Heat collection efficiency evaluation method considering fracture distribution and hydraulic parameter heterogeneity

Abstract

The invention discloses a heat collection efficiency evaluation method considering fracture distribution and hydraulic parameter heterogeneity, and relates to the technical field of geothermal exploitation, and the method comprises the steps: S1, collecting matrix physical and mechanical parameters and fracture engineering parameters; s2, generating a discrete fracture network in heterogeneous spatial distribution through a random function based on the parameters; s3, meshing the discrete fracture network and establishing a coupling relationship among a heat transfer field, a seepage field and a stress field to generate a heat-water-force coupling model; s4, setting boundary conditions for the heat-water-force coupling model for solving to obtain a first calculation result; s5, the hydraulic parameters obeying the Weibull probability distribution are endowed to the fracture grids, then solution is carried out again, and a second calculation result is obtained; s6, the outlet temperature, the heat collection efficiency, the net electric power and the static recovery period are calculated; and S7, changing Weibull distribution shape parameters, repeating the steps S5 to S6, and outputting evaluation results of different heterogeneous coefficients. And the heat collection efficiency and the long-term performance of the fractured heat reservoir under different heterogeneous parameter conditions can be accurately calculated.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of geothermal exploitation, and particularly relates to a heat extraction efficiency evaluation method considering fracture distribution and hydraulic parameter heterogeneity. BACKGROUND

[0002] As a clean, stable and renewable energy, the efficient utilization of geothermal energy is of great significance to the transformation of global energy structure. Enhanced geothermal system (EGS) is a key technology for developing geothermal resources in deep dry hot rock mass. The basic principle is to construct an artificial fracture network in low permeability dry hot rock mass through reservoir stimulation methods such as hydraulic fracturing, and form the main channel of working fluid seepage and heat transfer. Therefore, the characteristics of fracture network fundamentally determine the heat extraction efficiency and long-term performance of EGS.

[0003] At present, most of the researches on seepage and heat transfer of fractured thermal reservoirs consider the fracture as a smooth plate model. Although this idealized assumption simplifies mathematical derivation, it deviates from the actual characteristics of natural irregular fractures. In the research considering fracture heterogeneity, most of them focus on a single influencing factor, such as the spatial heterogeneity of fracture network (length, density, inclination, etc.) or the hydraulic parameter heterogeneity of single fracture (such as roughness, tortuosity, opening, etc.). These research results establish the corresponding calculation methods and numerical models, which provide an important basis for understanding the heat extraction process of fractured geothermal reservoirs under the action of a single factor. However, the existing researches mostly focus on a single influencing factor, and the coupling effect of spatial heterogeneity and hydraulic parameter heterogeneity of fracture network, as well as their common influence on the long-term heat extraction performance of EGS, have not been fully understood.

[0004] Therefore, it is urgent to propose a heat extraction efficiency evaluation method that can comprehensively consider the fracture distribution and hydraulic parameter heterogeneity. SUMMARY

[0005] The present application provides a heat extraction efficiency evaluation method considering fracture distribution and hydraulic parameter heterogeneity, to solve the problem in the prior art that in the research on seepage and heat transfer of fractured thermal reservoirs, the spatial distribution heterogeneity and hydraulic parameter heterogeneity of fractures exist simultaneously and are coupled with each other, and jointly affect the seepage and heat transfer process of working fluid. However, the current research mainly considers the fracture as a homogeneous model or only considers the influence of single factor on the seepage and heat transfer process of fluid in EGS. This kind of model deviates from the actual characteristics of natural irregular fractures, and it is often difficult to effectively predict the heat extraction performance of fractured thermal reservoirs. At present, there is still a lack of a perfect calculation method for quantitatively predicting and evaluating the heat extraction efficiency and long-term performance of the above-mentioned problem considering the fracture distribution and hydraulic parameter heterogeneity.

[0006] In order to achieve the above purpose, the present application provides the following technical scheme:

[0007] A method for evaluating heat extraction efficiency considering fracture distribution and hydraulic parameter heterogeneity, comprising:

[0008] S1: collecting matrix physical and mechanical parameters and fracture engineering parameters;

[0009] S2: generating a discrete fracture network with heterogeneous spatial distribution based on the parameters through a random function;

[0010] S3: meshing the discrete fracture network and establishing a coupling relationship of heat transfer field, seepage field and stress field to generate a heat-water-force coupling model;

[0011] S4: setting boundary conditions for the heat-water-force coupling model to obtain a first calculation result;

[0012] S5: re-solve after assigning hydraulic parameters subject to Weibull probability distribution to the fracture grid to obtain a second calculation result;

[0013] S6: calculating outlet temperature, heat extraction efficiency, net power and static recovery period based on the second calculation result;

[0014] S7: repeating S5 to S6 by changing the shape parameter of Weibull distribution and outputting evaluation results of different heterogeneity coefficients.

[0015] Further, S1 comprises:

[0016] S11: collecting the elastic modulus, Poisson's ratio, density, specific heat capacity, permeability, thermal expansion coefficient, porosity and thermal conductivity of the matrix to form the matrix physical and mechanical parameters;

[0017] S12: collecting the permeability, opening, tangential stiffness and normal stiffness of the fracture to form the fracture engineering parameters;

[0018] The matrix physical and mechanical parameters and the fracture engineering parameters are used as input parameters for subsequent modeling.

[0019] Further, S2 comprises:

[0020] S21: establishing a two-dimensional reservoir geometry domain of a predetermined size, which represents the spatial range of the geothermal reservoir;

[0021] S22: generating a first fracture group with a first strike angle in the geometry domain through a first random function and generating a second fracture group with a second strike angle through a second random function;

[0022] S23: assigning length values to each fracture in the first fracture group and the second fracture group based on a normal distribution function, wherein the mean and variance of the fracture length are determined according to the geological conditions to form a discrete fracture network.

[0023] Further, S3 comprises:

[0024] S31: discretize the discrete fracture network by using a free triangle mesh to generate a calculation mesh containing matrix mesh units and fracture mesh units;

[0025] S32: establish a matrix seepage equation and a fracture seepage equation on the calculation mesh based on the poroelastic theory, establish a matrix heat transfer equation and a fracture heat transfer equation based on the local thermal equilibrium assumption, and establish a stress balance equation based on the effective stress principle;

[0026] S33: couple the seepage equation, the heat transfer equation and the stress balance equation to form a heat-water-force coupling model.

[0027] Further, the matrix seepage equation is: ;

[0028] wherein, is the fluid density, p is the fluid pressure, t is the time, is the matrix water storage coefficient, is the Biot coefficient of the matrix, is the bulk strain of the rock matrix, is the Darcy velocity in the matrix;

[0029] The fracture seepage equation is: ;

[0030] wherein, is the fracture opening, is the fracture water storage coefficient, is the Biot coefficient of the fracture, is the Darcy velocity in the fracture, and ∇T is the fracture tangential gradient operator.

[0031] Further, S5 comprises:

[0032] S51: construct a Weibull probability density function: wherein x is the hydraulic parameter to be assigned, n is the scale parameter, and m is the shape parameter;

[0033] S52: generate a random number sequence of permeability or opening based on the Weibull probability density function, and distribute the random number sequence to each fracture mesh unit;

[0034] S53: solve the assigned heat-water-force coupling model by using the finite element method to obtain a second calculation result containing temperature field distribution and pressure field distribution.

[0035] Further, S6 comprises:

[0036] S61: calculating the outlet temperature based on the temperature distribution of the production well position: wherein L is the length of the production well, and T(t) is the temperature at time t;

[0037] S62: calculating the heat extraction efficiency based on the reservoir temperature field: wherein is the initial temperature of the reservoir, is the injection temperature, and s is the area of the reservoir;

[0038] S63: calculating the net electric power based on the outlet temperature: wherein is the thermoelectric conversion efficiency, is the heat rejection temperature, is the specific heat capacity of the working medium, is the mass flow rate;

[0039] S64: calculating the static payback period based on the net electric power: wherein C is the initial investment, I is the annual income, and P is the annual cost.

[0040] Further, S4 comprises:

[0041] S41: setting the injection pressure and the injection temperature at the injection well boundary as the first type of boundary condition, and setting the production pressure at the production well boundary as the pressure boundary condition;

[0042] S42: setting the initial pressure field and the initial temperature field of the reservoir as the initial conditions, and setting the outer boundary of the model as the adiabatic impermeable boundary;

[0043] S43: solving the heat-water-force coupled model with the set boundary conditions and initial conditions by using the Newton-Raphson iteration method, and obtaining the first calculation result when the residual satisfies the convergence criterion.

[0044] Further, S7 comprises:

[0045] S71: setting a plurality of values of the shape parameter m of the Weibull distribution, respectively representing different degrees of heterogeneity;

[0046] S72: for the permeability heterogeneity, sequentially setting the shape parameter as each value and executing S5 to S6 to obtain the evaluation result based on the permeability heterogeneity;

[0047] S73: for the opening heterogeneity, sequentially setting the shape parameter as each value and executing S5 to S6 to obtain the evaluation result based on the opening heterogeneity;

[0048] S74: comparatively analyzing the evaluation results under different shape parameters, and outputting the sensitivity analysis result of the heterogeneous hydraulic parameters.

[0049] Compared with the prior art, the present application has the following advantages:

[0050] The present application provides a heat extraction efficiency evaluation method considering fracture distribution and hydraulic parameter heterogeneity, which can accurately calculate the heat extraction efficiency and long-term performance of the fractured heat reservoir under different heterogeneity parameters, and can be used as a theoretical tool for guiding the hydraulic fracturing design or reservoir reconstruction scheme optimization in geothermal exploitation.

[0051] Other features and advantages of the present application will be described in the following description, and some will become apparent from the description, or will be learned through implementation of the present application.

[0052] The technical solutions of the present application will be further described in detail below with the help of the accompanying drawings and embodiments. DETAILED DESCRIPTION

[0053] The accompanying drawings are used to provide a further understanding of the present application, and constitute a part of the specification, and are used to explain the present application together with the embodiments of the present application, and do not constitute a limitation on the present application. In the drawings:

[0054] Figure 1 A flow chart of the heat extraction efficiency evaluation method considering fracture distribution and hydraulic parameter heterogeneity in the embodiments of the present application is shown in the figure;

[0055] Figure 2 A numerical implementation framework of the heat-water-force coupling of the fractured rock mass in the embodiments of the present application is shown in the figure;

[0056] Figure 3 A numerical model geometry diagram in the embodiments of the present application is shown in the figure;

[0057] Figure 4 A water pressure distribution diagram in the heat extraction process in the embodiments of the present application is shown in the figure;

[0058] Figure 5 A temperature distribution diagram in the heat extraction process in the embodiments of the present application is shown in the figure;

[0059] Figure 6 An index evolution diagram of the heterogeneous fracture permeability in the heat extraction process in the embodiments of the present application is shown in the figure;

[0060] Figure 7 An index evolution diagram of the heterogeneous fracture aperture in the heat extraction process in the embodiments of the present application is shown in the figure. DETAILED DESCRIPTION

[0061] The preferred embodiments of the present application will be described below in combination with the accompanying drawings, and it should be understood that the preferred embodiments described herein are only used to illustrate and explain the present application, and are not used to limit the present application.

[0062] The embodiment of the present application provides a method for evaluating heat extraction efficiency considering the heterogeneity of fracture distribution and hydraulic parameters, which comprises the following steps: Figure 1 As shown in the figure, a method for evaluating heat extraction efficiency considering the heterogeneity of fracture distribution and hydraulic parameters comprises the following steps:

[0063] S1: Collecting matrix physical and mechanical parameters and fracture engineering parameters;

[0064] S2: Generating a discrete fracture network with heterogeneous spatial distribution based on the parameters through a random function;

[0065] S3: Griding the discrete fracture network and establishing the coupling relationship of heat transfer field, seepage field and stress field to generate a heat-water-force coupling model;

[0066] S4: Setting boundary conditions for the heat-water-force coupling model to obtain a first calculation result;

[0067] S5: Re-solve after assigning hydraulic parameters subject to Weibull probability distribution to the fracture grid to obtain a second calculation result;

[0068] S6: Calculating outlet temperature, heat extraction efficiency, net power and static recovery period based on the second calculation result;

[0069] S7: Repeating S5 to S6 by changing the shape parameter of Weibull distribution to output evaluation results of different heterogeneity coefficients.

[0070] The following will be specifically described in conjunction with the embodiments.

[0071] The embodiment provides a method for evaluating heat extraction efficiency considering the heterogeneity of fracture distribution and hydraulic parameters, which is used for evaluating the long-term heat extraction performance of an enhanced geothermal system (EGS). The method realizes accurate evaluation of heat extraction efficiency of a fracture-type geothermal reservoir by establishing a heat-water-force multi-field coupling model, considering the heterogeneity of spatial distribution of the fracture network and the heterogeneity of hydraulic parameters.

[0072] The method comprises the following steps:

[0073] S1: Collecting matrix physical and mechanical parameters and fracture engineering parameters;

[0074] S11: Collecting the physical and mechanical parameters of the matrix, including elastic modulus 30 GPa, Poisson's ratio 0.25, density 2700 kg / m³, specific heat capacity 1000 J / kg / K, permeability 1×10⁻¹ 8 m², thermal expansion coefficient 1.0, porosity 0.01%, thermal conductivity 3.0 W / m / K, and water storage coefficient 1.0×10⁻ 8 1 / Pa, to form a set of matrix physical and mechanical parameters.

[0075] S12: Collect the engineering parameters of the fracture, including permeability 8x10-11 m2, opening 0.5 mm, tangential stiffness 1200 GPa / m, normal stiffness 400 GPa / m, and storage coefficient 1.0x10-1 / Pa, to form a fracture engineering parameter set. 9 1 / Pa, to form a fracture engineering parameter set.

[0076] The working fluid parameters collected include: density 1000 kg / m³, specific heat capacity 4200 J / kg / K, thermal conductivity 1.0 W / m / K. These parameters are used as basic input data for subsequent modeling and numerical calculation.

[0077] S2: Generate a discrete fracture network with heterogeneous spatial distribution based on parameters through a random function;

[0078] S21: Use COMSOL software to establish a square two-dimensional reservoir geometry with a side length of 300 m on the canvas, which represents the spatial range of the geothermal reservoir.

[0079] S22: Generate a first fracture group with a strike angle of 30° in the geometry domain through a first random function, and generate a second fracture group with a strike angle of 110° through a second random function. The random function is based on the principles of geostatistics, ensuring that the spatial distribution of fractures has randomness and authenticity.

[0080] S23: Assign length values to each fracture in the first and second fracture groups based on a normal distribution function, where the fracture length follows a normal distribution with a mean of 30 m and a variance of 10 m. The discrete fracture network generated in this way can truly reflect the spatial heterogeneity characteristics of natural fractures, such as Figure 3 The numerical model geometry diagram shows the generated fracture network structure.

[0081] S3: Mesh the discrete fracture network and establish the coupling relationship between the heat field, seepage field and stress field to generate a thermal-water-force coupling model;

[0082] S31: Discretize the discrete fracture network containing matrix and fractures using free triangular mesh to generate calculation mesh containing matrix grid cells and fracture grid cells, as shown in Figure 3 . The mesh division needs to ensure sufficient grid density at the fractures to accurately capture the fluid flow and heat transfer characteristics.

[0083] S32: Based on the poroelastic theory, establish the matrix seepage equation and fracture seepage equation on the calculation mesh, based on the local thermal equilibrium assumption, establish the matrix heat transfer equation and fracture heat transfer equation, and based on the effective stress principle, establish the stress balance equation. Specifically as follows:

[0084] (1) The matrix seepage equation is:

[0085] ;

[0086] wherein, is the fluid density, is the fluid pressure, is time, is the bedrock storage coefficient, is the Biot coefficient of the bedrock, is the bulk strain of the rock matrix, is the Darcy velocity in the bedrock, defined as:

[0087] ;

[0088] wherein, is the initial permeability of the bedrock, is the dynamic water viscosity, is the gravitational acceleration vector.

[0089] (2) The fracture seepage equation is:

[0090] ;

[0091] wherein, is the fracture aperture, is the fracture storage coefficient, is the Biot coefficient of the fracture, is the Darcy velocity in the fracture, is the tangential gradient operator in the fracture. The Darcy velocity in the fracture is defined as:

[0092] ;

[0093] wherein, is the initial permeability of the fracture, is the longitudinal coordinate.

[0094] (3) The bedrock heat transfer equation is:

[0095] ;

[0096] At the same time:

[0097] ;

[0098] ;

[0099] wherein, is the temperature, is the rock density, is the bedrock porosity, , and , Specific heat capacity and thermal conductivity of bedrock and water, respectively.

[0100] (4) The crack heat transfer equation is:

[0101] ;

[0102] (5) The bedrock stress balance equation is:

[0103] ;

[0104] where: is the total stress tensor. According to Terzaghi's effective stress principle:

[0105] ;

[0106] where: is the second-order unit tensor, is the effective stress tensor.

[0107] Under non-isothermal conditions, the effective stress tensor of the bedrock can be expressed as:

[0108] ;

[0109] where: is the fourth-order tangent elastic tensor, is the drained bulk modulus, is the bulk thermal expansion coefficient of the bedrock, is the reference temperature, is the total strain tensor, which can be expressed as:

[0110] ;

[0111] where: is the displacement vector.

[0112] (6) The mechanical behavior of the crack is simulated by a thin elastic layer structure, and its constitutive relationship follows Hooke's law:

[0113] ;

[0114] where: is the force per unit area, is the deformation offset of the spring in the stress-free state, is the stiffness matrix, defined as:

[0115] ;

[0116] where: is the unit normal vector of the crack, and Normal stiffness and shear stiffness of the thin elastic layer, respectively.

[0117] Considering the high temperature range of geothermal reservoirs (150-350℃), fluid property parameters are set as functions of temperature:

[0118] ;

[0119] ;

[0120] ;

[0121] ;

[0122] S33: Coupling the above seepage equation, heat transfer equation and stress balance equation to form a heat-water-force coupling model. The coupling relationship is shown in Figure 2 , including three mutually coupled physical modules: (i) "Darcy's law" physical module for calculating the pressure distribution and seepage process of working fluid in heterogeneous fracture network and matrix pores; (ii) "solid mechanics" physical module for calculating the mechanical response of bedrock and fracture structure under the combined action of fluid pressure and thermal stress; (iii) "porous medium heat transfer" physical module for calculating the heat exchange process between fluid and bedrock. Figure 2 The arrows in the figure indicate the coupling relationship between the modules.

[0123] S4: Set the boundary conditions of the heat-water-force coupling model to solve and obtain the first calculation result;

[0124] S41: Set the injection pressure 58 MPa and the injection temperature 20℃ as the first type of boundary condition at the injection well boundary (left boundary of the model), and set the production pressure 41 MPa as the pressure boundary condition at the production well boundary (right boundary of the model).

[0125] S42: Set the initial pressure field of the reservoir to 43.5 MPa and the initial temperature field to 200℃ as the initial condition. The top and bottom boundaries of the model are set as adiabatic impermeable boundaries, and all external boundaries are constrained in the normal direction.

[0126] S43: The thermal-hydraulic coupled model with the set boundary conditions and initial conditions is solved by Newton-Raphson iteration method. The fully coupled solution strategy with unconditional stability is adopted in the numerical implementation, and the three physical modules are solved simultaneously in one iteration. The standard Galerkin method is adopted for spatial discretization, and the backward differentiation formula (BDF) is adopted for time discretization. The relative tolerance is set to 0.001, the absolute tolerance is set to 0.1, and the maximum iteration number is 25. The total calculation time is set to 40 years. When the residual satisfies the convergence criterion, the first calculation result containing the pressure field distribution and the temperature field distribution is obtained. After a 40-year production period, the reservoir water pressure distribution is as shown in Figure 4 , and the temperature distribution is as shown in Figure 5 .

[0127] S5: After assigning the hydraulic parameters subject to Weibull probability distribution to the fracture grid, the second calculation result is obtained by re-solution.

[0128] S51: The Weibull probability density function is constructed:

[0129] ;

[0130] wherein is the hydraulic parameter (permeability or opening) to be assigned, is the scale parameter, which controls the range of the parameter domain, is the shape parameter (i.e., the heterogeneity coefficient), which governs the divergence around . The smaller the shape parameter , the stronger the heterogeneity.

[0131] S52: Based on the Weibull probability density function, a random number sequence of permeability or opening is generated, and the random number sequence is distributed to each fracture grid cell. The assigned parameters are imported into the fracture network using the interpolation function in COMSOL, realizing the double-scale representation considering the fracture distribution and the heterogeneity of the hydraulic parameters.

[0132] S53: The thermal-hydraulic coupled model after assignment is solved by the finite element method. The solution method is the same as described in S43, and the fully coupled solution strategy and Newton-Raphson iteration method are adopted, obtaining the second calculation result containing the temperature field distribution and the pressure field distribution.

[0133] S6: Based on the second calculation result, the outlet temperature, the heat production efficiency, the net power, and the static recovery period

[0134] S61: The outlet temperature is calculated based on the temperature distribution at the production well location:

[0135] ; ​

[0136] wherein is the production well length, is the temperature of the production well at time . This indicator reflects the thermal quality of the fluid output by the geothermal system.

[0137] S62: Calculate the heat extraction efficiency based on the reservoir temperature field:

[0138] ;

[0139] wherein is the initial reservoir temperature 200℃, is the injection temperature 20℃, is the reservoir area. This indicator characterizes the degree of heat extraction from the reservoir.

[0140] S63: Calculate the net electric power based on the outlet temperature:

[0141] ;

[0142] wherein is the thermoelectric conversion efficiency, taking 0.3, is the heat rejection temperature, taking 288.75 K, is the specific heat capacity of the working medium, is the mass flow rate, taking 80 kg / s. This indicator characterizes the power generation capacity of the geothermal system.

[0143] S64: Calculate the static payback period based on the net electric power:

[0144] ;

[0145] wherein is the initial investment, taking 700 million yuan, is the annual income, is the annual cost. The annual cost mainly calculates the operation and maintenance cost of the geothermal well , which is calculated using the relationship between labor cost and drilling cost :

[0146]

[0147] wherein takes 6 million yuan, takes 28 million yuan. The annual income considers the power generation income:

[0148]

[0149] wherein is the power selling price, taking 1.0 yuan / kWh, The annual power generation is 0.5 TWh. In order to compare the static recovery period with the change of heat extraction process, the static recovery period is calculated every year within 40 years of heat extraction as an independent year. This index represents the economic feasibility of the project.

[0150] S7: Change the shape parameter of Weibull distribution, repeat S5-S6, and output evaluation results of different heterogeneity coefficients

[0151] S71: Set the shape parameter of Weibull distribution to , , , respectively, representing strong heterogeneity, medium heterogeneity and weak heterogeneity.

[0152] S72: For permeability heterogeneity, set the shape parameter to , , in turn, and execute S5-S6 to obtain three groups of evaluation results based on permeability heterogeneity. The evolution of the heat extraction process index of the heterogeneous fracture permeability is shown in Figure 6 , including outlet temperature Figure 6 a), heat extraction efficiency Figure 6 b), net power Figure 6 c) and static recovery period Figure 6 d).

[0153] S73: For opening heterogeneity, set the shape parameter to , , in turn, and execute S5-S6 to obtain three groups of evaluation results based on opening heterogeneity. The evolution of the heat extraction process index of the heterogeneous fracture opening is shown in Figure 6 , including outlet temperature Figure 6 a), heat extraction efficiency Figure 6 b), net power Figure 6 c) and static recovery period Figure 6 d).

[0154] S74: comparative analysis of evaluation results under different shape parameters, output of non-homogeneous hydraulic parameter sensitivity analysis results. The simulation results show that: within 20 years of heat extraction, the difference between each model is small, the outlet temperature is stable at about 200℃, the net electric power is about 7.0 MW, and the static recovery period is about 12.3 years. The heat extraction efficiency is in a steady upward stage, and the homogeneous model is always higher than the heterogeneous model. With the advancement of heat extraction time, the heat extraction performance characteristics of different models have significantly differentiated: the outlet temperature of the homogeneous model decreases significantly faster than the heterogeneous model, indicating that the heterogeneous permeability or opening characteristics of the fracture to some extent delay the seepage and heat transfer process of the fractured heat reservoir, and the stronger the heterogeneity, the more obvious the delay effect. In terms of net electric power, the model shows the best performance, its output power is always higher than that of the homogeneous model, while the homogeneous model is better than the model and the model. Among them, the static recovery period of the non-homogeneous permeability model is the shortest, the longest is only 13.06 years, showing the best economic benefit. This phenomenon reveals that in the long-term exploitation of fractured heat reservoir, moderate heterogeneity helps to maintain a relatively stable heat extraction efficiency and net electric power, while strong heterogeneity can increase the net electric power and shorten the static recovery period, but at the same time it will lead to lower system heat extraction efficiency.

[0155] The numerical model used in this embodiment calculates the relevant parameters as shown in Table 1, including rock matrix parameters, working fluid parameters, fracture parameters and initial value parameters. The innovation of this method lies in considering the double heterogeneity of fracture spatial distribution and hydraulic parameters at the same time, and combining thermodynamic performance and economic indicators to establish a complete EGS long-term heat extraction performance evaluation system. This evaluation method can provide theoretical guidance and decision support for the hydraulic fracturing design and reservoir optimization of fractured heat reservoir.

[0156]

[0157] Obviously, those skilled in the art can make various modifications and variations to the present application without departing from the spirit and scope of the present application.

Claims

1. A method for evaluating thermal recovery efficiency considering fracture distribution and heterogeneity of hydraulic parameters, characterized in that, include: S1: Collect matrix physical and mechanical parameters and fracture engineering parameters; S2: Based on parameters, a discrete fracture network with a non-homogeneous spatial distribution is generated using a random function; S3: Mesh the discrete fracture network and establish the coupling relationship between the heat transfer field, seepage field and stress field to generate a thermal-hydraulic-mechanical coupling model; S4: Set boundary conditions for the thermo-hydraulic-mechanical coupling model and solve it to obtain the first calculation result; S5: After assigning hydraulic parameters that follow the Weibull probability distribution to the fractured mesh, the solution is recalculated to obtain the second calculation result; S6: Calculate the outlet temperature, heat extraction efficiency, net power consumption, and static payback period based on the second calculation results; S7: Repeat S5 to S6 by changing the shape parameter of the Weibull distribution and output the evaluation results for different heterogeneity coefficients.

2. The method for evaluating thermal recovery efficiency considering fracture distribution and heterogeneity of hydraulic parameters according to claim 1, characterized in that, S1 includes: S11: Collect the matrix's elastic modulus, Poisson's ratio, density, specific heat capacity, permeability, coefficient of thermal expansion, porosity, and thermal conductivity to form the matrix's physical and mechanical parameters; S12: Collect the permeability, aperture, tangential stiffness, and normal stiffness of the fracture to form fracture engineering parameters; Among them, the physical and mechanical parameters of the matrix and the engineering parameters of the fracture are used as input parameters for subsequent modeling.

3. The method for evaluating thermal recovery efficiency considering fracture distribution and heterogeneity of hydraulic parameters according to claim 1, characterized in that, S2 include: S21: Establish a two-dimensional reservoir geometric domain of a preset size, which represents the spatial extent of the geothermal reservoir; S22: Generate a first set of fractures with a first orientation angle in the geometric domain using a first random function, and generate a second set of fractures with a second orientation angle using a second random function; S23: Based on the normal distribution function, assign length values ​​to each fracture in the first and second fracture groups, where the mean and variance of the fracture length are determined according to geological conditions, forming a discrete fracture network.

4. The method for evaluating thermal recovery efficiency considering fracture distribution and hydraulic parameter heterogeneity according to claim 1, characterized in that, S3 include: S31: Discretize the discrete fracture network using a free triangular mesh to generate a computational mesh containing matrix mesh elements and fracture mesh elements; S32: Based on the porosity elasticity theory, establish the bedrock seepage equation and the fracture seepage equation on the computational grid; based on the local thermal equilibrium assumption, establish the bedrock heat transfer equation and the fracture heat transfer equation; and based on the effective stress principle, establish the stress balance equation. S33: Couple the seepage equation, heat transfer equation and stress balance equation to form a thermal-hydraulic-mechanical coupled model.

5. The method for evaluating thermal recovery efficiency considering fracture distribution and heterogeneity of hydraulic parameters according to claim 4, characterized in that: The bedrock seepage equation is: ; in, Let p be the fluid density, t be the fluid pressure, and t be the time. The bedrock water storage coefficient, The Biot coefficient for bedrock. For the volumetric strain of the rock matrix, Darcy velocity in bedrock; The equation for fracture seepage is: ; in, For crack aperture, The fracture water storage coefficient is... denoted as the Biot coefficient of the crack. Let be the Darcy velocity in the fracture, and ∇T be the fracture tangential gradient operator.

6. The method for evaluating thermal recovery efficiency considering fracture distribution and hydraulic parameter heterogeneity according to claim 1, characterized in that, S5 include: S51: Constructing the Weibull probability density function: , where x is the hydraulic parameter to be assigned, n is the scale parameter, and m is the shape parameter; S52: Generate a random number sequence of permeability or aperture based on the Weibull probability density function, and distribute the random number sequence to each fracture grid cell; S53: The finite element method is used to solve the assigned thermo-water-mechanical coupling model to obtain a second calculation result that includes the temperature field distribution and the pressure field distribution.

7. The method for evaluating thermal recovery efficiency considering fracture distribution and heterogeneity of hydraulic parameters according to claim 1, characterized in that, S6 include: S61: Calculate the outlet temperature based on the temperature distribution at the production well location: Where L is the length of the production well and T(t) is the temperature at time t; S62: Calculating thermal recovery efficiency based on reservoir temperature field: ,in The initial temperature of the reservoir. Where s is the injection temperature and s is the reservoir area; S63: Calculate net power based on outlet temperature: ,in For thermoelectric conversion efficiency, This refers to the heat emission temperature. The specific heat capacity of the working fluid, For mass flow rate; S64: Calculate static payback period based on net power: Where C is the initial investment, I is the annual revenue, and P is the annual cost.

8. The method for evaluating thermal recovery efficiency considering fracture distribution and hydraulic parameter heterogeneity according to claim 1, characterized in that, S4 include: S41: Set the injection pressure and injection temperature as first-type boundary conditions at the injection well boundary, and set the production pressure as a pressure boundary condition at the production well boundary. S42: Set the initial pressure field and initial temperature field of the reservoir as initial conditions, and set the outer boundary of the model as an adiabatic and impermeable boundary. S43: The Newton-Raphson iteration method is used to solve the thermo-hydraulic-mechanical coupling model with set boundary conditions and initial conditions. The first calculation result is obtained when the residuals meet the convergence criterion.

9. The method for evaluating thermal recovery efficiency considering fracture distribution and heterogeneity of hydraulic parameters according to claim 1, characterized in that, S7 includes: S71: Set multiple values ​​for the shape parameter m of the Weibull distribution to represent different degrees of heterogeneity; S72: To address the permeability heterogeneity, set the shape parameters to various values ​​sequentially and execute S5 to S6 to obtain evaluation results based on permeability heterogeneity. S73: For the non-homogeneity of the opening, set the shape parameters to various values ​​in sequence and execute S5 to S6 to obtain the evaluation results based on the non-homogeneity of the opening. S74: Compare and analyze the evaluation results under different shape parameters, and output the sensitivity analysis results of heterogeneous hydraulic parameters.

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