A method for predicting the effect of in-situ leaching of low-permeability sandstone-type uranium deposits

Abstract

The application relates to the technical field of low-permeability sandstone uranium ore in-situ leaching, and particularly relates to a method for predicting the in-situ leaching effect of low-permeability sandstone uranium ore. A single-hole blasting physical model is constructed, the uncoupling coefficient is updated, and the changes in the radius of a uranium ore crushing zone and a crack zone are simulated. Then, a multi-physical field coupling model is constructed, including a geometric model, rock parameter definition, initial and boundary condition setting, introduction of a crack geometric model, and simulation of the in-situ leaching uranium concentration and uranium recovery rate change curve after blasting permeability increase. The multi-physical field model covers a rare substance transfer field, a Darcy seepage field and a chemical field. Based on the uncoupling coefficient corresponding to the peak values of the uranium concentration and the uranium recovery rate, the optimal uncoupling coefficient is determined, and then a HJC field scale blasting model is constructed, the blasting parameters are adjusted, and the uranium ore crack expansion and the in-situ leaching effect are optimized. Finally, in combination with the optimal blasting parameters, the influence of different in-situ leaching parameters on the in-situ leaching process is analyzed, the reaction rate is optimized, and thus the whole process is optimized, and the in-situ leaching efficiency is improved.

Description

Technical Field

[0001] This application relates to the field of in-situ leaching mining technology for low-permeability sandstone uranium deposits, and more specifically, to a method for predicting the effectiveness of in-situ leaching in low-permeability sandstone uranium deposits. Background Technology

[0002] Low-permeability sandstone uranium deposits, as an important type of uranium resource, have become a key research direction in the global nuclear energy industry. In-situ leaching (ISL), as a highly efficient and environmentally friendly uranium mining method, has demonstrated unique advantages in the exploitation of low-permeability sandstone uranium deposits. Compared with traditional mining methods, ISL eliminates the need for large-scale excavation, enables rapid recovery of underground uranium resources, and offers advantages such as low cost and minimal environmental impact. Therefore, ISL has become one of the preferred methods for mining low-permeability sandstone uranium deposits.

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

[0004] Based on the aforementioned problems, blasting permeability enhancement technology has emerged. However, existing methods for predicting the effects of blasting permeability enhancement mainly rely on traditional empirical formulas or simulation calculations. These methods often suffer from significant prediction errors and uncertainties under complex geological conditions. Therefore, developing a more accurate and reliable method for predicting the effects of in-situ leaching in low-permeability sandstone-type uranium deposits, thereby improving the recovery efficiency of uranium resources, has become a technical problem that needs to be solved. Summary of the Invention

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

[0006] The technical solution provided in this application is as follows:

[0007] A method for predicting the effectiveness of in-situ leaching in low-permeability sandstone-type uranium deposits includes:

[0008] A single-hole blasting physical model is constructed, and the decoupling coefficient of the single-hole blasting physical model is updated with a preset time step to obtain the variation curves of the radius of the uranium ore crushing zone and the fracture zone.

[0009] A multiphysics coupled model of uranium ore is constructed, including constructing a geometric model, defining rock parameters, setting initial and boundary conditions, importing a fracture geometric model into the geometric model, and simulating the variation curves of in-situ leaching uranium concentration and uranium recovery rate in blast-enhanced uranium ore. The multiphysics field includes a rare matter transport field, a Darcy flow field, and a chemical field.

[0010] Based on the variation curves of the in-situ leaching uranium concentration and uranium recovery rate, the decoupling coefficient corresponding to the peak value of uranium concentration and uranium recovery rate is taken as the optimal decoupling coefficient.

[0011] Based on the optimal decoupling coefficient, an HJC field-scale blasting model is constructed. By adjusting the blasting parameters of the HJC field-scale blasting model, curves showing the fracture propagation, in-situ leaching uranium concentration, and uranium recovery rate under different blasting parameters are obtained to determine the optimal blasting parameters. The blasting parameters include blasting pressure, blasting time difference, and blasting sequence.

[0012] Based on the optimal blasting parameters, the variation curves of uranium concentration and uranium recovery rate under the influence of different leaching parameters were analyzed. The reaction rate during the leaching process was optimized by adjusting the leaching parameters. The leaching parameters include matrix permeability, O2 concentration, and HCO3. - Concentration, injection rate, and average uranium grade.

[0013] One possible implementation is that 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] 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.

[0017] One possible implementation method, based on the single-hole blasting physical model, is to obtain the variation curves of the radii of the uranium ore crushing zone and the fracture zone, including:

[0018] According to the preset time step, the damage degree D of the single-hole blasting physical model is calculated. Combined with the fracture geometry model, the radius changes of the crushing zone and fracture zone during the uranium ore blasting process are analyzed to obtain the radius change curves of the crushing zone and fracture zone of the uranium ore.

[0019] One possible implementation involves constructing a multiphysics coupling model of uranium ore, including:

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

[0021] Using the transient model interface of rare matter transport, Darcy flow field, and chemical field, the corresponding physical fields are set and rock parameters are defined; wherein, the rock parameters include the potassium feldspar mass fraction W. KAlSi3O8 Calcium mass fraction W CaCO3 Initial concentration cin KAlSi3O8 Volume V of the rock sample RQ ;

[0022] Set the initial value for dilute mass transfer in porous media, define the mass reaction rate, and select concentration constraints as the boundary conditions;

[0023] In the Darcy seepage field, the injection well pressure, pumping well pressure, injection rate of the injection well, and fracture thickness are set.

[0024] One possible implementation is that the initial conditions set when constructing the multiphysics coupling model also include the initial formation pressure.

[0025] The construction of the multiphysics coupling model for uranium mines also includes;

[0026] Based on the initial formation pressure, seepage conditions are set, including fracture thickness d. f Mass flow rate M0 and pressure difference P0 between injection well and extraction well;

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

[0028] f=chem.r1*V m_KAlSi3O8 +chem.r3*V m_UO2 -chem.r2*V m_CaCO3 -chem.r4*V m_CaSO4

[0029] In the formula, chem.r1 is the chemical reaction rate constant of KAlSi3O8, and V m_KAlSi3O8 V is the molar volume of KAlSi3O8, chem.r3 is the chemical reaction rate constant of UO2, and V m_UO2 UO2 is the molar volume, chem.r2 is the chemical reaction rate constant of CaCO3, and V is the volume of UO2. m_CaCO3 V is the molar volume of CaCO3, chem.r4 is the chemical reaction rate constant of CaSO4, and V m_CaSO4 This represents the molar volume of CaSO4.

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

[0031] KAlSi3O8(s) + 4H + →K + +Al 3+ +2H₂O+3SiO₂

[0032] reaction rate r j For chem.kf1*chem.c H *1000[mol 4 / m 12 The overall volumetric reaction order is 5 units forward, and the forward reaction rate constant is k. f For k f-KAlSi3O8 *A n-KAlSi3O8 [m 12 *kg / mol 5 ]; where A n-KAlSi3O8 Represents the specific surface area of ​​potassium feldspar; k f-KAlSi3O8 The determined rate constant for the forward reaction involving potassium feldspar is expressed as:

[0033] k f-KAlSi3O8 =k 25_KAlSi3O8 +k 25H_KAlSi3O8

[0034] In the formula, k 25_KAlSi3O8 Let k be the rate constant for potassium feldspar. 25H_KAlSi3O8 The rate constant for potassium feldspar in an acidic mechanism;

[0035] Ca + HCO3 - →CaCO3(s) + H +

[0036] Its reaction rate r j For chem.kf2*chem.c Ca *chem.c HCO3 The overall reaction order is shifted forward by 2; the forward reaction rate constant k f For k f-CaCO3 *A n-CaCO3 [m / mol*kg / s];

[0037] Ca 2+ +SO4 2- →CaSO4(s)

[0038] Its reaction rate r j For chem.kf4*chem.c Ca *chem.c SO4 The overall reaction order is shifted forward by 2, and the forward reaction rate constant is k. f It is 5e-8;

[0039] UO2(s) + 0.5O2 + 3HCO3 - →[UO2(CO3)3] 4- +H2O+H +

[0040] Its reaction rate r j For k f-UO2 *A n-UO2 [kg / m 3 The overall volumetric reaction order is forward 9, and the forward reaction rate constant k is... f The value is 1.

[0041] One possible implementation, after constructing the multiphysics coupling model, further includes:

[0042] Select the physics-controlled mesh, and choose the normalized cell size;

[0043] Darcy's law is selected as the variable in the steady-state solver, and MUMPS is set as the transient solver with an output time range of 0, 1, 900 and a relative tolerance of 0.1. The uranium concentration leaching cloud map under the burst fracture morphology is calculated and plotted.

[0044] One possible implementation method analyzes the influence of different leaching parameters on uranium concentration and uranium recovery rate based on the variation curves of uranium concentration and uranium recovery rate under different leaching parameters, and sets the output step size as follows:

[0045] range(0,dt,T)

[0046] In the formula, dt is the time node for calculating leaching, and T is the total leaching time of uranium ore.

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

[0048] By constructing a single-hole blasting physical model and a multi-physics coupled model, the changes in uranium concentration and uranium recovery rate in in-situ leaching after blasting-enhanced uranium deposits in low-permeability sandstone uranium deposits can be comprehensively and accurately simulated. This method not only considers the influence of the decoupling coefficient during the blasting process on the radius of the uranium ore crushing zone and fracture zone, but also integrates multiple physical field factors such as rare matter transport field, Darcy flow field, and chemical field, making the prediction results more accurate and reliable. Furthermore, based on the optimal decoupling coefficient, an HJC field-scale blasting model is constructed, and the blasting parameters are adjusted to determine the optimal combination of blasting parameters, thereby optimizing the blasting process and improving the fracture propagation effect, in-situ uranium concentration, and uranium recovery rate in uranium deposits. In addition, by combining the optimal blasting parameters to analyze the influence of different in-situ leaching parameters on the in-situ leaching process and optimizing the reaction rate during in-situ leaching, the entire process from blasting to in-situ leaching is optimized, effectively improving the efficiency and economy of in-situ leaching in low-permeability sandstone uranium deposits. This provides scientific and efficient technical support for uranium mining and has significant economic benefits and broad application prospects. Attached Figure Description

[0049] Figure 1 The flowchart illustrates a method for predicting the leaching effect of low-permeability sandstone-type uranium deposits based on blasting permeability enhancement technology, provided in Embodiment 1 of this application.

[0050] Figure 2 This is a schematic diagram of the single-hole blasting physical model constructed according to Embodiment 1 of this application.

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

[0052] Figure 4 This is a schematic diagram of the field-scale HJC blasting model constructed according to Embodiment 1 of this application.

[0053] Figure 5 This is a ground leaching cloud map of uranium concentration under the morphology of explosion fractures provided in Embodiment 1 of this application.

[0054] Figure 6 The curves showing the changes in peak uranium concentration and uranium recovery rate are provided in Example 1 of this application.

[0055] Figure 7 Sensitivity analysis curves of peak uranium concentration under different influencing factors provided in Embodiment 1 of this application.

[0056] Figure 8 Sensitivity analysis curves of uranium recovery rate under different influencing factors provided in Embodiment 1 of this application.

[0057] Figure 9 This is a flowchart illustrating a method for predicting the leaching effect of low-permeability sandstone-type uranium deposits, as provided in Embodiment 2 of this application. Detailed Implementation

[0058] The technical solutions in the embodiments of this application will be clearly and completely described below with reference to the embodiments of this application. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application.

[0059] This application addresses the problem that existing numerical simulation models for in-situ leaching using blasting-enhanced permeability only consider the permeability increase effect of blasting, without fully taking into account the heterogeneity of the ore body, changes in mineral composition, and their impact on the leaching process. It provides a method for predicting the leaching effect of low-permeability sandstone-type uranium deposits based on blasting-enhanced permeability technology. By comprehensively considering factors such as stratigraphic characteristics, blasting parameters, and mineral reactions, this method can more accurately predict the leaching effect of uranium deposits. The technical solution provided in this application will be described in detail below with specific embodiments.

[0060] Example 1

[0061] See Figure 1 This is a flowchart illustrating a method for predicting the leaching effect of low-permeability sandstone-type uranium deposits based on blasting-enhanced permeability technology, provided in Embodiment 1 of this application. Figure 1 As shown, the specific implementation steps of the above method include:

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

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

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

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

[0066] The process of constructing a single-hole blasting physical model based on ANSYS / LS-DYNA software is described in detail below.

[0067] First, in the LS-DYNA software, navigate to the Preprocessor module. In the Preprocessor, select Element Type / Material Props and then Material Models to define the element material type. For example, select "3D Solid 164" as the element type for rock material.

[0068] Define the model dimensions in the "Modeling" module. See also... Figure 2 This is a schematic diagram of the single-hole blasting physical model constructed according to Embodiment 1 of this application. The dimensions of the single-hole blasting physical model are 17.5m in length and 17.5m in width.

[0069] Subsequently, in the "Meshing" module, select "MeshTool" to mesh the rock, air, and explosives separately. In the "Solution" module, select "Solution Time" from the "Time Controls" module and set the initiation time to 25000μs. Finally, export the k file through the "Write Jobname.k" module. In the "LS-Prepost" post-processing, select "SET_NODE" from the "CreEnt" module to set boundary conditions, including adding non-reflective boundary conditions through "SET_SEGM". In "Keywrd", add the boundary conditions to the k file and set the blasting parameters, including the decoupling coefficient, blasting pressure, time delay, 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 fracture zone of the sandstone-type uranium mine to determine the optimal fracture propagation scheme.

[0071] The aforementioned time nodes represent the preset time steps of the simulation. This application's embodiments evaluate the impact of different decoupling coefficients on the radius of the fracture zone and the radius of the pulverized zone based on the damage degree D of each single-hole blasting model. It should be noted that blasting effectively increases the permeability of low-permeability sandstone uranium reservoirs, thereby improving uranium extraction efficiency. The increased leaching range is related to the fracture length; the fracture extension length is the rock damage range caused by the blasting. In this embodiment, the relationship curve between the rock blasting damage range and the decoupling coefficient is shown below. Figure 3 As shown. Combined with Figure 3 It can be seen that the radius of the pulverized zone gradually decreases with the increase of the decoupling coefficient, while the radius of the fracture zone first increases and then decreases with the increase of the decoupling coefficient. The fracture zone radius is the largest, R=448.1cm, at the decoupling coefficient K=1.75. That is, when the decoupling coefficient k=1.75, the resulting rock damage range is the largest, and the fracture propagation effect is the most ideal. With such fractures, in-situ CO2+O2 leaching in COMSOL can increase the contact area between the leaching solution and the sandstone, thereby allowing the leaching solution to react fully with the sandstone.

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

[0073] In this embodiment, a field-scale HJC blasting model with "six injections and two extractions" is constructed based on the Holmquist-Johnson-Cook (HJC) constitutive model. "Injection" refers to injection wells, used to inject liquid into sandstone-type uranium ore layers to improve the permeability of the ore layer and the uranium leaching efficiency. "Extraction" refers to extraction wells, used to extract uranium-containing liquid to achieve uranium mining.

[0074] In this embodiment, six injection wells can inject liquid into the ore layer over a wider area. Due to the complex geological conditions and uneven permeability of sandstone-type uranium ore layers, multiple injection wells can enhance permeability from different directions and locations, ensuring that the entire ore layer is fully in contact with the injected liquid. This comprehensively improves the permeability of the ore layer, allowing for a more complete uranium leaching reaction. Two pumping wells are distributed between the four injection wells, enabling timely and effective extraction of the leached uranium-containing liquid, preventing excessive accumulation of liquid within the ore layer, and ensuring the continuous and efficient leaching reaction.

[0075] When performing blasting modeling in LS-DYNA, a blank blasting model is established using the initial volume method. Then, in the k file, the peak blasting pressure is set, and the diameter of the explosive in the borehole is set under the keyword *INITIAL_VOLUME_FRACTION_GEOMETRY. After that, the k file is placed in LS-Run to obtain crack propagation under different peak blasting pressures and decoupling coefficients.

[0076] After performing blasting modeling in LS-DYNA, the explosive, rock, and air parameters are defined in the k file. Then, the detonation sequence and time difference are defined under the keyword *INITIAL_DETONATION. Finally, the k file is placed in LS-Run to obtain the crack propagation under different time differences and blasting sequences.

[0077] See Figure 4 This is a schematic diagram of the field-scale HJC blasting model constructed according to Embodiment 1 of this application. The field-scale HJC blasting model is set to a length of 105m and a width of 70m. The air diameter is R. 气 =1m, borehole radius is R 炮 =0.1m.

[0078] Step 104: Construct steady-state and transient models of porous rare matter transport, Darcy flow field, and chemical field.

[0079] Specifically, in the multiphysics simulation software COMSOL, a multiphysics coupled model for simulating processes such as rarefaction transport, fluid flow, and chemical reactions is constructed through physics field interfaces. Utilizing the transient model interfaces for rarefaction transport, Darcy flow, and chemical fields, corresponding physics fields and boundary conditions are set in each interface. These various physics field interfaces are coupled together to form a multiphysics coupled model, including a multiphysics steady-state model and a multiphysics transient model.

[0080] Furthermore, rock parameters are defined, including the potassium feldspar mass fraction W. KAlSi3O8 Calcium mass fraction W CaCO3 Initial concentration cin KAlSi3O8 Volume V of the rock sample RQ The process involves importing a fracture geometry model to simulate the variations in uranium concentration and recovery rate during in-situ leaching in blast-enhanced uranium deposits. The specific steps are as follows: by considering different permeabilities, the chemical reaction 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, thereby optimizing the in-situ leaching effect of blast-enhanced uranium deposits.

[0081] Step 105: Import the fracture geometry model to simulate the variation curves of uranium concentration and uranium recovery rate in in-situ leaching of blasted uranium deposits.

[0082] The fracture geometry model refers to the mathematical model used to describe the distribution, shape, and size of fractures. A key aspect of blasting-induced permeability enhancement is the formation of fractures to improve the permeability of the ore layer. This application's embodiments simulate the distribution of fractures in the ore layer after blasting by importing a fracture geometry model into COMSOL. These fractures affect the flow path of the leaching solution and the uranium transport efficiency. By simulating the changes in uranium concentration distribution in the ore layer over time and the uranium recovery rate over time, the impact of blasting-induced permeability enhancement on uranium recovery can be assessed, thereby optimizing blasting parameters and injection / extraction strategies to improve uranium leaching efficiency.

[0083] In one feasible approach, the crack geometry model is obtained through numerical simulation of blasting and infiltration in LS-DYNA. In COMSOL Multiphysics, this crack geometry model is imported into COMSOL's component geometry using a plugin tool. Optionally, this plugin tool can be R2V (Ragged to Vector). Component geometry refers to the geometric structure of the model, including all physical regions and boundaries involved in the simulation. Importing the crack geometry model into COMSOL's component geometry via the R2V plugin embeds the crack geometry model into the overall simulation geometry, allowing the crack's influence to be considered in subsequent numerical simulations.

[0084] The above-mentioned simulated curves showing the changes in uranium concentration and uranium recovery rate during in-situ leaching of blast-enhanced uranium deposits involve the following steps: setting up the physical field, boundary conditions, and running the simulation. Specifically, in COMSOL, interfaces for physical fields such as rare earth transfer, Darcy flow field, and chemical field are set, and corresponding boundary conditions are defined. In this embodiment, an initial value for rare earth transfer in the porous medium 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 Define the reaction rate of the substances, select concentration constraints as the boundary conditions, and input the injection concentrations of various substances. Run the simulation, including a transient simulation, to observe the changes in uranium concentration and leaching rate over time. Analyze the impact of fractures on the in-situ leaching process of uranium deposits, and optimize blasting parameters and injection / extraction strategies.

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

[0086] In COMSOL, a geometric model is a mathematical representation of the simulated physical space, defining the shape, size, and structure of the simulated region. For uranium leaching simulations, the geometric model includes the boundaries of the uranium ore layer, the locations of injection and pumping wells, and the distribution of any potential fractures.

[0087] Furthermore, after setting the physical parameters related to the geometric model, the method also includes adding material parameters. An original sandstone sample is taken, and the initial porosity p0 = 0.2 and the initial permeability kappa = 1e-14m are measured. 2 .

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

[0089] Specifically, setting seepage conditions includes setting the initial formation pressure P and the fracture thickness d. f Mass flow rate M0, pressure difference P0 between injection and extraction wells. In COMSOL, the initial formation pressure P is one of the starting conditions for the simulation, which can be specified in the "Initial Conditions" settings. For example, the initial formation pressure can be set to a constant value, or a distribution function can be set according to the actual geological conditions. Fracture thickness d f The mass flow rate (M0) is a crucial parameter in the fracture geometry model, influencing fluid flow characteristics. In COMSOL, fracture thickness can be defined through geometric model settings. For example, if the fracture is modeled as a thin layer, the fracture thickness parameter can be directly set in the geometry module. The mass flow rate (M0) characterizes the flow rate of fluid through the fracture or wellhead. In COMSOL, the mass flow rate can be defined through boundary condition settings. For example, flow boundary conditions can be set at the boundary between injection and extraction wells to specify the inflow and outflow rates of the fluid. The pressure difference (P0) between the injection and extraction wells drives fluid flow and can be achieved by setting different pressures at the boundary between the injection and extraction wells. For example, setting the pressure of the injection well to P0... 注 The pressure of the pumping well is set to P. 抽 Then the pressure difference P0 = P 注 -P 抽 .

[0090] Setting up the reaction equation involves 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. The initial source term f of the distributed ordinary differential equation is a key parameter controlling the reaction rate between the leaching solution and the uranium ore layer. In COMSOL, this can be defined and set through the "Domain Ordinary Differential Equations and Differential Algebraic Equations" interface.

[0091] In this embodiment, the chemical reaction equation between the leaching solution and the ore layer is input into the chemical field of the established COMSOL model, and open boundary conditions are selected to simulate the chemical reactions and material migration during actual blasting and leaching processes. The expression for the source term f of its distributed ordinary differential equation is as follows:

[0092] f=chem.r _ 1*V m_KAlSi3O8 +chem.r _ 3*V m_UO2 -chem.r _ 2*V m_CaCO3 -chem.r _ 4*V m_CaSO4

[0093] In the formula, chem.r_1 is the chemical reaction rate constant of KAlSi3O8. V m _ KAlSi3O8 V is the molar volume of KAlSi3O8. chem.r_3 is the rate constant γ of the UO2 chemical reaction. m _ UO2 V represents the molar volume of UO2. chem.r_2 represents the chemical reaction rate constant of CaCO3. m_CaCO3 V represents the molar volume of CaCO3. chem.r_4 represents the chemical reaction rate constant for CaSO4. m_CaCO4 denoted as , where is the molar volume of CaSO4.

[0094] Actual seepage-reaction processes involve multiple continuous and parallel chemical reaction steps. Each step has its unique reaction rate and mechanism. Using ordinary differential equations and differential algebraic equations, each reaction step can be modeled separately, while considering their interrelationships to more realistically reflect the entire chemical reaction process. The seepage of liquids in rocks affects the transport and distribution of reactants, while chemical reactions alter the pore structure of the rock and the properties of the fluid, thus influencing the seepage process. Through domain ordinary differential equations and differential algebraic equations, equations describing seepage (such as Darcy's law) can also be coupled with equations describing chemical reactions.

[0095] In COMSOL, field ordinary differential equations 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 source term of the distributed ordinary differential equation, t is the immersion time, and e is the porosity. a For the quality coefficient, d a This is the damping or mass coefficient.

[0098] In this embodiment, the damping or mass coefficient d a =1, quality coefficient e a =0. The discretization function type is chosen as discontinuous Lagrangian, and the dependent variable is defined as p, then the initial porosity p0 = 0.2.

[0099] Specifically, in the simulation of the seepage reaction of liquids in rocks, if the seepage process proceeds very slowly, or the inertial influence of the fluid and rock is small, then e can be used. a Setting it to 0 simplifies the equation, reduces computation, and yields sufficiently accurate results. In this case, the equation degenerates into a first-order ordinary differential equation or algebraic equation, making it easier to solve. a d represents the damping or mass coefficient. In simulations of fluid seepage reactions in rock, damping may be related to factors such as friction between the fluid and the rock pore walls, and viscous dissipation. a =1 means that the strength of this damping effect is represented by a unit coefficient in the equation. It will affect the evolution of the system over time and cause the system response to gradually stabilize.

[0100] The temperature in the chemical field was set to 293.15 K, and the chemical reaction equation between the leachate and sandstone was defined as follows:

[0101] KAlSi3O8(s) + 4H + →K + +Al 3+ +2H₂O+3SiO₂

[0102] Its reaction rate r j For chem.kf1*chem.c H *1000[mol 4 / m 12 The overall volumetric reaction order is forward 5. The forward reaction rate constant k... f For k f-KAlSi3O8 *A n-KAlSi3O8 [m 12 *kg / mol 5 ].

[0103] Where, k f-KAlSi3O8 The determined rate constant for the forward reaction involving potassium feldspar is expressed as:

[0104] k f-KAlSi3O8 =k25_KAlSi3O8 +k 25H_KAlSi3O8

[0105] In the formula, k 25_KAlSi3O8 Let k be the rate constant for potassium feldspar. 25H_KAlSi3O8 The rate constant for potassium feldspar in an acidic mechanism is given.

[0106] A n-KAlSi3O8 This represents the specific surface area of ​​potassium feldspar, which affects its solubility in water. A larger specific surface area means a greater contact area between potassium feldspar and water, making it easier for water molecules to interact with the atoms or ions on the potassium feldspar surface, thus promoting the dissolution process.

[0107] Ca + HCO3 - →CaCO3(s) + H +

[0108] Its reaction rate r j For chem.kf2*chem.c Ca *chem.c HCO3 The overall volumetric reaction order is shifted forward by 2. The forward rate constant k... f For k f-CaCO3 *A n-CaCO3 [m / mol*kg / s].

[0109] Ca 2+ +SO4 2- →CaSO4(s)

[0110] Its reaction rate r j For chem.kf4*chem.c Ca *chem.c SO4 The overall volumetric reaction order is shifted forward by 2. The forward rate constant k... f It is 5e-8.

[0111] UO2(s) + 0.5O2 + 3HCO3 - →[UO2(CO3)3] 4- +H2O+H +

[0112] Its reaction rate r j For k f-UO2 *A n-UO2 [kg / m 3 The overall volumetric reaction order is shifted forward by 9. The forward reaction rate constant k... f The value is 1.

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

[0114] Specifically, the in-situ leaching parameters include matrix permeability, O2 concentration, and HCO3-. - Concentration, injection rate, and average uranium grade. In this embodiment, time node d is used... t The analysis of uranium concentration and uranium recovery curves under the influence of different leaching parameters demonstrates the varying degrees of importance of these parameters on uranium leaching. Specifically, time node d... t Used to define the time step of the simulation. By selecting an appropriate time node d t This allows us to capture changes in uranium concentration and uranium recovery rate over time. Specifically, the time step is set as follows:

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

[0116] In the formula d t The time point for the in-situ leaching calculation is T, where T is the total duration of the uranium ore in-situ leaching.

[0117] Furthermore, the above method also includes selecting a physics control grid and setting the solver. Specifically, in the simulation, the physics control grid is used to define the mesh generation of the physics field. Selecting an appropriate mesh cell size improves the accuracy and efficiency of the simulation. In this embodiment, the cell size selection is conventional, i.e., the default mesh generation strategy is used to ensure that the mesh density is high enough to capture complex physical phenomena.

[0118] The solver setup described above includes both steady-state and transient solvers. Darcy's Law is chosen as the governing equation for the steady-state solver to describe fluid flow in porous media. The transient solver is configured as a high-efficiency sparse matrix solver, MUMPS, for solving transient problems. The output time is set to range(0,1,900), representing a time interval from 0 to 900 seconds, with results output every second. A relative tolerance of 0.1 is used to control the accuracy of the solver. Based on this, a ground-based leaching cloud map of uranium concentration under burst fracture morphology is calculated and plotted, as shown below. Figure 5 As shown.

[0119] Furthermore, based on the calculation results, the influence curves of different fracture morphologies on in-situ leaching uranium concentration and uranium recovery rate were analyzed by adjusting the decoupling coefficient K, thereby evaluating the uranium mining efficiency. This was achieved by adjusting parameters of influencing factors, including matrix permeability, O2 concentration, and HCO3-. - Concentration, injection rate, and average uranium grade are used to optimize uranium mining efficiency and improve uranium leaching rate.

[0120] In this embodiment, the peak uranium concentration and uranium recovery rate change curves are as follows: Figure 6 As shown, different influencing factors include: matrix permeability, O2 concentration, and HCO3. -The peak uranium concentration and uranium recovery curves for concentration, injection rate, and average uranium grade are shown in the figures below. Figure 7 and Figure 8 As shown in the figure, the peak uranium concentration and uranium recovery rate reach their highest values ​​when the decoupling coefficient K = 1.75. Therefore, the optimal decoupling coefficient is determined. Furthermore, under this optimal decoupling coefficient, the influence of different factors on uranium ore in-situ leaching is as follows: O2 concentration > matrix permeability > injection rate > average uranium grade > HCO3. - concentration.

[0121] Example 2

[0122] See Figure 9 This is a flowchart illustrating a method for predicting the leaching effect of low-permeability sandstone-type uranium deposits, provided in Embodiment 2 of this application. Figure 7 As shown, 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 with a preset time step, and obtain the variation curves of the radius 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 crack geometry model of the blasting crack, the radius changes of the crushing zone and the crack zone during the blasting process can be accurately analyzed, and the optimal crack propagation can be obtained through these results.

[0125] Step 202: Construct a multiphysics coupling model of 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 in blast-enhanced uranium ore.

[0126] Specifically, the aforementioned multiphysics field includes the rare matter transport field, the Darcy flow field, and the chemical field.

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

[0128] Step 204: Based on the above-mentioned optimal decoupling coefficient, construct the HJC field-scale blasting model. Adjust the blasting parameters of the HJC field-scale blasting model to obtain the curves showing the fracture propagation, in-situ leaching uranium concentration, and uranium recovery rate under different blasting parameters, which are used to determine the optimal blasting parameters. The aforementioned blasting parameters include blasting pressure, blasting time difference, and blasting sequence.

[0129] In this embodiment, by constructing a "six-injection, two-extraction" field-scale blasting model, the effects of different decoupling coefficients, different blasting pressures, different time differences, and different blasting sequences on the crack propagation effect were clarified. In turn, the blasting parameters were optimized, and the crack development during the blasting permeability enhancement process and its impact on the uranium leaching effect were accurately predicted.

[0130] Step 205: Based on the above optimal blasting parameters, analyze the variation curves of uranium concentration and uranium recovery rate under the influence of different leaching parameters, and optimize the reaction rate during the leaching process by adjusting the leaching parameters. The above leaching parameters include matrix permeability, O2 concentration, and HCO3- concentration. - Concentration, injection rate, and average uranium grade.

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

[0132] It should be noted that the specific implementation methods of each step in Embodiment 2 of this application can be further referred to Embodiment 1 above, and will not be repeated here.

[0133] Compared with the prior art, the technical solution provided in Embodiment 2 of this application has the following beneficial effects:

[0134] By combining blasting-based permeability enhancement technology with the geological characteristics of low-permeability sandstone-type uranium deposits, this invention provides a more accurate method for predicting in-situ leaching effects. This method comprehensively considers multiple factors such as the heterogeneity of the ore body, blasting parameters, and formation reactions, effectively improving the accuracy of uranium leaching effect prediction. Secondly, this invention can better simulate the interaction between ore and leaching solution during blasting-based permeability enhancement, predicting the reaction rate and mineral changes during in-situ leaching, thereby providing optimized solutions for actual in-situ leaching operations, reducing resource waste, and improving mining efficiency. Finally, the technical solution of this invention has strong operability and scalability, and can be widely applied to the development of low-permeability sandstone-type uranium deposits, possessing significant economic value and environmental benefits.

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

Claims

1. A method for predicting the leaching effect of low-permeability sandstone-type uranium deposits, characterized in that, include: A single-hole blasting physical model is constructed, and the decoupling coefficient of the single-hole blasting physical model is updated with a preset time step to obtain the variation curves of the radius of the uranium ore crushing zone and the fracture zone. A multiphysics coupled model of uranium ore is constructed, including constructing a geometric model, defining rock parameters, setting initial and boundary conditions, importing a fracture geometric model into the geometric model, and simulating the variation curves of in-situ leaching uranium concentration and uranium recovery rate in blast-enhanced uranium ore. The multiphysics field includes a rare matter transport field, a Darcy flow field, and a chemical field. Based on the variation curves of the in-situ leaching uranium concentration and uranium recovery rate, the decoupling coefficient corresponding to the peak value of uranium concentration and uranium recovery rate is taken as the optimal decoupling coefficient. Based on the optimal decoupling coefficient, an HJC field-scale blasting model is constructed. By adjusting the blasting parameters of the HJC field-scale blasting model, curves showing the fracture propagation, in-situ leaching uranium concentration, and uranium recovery rate under different blasting parameters are obtained 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 variation curves of uranium concentration and uranium recovery rate under the influence of different leaching parameters were analyzed. The reaction rate during the leaching process was optimized by adjusting the leaching parameters. The leaching parameters include matrix permeability, O2 concentration, and HCO3. - Concentration, injection rate, and average uranium grade.

2. The method for predicting the leaching effect of low-permeability sandstone-type uranium deposits according to claim 1, characterized in that, The physical model for single-hole blasting is a two-dimensional RHT constitutive model. The construction of the single-hole blasting physical model includes: 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 leaching effect of low-permeability sandstone-type uranium deposits according to claim 1, characterized in that, Based on the single-hole blasting physical model, the variation curves of the radii of the uranium ore crushing zone and the fracture zone were obtained, including: According to the preset time step, the damage degree D of the single-hole blasting physical model is calculated. Combined with the fracture geometry model, the radius changes of the crushing zone and fracture zone during the uranium ore blasting process are analyzed to obtain the radius change curves of the crushing zone and fracture zone of the uranium ore.

4. The method for predicting the leaching effect of low-permeability sandstone-type uranium deposits according to claim 1, characterized in that, Constructing a multiphysics coupling model for uranium ore, including: Create a geometric model and set 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 interface of rare matter transport, Darcy flow field, and chemical field, the corresponding physical fields are set and rock parameters are defined; wherein, the rock parameters include the potassium feldspar mass fraction W. KAlSi3O8 Calcium mass fraction W CaCO3 Initial concentration cin KAlSi3O8 Volume V of the rock sample RQ ; Set the initial value for dilute mass transfer in porous media, define the mass reaction rate, and select concentration constraints as the boundary conditions; In the Darcy seepage field, the injection well pressure, pumping well pressure, injection rate of the injection well, and fracture thickness are set.

5. The method for predicting the leaching effect of low-permeability sandstone-type uranium deposits according to claim 1, characterized in that, The initial conditions set when constructing the multiphysics coupling model also include the initial formation pressure; The construction of the multiphysics coupling model for uranium mines also includes; Based on the initial formation pressure, seepage conditions are set, including fracture thickness d. f Mass flow rate M0 and pressure difference P0 between injection well and extraction well; The reaction equation, including the source term f of the distributed ordinary differential equation, is set through the interface of domain ordinary differential equation and differential algebraic equation to control the reaction rate between the leaching solution and the uranium ore layer, and is expressed as: f=chem.r1*V m_KAlSi3O8 +chem.r3*V m_UO2 -chem.r2*V m_CaCO3 -chem.r4*V m_CaSO4 In the formula, chem.r1 is the chemical reaction rate constant of KAlSi3O8, and V m_KAlSi3O8 V is the molar volume of KAlSi3O8, chem.r3 is the chemical reaction rate constant of UO2, and V m_UO2 UO2 is the molar volume, chem.r2 is the chemical reaction rate constant of CaCO3, and V is the volume of UO2. m_CaCO3 V is the molar volume of CaCO3, chem.r4 is the chemical reaction rate constant of CaSO4, and V m_CaSO4 This represents the molar volume of CaSO4. The temperature in the chemical field is set to a fixed value, and the chemical reaction equation between the leachate and 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 overall volumetric reaction order is 5 units forward, and the forward reaction rate constant is k. f For k f-KAlSi3O8 *A n-KAlSi3O8 [m 12 *kg / mol 5 ]; where A n-KAlSi3O8 Represents the specific surface area of ​​potassium feldspar; k f-KAlSi3O8 The determined rate constant for the forward reaction involving potassium feldspar is expressed as: k f-KAlSi3O8 =k 25_KAlSi3O8 +k 25H_KAlSi3O8 In the formula, k 25_KAlSi3O8 Let k be the rate constant for potassium feldspar. 25H_KAlSi3O8 The rate constant for potassium feldspar in an acidic mechanism; Ca+HCO3 - →CaCO3(s)+H + Its reaction rate r j For chem.kf2*chem.c Ca *chem.c HCO3 The overall reaction order is shifted forward by 2; the forward reaction rate constant k f For 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 overall reaction order is shifted forward by 2, and the forward reaction rate constant is k. f It is 5e-8; UO2(s)+0.5O2+3HCO3 - →[UO2(CO3)3] 4- +H2O+H + Its reaction rate r j For k f-UO2 *A n-UO2 [kg / m 3 The overall volumetric reaction order is forward 9, and the forward reaction rate constant k is... f The value is 1.

6. The method for predicting the leaching effect of low-permeability sandstone-type uranium deposits according to claim 1, characterized in that, After constructing the multiphysics coupling model, the method further includes: Select the physics-controlled mesh, and choose the normalized cell size; Darcy's law is selected as the variable in the steady-state solver, and MUMPS is set as the transient solver with an output time range of 0, 1, 900 and a relative tolerance of 0.

1. The uranium concentration leaching cloud map under the burst fracture morphology is calculated and plotted.

7. The method for predicting the leaching effect of low-permeability sandstone-type uranium deposits according to claim 1, characterized in that, Based on the variation curves of uranium concentration and uranium recovery rate under 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 as follows: range(0,dt,T) In the formula, dt is the time node for calculating leaching, and T is the total leaching time of uranium ore.

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