Methods and systems for predicting the dissolution of crack filling

Abstract

This invention discloses a method and system for predicting fracture filling and dissolution. The prediction method is used to predict the filling and dissolution of fractures under complex fracture network conditions, and includes the following steps: obtaining geological characteristic data, including stratigraphic characteristic data and fracture characteristic data, based on geological data of the study area and test and analysis results of geological samples in the study area; constructing a fracture attribute model based on the geological characteristic data; constructing a quantitative calculation model for fracture filling and dissolution based on the fracture attribute model and the principle of water-rock interaction; setting the water-rock interaction environment and fracture attributes based on the quantitative calculation model for fracture filling and dissolution, simulating the coupled process of fracture filling and dissolution, and predicting the filling and dissolution of fractures; thus, the coupled process of fracture filling and dissolution can be fully simulated, and the filling and dissolution of fractures can be analyzed, predicted, and evaluated, improving the efficiency and success rate of resource exploration and development.

Description

Technical Field

[0001] This invention relates to the field of oil and gas exploration and development technology, specifically to a method and system for predicting fracture filling and dissolution. Background Technology

[0002] Under complex fracture network conditions, the fracture network is intricate and the groundwater flow path is complex and diverse. The filling and dissolution processes are affected by a variety of factors. As a result, when predicting and assessing the degree of fracture filling and dissolution under complex fracture network conditions, traditional experimental methods and geological observation means are often limited by experimental equipment, field observation and investigation conditions and scale. It is difficult to fully and accurately reveal the details of fracture filling and dissolution mechanisms, and cannot completely reconstruct the fracture filling and dissolution process. Therefore, it is difficult to obtain accurate fracture filling and dissolution prediction results. Summary of the Invention

[0003] The main objective of this invention is to propose a method and system for predicting crack filling and dissolution, in order to solve the aforementioned problems.

[0004] To achieve the above objectives, this invention proposes a method for predicting crack filling and dissolution, used to predict the filling and dissolution of cracks under complex crack network conditions. The method includes:

[0005] Based on the geological data of the study area and the test and analysis results of the geological samples in the study area, geological characteristic data are obtained, including stratigraphic characteristic data and fracture characteristic data.

[0006] Based on the geological feature data, a fracture attribute model is constructed;

[0007] Based on the fracture property model, a quantitative calculation model for fracture filling and dissolution is constructed by combining the principle of water-rock interaction.

[0008] Based on the quantitative calculation model of fracture filling and dissolution, the water-rock interaction environment and fracture properties are set to simulate the coupled process of fracture filling and dissolution, and to predict the fracture filling and dissolution situation.

[0009] Furthermore, the step of obtaining geological characteristic data based on geological data of the study area and the test and analysis results of geological samples from the study area, including stratigraphic characteristic data and fracture characteristic data, specifically includes:

[0010] Based on the geological survey data, drilling data, and seismic exploration data of the study area, first stratigraphic characteristic data is obtained. The first stratigraphic characteristic data includes at least stratigraphic length, stratigraphic width, and stratigraphic depth. The stratigraphic characteristic data includes the first stratigraphic characteristic data.

[0011] Geological samples from the study area were measured to obtain second stratigraphic characteristic data and fracture characteristic data. The fracture characteristic data included at least fracture density, fracture aperture, fracture dip angle, degree of fracture filling and dissolution, fracture filling stage, cave filling stage, and paleodepositional environment. The second stratigraphic characteristic data included at least density, volume, porosity, porosity, permeability, pressure, temperature, chemical composition, salt mass fraction, hygrothermal conductivity, and specific heat capacity. The stratigraphic characteristic data included the second stratigraphic characteristic data.

[0012] Further, the geological samples of the study area are measured to obtain second stratigraphic characteristic data and fracture characteristic data. The fracture characteristic data includes at least fracture density, fracture aperture, fracture dip angle, degree of fracture filling and dissolution, fracture filling stage, cavern filling stage, and paleodepositional environment. The second stratigraphic characteristic data includes at least density, volume, porosity, porosity, permeability, pressure, temperature, chemical composition, salt mass fraction, hygrothermal conductivity, and specific heat capacity. The stratigraphic characteristic data includes the second stratigraphic characteristic data step, specifically including:

[0013] The cracks in the geological sample are divided into macroscopic cracks and microscopic cracks. By observing the macroscopic cracks, the density, aperture, dip angle, and degree of filling and dissolution of the macroscopic cracks are obtained. By preparing thin sections of cast bodies and using scanning electron microscopy imaging technology, the density, aperture, dip angle, and degree of filling and dissolution of the microscopic cracks are obtained.

[0014] Geochemical testing and analysis techniques were used on the geological samples to obtain data on the characteristics of the second stratigraphy, the stages of fracture filling, the stages of cave filling, and the paleodepositional environment.

[0015] Furthermore, the step of constructing a fracture attribute model based on the geological feature data specifically includes:

[0016] A stratigraphic model is established based on the first stratigraphic feature data;

[0017] Based on the geological model, a fault / fracture model is constructed according to the fracture feature data;

[0018] The fault / fracture model is meshed to construct a finite element mesh model;

[0019] Based on the finite element mesh model, the fracture attribute model is constructed according to the second formation feature data.

[0020] Furthermore, the step of constructing a quantitative calculation model for fracture filling and dissolution based on the fracture property model and the principle of water-rock interaction specifically includes:

[0021] Based on the crack attribute model, a quantitative characterization model of single-phase fluid seepage characteristics is obtained according to the calculation formula of single-phase fluid seepage characteristics, and a quantitative characterization model of multiphase fluid seepage characteristics is obtained according to the calculation formula of multiphase fluid seepage characteristics.

[0022] The mass and energy balance model for fracture filling and dissolution is calculated based on the basic mass and energy balance equation formula.

[0023] A quantitative calculation model for the average volume and average surface area of ​​crack filling and dissolution is obtained based on the finite difference formula.

[0024] Combining the mass and energy balance model of fracture filling and corrosion and the quantitative calculation model of average volume and average surface area of ​​fracture filling and corrosion, a quantitative calculation model of fracture filling and corrosion under the condition of average volume and surface area is obtained according to the quantitative calculation formula.

[0025] Furthermore, the formula for calculating the seepage characteristics of the single-phase fluid is as follows:

[0026] U = -k(δp - ρg) / μ,

[0027] In the formula, U is the seepage velocity vector, k is the total permeability in mD, δ is the change in pressure of the single-phase fluid in Pa, p is the pressure in Pa, ρ is the liquid density in kg / m3, g is the gravity vector in N / kg, and μ is the viscosity.

[0028] The formula for calculating the seepage characteristics of the multiphase fluid is as follows:

[0029] u β =-kk rβ (δp β -ρ β g) / μ β ,

[0030] p β =p+p cβ ,

[0031] In the formula, β represents fluids in different phases, and u β Let k be the seepage velocity vector corresponding to the phase fluid, and k be the total permeability in mD. rβ The relative permeability of the corresponding phase fluid, in mD, δ β The pressure change of the corresponding phase fluid, in Pa, p β The pressure of the fluid in the corresponding phase is expressed in Pa, and p is the overall pressure of the fluid in the solution, also expressed in Pa. cβ The capillary pressure of the rock is expressed in Pa and ρ. β For the corresponding phase fluid density, the unit is kg / m3; μ β This corresponds to the viscosity of the fluid in the corresponding phase.

[0032] The basic mass and energy balance equation is as follows:

[0033]

[0034] In the formula, V n For any mesh block after the model is meshed, T n The area enclosed by the grid block, in meters. 2 M represents the mass or energy per unit volume, expressed in kg or J / m³. 3 k represents the mass component and additional caloric component, in %; F represents the mass or heat flux, in kg or J; q represents the fluid sink and source; and n represents the surface normal vector pointing to V (dT). n );

[0035] The finite difference formula is:

[0036]

[0037]

[0038] In the formula, V n For any mesh block after the model is meshed, T n The area enclosed by the grid block, in meters. 2 M is the volume normalization, which is a large and dimensionless quantity. n For M in V n The dimensionless average value of A, where k is the mass component and the additional calorie component, in %. nm The average area at the cross-section between grid blocks n and m, in meters. 2 F nm For volume element V n and A nm The average value of the normal component of the surface portion F (inward);

[0039] The quantitative calculation formula is as follows:

[0040]

[0041] D nm =D n +D m ,

[0042]

[0043] In the formula, F is the mass or heat flux, in kg or J, nm is the average value at the cross-section between grid blocks n and m, and β nm The value of k is the average value of the corresponding phase at the cross section between grid blocks n and m, where k is the total permeability in mD.rβρβ Permeability of the corresponding phase, in mD, μ β For the viscosity of the corresponding phase fluid, p β,n The fluid pressure at grid block n corresponding to the phase state is expressed in MPa, p. β,m The fluid pressure at grid block m corresponding to the phase state is expressed in MPa, ρ β,nm The components of fluid density corresponding to the phase state in grid blocks m to n, in kg / m³ 3 A nm The average area at the cross-section between grid blocks n and m, in meters. 2 g nm D refers to the component of gravitational acceleration from m to n. nm Let n be the distance between nodes n and m.

[0044] Furthermore, the water-rock interaction environment includes pressure, temperature, salt mass fraction, fluid inlet location, fluid injection rate, and enthalpy.

[0045] Furthermore, the crack attributes include at least crack aperture, crack dip angle, and crack group.

[0046] Furthermore, after the step of constructing a quantitative calculation model for fracture filling and dissolution based on the fracture attribute model and the principle of water-rock interaction, and before the step of setting the water-rock interaction environment and fracture attributes based on the quantitative calculation model for fracture filling and dissolution, simulating the coupled process of fracture filling and dissolution, and predicting the fracture filling and dissolution situation, the method further includes:

[0047] Obtain the accuracy of the quantitative calculation model for crack filling and dissolution. If the accuracy is less than 90%, optimize the quantitative calculation model for crack filling and dissolution.

[0048] This invention also provides a crack filling and dissolution prediction system for predicting crack filling and dissolution under complex crack network conditions, comprising:

[0049] The geological feature data acquisition module is used to acquire geological feature data based on geological data of the study area and testing and analysis of geological samples of the study area. The geological feature data includes stratigraphic feature data and fracture feature data.

[0050] A fracture attribute model construction module is used to construct a fracture attribute model based on the geological feature data.

[0051] A module for constructing a quantitative calculation model for fracture filling and dissolution is used to construct a quantitative calculation model for fracture filling and dissolution based on the fracture attribute model and the principle of water-rock interaction; and...

[0052] The simulation and prediction module is used to simulate the filling and dissolution coupling process of the fracture based on the quantitative calculation model of fracture filling and dissolution, set the water-rock interaction environment and fracture properties, and predict the filling and dissolution of the fracture.

[0053] In the technical solution of this invention, geological characteristic data, including stratigraphic characteristic data and fracture characteristic data, are obtained from geological data of the study area and test and analysis results of geological samples. Stratigraphic structural characteristics are obtained based on the stratigraphic characteristic data, and structural characteristics of complex fracture networks are obtained based on the fracture characteristic data. A fracture attribute model is then constructed based on this model, providing fundamental data for the construction of a quantitative calculation model for fracture filling and dissolution. Then, combining the principle of water-rock interaction, the influence of groundwater flow characteristics, hydrochemical properties, and rock dissolution and deposition on fracture filling and dissolution is added to optimize the fracture attribute model, thereby constructing... A quantitative calculation model for fracture filling and dissolution is developed. Based on this model, the water-rock interaction environment and fracture properties are set to fully simulate the coupled process of fracture filling and dissolution. According to the real-time data output by the quantitative calculation model, the filling and dissolution of fractures in the study area are analyzed, predicted, and evaluated. The development patterns of karst fractures and cavities, the sources of fracture and cavity filling materials, and the paleosedimentary environment are studied to improve the efficiency and success rate of resource exploration and development. Furthermore, by simulating the process of fracture filling and dissolution, the stability and engineering safety during drilling can be predicted and evaluated, thereby optimizing the engineering design scheme. Attached Figure Description

[0054] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the structures shown in these drawings without creative effort.

[0055] Figure 1 A flowchart of the crack filling and dissolution prediction method provided by the present invention;

[0056] Figure 2 for Figure 1 Flowchart of step S100;

[0057] Figure 3 for Figure 2 Flowchart of step S120;

[0058] Figure 4 for Figure 1 Flowchart of step S200;

[0059] Figure 5 for Figure 1 Flowchart of step S300;

[0060] Figure 6 A macroscopic fracture characterization diagram of a carbonate reservoir in a certain area of ​​the Tarim Basin;

[0061] Figure 7 A diagram showing the microscopic fracture development of a carbonate reservoir in a certain area of ​​the Tarim Basin;

[0062] Figure 8 A diagram showing the geochemical test results of cave fillings, fracture fillings, and surrounding rocks in a carbonate reservoir in a certain area of ​​the Tarim Basin.

[0063] Figure 9 Schematic diagrams of formation model, fracture model, finite element mesh model, and fracture attribute model;

[0064] Figure 10 This is a schematic diagram of crack simulation at different dip angles based on a quantitative calculation model for crack filling and dissolution.

[0065] Figure 11 This is a schematic diagram of different fracture systems simulated based on a quantitative calculation model for fracture filling and dissolution.

[0066] Figure 12 This is a schematic diagram of an embodiment of the crack filling and dissolution prediction system provided by the present invention.

[0067] Explanation of icon numbers:

[0068]

[0069] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0070] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0071] It should be noted that if the embodiments of the present invention involve directional indicators (such as up, down, left, right, front, back, etc.), the directional indicators are only used to explain the relative positional relationship and movement of the components in a certain specific posture (as shown in the figure). If the specific posture changes, the directional indicators will also change accordingly.

[0072] Furthermore, if the embodiments of this invention involve descriptions such as "first" or "second," these descriptions are for descriptive purposes only and should not be construed as indicating or implying their relative importance or implicitly specifying the number of technical features indicated. Therefore, a feature defined with "first" or "second" may explicitly or implicitly include at least one of those features. Additionally, the meaning of "and / or" throughout the text includes three parallel solutions; for example, "A and / or B" includes solution A, solution B, or a solution where both A and B are satisfied simultaneously. Furthermore, the technical solutions of the various embodiments can be combined with each other, but this must be based on the ability of those skilled in the art to implement them. When the combination of technical solutions is contradictory or impossible to implement, it should be considered that such a combination of technical solutions does not exist and is not within the scope of protection claimed by this invention.

[0073] Under complex fracture network conditions, the fracture network is intricate and the groundwater flow path is complex and diverse. The filling and dissolution processes are affected by a variety of factors. As a result, when predicting and assessing the degree of fracture filling and dissolution under complex fracture network conditions, traditional experimental methods and geological observation means are often limited by experimental equipment, field observation and investigation conditions and scale. It is difficult to fully and accurately reveal the details of fracture filling and dissolution mechanisms, and cannot completely reconstruct the fracture filling and dissolution process. Therefore, it is difficult to obtain accurate fracture filling and dissolution prediction results.

[0074] In view of this, the present invention provides a method for predicting crack filling and dissolution, used to predict the filling and dissolution of cracks under complex crack network conditions. Figures 1 to 5 The flowchart illustrates the crack filling and dissolution prediction method provided by this invention.

[0075] Specifically, the fracture filling and dissolution prediction method will be described in detail using a carbonate reservoir in a certain area of ​​the Tarim Basin as the study area.

[0076] Please see Figure 1 The method for predicting crack filling and dissolution includes the following steps:

[0077] Step S100: Based on the geological data of the study area and the test and analysis results of the geological samples of the study area, geological feature data is obtained, including stratigraphic feature data and fracture feature data.

[0078] In this step, geological feature data related to the crack filling and dissolution mechanism are screened from a large amount of collected data. This allows for the analysis of information such as groundwater flow path, crack development characteristics during different tectonic movements, crack filling and dissolution characteristics, and the source and formation environment of crack filling materials in the study area. This is beneficial for subsequent qualitative and quantitative prediction of crack filling and dissolution.

[0079] For details, please refer to Figure 2 Step S100 specifically includes:

[0080] Step S110: Based on the geological survey data, drilling data, and seismic exploration data of the study area, obtain the first stratigraphic feature data. The first stratigraphic feature data includes at least the stratigraphic length, stratigraphic width, and stratigraphic depth. The stratigraphic feature data includes the first stratigraphic feature data.

[0081] Step S120: Measure the geological samples of the study area to obtain second stratigraphic characteristic data and fracture characteristic data. The fracture characteristic data includes at least fracture density, fracture aperture, fracture dip angle, degree of fracture filling and dissolution, fracture filling stage, cave filling stage, and paleodepositional environment. The second stratigraphic characteristic data includes at least density, volume, porosity, porosity, permeability, pressure, temperature, chemical composition, salt mass fraction, hygrothermal conductivity, and specific heat capacity. The stratigraphic characteristic data includes the second stratigraphic characteristic data.

[0082] Further, please refer to Figure 3 Step S120 specifically includes:

[0083] Step S121: Divide the cracks in the geological sample into macroscopic cracks and microscopic cracks. By observing the macroscopic cracks, obtain the density, aperture, dip angle, and degree of filling and dissolution of the macroscopic cracks. By preparing thin sections of the casting and using scanning electron microscopy imaging technology, obtain the density, aperture, dip angle, and degree of filling and dissolution of the microscopic cracks.

[0084] In this step, the relationship between crack parameters (including crack density, aperture, dip angle, etc.) and crack filling and dissolution characteristics can be obtained by analyzing crack characteristic data.

[0085] It should be noted that the macroscopic cracks referred to are cracks that can be directly observed with the naked eye. In specific embodiments, for example, cracks formed on outcrops in the study area (a carbonate reservoir in a certain area of ​​the Tarim Basin), such as... Figure 6 As shown in the figure, the filling and dissolution areas of the cracks are marked with different colors. This allows us to understand the characteristics of multi-stage tectonic activity of the cracks and the complex combination of crack systems (such as two parallel cracks, three intersecting cracks, four intersecting cracks, and five cracks that are partially parallel and partially intersecting).

[0086] Correspondingly, the microscopic cracks refer to cracks that need to be observed using electronic instruments. In a specific embodiment, core samples are measured by preparing cast thin sections and using scanning electron microscopy imaging technology, such as... Figure 7As shown, the relationship between the development characteristics of fractures (including fracture density, aperture, dip angle, degree of filling and dissolution, etc.) in different tectonic periods (including Late Caledonian, Early Hercynian, Indosinian-Yanshanian, Himalayan, etc.) can be obtained.

[0087] Step S122: Geochemical testing and analysis techniques are used on the geological samples to obtain second stratigraphic characteristic data, fracture filling phases, cave filling phases, and paleodepositional environment.

[0088] Specifically, in a specific embodiment, geochemical tests and analyses (carbon and oxygen isotopes and strontium isotopes) were conducted on the cave filling material, fracture filling material, and surrounding rock. The test and analysis results are as follows: Figure 8 As shown, this allows us to determine the stages of fracture filling, cave filling, and paleodepositional environments, which is beneficial for subsequent water-rock numerical simulations based on the principle of water-rock interaction and for setting up water-rock interaction environments.

[0089] Step S200: Construct a fracture attribute model based on the geological feature data.

[0090] Further, please refer to Figure 4 Step S200 specifically includes:

[0091] Step S210: Establish a stratigraphic model based on the first stratigraphic feature data.

[0092] In this step, a cuboid stratigraphic model is established based on the first stratigraphic feature data (e.g., ...). Figure 9 (As shown in A).

[0093] Step S220: Based on the stratigraphic model, construct a fault / fracture model according to the fracture feature data.

[0094] In this step, the fracture characteristic data (including fracture density, fracture aperture, fracture dip angle, etc.) are input into the stratigraphic model established in step S210 to construct the fault / fracture model, such as... Figure 9 As shown in B and DN, multiple crack models with different apertures and / or different dip angles and / or different crack systems can be constructed. For example, crack models with apertures of 50m, 100m, and 150m, crack models with dip angles of 30°, 60°, and 90°, and crack systems of single cracks, two cracks (parallel to each other), three cracks (intersecting), four cracks (intersecting), and five cracks (parallel and intersecting) can be constructed.

[0095] Step S230: Mesh the fault / crack model to construct a finite element mesh model.

[0096] In this step, the fault / fracture model is divided into meshes (e.g., Figure 9 As shown in C), the finite element mesh model will be further optimized by dividing it into regions.

[0097] Step S240: Based on the finite element mesh model, construct the fracture attribute model according to the second formation feature data.

[0098] In this step, the second stratigraphic feature data is assigned to each grid of the finite element mesh model to optimize the fracture attribute model, which can simulate complex fracture network structures.

[0099] More specifically, in a specific embodiment, the second stratigraphic feature data are shown in Table 1 below:

[0100] Table 1

[0101]

[0102] The porosity is calculated as follows:

[0103] P=(V0-V)×100%=(ρ-ρ0)×100%; (1)

[0104] In equation (1), P is the porosity of the geological sample;

[0105] V0 is the volume of the geological sample under natural conditions, in cm³. 3 or m 3 ;

[0106] V is the absolute compacted volume of the geological sample, in cm³. 3 or m 3 ;

[0107] ρ is the density of the geological sample, in g / cm³. 3 or kg / m 3 ;

[0108] ρ0 is the bulk density of the geological sample, in g / cm3 or kg / m3.

[0109] The penetration rate is calculated as follows:

[0110] K=(Q / A) / (ΔP / L); (2)

[0111] In equation (2), K is the permeability of the geological sample, in units of D;

[0112] Q represents the flow rate of the liquid through the geological sample, in cm³. 3 / s;

[0113] A represents the cross-sectional area of ​​the geological sample, in cm². 2 ;

[0114] ΔP is the pressure difference of the fluid passing through the geological sample, in Pa;

[0115] L represents the length of the fluid in the geological sample, measured in cm.

[0116] The hygrothermal conductivity and specific heat are derived empirically.

[0117] Step S300: Based on the fracture attribute model, construct a quantitative calculation model for fracture filling and dissolution by combining the principle of water-rock interaction.

[0118] In this step, factors such as groundwater flow, dissolution chemical reactions, and rock mechanical properties are considered to construct a quantitative calculation model for fracture filling and dissolution to simulate complex water-rock interaction processes.

[0119] More specifically, a quantitative calculation model for fracture filling and dissolution was constructed using numerical simulation software for water-rock interactions (the Tough-2 and Tough-react modules in PetraSim). The Tough-2 module is a numerical simulation module for multiphase fluids and heat transfer in porous / fractured media, while the Tough-react module is a numerical simulation module for non-isothermal flow chemical reactions in multiphase fluids, including reactions between mineral aggregates and liquids under local equilibrium or dynamic rate conditions. The composition and environment of the paleofluid are important factors in the numerical simulation; the anhydrous CaCl2-(NH4)2CO3-NH4Cl system and the CO2-H2O-CaCO3-NaCl thermodynamic system were mainly used to simulate precipitation and dissolution, respectively. The main chemical reactions involved in the water-rock numerical simulation are:

[0120] Small amount of CO2: CaCl2 + (NH4)2CO3 = CaCO3 (precipitate) + NH4Cl;

[0121] CO2 + Ca(OH)2 = CaCO3 (precipitate) + H2O;

[0122] Excess CO2: CO2 + H2O + CaCO3 + 2NaCl = 2NaHCO3 + CaCl2 (dissolves).

[0123] During the simulation, CaCO3 rapidly precipitates and then dissolves in the established fracture property model at a CO2 injection rate of 30 kg / s. Dissolution and infilling of carbonate rocks typically occur simultaneously. The numerical model primarily uses equations for the EOS2 state (fluid properties: water and CO2).

[0124] Further, please refer to Figure 5 Step S300 specifically includes:

[0125] Step S310: Based on the crack attribute model, obtain a quantitative characterization model of single-phase fluid seepage characteristics according to the calculation formula of single-phase fluid seepage characteristics, and obtain a quantitative characterization model of multiphase fluid seepage characteristics according to the calculation formula of multiphase fluid seepage characteristics.

[0126] In this step, based on Darcy's law and the fracture property model, and combined with the water-rock numerical simulation module, the seepage characteristics under single-phase fluid conditions are solved using the single-phase fluid seepage characteristic calculation formula, and the seepage characteristics under multiphase fluid conditions are solved using the phase fluid seepage characteristic calculation formula.

[0127] The formula for calculating the seepage characteristics of the single-phase fluid is as follows:

[0128] U=-k(δp-ρg) / μ; (3)

[0129] In equation (3), U is the seepage velocity vector;

[0130] k represents total permeability, in mD;

[0131] δ represents the change in pressure of a single-phase fluid, in Pa.

[0132] p represents pressure, in Pa;

[0133] ρ is the liquid density, in kg / m³.

[0134] g is the gravitational vector, with units of N / kg;

[0135] μ represents viscosity.

[0136] It should be noted that the quantitative characterization model of single-phase fluid seepage characteristics is mainly for the presence of water or CO2 in a single phase, that is, when CO2 is in liquid state, and is a quantitative characterization model of the relationship between seepage rate and total permeability, liquid viscosity, pressure and liquid density.

[0137] The formula for calculating the seepage characteristics of the multiphase fluid is as follows:

[0138] u β =-kk rβ (δ β p β -ρ β g) / μ β (4)

[0139] p β =p+p cβ (5)

[0140] In equations (4) and (5), β represents fluids in different phases;

[0141] u βThis represents the seepage velocity vector of the fluid in the corresponding phase.

[0142] k represents total permeability, in mD;

[0143] k rβ The relative permeability of the corresponding phase fluid, in mD;

[0144] δ β The pressure change of the corresponding phase fluid is expressed in Pa.

[0145] p β The pressure of the corresponding phase fluid is expressed in Pa.

[0146] p is the overall pressure of the fluid in the solution, in Pa;

[0147] p cβ The capillary pressure of the rock is expressed in Pa.

[0148] ρ β The density of the corresponding phase fluid is expressed in kg / m³.

[0149] μ β This represents the viscosity of the fluid in the corresponding phase.

[0150] It should be noted that the quantitative characterization model of multiphase fluid seepage characteristics is mainly for the coexistence of multiple phases such as water and CO2, that is, when CO2 is in the gaseous state, and is a quantitative characterization model of the relationship between the deep flow rate and the relative permeability, fluid pressure and rock capillary pressure of different phases of water and CO2.

[0151] It should also be noted that the rock capillary pressure can be measured by methods such as the semi-permeable diaphragm method, mercury intrusion porosimetry, and centrifugation.

[0152] Step S320: Calculate the mass and capacity balance model of crack filling and dissolution based on the basic mass and capacity balance equation formula.

[0153] The basic mass and capacity balance equation is as follows:

[0154]

[0155] In equation (6), V n For any grid block after the model is meshed;

[0156] T n The area enclosed by the grid block, in meters. 2 ;

[0157] M represents the mass or energy per unit volume, measured in kg or J / m³. 3 ;

[0158] k represents the mass component and the additional calorie component, expressed as a percentage.

[0159] F represents mass or heat flux, in kg or J.

[0160] q represents the fluid's source and sink;

[0161] n is the surface normal vector pointing to V (dT) n ).

[0162] It should be noted that the mass and energy balance model of fracture filling and dissolution represents the mass and energy balance model of fracture filling and dissolution under the action of fluids in different directions and at different flow rates when water and CO2 are in multiphase states.

[0163] Step S330: Calculate the quantitative calculation model of the average volume and average surface area of ​​the crack filling and dissolution based on the finite difference formula.

[0164] In this step, the model is spatially discretized using the finite difference method of integrals, and the average volume and average surface area of ​​the crack filling and dissolution are obtained by the finite difference formula.

[0165] The finite difference formula is as follows:

[0166]

[0167]

[0168] In equations (7) and (8), V n For any grid block after the model is meshed;

[0169] T n The area enclosed by the grid block, in meters. 2 ;

[0170] M is a volume normalization, which is huge and dimensionless;

[0171] M n For M in V n The dimensionless average value of the above;

[0172] k represents the mass component and the additional calorie component, expressed as a percentage.

[0173] A nm The average area at the cross-section between grid blocks n and m, in meters. 2 ;

[0174] F nm For volume element V n and A nm The average value of the normal component of the surface portion F (inward).

[0175] Step S340: Combining the mass and energy balance model of the crack filling and dissolution and the quantitative calculation model of the average volume and average surface area of ​​the crack filling and dissolution, the quantitative calculation model of crack filling and dissolution under the average volume and surface area conditions is calculated according to the quantitative calculation formula.

[0176] The quantitative calculation formula is as follows:

[0177]

[0178] D nm =D n +D m (10)

[0179]

[0180] In equations (9), (10), and (11), F represents mass or heat flux, in kg or J.

[0181] nm is the average value at the cross section between grid blocks n and m;

[0182] β nm This represents the average value of the corresponding phase state at the cross section between grid blocks n and m;

[0183] k represents total permeability, in mD;

[0184] k rβρβ Permeability of the corresponding phase, in mD;

[0185] μ β This corresponds to the viscosity of the fluid in the corresponding phase.

[0186] p β,n The fluid pressure at grid block n corresponding to the phase state is expressed in MPa.

[0187] p β,m The fluid pressure at grid block m corresponding to the phase state is expressed in MPa.

[0188] ρ β,nm The components of fluid density corresponding to the phase state in grid blocks m to n, in kg / m³ 3 ;

[0189] A nm The average area at the cross-section between grid blocks n and m, in meters. 2 ;

[0190] g nm This refers to the component of gravitational acceleration from m to n;

[0191] D nm Let n be the distance between nodes n and m.

[0192] In this step, the average value of the element parameters is used to represent the discrete flux, V. n and V m Suitable for the basic Darcy flux term, the average volume and surface area obtained through the quantitative calculation model of the average volume and average surface area of ​​fracture filling and dissolution are substituted into the mass and energy balance model of fracture filling and dissolution, respectively. This yields a set of first-order ordinary differential equations. Time is discretized into first-order finite difference equations, and the flux, sink, and source options on the right side are evaluated at the new time to obtain the numerical stability required for effective calculation of multiphase flow. The quantitative calculation model of fracture filling and dissolution under the average volume and surface area conditions represents the quantitative calculation model of fracture filling and dissolution under the average volume and surface area conditions when water and CO2 multiphase states exist and all elements reach equilibrium, and when CO2 is injected from different directions and at different flow rates.

[0193] Step S500: Based on the quantitative calculation model of fracture filling and dissolution, set the water-rock interaction environment and fracture properties, simulate the coupled process of fracture filling and dissolution, and predict the fracture filling and dissolution situation.

[0194] In this step, based on the quantitative calculation model of fracture filling and dissolution, complex fracture network conditions can be set according to actual needs, that is, the fracture attributes of the water-rock interaction environment can be set, and the coupled process of fracture filling and dissolution under the complex fracture network conditions can be simulated. Based on the numerical simulation results of the model and experimental data, the fracture filling and dissolution in oil and gas reservoirs can be analyzed, predicted and evaluated, and the development patterns of different types of karst fractures and cavities, the sources of fracture and cavity filling materials and paleosedimentary environments can be studied, thereby improving the efficiency and success rate of resource exploration and development.

[0195] Specifically, the water-rock interaction environment includes pressure, temperature, salt mass fraction, fluid inlet location, fluid injection rate, and enthalpy.

[0196] Specifically, the crack attributes include at least crack aperture, crack dip angle, and crack group.

[0197] In a specific embodiment, firstly, please refer to... Figure 10 Based on a formation model of 10000×2000×500m, a fracture model of 2000×500m, and a fracture aperture of 50m, different fracture dip angles were input to form dip angles of 30°, 60°, and 90°. Figure 10 Multiple fractures (A1-A2) were simulated, and the water-rock interaction environment was specifically set as follows: CO2 injection rate of 30 kg / s, enthalpy of 1000 J / kg, initial temperature of 75℃, pressure of 2.0e7 Pa, and grid block output frequency of 10. Then, the filling and dissolution coupling process of fractures with different dip angles was simulated, such as... Figure 10As shown in Figures A3-B4, the analysis reveals that under the condition of a fracture network structure with cracks of different inclination angles, the dissolution and filling of cracks includes four main characteristics:

[0198] 1) The content of carbonate precipitates (calcite precipitates) in the fractured area and its adjacent areas is higher than that of carbonate precipitates in the formation. The amount of precipitates gradually increases with increasing CO2 injection (e.g., Figure 10 (As shown in B1-B4).

[0199] 2) During the simulation time from 3.3e-5 to 3.8e-5 s, the calcite precipitate content in the fracture region gradually increased, and the larger the dip angle of the fracture, the higher the calcite precipitate content.

[0200] 3) The calcium ion content in the fractures is relatively low compared to the formation. The calcium ion content corresponding to fractures with dip angles of 90°, 60° and 30° are between 0.9742-0.9753, 0.9739-0.97535 and 0.9741-0.9757 g, respectively. The fractures with the lowest calcium ion content and larger dip angles show stronger dissolution. When the calcium ion content decreases rapidly, calcite is more likely to precipitate.

[0201] 4) The greater the inclination angle of the crack, the higher the CO2 value of the solution.

[0202] It should be noted that the grid block output frequency means that data is output at intervals of a certain number of grid blocks. In a specific embodiment, a set of data is output every 10 grid blocks, that is, the 10th grid block, the 20th grid block, the 30th grid block, the 10nth grid block, and so on, output n sets of data in sequence.

[0203] Furthermore, based on a formation model of 10000×2000×500m and a fracture model of 2000×500m, different fracture series (such as...) are input. Figure 11 As shown), multiple models were created, including single-crack, two-crack (parallel), three-crack (intersecting, different apertures), four-crack (intersecting), and five-crack (parallel, intersecting). The water-rock interaction environment was specifically set as follows: CO2 injection rate of 30 kg / s, enthalpy of 1000 J / kg, initial temperature of 75℃, pressure of 2.0e7 Pa, and grid block output frequency of 10. Then, the filling and dissolution coupling process of cracks with different dip angles was simulated, such as... Figure 11 As shown, the analysis reveals that under fracture network structures with different fracture assemblages, the dissolution and filling of fractures exhibits six main characteristics:

[0204] 1) Due to the influence of the cracks, calcite first precipitates in the core of the crack and then moves to the end of the crack.

[0205] 2) Under the condition of parallel cracks, cracks with relatively large apertures are more likely to produce a large amount of calcite precipitation, and cracks with relatively large apertures have a relatively low filling rate.

[0206] 3) When the fractures intersect, the fractures with a smaller angle (30°) to the direction of water flow have a higher content of calcite precipitates. The calcite precipitates are mainly concentrated inside the fractures, and their direction is consistent with the direction of water flow. The calcite precipitate content in the core of the fracture and its adjacent area is between 3.20e-5 and 6.73e-5g. The precipitation is mainly concentrated at the intersection of the fractures. The filling material and sediments mainly extend along the direction of the fracture with the larger opening in the intersecting fractures.

[0207] 4) As the number of fractures increases, the filling and precipitation of calcite become increasingly complex. In a single fracture, precipitation and dissolution mainly develop in the core of the fracture; in two parallel fractures, precipitation and dissolution mainly occur in fractures with larger openings; when there are a large number of fractures with different dip angles and openings, dissolution and precipitation exhibit complex and diverse distribution characteristics, with some concentrated at the fracture confluence, some concentrated in the core of fractures with larger openings, and others appearing in the core of fractures with smaller angles to the water flow.

[0208] 5) With the injection of CO2 and water, the precipitation rate and amount of calcite in the core and adjacent areas of the fracture gradually increase, the concentration of calcium ions and CO2 in the fracture decreases, and the concentration of calcite gradually increases.

[0209] 6) The calcite content is highest in the core of fractures with larger openings and scales, and the rate of calcium ion reduction and calcite precipitation is highest at the fracture intersections.

[0210] Simulations of the coupled filling and dissolution processes of fractures with different fracture properties reveal that the combination patterns of different fractures are crucial factors controlling precipitation and dissolution. At fracture intersections, water and CO2 fluids converge more readily. Based on the principles of dissolution and precipitation, intense dissolution occurs in fracture intersection areas, with the direction of dissolution aligning with the orientation of fractures with relatively large apertures, followed by calcite precipitation. Large-aperture fractures exhibit stronger dissolution and precipitation effects than small-aperture fractures. Similarly, fracture intersection areas are the primary sites of dissolution and precipitation in carbonate reservoirs and outcrops.

[0211] When hydrothermal fluids upwell from the bottom, calcite precipitation shifts from relatively shallow to deeper areas (the shallow areas being the highest points the upwelling fluids can reach). The amount of calcite precipitation in fractures is far greater than that in the formation. Temperature has a crucial influence on fracture filling; as temperature increases, the rate of calcite precipitation increases. The amount of calcite precipitation at fracture intersections is higher than in the surrounding formations. Furthermore, vertical faults also significantly influence the upwelling of hydrothermal fluids and calcite precipitation. Deeper fractures with larger openings contain more abundant calcite precipitation. During the formation of fault-controlled karst caves, relatively wider fractures or fracture zones are more prone to dissolution, and during the hydrothermal filling stage, they are more likely to accumulate calcite and other infill materials.

[0212] In the technical solution of this invention, geological characteristic data, including stratigraphic characteristic data and fracture characteristic data, are obtained from geological data of the study area and test and analysis results of geological samples. Stratigraphic structural characteristics are obtained based on the stratigraphic characteristic data, and structural characteristics of complex fracture networks are obtained based on the fracture characteristic data. A fracture attribute model is then constructed based on this model, providing fundamental data for the construction of a quantitative calculation model for fracture filling and dissolution. Then, combining the principle of water-rock interaction, the influence of groundwater flow characteristics, hydrochemical properties, and rock dissolution and deposition on fracture filling and dissolution is added to optimize the fracture attribute model, thereby constructing... A quantitative calculation model for fracture filling and dissolution is established. Based on this model, the water-rock interaction environment and fracture properties are set to simulate the coupled process of fracture filling and dissolution. According to the real-time data output by the quantitative calculation model, the filling and dissolution of fractures in the study area are analyzed, predicted, and evaluated. The development pattern of karst fractures and cavities, the source of fracture and cavity filling materials, and the paleosedimentary environment are studied to improve the efficiency and success rate of resource exploration and development. Furthermore, by simulating the process of fracture filling and dissolution, the stability and engineering safety during drilling can be predicted and evaluated, thereby optimizing the engineering design scheme.

[0213] Specifically, after step S300 and before step S500, the following steps are also included:

[0214] Step S400: Obtain the accuracy of the quantitative calculation model for crack filling and dissolution. If the accuracy is less than 90%, optimize the quantitative calculation model for crack filling and dissolution.

[0215] Specifically, step S400 includes:

[0216] Step S410: Divide the study area into a first region and a second region. Set the geological feature data of the first region as construction data and the geological feature data of the second region as test data. The construction data is used to construct the quantitative calculation model of fracture filling and dissolution.

[0217] Step S420: Based on the quantitative calculation model of crack filling and dissolution, input the water-rock interaction environment and crack properties of the second region, simulate the crack filling and dissolution coupling process in the second region, predict the crack filling and dissolution situation, and obtain the crack prediction results of the second region.

[0218] Step S430: Compare the crack prediction results of the second region with the test data of the second region to obtain the accuracy of the crack filling and dissolution quantitative calculation model;

[0219] Step S440: If the accuracy is less than 90%, optimize the quantitative calculation model for crack filling and dissolution based on the test data of the second region.

[0220] This improves the predictive accuracy and reliability of the quantitative calculation model for fracture filling and dissolution, further enhancing the efficiency and success rate of resource exploration and development.

[0221] This invention also provides a crack filling and dissolution prediction system 100, used to predict the filling and dissolution of cracks under complex crack network conditions. Please refer to [link to relevant documentation]. Figure 12 The fracture filling and dissolution prediction system 100 includes a geological feature data acquisition module 1, a fracture attribute model construction module 2, a fracture filling and dissolution quantitative calculation model construction module 3, and a simulation prediction module 4. The geological feature data acquisition module 1 is used to acquire geological feature data based on geological data of the study area and the test analysis of geological samples of the study area. The geological feature data includes stratigraphic feature data and fracture feature data. The fracture attribute model construction module 2 is used to construct a fracture attribute model based on the geological feature data. The fracture filling and dissolution quantitative calculation model construction module 3 is used to construct a fracture filling and dissolution quantitative calculation model based on the fracture attribute model and the principle of water-rock interaction. The simulation prediction module 4 is used to simulate the fracture filling and dissolution coupling process by setting the water-rock interaction environment and fracture attributes based on the fracture filling and dissolution quantitative calculation model, and predict the fracture filling and dissolution situation.

[0222] The above description is merely a preferred embodiment of the present invention and does not limit the patent scope of the present invention. Any equivalent structural transformations made using the contents of the present invention's specification and drawings under the inventive concept of the present invention, or direct / indirect applications in other related technical fields, are included within the patent protection scope of the present invention.

Claims

1. A method for predicting crack filling and dissolution, used to predict the filling and dissolution of cracks under complex crack network conditions, characterized in that, The method for predicting crack filling and dissolution includes the following steps: Based on the geological data of the study area and the test and analysis results of the geological samples in the study area, geological characteristic data are obtained, including stratigraphic characteristic data and fracture characteristic data. Based on the geological feature data, a fracture attribute model is constructed; Based on the fracture property model, a quantitative calculation model for fracture filling and dissolution is constructed by combining the principle of water-rock interaction. Based on the quantitative calculation model for fracture filling and dissolution, the water-rock interaction environment and fracture properties are set to simulate the coupled process of fracture filling and dissolution, and predict the fracture filling and dissolution situation. The quantitative calculation model for fracture filling and dissolution includes the simultaneous dissolution reaction of carbonate rocks and the precipitation reaction of minerals. The coupled process of fracture filling and dissolution simulated based on the quantitative calculation model includes the simultaneous dissolution and filling of carbonate rocks. The step of obtaining geological characteristic data, including stratigraphic characteristic data and fracture characteristic data, based on geological data of the study area and test and analysis results of geological samples from the study area, specifically includes: Based on the geological survey data, drilling data, and seismic exploration data of the study area, first stratigraphic characteristic data is obtained. The first stratigraphic characteristic data includes at least stratigraphic length, stratigraphic width, and stratigraphic depth. The stratigraphic characteristic data includes the first stratigraphic characteristic data. The cracks in the geological sample are divided into macroscopic cracks and microscopic cracks. By observing the macroscopic cracks, the density, aperture, dip angle, and degree of filling and dissolution of the macroscopic cracks are obtained. By preparing thin sections of cast bodies and using scanning electron microscopy imaging technology, the density, aperture, dip angle, and degree of filling and dissolution of the microscopic cracks are obtained. Geochemical testing and analysis techniques were used on the geological samples to obtain second stratigraphic characteristic data, fracture filling phases, cave filling phases, and paleodepositional environments. The fracture characteristic data included at least fracture density, fracture aperture, fracture dip angle, degree of fracture filling dissolution, fracture filling phases, cave filling phases, and paleodepositional environments. The second stratigraphic characteristic data included at least density, volume, porosity, porosity, permeability, pressure, temperature, chemical composition, salt mass fraction, hygrothermal conductivity, and specific heat capacity. The stratigraphic characteristic data included the second stratigraphic characteristic data.

2. The method for predicting crack filling and dissolution as described in claim 1, characterized in that, The step of constructing a fracture attribute model based on the geological feature data specifically includes: A stratigraphic model is established based on the first stratigraphic feature data; Based on the geological model, a fault / fracture model is constructed according to the fracture feature data; The fault / fracture model is meshed to construct a finite element mesh model; Based on the finite element mesh model, the fracture attribute model is constructed according to the second formation feature data.

3. The method for predicting crack filling and dissolution as described in claim 2, characterized in that, The steps for constructing a quantitative calculation model for fracture filling and dissolution based on the fracture property model and the principle of water-rock interaction specifically include: Based on the crack attribute model, a quantitative characterization model of single-phase fluid seepage characteristics is obtained according to the calculation formula of single-phase fluid seepage characteristics, and a quantitative characterization model of multiphase fluid seepage characteristics is obtained according to the calculation formula of multiphase fluid seepage characteristics. The mass and energy balance model for fracture filling and dissolution is calculated based on the basic mass and energy balance equation formula. A quantitative calculation model for the average volume and average surface area of ​​crack filling and dissolution is obtained based on the finite difference formula. Combining the mass and energy balance model of fracture filling and corrosion and the quantitative calculation model of average volume and average surface area of ​​fracture filling and corrosion, a quantitative calculation model of fracture filling and corrosion under the condition of average volume and surface area is obtained according to the quantitative calculation formula.

4. The method for predicting crack filling and dissolution as described in claim 3, characterized in that, The formula for calculating the seepage characteristics of the single-phase fluid is as follows: ， In the formula, U is the seepage velocity vector, k is the total permeability in mD, δ is the change in single-phase fluid pressure in Pa, p is the pressure in Pa, ρ is the liquid density in kg / m3, g is the gravity vector in N / kg, and μ is the viscosity. The formula for calculating the seepage characteristics of the multiphase fluid is as follows: ， ， In the formula, β represents fluids in different phases, and u β Let k be the seepage velocity vector corresponding to the phase fluid, and k be the total permeability in mD. rβ The relative permeability of the corresponding phase fluid, in mD, δ β The pressure change of the corresponding phase fluid, in Pa, p β The pressure of the fluid in the corresponding phase is expressed in Pa, and p is the overall pressure of the fluid in the solution, also expressed in Pa. cβ The capillary pressure of the rock is expressed in Pa and ρ. β For the corresponding phase fluid density, the unit is kg / m3; μ β This corresponds to the viscosity of the fluid in the corresponding phase. The basic mass and energy balance equation is as follows: ， In the formula, V n For any mesh block after the model is meshed, T n The area enclosed by the grid block, in meters. 2 M represents the mass or energy per unit volume, expressed in kg or J / m³. 3 , k is the mass component and the additional caloric component, in %, F is the mass or heat flux, in kg or J, q is the fluid sink and source, and n is the surface normal vector pointing to V; The finite difference formula is: ， ， In the formula, V n For any mesh block after the model is meshed, T n The area enclosed by the grid block, in meters. 2 M is the volume normalization, which is a large and dimensionless quantity. n For M in V n The dimensionless average value of A, where k is the mass component and the additional calorie component, in %. nm The average area at the cross-section between grid blocks n and m, in meters. 2 F nm For volume element V n and A nm The average value of the inward normal component of the surface portion F; The quantitative calculation formula is as follows: ， ， ， In the formula, F is the mass or heat flux, in kg or J, nm is the average value at the cross-section between grid blocks n and m, and β nm The value of k is the average value of the corresponding phase at the cross section between grid blocks n and m, where k is the total permeability in mD. rβρβ Permeability of the corresponding phase, in mD, μ β p represents the viscosity of the fluid in the corresponding phase. β,n The fluid pressure at grid block n corresponding to the phase state is expressed in MPa, p. β,m The fluid pressure at grid block m corresponding to the phase state is expressed in MPa, ρ β,nm The components of fluid density corresponding to the phase state in grid blocks m to n, in kg / m³ 3 A nm The average area at the cross-section between grid blocks n and m, in meters. 2 g nm D refers to the component of gravitational acceleration from m to n. nm Let n be the distance between nodes n and m.

5. The method for predicting crack filling and dissolution as described in claim 1, characterized in that, The water-rock interaction environment includes pressure, temperature, salt mass fraction, fluid inlet location, fluid injection rate, and enthalpy.

6. The method for predicting crack filling and dissolution as described in claim 1, characterized in that, The crack attributes include at least crack aperture, crack dip angle, and crack group.

7. The method for predicting crack filling and dissolution as described in claim 1, characterized in that, After the step of constructing a quantitative calculation model for fracture filling and dissolution based on the fracture attribute model and the principle of water-rock interaction, and before the step of setting the water-rock interaction environment and fracture attributes based on the quantitative calculation model for fracture filling and dissolution, simulating the coupled process of fracture filling and dissolution, and predicting the fracture filling and dissolution situation, the method further includes: Obtain the accuracy of the quantitative calculation model for crack filling and dissolution. If the accuracy is less than 90%, optimize the quantitative calculation model for crack filling and dissolution.

8. A crack filling and dissolution prediction system, applicable to the crack filling and dissolution prediction method as described in any one of claims 1-7, used to predict the filling and dissolution of cracks under complex crack network conditions, characterized in that, include: The geological feature data acquisition module is used to acquire geological feature data based on geological data of the study area and testing and analysis of geological samples of the study area. The geological feature data includes stratigraphic feature data and fracture feature data. A fracture attribute model construction module is used to construct a fracture attribute model based on the geological feature data. A module for constructing a quantitative calculation model for fracture filling and dissolution is used to construct a quantitative calculation model for fracture filling and dissolution based on the fracture attribute model and the principle of water-rock interaction; and... The simulation and prediction module is used to simulate the filling and dissolution coupling process of the fracture based on the quantitative calculation model of fracture filling and dissolution, set the water-rock interaction environment and fracture properties, and predict the filling and dissolution of the fracture.

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