A Multi-Field Coupled Numerical Simulation Method for In-situ Upgrading of Shale Oil at the Pore Scale

Abstract

This invention discloses a multi-field coupled numerical simulation method for in-situ upgrading of shale oil at the pore scale, relating to the field of shale oil extraction technology. The system includes a model assumption module, a mathematical model module, a model solving and parameter setting module, and a result analysis module. Based on the above system, a multi-field coupled numerical simulation method for in-situ upgrading of medium- and low-maturity shale oil at the pore scale is further proposed. Through reasonable model assumptions and mathematical model construction, combined with effective numerical solution strategies and parameter settings, it can accurately simulate the multi-field coupling phenomena in the in-situ upgrading process of medium- and low-maturity shale oil. This invention considers the dynamic changes of various chemical components during the multi-stage pyrolysis of kerogen, as well as the interaction of chemical fields, temperature fields, and seepage fields, resulting in more accurate and reliable simulation results. Furthermore, through grid independence verification, a suitable grid partitioning scheme is selected, improving computational efficiency while ensuring computational accuracy.

Description

Technical Field

[0001] This invention relates to the field of shale oil extraction technology, and in particular to a multi-field coupled numerical simulation method for in-situ shale oil upgrading at the pore scale. Background Technology

[0002] Shale oil, as a crucial component of unconventional oil and gas resources, occupies an increasingly important position in the global energy landscape. With the gradual depletion of traditional oil and gas resources, the efficient development of unconventional energy sources such as shale oil has become a key approach to alleviating energy pressure and ensuring energy security. In-situ upgrading technology for medium- and low-maturity shale oil, capable of converting low-quality shale oil into more easily extracted and utilized light oil and gas underground, is considered one of the core technologies for improving shale oil extraction efficiency. However, the development of this technology faces numerous challenges, among which the accurate understanding and simulation of the complex physicochemical reactions and multi-field coupling phenomena during the in-situ upgrading process is a critical difficulty.

[0003] In-situ upgrading of low- to medium-maturity shale oil involves complex processes spanning multiple disciplines, including chemistry, thermodynamics, and fluid mechanics. From a chemical perspective, the thermal decomposition of kerogen is an extremely complex process, encompassing various kinetic reactions, dynamic changes in multiple chemical components, and competition among products under different heating conditions. While some experimental studies have explored the pyrolysis of kerogen, limitations in experimental conditions have hindered a comprehensive and in-depth understanding of the microscopic mechanisms and macroscopic laws governing the reaction process.

[0004] From a thermal perspective, heat transfer during kerogen pyrolysis involves both conduction and convection, and the process is interdependent with changes in chemical composition. On one hand, the pyrolysis reaction requires heat to drive it, and the reaction itself generates heat of chemical reaction, making the distribution and changes in the temperature field extremely complex. On the other hand, temperature changes, in turn, affect the chemical reaction rate and the physical properties of the fluid, further increasing the complexity of the heat transfer process. Existing heat transfer models, when dealing with this complex multi-field coupling problem, suffer from insufficient accuracy and incomplete consideration of factors, failing to accurately predict changes in the temperature field.

[0005] In the field of fluid mechanics, the flow behavior of heavy oil, light oil, and gas products generated from kerogen pyrolysis in porous media is also highly complex. The flow of these mixed fluids within the pores is influenced not only by the pore structure and fluid properties but also by the pyrolysis reaction and temperature changes. Traditional seepage models are mostly based on simple assumptions and struggle to accurately describe the actual flow of shale oil in complex pore structures, leading to significant errors in predictions of shale oil production and recovery rates.

[0006] Furthermore, the diverse geological conditions of shale, including its pore structure, permeability, and mineral composition, significantly increase the difficulty of simulation. Existing numerical simulation methods and systems often fail to comprehensively consider these complex factors, making it challenging to effectively simulate the in-situ upgrading process of shale oil under different geological conditions.

[0007] In summary, there is currently a lack of effective methods and systems capable of comprehensively and accurately simulating the complex physicochemical reactions and multi-field coupling phenomena during the in-situ upgrading of medium- and low-maturity shale oil. This not only limits a deeper understanding of the in-situ upgrading process of medium- and low-maturity shale oil but also hinders the research and optimization of related extraction technologies, resulting in low extraction efficiency and high costs for medium- and low-maturity shale oil. Therefore, developing a method that can accurately simulate the multi-field coupling process of in-situ upgrading of medium- and low-maturity shale oil at the pore scale is of significant practical importance for promoting the efficient development and utilization of shale oil resources. Summary of the Invention

[0008] The purpose of this invention is to propose a multi-field coupled numerical simulation method for in-situ upgrading of shale oil at the pore scale to solve the problems mentioned in the background art. This invention realizes the bidirectional coupling of chemical field, temperature field and seepage field, and can effectively simulate the in-situ upgrading process of medium and low maturity shale oil.

[0009] To achieve the above objectives, the present invention adopts the following technical solution:

[0010] A multi-field coupled numerical simulation method for in-situ upgrading of shale oil at the pore scale includes a model assumption module, a mathematical model module, a model solving and parameter setting module, and a result analysis module; wherein:

[0011] The model assumption module is used to set the assumptions in the simulation process, including ignoring the influence of water, not considering fluid phase change, treating pyrolysis products as a mixed fluid phase, using Darcy's law to describe the flow of the mixed fluid, and assuming that the matrix has homogeneous and isotropic porous properties.

[0012] The mathematical model module includes a chemical field (pyrolysis reaction kinetics) model, a temperature field (porous medium heat transfer) model, and a seepage field (porous medium flow) model, which are used to describe the physicochemical reactions and fluid flows in the in-situ upgrading process of medium and low maturity shale oil.

[0013] The model solving and parameter setting module includes numerical solution strategies, network partitioning, independence verification, and simulation conditions and parameter settings, which are used to solve the model and optimize the parameters.

[0014] The results analysis module is used to analyze the changes in the yield of various products, the changes in the mass ratio of each fluid component at different temperatures, and the changes in related physical parameters during the in-situ upgrading of medium- and low-maturity shale oil obtained from the simulation, in order to evaluate the correctness and effectiveness of the simulation results.

[0015] Preferably, the chemical field (pyrolysis reaction kinetics) model uses multiple thermal decomposition reactions to characterize the decomposition process of kerogen, and calculates the chemical reaction rate constant using the Arrhenius equation, expressed as follows:

[0016]

[0017] Among them, K l A represents the rate constant of a chemical reaction; l E represents the frequency factor; l R represents the activation energy of the reaction. g T represents the ideal gas constant; T represents the temperature.

[0018] The mass change of a fluid component is described using the mass conservation equation, and its formula is expressed as:

[0019]

[0020] in, Indicates porosity; ρ f The density of the fluid mixture is represented by ; w represents the mass fraction. Represents the gradient operator; u f Represents the velocity vector; j represents the effective diffusion flux; R represents the mass source generated by the chemical reaction; the subscript i represents different fluid components;

[0021] Simultaneously considering the porosity change and effective diffusion flux calculation during kerogen pyrolysis, the formulas are expressed as follows:

[0022]

[0023] in, Indicates initial porosity; ρ ker,0 The initial mass concentration of kerogen is represented by ; D represents the diffusion coefficient.

[0024] Preferably, the temperature field (porous medium heat transfer) model couples heat conduction and heat convection, describes temperature field changes through governing equations, characterizes the thermal properties of the mixed fluid using a mass fraction and density weighting method, and incorporates the heat source of chemical reaction, as detailed below:

[0025] The governing equations for the temperature field are expressed as follows:

[0026]

[0027] Among them, C f λ represents the specific heat capacity at constant pressure; Q represents the heat source; λ represents the specific heat capacity at constant pressure. t The effective thermal conductivity of a porous medium is defined as follows:

[0028]

[0029] Where, λ s λ represents the thermal conductivity of shale; f The thermal conductivity of the fluid mixture is represented by a weighted method that comprehensively considers mass fraction and density to characterize the fluid mixture and describe the dynamic evolution of fluid components during the multi-stage pyrolysis of kerogen. The definition is as follows:

[0030]

[0031] In the above formula (ρC) eff Defined as:

[0032]

[0033] Where, ρ s Indicates shale density; C s This represents the isobaric specific heat capacity of shale; the isobaric specific heat capacity C of a fluid mixture. f The calculation formula is:

[0034]

[0035] The heat source Q includes an external heating source Q. in The heat of chemical reaction Q r :

[0036] Q = Q in +Q r

[0037] Among them, the heat of chemical reaction Q r Represented as:

[0038] Q r =∑ n -K n ΔH n M n

[0039] Among them, K n ΔH n and M n Let represent the chemical reaction rate, enthalpy, and mass concentration of the reactants in the nth pyrolysis reaction, respectively.

[0040] Preferably, the seepage field (porous media flow) model follows Darcy's law to describe the flow of the mixed fluid in the porous medium, uses the Kozeny-Carman relationship to characterize the relationship between porosity and permeability, and satisfies the law of conservation of mass, as detailed below:

[0041] The flow of a mixed fluid in a porous medium is defined as:

[0042]

[0043] Where k represents shale permeability; p represents pressure; μ f The viscosity of a fluid mixture is expressed by the following formula:

[0044]

[0045] As kerogen continues to cleave, the porosity of the porous medium gradually increases, leading to an increase in permeability. A simplified Kozeny-Carman relationship is used to describe the relationship between porosity and permeability.

[0046]

[0047] Fluid flow within porous media is governed by the principle of mass conservation, expressed as:

[0048]

[0049] Preferably, the numerical solution strategy adopts a split solution method, which automatically adjusts the time step according to the convergence and sets a more refined time step in the initial stage;

[0050] The network partitioning adopts a Delaunay triangle network and sets a boundary layer on the kerogen surface to achieve mesh refinement;

[0051] The independence verification was conducted by designing network generation scenarios with different numbers of grids and selecting a grid partitioning scheme that stabilized the simulation results.

[0052] The simulation conditions and parameter settings include setting the initial porosity, permeability, initial kerogen mass concentration of oil shale, heating rate of the simulation area, and physicochemical parameters of other relevant substances.

[0053] This invention further protects a multi-field coupled numerical simulation method for in-situ upgrading of medium- and low-maturity shale oil, comprising the following steps:

[0054] S1. Model Building: Based on the model assumption module, construct the mathematical model module in the simulation software, including numerical models of the chemical field (pyrolysis reaction kinetics) model, temperature field (heat transfer in porous media) model, and seepage field (flow in porous media) model, and define the geometry and material properties.

[0055] S2. Solver Settings: Based on the model solver and parameter setting module, select the separate solver method, set the initial time step, perform mesh generation and select a suitable mesh scheme based on independence verification, and set the initial conditions and parameters for the simulation.

[0056] S3. Simulation Run: Based on the model assumption module, mathematical model module, model solving and parameter setting module, construct a numerical simulation model; run the numerical simulation model and obtain simulation results;

[0057] S4. Results Analysis: Analyze the changes in the yield of various products, the changes in the mass ratio of each fluid component, and the changes in related physical parameters in the simulation results to evaluate the correctness and effectiveness of the simulation results.

[0058] Compared with existing technologies, it has the following beneficial effects:

[0059] This invention proposes a multi-field coupling numerical simulation method for in-situ upgrading of shale oil at the pore scale. Through reasonable model assumptions and mathematical model construction, combined with effective numerical solution strategies and parameter settings, it can accurately simulate the multi-field coupling phenomena in the in-situ upgrading process of medium- and low-maturity shale oil. Specifically, it includes the following advantages:

[0060] (1) This invention takes into account the dynamic changes of various chemical components during the multi-stage pyrolysis of kerogen, as well as the interaction between chemical field, temperature field and seepage field, and the simulation results are more accurate and reliable.

[0061] (2) This invention selects a suitable grid partitioning scheme through grid independence verification, which improves computational efficiency while ensuring computational accuracy. The simulation results obtained in the embodiments are consistent with existing research, which verifies the correctness of the model. It provides a powerful tool for the research and development of in-situ shale oil upgrading technology, which helps to improve shale oil extraction efficiency and reduce extraction costs. Attached Figure Description

[0062] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the accompanying drawings involved in the embodiments are now briefly described. Obviously, the drawings in the following description are merely illustrative of some embodiments of the present invention. For those skilled in the art, other forms of drawings can be constructed based on these drawings without creative effort.

[0063] Figure 1 This is a schematic diagram of multi-field coupling of thermal fluidization during in-situ thermal upgrading mentioned in Embodiment 1 of the present invention;

[0064] Figure 2 This is a schematic diagram of mesh generation mentioned in Embodiment 1 of the present invention, wherein (a) is a refined enlarged view of the boundary layer mesh, and (b) is the mesh generation of the numerical model;

[0065] Figure 3 This is a comparison chart of heavy oil production under different grid generation schemes for the grid independence test mentioned in Embodiment 1 of the present invention;

[0066] Figure 4 The changes in the mass concentration of solid components, average porosity, and average permeability mentioned in Example 1 of this invention during in-situ thermal upgrading are shown in the figure. The upper part represents the average temperature, mass concentration of kerogen and various carbons, and the lower part represents the average porosity and average permeability.

[0067] Figure 5 The variation in fluid component content during in-situ thermal upgrading of medium- and low-maturity shale oil, as mentioned in Example 1 of this invention, includes methane (C1), other gases (C2-C5), and light oil (C6-C5). 20 ) and heavy oil (C 21 -C 45 ). Detailed Implementation

[0068] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments.

[0069] The following describes the multi-field coupled numerical simulation method for in-situ shale oil upgrading at the pore scale proposed in this invention, with reference to relevant accompanying drawings and specific examples.

[0070] Example 1:

[0071] This invention proposes a multi-field coupled numerical simulation method for in-situ upgrading of shale oil at the pore scale, and further designs a matching multi-field coupled numerical simulation system for medium- and low-maturity shale oil at the pore scale based on the proposed system, specifically including the following:

[0072] 1. Model Assumption Module

[0073] The microscopic model used for in-situ upgrading includes an inorganic rock framework and an organic component, kerogen. Under a stable heat source, the temperature of the microscopic model gradually increases, and the kerogen is gradually decomposed into heavy oil, light oil, gas, methane, and different types of coke as the temperature rises. The chemical components of the decomposed kerogen can be transported in the porous medium through diffusion and convection. To simulate the complex in-situ upgrading process of medium-to-low maturity shale oil, the following assumptions were made in this example:

[0074] (1) The simulated temperature is much higher than the boiling point of water, so the influence of water can be ignored;

[0075] (2) The effects of fluid phase change are not considered in the simulation process;

[0076] (3) The heavy oil, light oil, gas, and methane generated during the pyrolysis reaction form a mixed fluid phase:

[0077] (4) The flow of mixed fluids can be described by Darcy's law;

[0078] (5) The porous properties of the matrix are uniform and isotropic.

[0079] 2. Mathematical Model

[0080] 2.1 Chemical Field (Pyrolysis Reaction Kinetics) Model

[0081] The thermal decomposition of kerogen is a highly complex process involving multiple kinetic reactions and dynamic changes in various chemical components. Table 1 shows the decomposition process of kerogen characterized by seven thermal decomposition reactions.

[0082] Table 1 Kinetic data of the reaction model

[0083]

[0084]

[0085] During the pyrolysis of kerogen, competition exists between the yields of methane, hydrocarbon gases, heavy oil, light oil, and various types of coke due to different heating conditions. When the simulated system temperature reaches 300 degrees Celsius, kerogen gradually begins to decompose. Kerogen and the four types of coke are solid components, and their mass changes depend on the pyrolysis reaction. The mass concentration changes can be expressed as:

[0086]

[0087] Where M represents mass concentration; K represents reaction rate constant; t represents heating time; subscripts 1 to 7 represent different pyrolysis reaction stages; ker represents kerogen; HO, LO, and Hg represent heavy oil, light oil, and other gases, respectively; ck1 to ck4 represent different types of coke generated in different reaction stages; the reaction rate constant during pyrolysis is calculated using the Arrhenius equation and is specifically expressed as follows:

[0088]

[0089] Where A represents the frequency factor; E l The value represents the activation energy of the reaction; Rg represents the ideal gas constant; T represents the temperature; Table 1 below represents the stages of the pyrolysis reaction.

[0090] The heavy oil, light oil, mixed hydrocarbon gases, and methane gas produced after the pyrolysis of kerogen are defined as fluid components. The mass conservation equations for various fluid components in porous media include diffusion, convection, and pyrolysis reaction terms, with mass balance represented by their respective mass fractions, w.

[0091]

[0092] in, ρ represents the porosity of porous media. f The density of the fluid mixture is represented by w; the mass fraction is represented by u. f The vector represents velocity; j represents effective diffusion flux; R represents the mass source in the chemical reaction; and the subscript i represents different fluid components. The density of a fluid mixture is closely related to the content of its components. The density of the mixture is calculated using a mass fraction weighting method.

[0093] ρ f =∑ i ρ i w i (8)

[0094] The change in porosity during the pyrolysis of kerogen is expressed as follows:

[0095]

[0096] in, Indicates initial porosity; ρ ker，0 The initial mass concentration of kerogen is represented; the effective diffusion flux is described by Fick's law and calculated using the Millington Quirk model.

[0097]

[0098] Where D represents the diffusion coefficient;

[0099] The mass source of chemical reactions from various fluid components is:

[0100] R HO =0.279K1M ker -K2M HO (11)

[0101] R LO =0.143K1M ker +0.373K2M HO -K3M LO (12)

[0102] R Hg =0.018K1M ker +0.156K2M HO +0.595K3MLO +0.031K5M ck1 +0.003K6M ck2 -K4M Hg (13)

[0103]

[0104] 2.2 Temperature Field (Heat Transfer in Porous Media) Model

[0105] During the pyrolysis of kerogen, heat transfer occurs through a combination of conduction and convection. The governing equation for the temperature field is expressed as:

[0106]

[0107] Where T represents temperature; C represents isobaric heat capacity; Q represents the heat source term; λ t The effective thermal conductivity of a porous medium is specifically defined as:

[0108]

[0109] Where, λ s λ represents the thermal conductivity of shale; f The thermal conductivity of the mixed fluid is represented by the coefficient of mass. To describe the dynamic evolution of fluid components during the multi-stage pyrolysis of kerogen, a weighted method considering both mass fraction and density is used to characterize fluid mixing, specifically:

[0110]

[0111] In equation (15), (ρC) eff Defined as:

[0112]

[0113] Where, ρ s Indicates the density of shale; C s This represents the heat capacity of shale under constant pressure; the heat capacity of the mixed fluid under constant pressure can be calculated using the following formula:

[0114]

[0115] The heat source item Q mainly includes external heating source Q. in The heat of chemical reaction Q r :

[0116]

[0117] The heat of chemical reaction Q r Represented as:

[0118] Q r =∑n -K n ΔH n M n (twenty one)

[0119] Among them, K n ΔH n and M n These represent the chemical reaction rate, enthalpy, and mass concentration of the reactants in the nth pyrolysis reaction, respectively.

[0120] 2.3 Seepage Field (Porous Media Flow) Model

[0121] The petroleum and natural gas products from the pyrolysis of kerogen are a mixed fluid that flows in a porous medium according to Darcy's law, defined as follows:

[0122]

[0123] Where k represents the permeability of the shale; p represents the fluid pressure; μ f The viscosity of a fluid mixture is expressed as follows:

[0124]

[0125] As kerogen continuously breaks down, the porosity of the porous media gradually increases, leading to an increase in permeability k. This example uses a simple Kozeny-Carman relation to characterize the relationship between porosity and permeability:

[0126]

[0127] During seepage, the flow of fluid satisfies the law of conservation of mass:

[0128]

[0129] 3. Model Solving and Parameter Setting

[0130] 3.1 Numerical Solution Strategy

[0131] The physicochemical reactions and fluid flows involved in the in-situ upgrading process of medium- and low-maturity shale oil involve chemical, temperature, and seepage fields. In this example, the chemical, temperature, and seepage fields are bidirectionally coupled in the simulation model; the chemical field is calculated using a custom partial differential equation; and the temperature and seepage fields are calculated using a porous media heat transfer module and a Darcy's law module for groundwater flow. The coupling relationships between them are as follows: Figure 1 As shown.

[0132] 3.2 Network Partitioning

[0133] During the simulation, a Delaunay triangular mesh was used to mesh the physical model. Furthermore, to accurately capture the changes in fluid composition during the kerogen pyrolysis, a boundary layer was added to the kerogen surface during mesh generation to refine the mesh at the coupling interface. The numerical mesh generation model is as follows: Figure 2 As shown.

[0134] 3.3 Independence Verification

[0135] To achieve higher computational efficiency and reduce computational costs, this example conducted a mesh independence test to demonstrate the rationality of the network generation scenario chosen in this invention. Therefore, this example designed four network generation scenarios with different numbers of meshes, as shown in Table 2.

[0136] Table 2. Mesh information for mesh independence verification.

[0137]

[0138] Heavy oil (C) in different mesh generation scenarios 21 -C 45 Production comparison, for example Figure 3 As shown. From Figure 3 As can be seen, the production curve of grid 4 differs significantly during the simulation, showing marked differences from the calculation results of other network scenarios. Then, as the number of grids increases, the calculated heavy oil production becomes more stable. The results between grid numbers of 54833 and 84961 are almost identical, indicating that any further grid optimization will not produce different calculation results. Therefore, the network generation scenario of grid 2 (54866 grids) was selected as the grid partitioning for the numerical model in this example.

[0139] 3.4 Simulation conditions and parameters

[0140] Considering the poor permeability of medium- and low-maturity shale oil in its original state, its initial porosity and permeability were set to 0.013 and 6 × 10⁻⁶, respectively. -4 mD. Assuming a stable heat source in the simulation region with a heating rate of 10 K / min, and the initial mass concentration of kerogen set at 1250 kg / m³. 3 Other parameters are shown in Table 3.

[0141] Table 3. Parameters used in numerical simulation

[0142]

[0143] 4. Results and Discussion

[0144] 4.1 Pyrolysis characteristics of kerogen

[0145] Changes in solid component mass concentration, average porosity, and average permeability during in-situ thermal upgrading are as follows: Figure 4 As shown, where, Figure 4 The upper part shows the changes in average temperature, kerogen quality, and various cokes during the in-situ thermal upgrading of medium- and low-maturity shale oil. The entire kerogen pyrolysis process can be divided into three stages: the preheating stage, the pyrolysis conversion stage, and the pyrolysis completion stage.

[0146] Figure 4 The second half shows the changes in average porosity and average permeability with temperature during kerogen pyrolysis. These changes are divided into four distinct stages, with the kerogen pyrolysis stage considered as a period of rapid increase in average porosity and average permeability, followed by a period of slow increase.

[0147] 4.2 Production Characteristics

[0148] Changes in fluid component content during in-situ thermal upgrading of medium- and low-maturity shale oil, such as Figure 5 As shown, Figure 5 This study illustrates the changes in oil and gas production during in-situ thermal upgrading of medium- and low-maturity shale oil. As the pyrolysis process progresses, kerogen decomposition initially leads to a rapid increase in both heavy and light oil production, which subsequently declines due to kerogen consumption.

[0149] In summary, Figure 5 The results are consistent with the product change characteristics during in-situ thermal upgrading of medium- and low-maturity shale oil, verifying the correctness of the model.

[0150] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any equivalent substitutions or modifications made by those skilled in the art within the scope of the technology disclosed in the present invention, based on the technical solution and inventive concept of the present invention, should be covered within the scope of protection of the present invention.

Claims

1. A multi-field coupled numerical simulation method for in-situ upgrading of shale oil at the pore scale, characterized in that, The method is based on a multi-field coupled numerical simulation system for in-situ upgrading of shale oil at the pore scale. The system includes a model assumption module, a mathematical model module, a model solving and parameter setting module, and a result analysis module; wherein: The model assumption module is used to set the assumptions in the simulation process, including ignoring the influence of water, not considering fluid phase change, treating pyrolysis products as a mixed fluid phase, using Darcy's law to describe the flow of the mixed fluid, and assuming that the matrix has homogeneous and isotropic porous properties. The mathematical model module includes a chemical field model, a temperature field model, and a seepage field model, which are used to describe the physicochemical reactions and fluid flows during the in-situ upgrading process of shale oil. The model solving and parameter setting module includes numerical solution strategies, network partitioning, independence verification, and simulation conditions and parameter settings, which are used to solve the model and optimize the parameters. The results analysis module is used to analyze the changes in the yield of various products, the changes in the mass ratio of each fluid component at different temperatures, and the changes in related physical parameters during the simulated in-situ upgrading of shale oil, in order to evaluate the correctness and effectiveness of the simulation results. The method includes the following steps: S1. Model Building: Based on the model assumption module, construct the mathematical model module in the simulation software, including numerical models of the chemical field model, temperature field model, and seepage field model, and define the geometry and material properties. S2. Solver Settings: Based on the model solver and parameter setting module, select the separate solver method, set the initial time step, perform mesh generation and select a suitable mesh scheme based on independence verification, and set the initial conditions and parameters for the simulation. S3. Simulation Run: Based on the model assumption module, mathematical model module, model solving and parameter setting module, construct a numerical simulation model; run the numerical simulation model and obtain simulation results; S4. Results Analysis: Analyze the changes in the yield of various products, the changes in the mass ratio of each fluid component, and the changes in related physical parameters in the simulation results to evaluate the correctness and effectiveness of the simulation results.

2. The multi-field coupled numerical simulation method for in-situ upgrading of shale oil at the pore scale according to claim 1, characterized in that, The chemical field model uses multiple thermal decomposition reactions to characterize the decomposition process of kerogen, and calculates the chemical reaction rate constant using the Arrhenius equation, expressed as follows: in, K l Represents the rate constant of a chemical reaction; A l Represents the frequency factor; E l Indicates the activation energy of the reaction; R g Represents the ideal gas constant; T Indicates temperature; The mass change of a fluid component is described using the mass conservation equation, and its formula is expressed as: in, Indicates porosity; ρ f Indicates the density of a fluid mixture; w Indicates the mass fraction; " denotes the gradient operator; u f Represents the velocity vector; j Indicates the effective diffusion flux; R Indicates the mass source produced by a chemical reaction; subscript i Representing different fluid components; Simultaneously considering the porosity change and effective diffusion flux calculation during kerogen pyrolysis, the formulas are expressed as follows: in, Indicates initial porosity; Indicates the initial mass concentration of kerogen; D This represents the diffusion coefficient.

3. The multi-field coupled numerical simulation method for in-situ upgrading of shale oil at the pore scale according to claim 2, characterized in that, The temperature field model couples heat conduction and heat convection, describes temperature field changes through governing equations, characterizes the thermal properties of the mixed fluid using a mass fraction and density weighted method, and incorporates the heat source from chemical reactions. The specific details are as follows: The governing equations for the temperature field are expressed as follows: in, Cf This indicates the specific heat capacity at constant pressure. Q Indicates the heat source; λ t The effective thermal conductivity of a porous medium is defined as follows: in, λ s This indicates the thermal conductivity of shale; λ f The thermal conductivity of the fluid mixture is represented by a weighted method that comprehensively considers mass fraction and density to characterize the fluid mixture and describe the dynamic evolution of fluid components during the multi-stage pyrolysis of kerogen. The definition is as follows: In the above formula ( ρC ) eff Defined as: in, ρ s Indicates shale density; C s This represents the isobaric specific heat capacity of shale; the isobaric specific heat capacity of a fluid mixture. C f The calculation formula is: heat source Q Including external heating sources Q in and heat of chemical reaction Q r : Among them, the heat of chemical reaction Q r Represented as: in, K n , and M n Let represent the chemical reaction rate, enthalpy, and mass concentration of the reactants for the nth pyrolysis reaction, respectively.

4. The multi-field coupled numerical simulation method for in-situ upgrading of shale oil at the pore scale according to claim 3, characterized in that, The seepage field model follows Darcy's law to describe the flow of the mixed fluid in the porous medium, uses the Kozeny-Carman relationship to characterize the relationship between porosity and permeability, and satisfies the law of conservation of mass. The specific details are as follows: The flow of a mixed fluid in a porous medium is defined as: in, k Indicates penetration rate; p Indicates pressure; μ f The viscosity of a fluid mixture is expressed by the following formula: As kerogen continues to cleave, the porosity of the porous medium gradually increases, leading to an increase in permeability. A simplified Kozeny–Carman relationship is used to describe the relationship between porosity and permeability: Fluid flow within porous media is governed by the principle of mass conservation, expressed as: 。 5. The multi-field coupled numerical simulation method for in-situ shale oil upgrading at the pore scale according to claim 4, characterized in that, The numerical solution strategy adopts a split solution method, which automatically adjusts the time step based on convergence and sets a more refined time step in the initial stage. The network partitioning adopts a Delaunay triangle network and sets a boundary layer on the kerogen surface to achieve mesh refinement; The independence verification was conducted by designing network generation scenarios with different numbers of grids and selecting a grid partitioning scheme that stabilized the simulation results. The simulation conditions and parameter settings include setting the initial porosity, permeability, initial kerogen content of the oil shale, the heating rate of the simulation area, and the physicochemical parameters of other relevant substances.

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