the weight distribution scheme corresponding to each weight distribution scheme number according to the preset weight distribution scheme number and the preset calculation formula;

[0104] The fourth processing subunit 70432 is used to calculate the score of each weight distribution scheme based on the preset weight distribution scheme score calculation formula, and based on the comparison of each weight distribution scheme, select each weight distribution scheme with the highest score as the best decision scheme corresponding to the preset number of weight distribution schemes.

[0105] The selection unit 704 further includes a calculation unit 705 and an adjustment unit 706 .

[0106] The calculation unit 705 is used to calculate the coefficient of variation of all the best decision solutions based on a preset coefficient of variation calculation formula to obtain the coefficient of variation corresponding to the best decision solution;

[0107] The adjustment unit 706 is used to adjust each optimal decision plan based on the coefficient of variation corresponding to the optimal decision plan, wherein if the coefficient of variation of the optimal decision plan is greater than or equal to a preset threshold, the optimal decision plan is subjected to flow control processing to obtain the optimal decision plan after flow control.

[0108] It should be noted that, regarding the system in the above embodiment, the specific manner in which each module performs operations has been described in detail in the embodiment of the method, and will not be elaborated here.

[0109] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

[0110] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. A method for determining flow rate of an in-situ leaching uranium injection well, characterized in that: include: Acquire measurement data and geological data information of the uranium mining well to be decided, wherein the measurement data includes basic hydrogeological parameter data of the uranium mining well to be decided, and the geological data information includes spatial distribution information of the ore layer and stratum distribution characteristic information of the uranium mining well to be decided; Sending the measurement data and geological data information of the uranium mining well to be decided to a preset modeling software for three-dimensional modeling, and marking the preset flow field operation parameters of the uranium mining well to be decided into the three-dimensional model obtained by modeling; Send all preset pumping well flow plans and injection well flow plans to Matlab software, and mark the pumping well flow and injection well flow of each uranium mining well to be decided in the three-dimensional model based on Matlab software to obtain a three-dimensional model with marked flow; Based on the preset multi-objective optimization model, the three-dimensional model with marked flow is simulated and optimized to select the optimal decision-making plan for all uranium mining wells to be decided.

2. The method for determining flow rate of in-situ leaching uranium injection wells according to claim 1, characterized in that , sending the measurement data and geological information of the uranium mining well to be decided to the preset modeling software for three-dimensional modeling, including: The measurement data and geological data information of the uranium mining well to be decided are formatted, and the contour map in the converted geological data is processed by XOY plane selection to obtain a terrain contour map after the selection; Sending the discrete elevation data in the geological data information and the selected terrain elevation line map to the three-dimensional modeling software for processing to obtain a three-dimensional model of the surface; The measurement point of the measurement data of the uranium mining well to be decided is used as the coordinate origin, and the spatial distribution information of the ore layer and the stratum distribution characteristic information in the geological data information are sent to the surface three-dimensional model for coupling processing to obtain at least one three-dimensional geological unit model, and the three-dimensional geological unit model is a three-dimensional model that includes the stratum information above the surface of each measurement point; The three-dimensional geological unit model is discretized to obtain at least one three-dimensional geological columnar unit, and each of the three-dimensional geological columnar units is linearly interpolated based on the linear interpolation method to obtain a three-dimensional geological model, which is a three-dimensional model that includes the hydrogeological basic parameter data of the uranium mining well locations above the surface and the uranium mining wells below the surface.

3. The method for determining flow rate of in-situ leaching uranium injection well according to claim 1, characterized in that The simulation optimization operation of the three-dimensional model after marking the flow based on the preset multi-objective optimization model includes: The pumping well flow rate and injection well flow rate of all schemes in the three-dimensional model are used as decision variables; Constructing the objective function and constraint conditions of the multi-objective optimization model based on the decision variables, and calculating the solution set corresponding to the flow rate of the pumping well and the flow rate of the injection well of all schemes; A preset number of solutions in the solution set are selected to calculate the solution scores according to a preset weight ratio, and the solution with the highest score is used as the optimal decision solution for the uranium mining well to be decided.

4. The method for determining flow rate of in-situ leaching uranium injection well according to claim 3, characterized in that , based on the decision variables, the objective function and constraint conditions of the multi-objective optimization model are constructed, and the solution set corresponding to the flow rate of the pumping well and the flow rate of the injection well of all schemes is calculated, including: Cost calculation is performed based on the pumping well flow rate, injection well flow rate and preset operating cost calculation formula of all schemes to obtain the operating cost corresponding to each scheme; The effective leaching range corresponding to each scheme is calculated based on the particle tracing simulation method, wherein a preset number of neutral particles is set to be injected into each injection well during the simulation, and all neutral particles captured by the pumping wells within the preset simulation time are counted, and the sum of the grid volumes through which the neutral particles flow is taken as the effective leaching range corresponding to each scheme; Based on the operation cost corresponding to each scheme and the effective leaching range corresponding to each scheme, an objective function and constraint conditions are constructed, and the objective function is solved while satisfying the constraint conditions to obtain the Pareto optimal solution corresponding to all the pumping well flow rates and injection well flow rates in each scheme; All Pareto optimal solutions in each scheme are constructed into a set to obtain the solution set corresponding to the pumping well flow rate and injection well flow rate of all schemes.

5. The method for determining flow rate of in-situ leaching uranium injection wells according to claim 3, characterized in that , selecting a preset number of solutions from the solution set and calculating the solution scores according to a preset weight ratio, and taking the solution with the highest score as the optimal decision solution for the uranium mining well to be decided, including: The weight distribution scheme corresponding to each weight distribution scheme number is calculated according to the preset weight distribution scheme number and the preset calculation formula; The score of each weight distribution scheme is calculated based on the preset weight distribution scheme score calculation formula, and based on the comparison of each weight distribution scheme, each weight distribution scheme with the highest score is selected as the best decision scheme corresponding to the preset number of weight distribution schemes.

6. A flow rate decision determination system for in-situ leaching uranium injection wells, characterized in that: include: An acquisition unit, used to acquire measurement data and geological data information of the uranium mining well to be decided, wherein the measurement data includes basic hydrogeological parameter data of the uranium mining well to be decided, and the geological data information includes spatial distribution information of the ore layer and stratum distribution characteristic information of the uranium mining well to be decided; A modeling unit, used for sending the measurement data and geological data information of the uranium mining well to be decided to a preset modeling software for three-dimensional modeling, and marking the preset flow field operation parameters of the uranium mining well to be decided into the three-dimensional model obtained by modeling; A marking unit is used to send all preset pumping well flow plans and injection well flow plans to Matlab software, and mark the pumping well flow and injection well flow of each uranium mining well to be decided in the three-dimensional model based on Matlab software to obtain a three-dimensional model with marked flow; The selection unit is used to perform simulation optimization calculation on the three-dimensional model after the flow is marked based on a preset multi-objective optimization model, and select the optimal decision plan for all uranium mining wells to be decided.

7. The flow rate decision determination system for in-situ leaching uranium injection wells according to claim 6, characterized in that: The modeling unit comprises: The first modeling subunit is used to convert the measurement data and geological data information of the uranium mining well to be decided, and perform XOY plane frame selection processing on the contour map in the converted geological data to obtain a terrain contour map after frame selection; The second modeling subunit is used to send the discrete elevation data in the geological data information and the selected terrain elevation line map to the three-dimensional modeling software for processing to obtain a three-dimensional model of the surface; The third modeling subunit is used to use the measurement point of the measurement data of the uranium mining well to be decided as the coordinate origin, send the spatial distribution information of the ore layer and the stratum distribution characteristic information in the geological data information to the surface three-dimensional model for coupling processing, and obtain at least one three-dimensional geological unit model, wherein the three-dimensional geological unit model is a three-dimensional model including the stratum information above the surface of each measurement point; The fourth modeling subunit is used to discretize the three-dimensional geological unit model to obtain at least one three-dimensional geological columnar unit, and to perform linear interpolation processing on each of the three-dimensional geological columnar units based on the linear interpolation method to obtain a three-dimensional geological model, wherein the three-dimensional geological model is a three-dimensional model that includes the hydrogeological basic parameter data of the uranium mining well locations above the surface and the uranium mining wells below the surface.

8. The flow rate decision determination system for in-situ leaching uranium injection wells according to claim 6, characterized in that: The selection unit comprises: A first processing subunit is used to use the pumping well flow rate and the injection well flow rate of all schemes in the three-dimensional model as decision variables; A first calculation subunit is used to construct the objective function and constraint conditions of the multi-objective optimization model based on the decision variables, and calculate the solution set corresponding to the flow rate of the pumping well and the flow rate of the injection well of all schemes; The second calculation subunit is used to select a preset number of solutions from the solution set and calculate the solution scores according to a preset weight ratio, and use the solution with the highest score as the optimal decision solution for the uranium mining well to be decided.

9. The flow rate decision determination system for in-situ leaching uranium injection wells according to claim 8, characterized in that: The first computing subunit comprises: The third calculation subunit is used to perform cost calculation based on the pumping well flow rate, injection well flow rate and a preset operation cost calculation formula of all schemes to obtain the operation cost corresponding to each scheme; The second processing subunit is used to calculate the effective leaching range corresponding to each scheme based on the particle tracing simulation method, wherein during the simulation, a preset number of neutral particles are set to be injected into each injection well, and all neutral particles captured by the pumping wells within a preset simulation time are counted, and the sum of the grid volumes through which the neutral particles flow is used as the effective leaching range corresponding to each scheme; A fourth calculation subunit is used to construct an objective function and constraint conditions based on the operation cost corresponding to each scheme and the effective leaching range corresponding to each scheme, and solve the objective function under the condition of satisfying the constraint conditions to obtain the Pareto optimal solution corresponding to all the pumping well flow rates and injection well flow rates in each scheme; The third processing subunit is used to construct a set of all Pareto optimal solutions in each scheme to obtain a solution set corresponding to the flow rates of the pumping wells and the flow rates of the injection wells of all schemes.

10. The flow rate decision determination system for in-situ leaching uranium injection wells according to claim 8, characterized in that: The second computing subunit comprises: A fifth calculation subunit, configured to calculate, according to a preset number of weight distribution schemes and a preset calculation formula, a weight distribution scheme corresponding to each number of weight distribution schemes; The fourth processing subunit is used to calculate the score of each weight distribution scheme based on a preset weight distribution scheme score calculation formula, and based on the comparison of each weight distribution scheme, select each weight distribution scheme with the highest score as the best decision scheme corresponding to the preset number of weight distribution schemes.

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