Prediction method for in-situ leaching effect of low-permeability sandstone type uranium ore

Abstract

The invention relates to the technical field of in-situ leaching mining of low-permeability sandstone type uranium ore, in particular to a prediction method for the in-situ leaching effect of the low-permeability sandstone type uranium ore. And constructing a single-hole blasting physical model, and simulating the change of the radiuses of the crushed region and the fractured region of the uranium mine by updating a non-coupling coefficient. Thirdly, constructing a multi-physics field coupling model, including a geometric model, rock parameter definition, initial and boundary condition setting, introduction of a fracture geometric model, and simulation of in-situ leaching uranium concentration and uranium recovery rate change curves after blasting permeation enhancement; the multi-physical field model covers a dilute material transfer field, a Darcy seepage field and a chemical field. And based on the uncoupling coefficients corresponding to the uranium concentration and the uranium recovery rate peak value, determining the optimal uncoupling coefficient, further constructing an HJC field scale blasting model, adjusting blasting parameters, and optimizing the uranium mine crack expansion condition and the in-situ leaching effect. And finally, in combination with the optimal blasting parameter, analyzing the influence of different in-situ leaching parameters on the in-situ leaching process, and optimizing the reaction rate, so that the whole process optimization is realized, and the in-situ leaching efficiency is improved.

Description

Technical Field

[0001] The present application relates to the technical field of in-situ leaching mining of low-permeability sandstone uranium deposits, and more specifically, to a method for predicting the in-situ leaching effect of low-permeability sandstone-type uranium deposits. Background Technique

[0002] As an important type of uranium ore resources, the development and utilization of low-permeability sandstone-type uranium deposits have become a key research direction in the global nuclear energy industry. In-situ leaching technology (ISL), as an efficient and environmentally friendly uranium ore mining method, shows unique advantages in the mining of low-permeability sandstone-type uranium deposits. Compared with traditional mine mining methods, in-situ leaching technology does not require large-scale excavation and can achieve rapid recovery of underground uranium ore resources, with advantages such as low cost and small environmental impact. Therefore, in-situ leaching technology has become one of the preferred methods for the mining of low-permeability sandstone-type uranium deposits.

[0003] However, the ore permeability of low-permeability sandstone-type uranium ore is poor, the distribution of uranium minerals in the ore body is uneven, and the formation of permeation channels and the permeation of leaching solution are affected by various factors. Due to the low permeability of the ore body, problems such as low leaching efficiency and difficult permeation of leaching solution often occur during the in-situ leaching process, thus limiting the application effect of in-situ leaching technology in low-permeability sandstone-type uranium deposits. Therefore, how to improve the in-situ leaching effect of low-permeability sandstone-type uranium ore has always been a difficult point in the research of in-situ leaching technology.

[0004] Based on the above problems, the fracturing permeability enhancement technology has emerged. However, the existing prediction methods for fracturing permeability enhancement effect mainly rely on traditional empirical formulas or simulation calculations, and these methods often have large prediction errors and uncertainties under complex geological conditions. Therefore, how to develop a more accurate and reliable prediction method for the in-situ leaching effect of low-permeability sandstone-type uranium ore, so as to improve the recovery efficiency of uranium ore resources, has become a technical problem to be solved. Summary of the Invention

[0005] In view of this, the present application provides a method for predicting the in-situ leaching effect of low-permeability sandstone-type uranium ore, which can more accurately predict the in-situ leaching effect of uranium ore by comprehensively considering factors such as formation characteristics, blasting parameters, and mineral reactions.

[0006] The technical solution provided by the present application is as follows:

[0007] A method for predicting the in-situ leaching effect of low-permeability sandstone-type uranium ore, comprising:

[0008] Construct a single-hole blasting physical model, update the decoupling coefficient of the single-hole blasting physical model with a preset time step, and obtain the change curves of the radii of the uranium ore crushing zone and the fracture zone;

[0009] Construct a multi - physical - field coupling model for uranium ore, including constructing a geometric model, defining rock parameters, setting initial conditions and boundary conditions, importing the fracture geometric model into the geometric model, and simulating the variation curves of in - situ leaching uranium concentration and uranium recovery rate for enhancing permeability of uranium ore by blasting; the multi - physical fields include dilute substance transfer field, Darcy seepage field and chemical field;

[0010] Based on the variation curves of the in - situ leaching uranium concentration and uranium recovery rate, take the decoupling coefficient corresponding to the peak values of uranium concentration and uranium recovery rate as the optimal decoupling coefficient;

[0011] Based on the optimal decoupling coefficient, construct an HJC in - situ scale blasting model, adjust the blasting parameters of the HJC in - situ scale blasting model to obtain the fracture propagation situation of uranium ore and the variation curves of in - situ leaching uranium concentration and uranium recovery rate under different blasting parameters, which are used to determine the optimal blasting parameters; the blasting parameters include blasting pressure, blasting time interval and blasting sequence;

[0012] Based on the optimal blasting parameters, analyze the variation curves of in - situ leaching uranium concentration and uranium recovery rate under the influence of different in - situ leaching parameters, and optimize the reaction rate in the in - situ leaching process by adjusting the in - situ leaching parameters; the in - situ leaching parameters include matrix permeability, O 2 concentration, HCO 3 - concentration, injection rate and average uranium grade.

[0013] One possible implementation, the single - hole blasting physical model is a two - dimensional RHT constitutive model;

[0014] The construction of the single - hole blasting physical model includes:

[0015] Construct a two - dimensional RHT constitutive model and define the rock material type and model size;

[0016] Perform mesh division on the two - dimensional RHT constitutive model and set the corresponding boundary stress conditions and blasting parameters; among them, the boundary stress conditions include vertical constraint boundary and horizontal non - reflective boundary.

[0017] One possible implementation, based on the single - hole blasting physical model, obtaining the variation curves of the radii of the crushed zone and fracture zone of uranium ore includes:

[0018] According to the preset time step, calculate the damage degree D of the single - hole blasting physical model, and combine with the fracture geometric model to analyze the radius changes of the crushed zone and fracture zone during the uranium ore blasting process, so as to obtain the variation curves of the radii of the crushed zone and fracture zone of uranium ore.

[0019] One possible implementation, constructing a multi - physical - field coupling model for uranium ore includes:

[0020] Create a geometric model and set the initial conditions and material parameters; among them, the initial conditions include the initial permeability, the leaching solution, and the initial concentration of the uranium ore layer;

[0021] Using the transient model interfaces of dilute mass transfer, Darcy seepage field, and chemical field, set the corresponding physical fields and define the rock parameters; among them, the rock parameters include the mass fraction of potassium feldspar W KAIS308 , the mass fraction of calcite W CaCO3 , the initial concentration cin KAS308 , the volume V of the rock sample R0 ;

[0022] Set the initial value of dilute mass transfer in the porous medium, define the substance reaction rate, and select the concentration constraint for the boundary condition;

[0023] Set the injection well pressure, production well pressure, injection rate of the injection well, and define the fracture thickness in the Darcy seepage field.

[0024] One possible implementation method is that the initial conditions correspondingly set when constructing the multi-physical field coupling model further include the initial formation pressure;

[0025] The construction of the multi-physical field coupling model of uranium ore further includes;

[0026] According to the initial formation pressure, set the seepage conditions including the fracture thickness d f , the mass flow rate M 0 and the pressure difference P0 between the injection well and the production well;

[0027] Set the reaction equation through the domain ordinary differential and differential algebraic equation interface, including the initial source term f of the distributed ordinary differential equation, which is used to control the reaction rate between the leaching solution and the uranium ore layer, and is expressed as:

[0028] f = chem.r 1 *V m_KAI5i308 +chem.r 3 *V m_U02 -chem.r 2 *V m_CaCO3 -chem.r 4 *V m_Ca504

[0029] In the formula, chem.r 1 is the chemical reaction rate constant of KAISi 3 O 8 , V m_KA5i308 is the molar volume of KAISi 3 O 8 , chem.r 3 is UO2 Chemical reaction rate constant, V m_UO2 is UO 2 Molar volume, chem.r 2 is CaCO 3 Chemical reaction rate constant, V m-CaCO3 is CaCO 3 Molar volume, chem.r 4 is CaSO 4 Chemical reaction rate constant, V m-CaSO4 is CaSO 4 of molar volume;

[0030] The temperature in the chemical field is set to a fixed value, and the chemical reaction equation between the leaching solution and sandstone is defined, expressed as:

[0031] KAISi 3 O 8 (s)+4H + →K + +Al 3+ +2H 2 O+3SiO 2

[0032] Reaction rate r i is chem.kf 1 *chem.c H *1000[mol 4 / m 12 , the total volume reaction order is 5 forward, and the forward reaction rate constant k f is k f-KAISi308 *A n-KAlSi308 [m 12 *kg / mol 5 ; where, A n-KAlSi308 represents the specific surface area of potassium feldspar; k f-KAlSi308 is a specific rate constant determined for the forward reaction of potassium feldspar participation, expressed as:

[0033] k f-KAISi308 =k 25_KAI5i308 +k 25H_KAI5i306

[0034] In the formula, k 25_KAISi308 is the potassium feldspar rate constant, k 25H_KAISi308 is the potassium feldspar rate constant of the acidic mechanism;

[0035] Ca+HCO 3 - →CaC03(s)+H +

[0036] Its reaction rate r j is chem.kf2 *chem.c Ca *chem.c HCO3 The overall reaction order with respect to volume is 2 for the forward reaction. The forward reaction rate constant kf is k f-CaCO3 *A n-CaCO3 [m / mol·kg / s];

[0037] Ca 2+ +SO 4 2- →CaSO 4 (s)

[0038] The reaction rate r j is chem.kf 4 *chem.c Ca *chem.c 504 The overall reaction order with respect to volume is 2 for the forward reaction, and the forward reaction rate constant k f is 5e-8;

[0039] UO 2 (s)+0.50 2 +3HCO 3 - →[UO 2 (CO 3 ) 3 4- +H 2 O+H +

[0040] The reaction rate r j is k f-UO2 *A n-UO2 [kg / m 3 , the overall reaction order with respect to volume is 9 for the forward reaction, and the forward reaction rate constant k f is 1.

[0041] One possible implementation is that after constructing the multi-physics coupling model, the method further includes:

[0042] Select the physical field control grid and regularize the element size;

[0043] In the steady-state solver, select Darcy's law for the variable, set the transient solver to MUMPS, the output time to range(0, 1, 900), the relative tolerance to 0.1, and calculate and plot the in-situ leaching uranium concentration cloud map under the fracture morphology of explosion.

[0044] One possible implementation is that based on the variation curves of in-situ leaching uranium concentration and uranium recovery rate under the influence of different in-situ leaching parameters, the influence of different in-situ leaching parameters on the uranium concentration and uranium recovery curves is analyzed, and the output step size is set to:

[0045] ​range(0, dt, T)

[0046] Where dt is the time node for in-situ leaching calculation, and T is the total duration of in-situ leaching of uranium ore.

[0047] Compared with the prior art, the technical solution of the present application has the following beneficial effects:

[0048] By constructing a single-hole blasting physical model and a multi-physical-field coupling model, it is possible to comprehensively and accurately simulate the changes in in-situ leaching uranium concentration and uranium recovery rate after blasting-induced permeability enhancement in low-permeability sandstone-type uranium ore. This method not only considers the influence of the decoupling coefficient during the blasting process on the radii of the crushed zone and fracture zone of uranium ore, but also comprehensively takes into account various physical-field factors such as the dilute substance transfer field, Darcy seepage field, and chemical field, making the prediction results more accurate and reliable. Further, based on the optimal decoupling coefficient, an HJC in-situ scale blasting model is constructed and the blasting parameters are adjusted, enabling the determination of the optimal combination of blasting parameters, thereby optimizing the blasting process, improving the fracture propagation effect of uranium ore, and increasing the in-situ leaching uranium concentration and uranium recovery rate. In addition, by analyzing the influence of different in-situ leaching parameters on the in-situ leaching process in combination with the optimal blasting parameters and optimizing the reaction rate during the in-situ leaching process, the whole process from blasting to in-situ leaching is optimized, effectively improving the efficiency and economy of in-situ leaching of low-permeability sandstone-type uranium ore, providing scientific and efficient technical support for uranium ore mining, and having significant economic benefits and broad application prospects. Description of the Drawings

[0049] Figure 1 It is a flowchart of a method for predicting the in-situ leaching effect of low-permeability sandstone-type uranium ore based on blasting-induced permeability enhancement provided in Embodiment 1 of the present application.

[0050] Figure 2 It is a schematic diagram of the single-hole blasting physical model constructed in Embodiment 1 of the present application.

[0051] Figure 3 It is a schematic diagram of the relationship curve between the rock blasting damage range and the decoupling coefficient provided in Embodiment 1 of the present application.

[0052] Figure 4 It is a schematic diagram of the in-situ scale HJC blasting model constructed in Embodiment 1 of the present application.

[0053] Figure 5 It is an in-situ leaching cloud map of uranium concentration under the blasting fracture morphology provided in Embodiment 1 of the present application.

[0054] Figure 6 It is a curve of the change in peak uranium concentration and uranium recovery rate provided in Embodiment 1 of the present application.

[0055] Figure 7 It is a sensitivity analysis curve graph of peak uranium concentration under different influencing factors provided in Embodiment 1 of the present application.

[0056] Figure 8 This is a sensitivity analysis curve graph of uranium recovery rate under different influencing factors provided in the first embodiment of the present application.

[0057] Figure 9 This is a flowchart of a method for predicting the in-situ leaching effect of low-permeability sandstone-type uranium ore provided in the second embodiment of the present application. Specific implementation manners

[0058] Next, in combination with the embodiments of the present application, the technical solutions in the embodiments of the present application will be clearly and completely described. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without making creative efforts shall fall within the protection scope of the present application.

[0059] In view of the problem that the existing numerical simulation research model for in-situ leaching with explosive permeability enhancement only considers the improvement effect of explosive permeability enhancement on permeability, but does not fully consider the heterogeneity of the ore body, the change of mineral composition and its influence on the in-situ leaching process, the present application provides a method for predicting the in-situ leaching effect of low-permeability sandstone-type uranium ore based on the explosive permeability enhancement technology. By comprehensively considering factors such as formation characteristics, blasting parameters, and mineral reactions, the in-situ leaching effect of uranium ore can be predicted more accurately. Next, in combination with specific embodiments, the technical solutions provided by the present application will be elaborated in detail.

[0060] Embodiment 1

[0061] See Figure 1 , which is a flowchart of a method for predicting the in-situ leaching effect of low-permeability sandstone-type uranium ore based on the explosive permeability enhancement technology provided in the first embodiment of the present application. As Figure 1 shown in

[0062] Step 101: Construct a single-hole blasting physical model.

[0063] The single-hole blasting physical model in the embodiment of the present application is the RHT constitutive model (Riedel-Hiermaier-Thoma model), which is used to describe the dynamic mechanical behavior of brittle materials such as rocks and concretes under high strain rate and large deformation conditions.

[0064] In this embodiment, a single-hole blasting physical model is constructed in the explicit dynamics solver ANSYS / LS-DYNA, and the above single-hole blasting physical model is meshed, and the corresponding boundary stress conditions and calculation duration are set to simulate the damage cloud map of sandstone-type uranium ore under specific working conditions.

[0065] Among them, the above boundary stress conditions include vertical constraint boundaries and lateral non-reflective boundaries. In blasting simulation, the vertical constraint boundary is used to simulate the fixed or constrained conditions of the single-hole blasting physical model in the vertical direction, representing the constraint effect of the foundation or other supporting structures on the rock. For example, applying a vertical constraint boundary at the bottom of the single-hole blasting physical model can prevent the displacement of the single-hole blasting physical model in the vertical direction, thus more realistically reflecting the actual working conditions. The lateral non-reflective boundary is used to simulate the infinite space conditions of the single-hole blasting physical model in the horizontal direction. In blasting simulation, the stress waves generated by the explosion will reflect at the model boundary, thus affecting the accuracy of the simulation results. The lateral non-reflective boundary can effectively absorb these stress waves and prevent them from reflecting back into the model interior, thus more realistically simulating the wave propagation in infinite space.

[0066] Next, the process of constructing a single-hole blasting physical model based on ANSYS / LS-DYNA software will be elaborated in detail.

[0067] First, enter the preprocessing module Preprocessor in LS-DYNA software. In the preprocessing module Preprocessor, select the element type ElementType / material property MaterialProps' material model MaterialModels to define the unit material type. For example, select "3D Solid 164" as the unit type of the rock material.

[0068] Define the model size in the "Modeling" module. Refer to Figure 2 , which is a schematic diagram of the constructed single-hole blasting physical model provided in the first embodiment of this application. For the single-hole blasting physical model, the size is 17.5 m in length and 17.5 m in width.

[0069] Subsequently, in the "Meshing" module, select "MeshTool" to perform mesh division on the rock, air, and explosive respectively. In the "Solution" module, select "Solution Time" in the "Time Controls" module and set the initiation time to 25000 μs. Finally, export the k file through the "Write Jobname.k" module. In the "LS-Prepost" post-processing, select "SET_NODE" in the "CreEnt" module, set the boundary conditions, including adding non-reflective boundary conditions through "SET_SEGM", and add the boundary conditions to the k file in "Keywrd", and set the blasting parameters, including the decoupling coefficient, blasting pressure, time difference, and blasting sequence.

[0070] Step 102: Calculate the damage degree D of each single-hole blasting physical model according to the time node, and analyze the radius curves of the crushed zone and the fissure zone of the sandstone-type uranium ore to clarify the optimal crack propagation plan.

[0071] Among them, the above time node is used to represent the preset time step of the simulation. In the embodiment of the present application, based on the damage degree D of each single-hole blasting model, the influence of different decoupling coefficients on the radius of the fissure zone and the radius of the crushed zone is evaluated. It should be noted that the blasting effect is to effectively improve the permeability of the low-permeability sandstone uranium reservoir and improve the uranium extraction efficiency. The increased leaching range is related to the length of the crack, and the extended length of the crack is the rock damage range of the blasting effect. In this embodiment, the relationship curve between the rock blasting damage range and the decoupling coefficient is as Figure 3 shown. Combining Figure 3 it can be seen that the radius of the crushed zone gradually decreases with the increase of the decoupling coefficient, and the radius of the fissure zone first increases and then decreases with the increase of the decoupling coefficient. At the decoupling coefficient K = 1.75, the radius of the fissure zone is the largest, R = 448.1 cm. That is, when the decoupling coefficient k = 1.75, the obtained rock damage range is the largest, and the crack propagation effect is the most ideal. Using such cracks for in-situ leaching in COMSOL with CO 2 +O 2 can increase the contact area between the leaching solution and the sandstone, so that the leaching solution and the sandstone can react fully.

[0072] Step 103: Construct a field-scale HJC blasting model to determine the crack propagation conditions under different decoupling coefficients, different blasting pressures, different time differences, and different blasting sequences.

[0073] In the embodiment of the present application, a "six-injection and two-extraction" field-scale HJC blasting model is constructed based on the Holmquist-Johnson-Cook (hereinafter referred to as HJC) constitutive model. Among them, "injection" refers to the injection well, which is used to inject liquid into the sandstone-type uranium ore layer to improve the permeability of the ore layer and the uranium leaching efficiency. "Extraction" refers to the extraction well, which is used to extract the uranium-containing liquid to realize uranium mining.

[0074] In the embodiment of the present application, six injection wells can inject liquid into the ore layer in a larger range. Due to the complex geological conditions and uneven permeability of the sandstone-type uranium ore layer, multiple injection wells can strengthen the permeability of the ore layer from different directions and positions to ensure that the entire ore layer can fully contact the injected liquid, thereby comprehensively improving the permeability of the ore layer and making the uranium leaching reaction more sufficient. The two extraction wells are distributed in the middle of the four injection wells, which can timely and effectively extract the leached uranium-containing liquid, avoid excessive accumulation of liquid in the ore layer, and ensure the continuous and efficient progress of the leaching reaction.

[0075] When conducting blasting modeling in LS-DYNA, a blank blasting model is established using the initial volume method. Then, in the k file, by setting the peak blasting pressure and simultaneously setting the diameter of the explosive in the borehole under the keyword *INITIAL_VOLUME_FRACTION_GEOMETRY, and then putting the k file into LS-Run, the crack propagation conditions under different peak blasting pressures and decoupling coefficients can be obtained.

[0076] After conducting blasting modeling in LS-DYNA, define the parameters of explosives, rocks, and air in the k file. Then, define the initiation sequence and time difference under the keyword *INITIAL_DETONATION, and then put the k file into LS-Run to obtain the crack propagation conditions under different time differences and blasting sequences.

[0077] See Figure 4 , which is a schematic diagram of the constructed in-situ scale HJC blasting model provided in the first embodiment of this application. For the in-situ scale HJC blasting model, the set size is 105 m in length and 70 m in width. The air diameter is R 气 = 1 m, and the borehole radius is R 地 = 0.1 m.

[0078] Step 104: Construct a steady-state and transient model for porous dilute substance transfer, Darcy seepage field, and chemical field.

[0079] Specifically, in the Multiphysics of the multi-physics simulation software COMSOL, a multi-physics coupling model for simulating processes such as dilute substance transfer, fluid flow, and chemical reactions is constructed through physical field interfaces. Using the transient model interfaces of dilute substance transfer, Darcy seepage field, and chemical field, corresponding physical fields and boundary conditions are set in each interface. Coupling the above physical field interfaces together forms a multi-physics coupling model, including a multi-physics steady-state model and a multi-physics transient model.

[0080] Furthermore, define rock parameters, including the mass fraction of potassium feldspar W KAlSi3O8 , the mass fraction of calcite W CaCO3 , the initial concentration cin KAlSi3O8 , the volume V of the rock sample RQ , etc. And import the crack geometry model to simulate the change curves of uranium concentration and uranium recovery rate in the in-situ leaching of uranium ore with enhanced permeability by blasting. The specific steps are as follows. By considering different permeabilities, chemical reactions between the leaching solution and the ore layer, solute transport, and fluid flow processes, the uranium concentration distribution and uranium recovery process are calculated in real-time under transient conditions, so as to optimize the in-situ leaching effect of uranium ore with enhanced permeability by blasting.

[0081] Step 105: Import the crack geometry model to simulate the change curves of uranium concentration and uranium recovery rate in the in-situ leaching of uranium ore with enhanced permeability by blasting.

[0082] Among them, the fracture geometry model refers to a mathematical model used to describe the distribution, shape, and size of fractures. A key link in explosive permeability enhancement is to form fractures to improve the permeability of the ore layer. In the embodiments of this application, the fracture geometry model is imported into COMSOL to simulate the fracture distribution in the ore layer after blasting, and these fractures will affect the flow path of the leaching solution and the uranium transport efficiency. By simulating the change of uranium concentration distribution in the ore layer over time and the change curve of uranium recovery rate over time, it helps to evaluate the impact of explosive permeability enhancement on uranium recovery effect, so as to optimize the blasting parameters and injection / extraction strategies to improve the uranium leaching efficiency.

[0083] In one achievable way, the fracture geometry model is obtained by conducting numerical simulation of explosive permeability enhancement in LS-DYNA. In COMSOL Multiphysics, the above fracture geometry model is imported into the component geometry of COMSOL using a plug-in tool. Optionally, the above plug-in tool can be the plug-in R2V (Ragged to Vector). Component geometry refers to the geometric structure of the model, including all physical regions and boundaries involved in the simulation. The above fracture geometry model is imported into the component geometry of COMSOL through the plug-in R2V, that is, the fracture geometry model is embedded into the geometric structure of the entire simulation, so as to consider the influence of fractures in subsequent numerical simulations.

[0084] The specific steps for simulating the change curves of uranium concentration and uranium recovery rate in in-situ leaching of uranium ore by explosive permeability enhancement include: setting the physical field, boundary conditions, and running the simulation. Specifically, in COMSOL, physical field interfaces such as dilute species transport, Darcy seepage field, and chemical field are set, and the corresponding boundary conditions are defined. In the embodiments of this application, the initial value of dilute species transport in porous media is set, where c H = 1e-4 (mol·m- 3 ), c HCO3 = 1e-4 (mol·m -3 ), c O2 = 1e-4 (mol·m -3 ), c Ca = 1e-4 (mol·m -3 ), c SO4 = 1e-4 (mol·m -3 ). The substance reaction rate is defined, the boundary condition is selected as concentration constraint, and the injection concentration of various substances is input. Running the simulation includes running a transient simulation to observe the change of uranium concentration and leaching rate over time. Analyze the influence of fractures on the in-situ leaching process of uranium ore, and optimize the blasting parameters and injection / extraction strategies.

[0085] Step 106: Create a geometric model in COMSOL and define the physical parameters related to the above geometric model, including the initial permeability kappa, the leaching solution cliq, and the initial concentration core of the uranium ore layer.

[0086] In COMSOL, the geometric model is a mathematical representation of the physical space of the simulation, defining the shape, size, and structure of the simulation region. For the simulation of in-situ leaching of uranium ore, the geometric model includes the boundaries of the uranium ore layer, the positions of the injection wells and pumping wells, and the possible fracture distributions.

[0087] Furthermore, after the above physical parameter settings related to the geometric model are completed, the above method further includes adding material parameters. Take the original sandstone specimen and measure the initial porosity p 0 = 0.2, and the initial permeability kappa = 1e-14 m 2 .

[0088] Step 107: Set the seepage conditions and reaction equations in COMSOL.

[0089] Specifically, setting the seepage conditions includes setting the initial formation pressure P, the fracture thickness d f , the mass flow rate M 0 , and the pressure difference P 0 between the injection well and the pumping well. In COMSOL, the initial formation pressure P is one of the starting conditions of the simulation, which can be achieved by specifying the formation pressure in the "Initial Conditions" setting. For example, set the initial pressure of the formation to a constant value, or set a distribution function according to the actual geological conditions. The fracture thickness d f is an important parameter in the fracture geometric model, affecting the characteristics of fluid flow. In COMSOL, the thickness of the fracture can be defined through the settings of the geometric model. For example, if the fracture is modeled as a thin layer, the thickness parameter of the fracture can be directly set in the geometric module. The mass flow rate M 0 is used to characterize the flow rate of the fluid through the fracture or the wellhead. In COMSOL, the mass flow rate can be defined through the boundary condition settings. For example, set the flow boundary condition on the boundaries of the injection well and the pumping well to specify the inflow and outflow rates of the fluid. The pressure difference P 0 between the injection well and the pumping well, which is used to drive the fluid flow, can be achieved by setting different pressures on the boundaries of the injection well and the pumping well. For example, set the pressure of the injection well to P 注 , and the pressure of the pumping well to P 物 , then the pressure difference P 0 = P 注 - P 物 .

[0090] The set reaction equation includes inputting the initial source term f of the distributed ordinary differential equation into the model to control the reaction rate between the leaching solution and the uranium ore layer. Among them, the initial source term f of the distributed ordinary differential equation is the key parameter for controlling the reaction rate between the leaching solution and the uranium ore layer. In COMSOL, it can be defined and set through the "Domain ODE and DAEs" interface.

[0091] In the embodiment of the present application, the chemical reaction equation between the leaching solution and the ore layer is input into the chemical field in the established COMSOL model, and the open boundary condition is selected to simulate the chemical reaction and material migration during the actual blasting and leaching process. The expression of the distributed ordinary differential equation source term f is:

[0092] f = chem.r_1 * V m_ KAISi 3 O 8 + chem.r_3”V m _UO 2 - chem.r_2 * V m _CaCO 3 - chem.r_4 * V m _CaSO 4

[0093] In the formula, chem.r_1 is the chemical reaction rate constant of KAISi 3 O 8 . V m _KAISi 3 O 8 is the molar volume of KAISi 3 O 8 . chem.r_3 is the chemical reaction rate constant of UO 2 . V m _UO 2 is the molar volume of UO 2 . chem.r_2 is the chemical reaction rate constant of CaCO 3 . V m-CaCO3 is the molar volume of CaCO 3 . chem.r_4 is the chemical reaction rate constant of CaSO 4 . V m-Ca504 is the molar volume of CaSO 4 .

[0094] The actual seepage-reaction process involves multiple consecutive and parallel chemical reaction steps. Each step has its unique reaction rate and mechanism. Ordinary differential and differential-algebraic equations can be used to model each reaction step separately, taking into account their mutual influence to more realistically reflect the entire chemical reaction process. The seepage of liquid in rock affects the transport and distribution of reactants, while chemical reactions change the pore structure of the rock and the properties of the fluid, thereby affecting the seepage process. Through domain ordinary differential and differential-algebraic equations, it is also possible to couple the equations describing seepage (such as Darcy's law) with the equations describing chemical reactions.

[0095] In COMSOL, domain ordinary differential and differential-algebraic equations are usually presented in the following general form:

[0096]

[0097] In the formula, p is the porosity variable to be solved, f is the distributed ordinary differential equation source term, t is the in-situ leaching time, e a is the mass coefficient, d a is the damping or mass coefficient.

[0098] In the embodiments of this application, the damping or mass coefficient d a = 1, and the mass coefficient e a = 0. The discontinuous Lagrangian is selected as the discretized shape function type, and the dependent variable is defined as p, then the initial porosity p 0 = 0.2.

[0099] Specifically, in the simulation of the seepage reaction of liquid in rock, if the seepage process proceeds very slowly, or the inertial effects of the fluid and the rock are very small, then e a can be set to 0. This can simplify the equation, reduce the computational amount, and at the same time obtain sufficiently accurate results. At this time, the equation degenerates into a first-order ordinary differential equation or an algebraic equation, which is easier to solve. d a is the damping or mass coefficient. In the simulation of the seepage reaction of liquid in rock, the damping may be related to factors such as the friction between the fluid and the pore wall of the rock and viscous dissipation. d a = 1 means that the intensity of this damping effect is reflected by a unit coefficient in the equation, which will affect the evolution process of the system over time and make the response of the system gradually tend to be stable.

[0100] The temperature in the chemical field is set to 293.15 K, and the chemical reaction equation between the leaching solution and sandstone is defined as:

[0101] KAISi 3 O 8 (s)+4H + →K + +Al 3+ +2H2 O + 3SiO 2

[0102] The reaction rate r j is chem.kf 1 *chem.c H *1000 [mol 4 / m 12 . The overall reaction order with respect to volume is 5. The forward reaction rate constant k f is k f-KAI5i308 *A n-KAI5i308 [m 12 *kg / mol 5 .

[0103] Among them, k f-KAI5i308 is a specific rate constant determined for the substance, i.e., potassium feldspar participating in the forward reaction, expressed as:

[0104] k f-KAl5i308 = k 25_KA15i308 + k 25H_KA15i308

[0105] In the formula, k 25_KAI5i308 is the potassium feldspar rate constant, and k 25H_KAI5i3O8 is the potassium feldspar rate constant for the acidic mechanism.

[0106] A n-KAI5i308 represents the specific surface area of potassium feldspar. The size of its specific surface area will affect its dissolution in water. A larger specific surface area means a larger contact area between potassium feldspar and water, and water molecules are more likely to interact with the atoms or ions on the surface of potassium feldspar, thus promoting the dissolution process.

[0107] Ca + HCO 3 - → CaCO3(s) + H +

[0108] The reaction rate r j is chem.kf 2 *chem.c Ca *chem.c HCO3 . The overall reaction order with respect to volume is 2. The forward reaction rate constant k f is k f-CaCO3 *A n-CaC03 [m / mol*kg / s].[[]END]]

[0109] Ca 2+ + SO 4 2- → CaSO 4 (s)

[0110] The reaction rate rj For chem.kf 4 *chem.c Ca *chem.c SO4 . The overall volumetric reaction order is 2 forward. The forward reaction rate constant kf is 5e-8.

[0111] UO 2 (s) + 0.50 2 + 3HCO 3 - → [UO 2 (CO 3 ) 3 4- + H 2 O + H +

[0112] Its reaction rate r j is kf -U02 *A n-U02 [kg / m 3 . The overall volumetric reaction order is 9 forward. The forward reaction rate constant k f is 1.

[0113] Step 108: Analyze the influence of different in-situ leaching parameters on the in-situ leaching process of uranium ore through numerical simulation, and optimize these parameters to improve the uranium ore mining efficiency.

[0114] Specifically, the in-situ leaching parameters include matrix permeability, O 2 concentration, HCO 3 - concentration, injection rate, and average uranium grade. In the embodiments of the present application, by the time node d t analyze the uranium concentration and uranium recovery curves under the influence of different in-situ leaching parameters, indicating the importance of different in-situ leaching parameters on the in-situ leaching of uranium ore. Among them, the time node d t is used to define the time step of the simulation. By selecting an appropriate time node d t , the changes in uranium concentration and uranium recovery rate over time can be captured. Specifically, set the time step to be expressed as:

[0115] range(0, d t , T)

[0116] where d t is the time node for in-situ leaching calculation, and T is the total duration of in-situ leaching of uranium ore.

[0117] ​Further, the above method specifically further includes selecting a physical field control grid and setting a solver. Specifically, in the simulation, the physical field control grid is used to define the grid division of the physical field. Selecting an appropriate grid cell size is used to improve the accuracy and efficiency of the simulation. In the embodiments of the present application, the cell size is selected to be normalized, that is, the default grid division strategy is used to ensure that the grid density is high enough to capture complex physical phenomena.

[0118] The above setting of the solver includes setting a steady-state solver and a transient solver. Darcy's Law is selected as the control equation for the steady-state solver to describe the flow of fluid in porous media. The transient solver is set to an efficient sparse matrix solver MUMPS for solving transient problems. The output time is range(0, 1, 900), indicating that the results are output every 1 second from 0 to 900 seconds. The relative tolerance is 0.1, which is used to control the accuracy of the above solver. Based on this, the fracture morphology of the explosion and the uranium concentration in-situ leaching cloud map are calculated and plotted, as Figure 5 shown.

[0119] Further, according to the calculation results, by adjusting the decoupling coefficient K, the influence curves of different fracture morphologies on the in-situ leaching uranium concentration and uranium recovery rate are analyzed to evaluate the uranium ore mining effect. By adjusting the parameters of the influencing factors, including matrix permeability, O 2 concentration, HCO 3 - concentration, injection rate, and average uranium grade, the uranium ore mining efficiency is optimized and the uranium ore leaching rate is increased.

[0120] Among them, in this embodiment, the change curves of the peak uranium concentration and uranium recovery rate are as Figure 6 shown, while the change curves of the peak uranium concentration and uranium recovery rate of different influencing factors: matrix permeability, O 2 concentration, HCO 3 - concentration, injection rate, and average uranium grade are respectively as Figure 7 and Figure 8 shown. Combining the figures, it can be seen that when the decoupling coefficient K = 1.75, the peak uranium concentration and uranium recovery rate reach the highest values, and thus the optimal decoupling coefficient is determined. And under the above optimal decoupling coefficient, the influence degrees of different influencing factors on the in-situ leaching of uranium ore are O 2 concentration > matrix permeability > injection rate > average uranium grade > HCO 3 - concentration.

[0121] Embodiment 2

[0122] See Figure 9 , which is a flowchart of a method for predicting the in-situ leaching effect of low-permeability sandstone-type uranium ore provided by the second embodiment of the present application. AsFigure 7 As shown in, the specific implementation steps of the above method include:

[0123] Step 201: Construct a single-hole blasting physical model, update the decoupling coefficient of the single-hole blasting physical model at a preset time step, and obtain the change curves of the radii of the uranium ore crushing zone and the fracture zone.

[0124] Furthermore, by calculating the damage degree D of the single-hole blasting physical model and combining it with the fracture geometry model of the blasting cracks, the radius changes of the crushing zone and the fissure zone during the blasting process can be accurately analyzed, and the best crack propagation situation can be obtained from these results.

[0125] Step 202: Construct a multi-physical field coupling model of uranium ore, including constructing a geometric model, defining rock parameters, setting initial conditions and boundary conditions, and importing the fracture geometry model into the geometric model to simulate the change curves of the in-situ leaching uranium concentration and the uranium recovery rate of the blasting enhanced permeability uranium ore.

[0126] Specifically, the above multi-physical fields include a dilute substance transfer field, a Darcy seepage field, and a chemical field.

[0127] Step 203: Based on the above change curves of the in-situ leaching uranium concentration and the uranium recovery rate, the decoupling coefficient corresponding to the peak values of the uranium concentration and the uranium recovery rate is taken as the optimal decoupling coefficient.

[0128] Step 204: Based on the above optimal decoupling coefficient, construct an HJC in-situ scale blasting model, adjust the blasting parameters of the HJC in-situ scale blasting model to obtain the crack propagation situation of uranium ore and the change curves of the in-situ leaching uranium concentration and the uranium recovery rate under different blasting parameters, which are used to determine the optimal blasting parameters. Among them, the above blasting parameters include blasting pressure, blasting time difference, and blasting sequence.

[0129] In the embodiment of the present application, by constructing an "injection six and pumping two" in-situ scale blasting model, the influence of different decoupling coefficients, different blasting pressures, different time differences, and different blasting sequences on the crack propagation effect is clarified, and then the blasting parameters are optimized, and the crack development during the blasting enhanced permeability process and its influence on the in-situ leaching effect of uranium ore are accurately predicted.

[0130] Step 205: Based on the above optimal blasting parameters, analyze the change curves of the in-situ leaching uranium concentration and the uranium recovery rate under the influence of different in-situ leaching parameters, and optimize the reaction rate during the in-situ leaching process by adjusting the in-situ leaching parameters. Among them, the above in-situ leaching parameters include matrix permeability, O 2 concentration, HCO 3 - concentration, injection rate, and average uranium grade.

[0131] This embodiment accurately simulates the change curves of uranium concentration and uranium recovery rate during the process of enhanced uranium leaching in-situ by blasting. By considering different permeabilities, chemical reactions between the leaching solution and the ore layer, solute transport, and fluid flow processes, this method calculates the uranium concentration distribution and uranium recovery process in real time under transient conditions, thereby optimizing the in-situ leaching effect of enhanced uranium leaching in-situ by blasting.

[0132] It should be noted that the specific implementation methods of each step in the second embodiment of this application can be further referred to the above-mentioned first embodiment, and will not be elaborated here.

[0133] Compared with the prior art, the technical solution provided by the second embodiment of this application has the following beneficial effects:

[0134] By combining the enhanced uranium leaching in-situ by blasting technology with the geological characteristics of low-permeability sandstone-type uranium ore, a more accurate prediction method for in-situ leaching effect is provided. This method comprehensively considers various factors such as the heterogeneity of the ore body, blasting parameters, and formation reactions, and can effectively improve the accuracy of predicting the in-situ leaching effect of uranium ore. Secondly, the present invention can better simulate the interaction between the ore and the leaching solution during the enhanced uranium leaching in-situ by blasting process, predict the reaction rate and mineral changes during the in-situ leaching process, thereby providing an optimized plan for actual in-situ leaching operations, reducing resource waste, and improving mining efficiency. Finally, the technical solution of the present invention has strong operability and popularization, can be widely applied to the development of low-permeability sandstone-type uranium ore, and has important economic value and environmental benefits.

[0135] Although the embodiments of this application have been shown and described, for those of ordinary skill in the art, it can be understood that various changes, modifications, substitutions, and variations can be made to these embodiments without departing from the principle and spirit of this application. The scope of this application is defined by the appended claims and their equivalents.

Claims

1. A method for predicting the in-situ leaching effect of low-permeability sandstone-type uranium deposits, characterized in that: include: A single-hole blasting physical model is constructed, and the uncoupling coefficient of the single-hole blasting physical model is updated with a preset time step to obtain a change curve of the radius of the uranium ore crushing zone and the fracture zone; Constructing a multi-physical field coupling model of uranium ore, including constructing a geometric model, defining rock parameters, setting initial conditions and boundary conditions, importing a fracture geometric model into the geometric model, and simulating the variation curve of in-situ leaching uranium concentration and uranium recovery rate of blasting-increased uranium ore; the multi-physical fields include a dilute species transfer field, a Darcy seepage field, and a chemical field; Based on the variation curve of the in-situ leaching uranium concentration and the uranium recovery rate, the uncoupling coefficient corresponding to the peak values ​​of the uranium concentration and the uranium recovery rate is taken as the optimal uncoupling coefficient; Based on the optimal uncoupling coefficient, a HJC field-scale blasting model is constructed, and the blasting parameters of the HJC field-scale blasting model are adjusted to obtain the crack expansion of the uranium ore and the change curves of the in-situ leaching uranium concentration and the uranium recovery rate under different blasting parameters, which are used to determine the optimal blasting parameters; the blasting parameters include blasting pressure, blasting time difference and blasting sequence; Based on the optimal blasting parameters, the change curves of in situ leaching uranium concentration and uranium recovery rate under the influence of different in situ leaching parameters are analyzed, and the reaction rate in the in situ leaching process is optimized by adjusting the in situ leaching parameters; the in situ leaching parameters include matrix permeability, O2 concentration, HCO3 - concentration, injection rate and average uranium grade.

2. The method for predicting the in-situ leaching effect of a low-permeability sandstone-type uranium mine according to claim 1, characterized in that: The single-hole blasting physical model is a two-dimensional RHT constitutive model; The single-hole blasting physical model is constructed, including: Construct a two-dimensional RHT constitutive model and define the rock material type and model size; The two-dimensional RHT constitutive model is meshed, and corresponding boundary stress conditions and blasting parameters are set; wherein the boundary stress conditions include vertical constraint boundaries and transverse non-reflective boundaries.

3. The method for predicting the in-situ leaching effect of a low-permeability sandstone-type uranium mine according to claim 1, characterized in that: Based on the single-hole blasting physical model, the change curves of the radius of the uranium ore crushing zone and the fracture zone are obtained, including: According to the preset time step, the damage degree D of the single-hole blasting physical model is calculated, and combined with the crack geometry model, the radius changes of the crushing zone and the crack zone during the uranium mine blasting process are analyzed to obtain the radius change curves of the crushing zone and the crack zone of the uranium mine.

4. The method for predicting the in-situ leaching effect of a low-permeability sandstone-type uranium mine according to claim 1, characterized in that: Construct a multi-physics coupled model of uranium ore, including: Creating a geometric model, setting initial conditions and material parameters; wherein the initial conditions include initial permeability, leaching solution and initial concentration of uranium ore layer; Using the transient model interfaces of dilute species transport, Darcy seepage field, and chemical field, the corresponding physical fields are set and rock parameters are defined; wherein the rock parameters include the mass fraction of potassium feldspar W KAlSi3O8 , calcite mass fraction W CaCO3 , initial concentration cin KAlSi3O8 , the volume of the rock sample V R0 ; Set the initial value of porous medium dilute species transport, define the species reaction rate, and select concentration constraint for boundary conditions; In the Darcy seepage field, the injection well pressure, the pumping well pressure, the injection rate of the injection well are set, and the fracture thickness is defined.

5. The method for predicting the in-situ leaching effect of a low-permeability sandstone-type uranium mine according to claim 1, characterized in that: The initial conditions correspondingly set when constructing the multi-physics field coupling model also include initial formation pressure; The construction of the multi-physics field coupling model of uranium ore also includes: According to the initial formation pressure, the seepage conditions are set including the fracture thickness d f , mass flow rate M0 and pressure difference P0 between injection well and extraction well; The reaction equation is set up through the Domain ODE and DAE interface, including the source term f of the distributed ODE, which is used to control the reaction rate between the leaching solution and the uranium ore layer, expressed as: f=chem.r1*V m_KAlSi3O8 +chem.r3*V m_U02 -chem.r2*V m_CaCO3 -chem.r4*V m_CaSO4 Where chem.r1 is the chemical reaction rate constant of KAlSi3O8, V m_KAlSi3O8 is the molar volume of KAlSi3O8, chem.r3 is the chemical reaction rate constant of UO2, V m_UO2 is the molar volume of UO2, chem.r2 is the chemical reaction rate constant of CaCO3, V m-CaCO3 is the molar volume of CaCO3, chem.r4 is the chemical reaction rate constant of CaSO4, V m-CaSO4 is the molar volume of CaSO4; The temperature in the chemical field is set to a fixed value, and the chemical reaction equation between the leaching solution and the sandstone is defined as follows: KAlSi3O8(s)+4H + →K + +Al 3+ 2H2O+3SiO2 Reaction rate r j For chem.kf1*chem.c H *1000[mol 4 / m 12 ], the total volume reaction order is forward 5, the forward reaction rate constant k f k f-KAlSi3O8 *A n-KAlSi3O8 [m 12 *kg / mol 5 ]; among them, A n-KAlSi3O8 represents the specific surface area of ​​potassium feldspar; k f-KAlSi3O8 is a specific rate constant determined for the forward reaction of potassium feldspar, expressed as: k f-KAlSi3O8 =k 25_KAlSi3O8 +k 25H_KAlSi3O8 In the formula, k 25_KAlSi3O8 is the potassium feldspar rate constant, k 25H_KAlSi3O8 is the rate constant of potassium feldspar in acidic mechanism; Ca+HCO3 - →CaCO3(s)+H + Its reaction rate r j For chem.kf2*chem.c Ca *chem.c HCO3 , the total volume reaction order is forward 2. The forward reaction rate constant k f k f-CaCO3 *A n-CaCO3 [m / mol*kg / s]; Ca 2+ +SO4 2- →CaSO4(s) Its reaction rate r j For chem.kf4*chem.c Ca *chem.c SO4 , the total volume reaction order is forward 2, and the forward reaction rate constant k f is 5e-8; UO2(s)+0.5O2+3HCO3 - →[UO2(CO3)3] 4- +H2O+H + Its reaction rate r j k f-UO2 *A n-UO2 [kg / m 3 ], the total volume reaction order is forward 9, and the forward reaction rate constant k f is 1.

6. The method for predicting the in-situ leaching effect of a low-permeability sandstone-type uranium mine according to claim 1, characterized in that: After constructing the multi-physics field coupling model, the method further includes: Select the physical field controlled mesh and select Normalize for the element size; In the steady-state solver, Darcy's law is selected as the variable, MUMPS is set as the transient solver, the output time is range (0, 1, 900), the relative tolerance is 0.1, and the uranium concentration in-situ leaching cloud map under the blasting gap morphology is calculated and drawn.

7. The method for predicting the in-situ leaching effect of a low-permeability sandstone-type uranium mine according to claim 1, characterized in that: Based on the variation curves of in situ leaching uranium concentration and uranium recovery rate under the influence of different in situ leaching parameters, the influence of different in situ leaching parameters on uranium concentration and uranium recovery curves was analyzed, and the output step size was set to: range(0, dt, T) Where dt is the calculation time node of in-situ leaching, and T is the total time of uranium leaching.

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