A method for evaluating the minimum miscibility pressure of carbon dioxide and shale oil under confinement effect

Abstract

The present invention discloses a method for evaluating the minimum miscibility pressure of carbon dioxide and shale oil under the confinement effect, and belongs to the field of minimum miscibility pressure determination. The technical scheme includes the steps of constructing a molecular model; selecting force field parameters, describing the interaction forces between molecules and within molecules; dividing the simulation area and boundary conditions; determining simulation parameters and calculation parameters, performing molecular simulation on the molecular model; and calculating the minimum miscibility pressure according to the interaction energy. The present invention is applied to the determination of the minimum miscibility pressure of carbon dioxide and shale oil under the confinement effect, solving the technical problem that the existing calculation method cannot accurately calculate the miscibility pressure of the two-phase interface of carbon dioxide and shale oil under the confinement effect, and can accurately and efficiently calculate the minimum miscibility pressure of carbon dioxide and shale oil under the confinement effect.

Description

Technical Field

[0001] The present invention belongs to the field of minimum miscible pressure measurement, and in particular relates to a method for evaluating the minimum miscible pressure of carbon dioxide and shale oil under confinement effect. Background Art

[0002] In the process of oil extraction, CO2-ESOR is one of the important methods to improve the recovery rate of shale oil. The minimum miscibility pressure (MMP) is a key parameter in the CO2 flooding process. Accurately determining the MMP is crucial for optimizing the flooding scheme and improving the recovery rate. However, in the nanoscale reservoir pores, due to the existence of the confinement effect, the phase behavior of CO2 and shale oil is significantly different from that under macroscopic bulk conditions. It is difficult for traditional methods to accurately calculate the MMP under the confinement effect. In addition, the accurate calculation method for the minimum miscibility pressure between CO2 and shale oil under the nano-confinement effect in molecular simulation is still imperfect. Therefore, it is of great practical significance to develop an efficient and accurate calculation method. Summary of the invention

[0003] In view of the shortcomings of the prior art, the technical problem to be solved by the present invention is to overcome the technical problem that the existing calculation methods cannot accurately calculate the miscibility pressure of the two-phase interface of carbon dioxide and shale oil under the confinement effect, and propose an evaluation method for the minimum miscibility pressure of carbon dioxide and shale oil under the confinement effect, which can accurately and efficiently calculate the minimum miscibility pressure of carbon dioxide and shale oil under the confinement effect.

[0004] In order to solve the technical problem, the technical solution adopted by the present invention is:

[0005] The invention provides an evaluation method for the minimum miscibility pressure of carbon dioxide and shale oil under confinement effect, comprising: a step of constructing a molecular model; a step of selecting force field parameters to describe the interaction forces between molecules and within molecules; a step of dividing simulation regions and boundary conditions; a step of determining simulation parameters and calculation parameters, and a step of performing molecular simulation on the molecular model; and a step of calculating the minimum miscibility pressure according to the interaction energy, specifically comprising: respectively calculating the interaction energy of carbon dioxide and shale oil under nanopore conditions and the interaction energy under bulk conditions, performing a difference operation on the interaction energy under nanopore conditions and the interaction energy under bulk conditions, and obtaining an interaction energy difference Δ E ; For the interaction energy difference Δ E The data is first processed using an interpolation function so that the discrete data points can be expressed continuously within the pressure range through the function. Then, Gaussian fitting is used to minimize the square sum of the errors between the actual data points and the predicted values ​​of the Gaussian function to determine the optimal Gaussian function parameters to fit the interpolated data points, thereby obtaining multiple values ​​that can accurately characterize the interaction energy difference Δ EThe discrete points of the relationship between the pressure P and the pressure P; for the above discrete points, the first-order central difference operation is used to obtain The relationship curve with pressure change; in this curve, the pressure corresponding to the maximum point of the first-order derivative is the minimum miscibility pressure of carbon dioxide and shale oil under the nanoconfinement effect.

[0006] Preferably, under both nanopore and bulk conditions, the interaction energy under different pressures and when the system reaches a stable state is calculated respectively, and the interaction energy under nanopore conditions and the interaction energy under bulk conditions are obtained; the criterion for reaching a stable state is that within a continuous simulation time, the fluctuation amplitude of the system energy is extremely small and tends to be stable.

[0007] Preferably, the first-order central difference formula is:

[0008] ,

[0009] in, P i is a specific pressure point, Δ E i+1 , Δ E i-1 Adjacent pressure points P i+1 and P i-1 The corresponding interaction energy difference is generated by performing this operation for each discrete point The relationship curve with pressure change.

[0010] Preferably, the step of constructing a molecular model specifically includes: constructing models of carbon dioxide molecules, oil molecules and porous rock minerals respectively; constructing a carbon dioxide-shale oil-porous rock formation carbon dioxide intake and output shale oil molecular model under confinement effect according to reservoir conditions and intake and output pressure; based on the carbon dioxide-shale oil-porous rock formation molecular model, deleting the pore wall surface, and constructing a carbon dioxide-oil two-phase molecular model under the same conditions.

[0011] Preferably, the porous rock mineral model includes a graphene model, a kerogen model, a montmorillonite model and a quartz model.

[0012] Preferably, Packmol software is used to construct a molecular model of carbon dioxide intake and output of shale oil, specifically including: selecting graphene as an organic mineral, constructing a single-layer or multi-layer graphene wall, and constructing graphene nanopores; selecting kerogen molecules as organic minerals, and constructing kerogen nanopores; selecting montmorillonite crystals as clay minerals, and constructing montmorillonite nanopores; selecting quartz crystals as siliceous minerals, and constructing quartz nanopores; the pore wall is composed according to the pore rock mineral model, the oil molecules are filled in the center of the pore, and different numbers of carbon dioxide molecules are filled on both sides to obtain a molecular model of carbon dioxide intake and output of shale oil.

[0013] Preferably, the steps of selecting force field parameters and describing the interaction forces between molecules and within molecules specifically include: using TraPPE force field and TraPPE-UA force field to describe the interaction between carbon dioxide molecules and oil molecules, wherein CVFF force field is used for graphene crystals and kerogen molecules, and CLAYFF force field is used for montmorillonite crystals and quartz crystals; LJ potential function is used to describe the interaction forces between different atoms in the system; and the cross-interaction terms between different molecules are calculated using the Lorentz-Berthelot mixing rule.

[0014] Preferably, the LJ potential function is used to describe the interaction force between different atoms in the system, which is given by equation (1):

[0015]

[0016] in, yes i Class and j The distance between atoms, is the potential well depth of the Lennard-Jones potential, which characterizes the strength of the interaction between atoms. is the distance at which the interaction energy between two particles is minimal.

[0017] Preferably, the cross-interaction terms between different molecules are calculated using the Lorentz-Berthelot mixing rule, expressed by equation (2) and equation (3):

[0018]

[0019] The long-range Coulomb force between atoms is expressed by equation (4):

[0020]

[0021] In the formula, , They are i Class and j The charge of the atom-like substance; is the dielectric constant of vacuum.

[0022] Preferably, the simulation parameters and calculation parameters are determined, and the molecular simulation steps for the molecular model specifically include: setting the simulation system to use the NVT ensemble, using the Nose-Hover heat bath method to control the temperature, and using the number of carbon dioxide molecules to control the pressure; the simulation time step is 1.0fs, the cutoff radius is 10.0Å, the initial temperatures are 343K and 363K, and the pressures are 5MPa, 7MPa, 9MPa, 11MPa, and 13MPa, respectively; and the calculation settings of the interaction energy are performed; the LAMMPS software is used to simulate the three-phase molecular model of carbon dioxide-shale oil-porous rock formation. The model was simulated. First, only the oil molecules in the pores were added to the ensemble for 5ns of relaxation equilibrium to obtain the shale oil distribution model under the real state. Then, the entire model was simulated and calculated for 5ns to obtain the molecular simulation results of carbon dioxide intake and exhalation of shale oil under the confinement effect, as well as the interaction energy between carbon dioxide and shale oil. LAMMPS software was used to simulate the carbon dioxide-shale oil two-phase molecules, and the entire model was simulated and calculated for 5ns to obtain the molecular simulation results of carbon dioxide intake and exhalation of shale oil under bulk conditions, as well as the interaction energy between carbon dioxide and shale oil.

[0023] Compared with the prior art, the present invention has the following beneficial effects:

[0024] The present invention provides an evaluation method for the minimum miscibility pressure of carbon dioxide and shale oil under the confinement effect. Based on a microscopic scale, by conducting molecular dynamics simulation research on the coexistence miscibility behavior of carbon dioxide, shale oil and mineral three-phases, the miscibility characteristics of carbon dioxide, shale oil and minerals under different cap rock minerals, temperatures and pressure conditions can be determined, thereby providing a theoretical basis for effectively characterizing the minimum miscibility pressure under the confinement effect. Based on the calculation method of the interaction energy between carbon dioxide and shale oil, the difficulty of being unable to determine the miscibility pressure at the two-phase interface under the confinement effect is overcome, and the minimum miscibility pressure of carbon dioxide and shale oil under the confinement effect can be accurately and efficiently calculated. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 A carbon dioxide molecular model provided by an embodiment of the present invention;

[0026] Figure 2 The molecular model of n-decane provided in the embodiment of the present invention;

[0027] Figure 3 The kerogen wall provided by the embodiment of the present invention;

[0028] Figure 4 The carbon dioxide-shale oil-porous rock formation molecular model provided by the embodiment of the present invention;

[0029] Figure 5The carbon dioxide-shale oil molecular model provided by the embodiment of the present invention;

[0030] Figure 6 The relationship between the interaction energy in a 5 nm pore and the simulation time provided by the embodiment of the present invention;

[0031] Figure 7 The relationship between the interaction energy in the bulk phase and the simulation time provided by the embodiment of the present invention;

[0032] Figure 8 The interaction energy under the pore and bulk conditions provided by the embodiments of the present invention;

[0033] Fig. 9 The minimum miscible pressure Δ provided in the embodiment of the present invention is calculated E The relationship with pressure and Δ E The rate of change. DETAILED DESCRIPTION

[0034] The technical scheme in the specific embodiment of the present invention is described in detail and completely below. Obviously, the described embodiment is only a part of the specific implementation of the overall technical scheme of the present invention, rather than all implementations. Based on the overall concept of the present invention, all other embodiments obtained by ordinary technicians in this field fall within the scope of protection of the present invention.

[0035] The present invention provides a method for evaluating the minimum miscibility pressure of carbon dioxide and shale oil under confinement effect, comprising the following steps:

[0036] S1, construct carbon dioxide molecule, oil molecule and porous rock mineral models respectively: the porous rock mineral models include graphene model, kerogen, montmorillonite model and quartz model;

[0037] S2, based on reservoir conditions and throughput pressure, a molecular model of CO2-shale oil-porous rock formation CO2 throughput shale oil under confinement effect is constructed;

[0038] S3, based on the molecular model of carbon dioxide-shale oil-porous rock formation, the pore wall is deleted and the carbon dioxide-oil two-phase molecular model under the same conditions is constructed;

[0039] S4, select force field parameters to describe the interaction forces between molecules and within molecules;

[0040] S5, division of simulation area and boundary conditions: the porous rock layer is set as a fixed atomic layer to prevent atomic loss caused by deformation due to heat, and the model x, y and z directions are all set as periodic boundaries;

[0041] S6, determining relevant simulation parameters and required calculation parameters, and performing molecular simulation on the molecular model;

[0042] S7, calculate the minimum miscibility pressure based on the interaction energy.

[0043] In S1 and S2, the Packmol software is used to build a simulation model of carbon dioxide injection into shale oil, including:

[0044] Selecting graphene as an organic mineral, constructing a single-layer or multi-layer graphene wall, and constructing graphene nanopores;

[0045] Kerogen molecules were selected as organic minerals to construct kerogen nanopores;

[0046] Montmorillonite crystals were selected as clay minerals to construct montmorillonite nanopores;

[0047] Quartz crystals are selected as siliceous minerals to construct quartz nanopores;

[0048] The pore wall can construct various nanopores such as 3nm, 5nm, and 10nm according to the composition of the pore rock mineral model. In order to ensure the reservoir environment under different throughput conditions, the number of oil molecules must be fixed, such as 165 for 5nm, and they are filled in the center of the pore; different numbers of carbon dioxide molecules are filled on both sides to obtain a carbon dioxide throughput shale oil molecular model. The number of n-decane and carbon dioxide can be calculated based on the density at the corresponding temperature and pressure in the experimental database of the National Institute of Standards and Technology (NIST) of the United States;

[0049] Select appropriate force field functions to describe the interaction forces within and between molecules, including:

[0050] TraPPE force field and TraPPE-UA force field were used to describe the interaction between carbon dioxide molecules and oil molecules. CVFF force field was used for graphene crystals and kerogen. CLAYFF force field was used for montmorillonite crystals and quartz crystals. Some force field parameters are given in Table 1.

[0051] Table 1 Force field parameters of carbon dioxide and oil

[0052]

[0053] The LJ potential function is used to describe the interaction force between different atoms in the system, which is given by equation (1):

[0054]

[0055] in, yes i Class and j The distance between atoms, is the potential well depth of the Lennard-Jones potential, which characterizes the strength of the interaction between atoms. is the distance at which the interaction energy between two particles is minimal.

[0056] The cross-interaction terms between different molecules are calculated using the Lorentz-Berthelot mixing rule, expressed by Eq. (2) and Eq. (3):

[0057]

[0058] The long-range Coulomb force between atoms is expressed by equation (4):

[0059]

[0060] In the formula, , They are i Class and j The charge of the atom-like substance; is the dielectric constant of vacuum. The Particle-particle / particle-mesh (PPPM) algorithm is used to calculate the long-range Coulomb force with an accuracy of 0.0001.

[0061] Determine the relevant simulation parameters and the required calculation parameters, and perform molecular simulation on the molecular model, including:

[0062] The simulation system was set to use the NVT ensemble, the Nose-Hover heat bath method was used to control the temperature, and the number of carbon dioxide molecules was used to control the pressure; the simulation time step was 1.0fs, the cutoff radius was 10.0Å, the initial temperatures were 343K and 363K, and the pressures were 5MPa, 7MPa, 9MPa, 11MPa, and 13MPa, respectively; and the calculation settings for the interaction energy were performed;

[0063] The LAMMPS software was used to simulate the three-phase molecular model of carbon dioxide, shale oil and porous rock formations. First, only the oil molecules in the pores were added to the ensemble for 5 ns of relaxation equilibrium to obtain the shale oil distribution model under the real state. Then, the whole model was simulated and calculated for 5 ns to obtain the simulation results of carbon dioxide intake and exhalation of shale oil molecules under the confinement effect, as well as the interaction energy between carbon dioxide and shale oil.

[0064] LAMMPS software was used to simulate the molecular structure of CO2-shale oil. The entire model was simulated for 5 ns to obtain the molecular simulation results of CO2 inhalation and exhalation of shale oil under bulk conditions, as well as the interaction energy between CO2 and shale oil.

[0065] According to the interaction energy, the minimum miscibility pressure is calculated, specifically including:

[0066] Under the conditions of nanopore (confined model) and bulk phase (two-phase model), for each pressure condition, when the system reaches a stable state, the average value of the interaction energy is calculated. The criterion for determining the stable state is that the fluctuation amplitude of the system energy is extremely small and tends to be stable during the continuous simulation time. By taking the average value, the interference of random factors in the simulation process can be effectively reduced, thereby obtaining more representative interaction energy data. Subsequently, the average value of the interaction energy under nanopore conditions is subtracted from the average value of the interaction energy under bulk phase conditions, thereby obtaining the interaction energy difference Δ E ;

[0067] For the obtained interaction energy difference Δ E The data is first processed using an interpolation function to optimize the continuity and smoothness of the data. Specifically, a suitable interpolation method, such as Lagrange interpolation, is selected to construct an interpolation function based on the distribution characteristics of the data, so that discrete data points can be expressed continuously within the pressure range through the function.

[0068] After the interpolation process is completed, the Gaussian fitting method is used to further analyze the data. In the fitting process, by minimizing the sum of squares of the errors between the actual data points and the predicted values ​​of the Gaussian function, the optimal Gaussian function parameters are determined to be as close as possible to the interpolated data points, thereby obtaining multiple values ​​that can accurately characterize the interaction energy difference Δ E The discrete points of the relationship between the change in interaction energy and pressure P. By connecting these discrete points, a curve showing the relationship between the difference in interaction energy and pressure can be drawn.

[0069] For the discrete points obtained above, a first-order central difference operation is used to obtain The relationship curve of the first-order central difference formula is:

[0070]

[0071] in, P i is a specific pressure point, Δ E i+1 , Δ E i-1 Adjacent pressure points P i+1 and P i-1 The corresponding interaction energy difference is generated by performing this operation for each discrete point The relationship curve with pressure change.

[0072] In this curve, the pressure corresponding to the maximum point of the first-order derivative is the minimum miscibility pressure of carbon dioxide and shale oil under the nanoconfinement effect. This is because the interaction energy between carbon dioxide and shale oil changes most significantly near the minimum miscibility pressure, which is reflected in the difference in interaction energy Δ E On, that is, its rate of change is the largest.

[0073] In order to more clearly and in detail introduce the evaluation method of the minimum miscibility pressure of carbon dioxide and shale oil under the confinement effect provided by the embodiment of the present invention, it will be described below in conjunction with specific embodiments.

[0074] Example 1

[0075] A method for evaluating the minimum miscibility pressure of carbon dioxide and shale oil under confinement effect, comprising:

[0076] S1, construct carbon dioxide molecule, oil molecule and porous rock mineral models respectively: the porous rock mineral models include graphene model, kerogen, montmorillonite model and quartz model;

[0077] S2, based on reservoir conditions and throughput pressure, a molecular model of CO2-shale oil-porous rock formation CO2 throughput shale oil under confinement effect is constructed;

[0078] S3, based on the molecular model of carbon dioxide-shale oil-porous rock formation, the pore wall is deleted and the carbon dioxide-oil two-phase molecular model under the same conditions is constructed;

[0079] S4, select appropriate force field parameters to describe the interaction forces between molecules and within molecules;

[0080] S5, division of simulation area and boundary conditions: the porous rock layer is set as a fixed atomic layer to prevent atomic loss caused by deformation due to heat, and the model x, y and z directions are all set as periodic boundaries;

[0081] S6, determining relevant simulation parameters and required calculation parameters, and performing molecular simulation on the molecular model;

[0082] S7, calculating the minimum miscibility pressure according to the interaction energy.

[0083] Taking the miscibility in kerogen nano-slits as an example, the minimum miscibility pressure of carbon dioxide and shale oil is calculated.

[0084] S1, build the carbon dioxide molecule, e.g. Figure 1 As shown in the figure, shale oil molecules are constructed. Due to the complex composition of oil products, only n-decane molecules are used as representatives of shale oil molecules, such as Figure 2 shown.

[0085] Construction of kerogen wall: 32 kerogen molecules were placed in an empty box with x, y, and z dimensions of 115.36Å×100Å×100Å. The x dimension was kept fixed, and the depressurization annealing simulation was performed in the y and z directions to form a kerogen wall with x, y, and z dimensions of 115.36Å×28.84Å×28.84Å, as shown in Figure 1. Figure 3 shown.

[0086] S2, with the xy plane as the inner wall of the pore, construct 3nm, 5nm and 10nm pores, and add carbon dioxide and n-decane molecules into them respectively; Table 2 shows the number of molecules added. To construct the molecular model of carbon dioxide-shale oil-porous rock formation, such as Figure 4 shown.

[0087] Table 2 Number of carbon dioxide molecules at 343K

[0088]

[0089] S3, based on the molecular model of carbon dioxide-shale oil-porous rock formation, the kerogen wall is removed and the molecular model of carbon dioxide-shale oil under bulk conditions is constructed, such as Figure 5 shown.

[0090] Steps S4-S6, perform molecular simulation in lammps to obtain mixed phase simulation results, which specifically include two aspects:

[0091] For the "CO2-shale oil-kerogen" system, the CVFF force field is used to describe the interaction force of kerogen, the TraPPE force field is used for CO2, and the TraPPE-UA force field is used for n-decane. The Lorentz-Berthelot mixing rule is used for calculation. i Class and j The cross-interactions between atoms are simulated in LAMMPS.

[0092] The simulation calculation process is as follows: first, initialize the parameters, read the model file, assign force field parameters and group them; fix the kerogen atoms, minimize the energy of the initial model, remove atomic overlap and other situations, and obtain the energy-optimized model; set the simulation step size to 1.0fs, the cutoff radius to 10.0Å, the initial temperature to 343K, the temperature control method uses the Nose-Hoover heat bath method, the pressure is controlled by the number of hydrogen molecules input into the model, and periodic boundaries are used in the x, y and z directions; first, the NVT ensemble is used only for n-decane, and a 1ns equilibrium relaxation simulation is performed in a fixed area to obtain the shale oil distribution state under real conditions; finally, the NVT ensemble is set for the entire system, and the same settings are used to perform a 5ns molecular simulation to obtain the molecular simulation results of the miscible process of carbon dioxide and n-decane under the kerogen wall, as well as the interaction energy between carbon dioxide and n-decane during the simulation process.

[0093] For the "CO2-shale oil" system, the TraPPE force field is used for CO2, the TraPPE-UA force field is used for n-decane, and the Lorentz-Berthelot mixing rule is used for calculation. i Class and j The cross-interactions between atoms are simulated in LAMMPS.

[0094] The simulation calculation process is as follows: first, the parameters are initialized, the model file is read, the force field parameters are assigned and grouped, and the energy of the initial model is minimized, atomic overlap and other situations are removed to obtain the energy-optimized model; the simulation step size is set to 1.0fs, the cutoff radius is 10.0Å, the initial temperature is given to 343K, the temperature control method adopts the Nose-Hoover heat bath method, the pressure is controlled by the number of hydrogen molecules input into the model, and periodic boundaries are used in the x, y and z directions; the NVT ensemble is set for the entire system, and a 5ns molecular simulation is performed to obtain the molecular simulation results of the miscible process of carbon dioxide and n-decane under bulk conditions, as well as the interaction energy between carbon dioxide and n-decane during the simulation process, such as Figure 6-Figure 7 shown.

[0095] S7, calculating the minimum miscible pressure according to the simulation results, specifically comprising:

[0096] Under the conditions of nanopores and bulk phase, for different pressures (5MPa, 7MPa, 9MPa, 11MPa, 13MPa), when the system reaches a stable state, the average value of the interaction energy is calculated to obtain the representative interaction energy, such as Figure 8 Then, the average value of the interaction energy under nanopore conditions and the average value of the interaction energy under bulk conditions are calculated to obtain the interaction energy difference ΔE ;

[0097] For the obtained interaction energy difference Δ E The data is first processed using the Lagrange interpolation function so that the discrete data points can be expressed continuously within the pressure range through the function. Then, Gaussian fitting is used to minimize the square sum of the errors between the actual data points and the predicted values ​​of the Gaussian function, and the optimal Gaussian function parameters are determined to be as close as possible to the interpolated data points, thereby obtaining multiple values ​​that can accurately characterize the interaction energy difference Δ E The discrete points of the relationship between the pressure P and the change in the interaction energy difference are obtained, and the curve expressing the relationship between the interaction energy difference and the pressure is obtained, such as Figure 8 .

[0098] For the discrete points obtained above, a first-order difference operation is used to obtain The relationship curve of the first-order central difference formula is:

[0099]

[0100] By calculating the first-order difference of each discrete point, we can generate The relationship curve with pressure change, such as Fig. 9 shown.

[0101] In this curve, the pressure corresponding to the maximum point of the first-order derivative is the minimum miscibility pressure of carbon dioxide and shale oil under the nanoconfinement effect. This is because the interaction energy between carbon dioxide and shale oil changes most significantly near the minimum miscibility pressure, which is reflected in the difference in interaction energy Δ E That is, its rate of change is the largest. The calculated minimum miscibility pressure between carbon dioxide and shale oil (n-decane) in the 5nm kerogen pores is 7.90MPa, which is consistent with the existing research results.

Claims

1. A method for evaluating the minimum miscibility pressure of carbon dioxide and shale oil under confinement effect, characterized in that: include: Steps to build a molecular model; Select force field parameters to describe the steps of intermolecular and intramolecular interaction forces; Divide the simulation area and the boundary condition steps; Determine simulation parameters and calculation parameters, and perform molecular simulation steps on the molecular model; And according to the interaction energy, the minimum miscible pressure step is calculated, which specifically includes: The interaction energy between carbon dioxide and shale oil under nanopore conditions and bulk conditions is calculated respectively, and the difference between the interaction energy under nanopore conditions and the interaction energy under bulk conditions is calculated to obtain the difference in interaction energy Δ E ; For the interaction energy difference Δ E The data is first processed using an interpolation function so that the discrete data points can be expressed continuously within the pressure range through the function. Then, Gaussian fitting is used to minimize the square sum of the errors between the actual data points and the predicted values ​​of the Gaussian function to determine the optimal Gaussian function parameters to fit the interpolated data points, thereby obtaining multiple values ​​that can accurately characterize the interaction energy difference Δ E Discrete points in relation to pressure P changes; For the above discrete points, a first-order central difference operation is used to obtain The relationship curve with pressure change; in this curve, the pressure corresponding to the maximum point of the first-order derivative is the minimum miscibility pressure of carbon dioxide and shale oil under the nanoconfinement effect.

2. The method for evaluating the minimum miscibility pressure of carbon dioxide and shale oil under the confinement effect according to claim 1, characterized in that: Under the conditions of nanopores and bulk phase, the interaction energy under different pressures and when the system reaches a stable state is calculated respectively, and the interaction energy under nanopore conditions and the interaction energy under bulk phase conditions are obtained; The criterion for reaching a stable state is that the fluctuation amplitude of the system energy is extremely small and tends to be stable during the continuous simulation time.

3. The method for evaluating the minimum miscibility pressure of carbon dioxide and shale oil under the confinement effect according to claim 1, characterized in that: The first-order central difference formula is: ， in, P i is a specific pressure point, Δ E i+1 , Δ E i-1 Adjacent pressure points P i+1 and P i-1 The corresponding interaction energy difference is generated by performing this operation for each discrete point The relationship curve with pressure change.

4. The method for evaluating the minimum miscibility pressure of carbon dioxide and shale oil under the confinement effect according to claim 1, characterized in that: The steps of building a molecular model include: Construct models of carbon dioxide molecules, oil molecules, and porous rock minerals respectively; According to reservoir conditions and throughput pressure, a molecular model of CO2-shale oil-porous rock formation CO2 throughput shale oil under confinement effect is constructed; According to the molecular model of carbon dioxide-shale oil-porous rock formation, the pore wall was deleted and a two-phase molecular model of carbon dioxide-oil was constructed under the same conditions.

5. The method for evaluating the minimum miscibility pressure of carbon dioxide and shale oil under the confinement effect according to claim 4, characterized in that: Porous rock mineral models include graphene model, kerogen model, montmorillonite model and quartz model.

6. The method for evaluating the minimum miscibility pressure of carbon dioxide and shale oil under the confinement effect according to claim 4, characterized in that: Packmol software was used to construct a molecular model of carbon dioxide injection into shale oil, including: Graphene is selected as an organic mineral to construct a single-layer or multi-layer graphene wall and graphene nanopores; kerogen molecules are selected as organic minerals to construct kerogen nanopores; montmorillonite crystals are selected as clay minerals to construct montmorillonite nanopores; quartz crystals are selected as siliceous minerals to construct quartz nanopores; The pore wall is composed according to the pore rock mineral model. Oil molecules are filled in the center of the pore and different numbers of carbon dioxide molecules are filled on both sides to obtain a carbon dioxide intake and exhalation shale oil molecular model.

7. The method for evaluating the minimum miscibility pressure of carbon dioxide and shale oil under the confinement effect according to claim 1, characterized in that: The steps for selecting force field parameters and describing the interaction forces between molecules and within molecules include: TraPPE force field and TraPPE-UA force field are used to describe the interaction between carbon dioxide molecules and oil molecules. CVFF force field is used for graphene crystals and kerogen molecules, and CLAYFF force field is used for montmorillonite crystals and quartz crystals. The LJ potential function is used to describe the interaction forces between different atoms in the system; the cross-interaction terms between different molecules are calculated using the Lorentz-Berthelot mixing rule.

8. The method for evaluating the minimum miscibility pressure of carbon dioxide and shale oil under the confinement effect according to claim 7, characterized in that: The LJ potential function is used to describe the interaction force between different atoms in the system, which is given by equation (1): in, yes i Class and j The distance between atoms, is the potential well depth of the Lennard-Jones potential, which characterizes the strength of the interaction between atoms. is the distance at which the interaction energy between two particles is minimal.

9. The method for evaluating the minimum miscibility pressure of carbon dioxide and shale oil under the confinement effect according to claim 7, characterized in that: The cross-interaction terms between different molecules are calculated using the Lorentz-Berthelot mixing rule, expressed by equations (2) and (3): The long-range Coulomb force between atoms is expressed by equation (4): In the formula, , They are i Class and j The charge of the atom-like substance; is the dielectric constant of vacuum.

10. The method for evaluating the minimum miscibility pressure of carbon dioxide and shale oil under the confinement effect according to claim 1, characterized in that: Determine the simulation parameters and calculation parameters, and perform molecular simulation on the molecular model in the following steps: The simulation system was set to use the NVT ensemble, the Nose-Hover heat bath method was used to control the temperature, and the number of carbon dioxide molecules was used to control the pressure; the simulation time step was 1.0fs, the cutoff radius was 10.0Å, the initial temperatures were 343K and 363K, and the pressures were 5MPa, 7MPa, 9MPa, 11MPa, and 13MPa, respectively; and the calculation settings for the interaction energy were performed; The LAMMPS software was used to simulate the three-phase molecular model of carbon dioxide, shale oil and porous rock formations. First, only the oil molecules in the pores were added to the ensemble for 5 ns of relaxation equilibrium to obtain the shale oil distribution model under the real state. Then, the whole model was simulated and calculated for 5 ns to obtain the simulation results of carbon dioxide intake and exhalation of shale oil molecules under the confinement effect, as well as the interaction energy between carbon dioxide and shale oil. LAMMPS software was used to simulate the CO2-shale oil two-phase molecules. The entire model was simulated for 5 ns to obtain the molecular simulation results of CO2 intake and output of shale oil under bulk conditions, as well as the interaction energy between CO2 and shale oil.

Images