A method, system and device for evaluating the performance of a displacing agent in a multiple composite oil displacement

Abstract

The present invention discloses a method, system and device for evaluating the performance of a displacement agent in a multi-component composite flooding, which relates to the technical field of displacement performance research, and includes the steps of: constructing a surfactant A model, a surfactant B model, an alkali molecule model, a water model and an oil model, and fusing the water model and the oil model to obtain an oil-water model; establishing an AC box, adjusting the positions of the oil-water model, the alkali molecule model, the surfactant A model and the surfactant B model in the AC box to obtain a multi-component composite flooding model of the surfactant; calculating thermodynamic parameters according to the results of molecular dynamics simulation, and evaluating the displacement performance and diffusion ability of the displacement agent in the multi-component composite flooding model through the thermodynamic parameters. The present invention reveals the interaction mechanism between different types of surfactant molecules, water molecules, oil molecules and alkali molecules from the molecular level, analyzes the influence of different types of surfactants on the sensitivity of the displacement rate, reservoir temperature and pressure, and obtains a good displacement effect.

Description

Technical Field

[0001] The present invention relates to the technical field of oil displacement performance research, and in particular to a method, system and equipment for evaluating the performance of an oil displacement agent in a multi-component composite oil displacement. Background Art

[0002] Chemical flooding is considered to be the most promising oil recovery technology. Chemical flooding refers to adding special reagents to the displacement fluid. The added special reagents can significantly change the physical properties of the displacement fluid and the properties of the oil / water interface of the displacement, thereby effectively increasing the recovery. Studies have found that chemical composite flooding technology, especially multi-component composite flooding, can more effectively improve the recovery rate of crude oil and is widely used in tertiary oil recovery. Surfactants are a type of reagent commonly used in chemical multi-component flooding. They can change the emulsification of crude oil and the wettability of the rock surface in the reservoir, which is conducive to the desorption of oil from the rock surface and dispersion into the displacement fluid, thereby effectively improving the recovery rate of crude oil. Experiments have shown that surfactants have strong selectivity, and the same surfactant cannot be applied to all oil reservoir exploitation. Therefore, surfactants need to be selected according to specific exploitation conditions. Macroscopic experimental research on multi-component flooding is underway, but there are many problems.

[0003] In the traditional experimental simulation of multi-component composite drive, the injection loss of surfactant in the system is about 80%. The greater the injection loss, the less likely the displacement system can maintain ultra-low interfacial tension, resulting in low oil displacement efficiency. In traditional experiments, whether it is the adsorption loss of surfactants or the viscosity loss of alkali, the amount of chemical agents used will increase. This experimental cost is very high, and only the macroscopic level is studied without involving microscopic mechanism research. In conventional macroscopic experiments, due to the complex environment of high temperature and high pressure in the reservoir, the oil displacement agent loss is large, and the application of multi-component composite drive is very limited.

[0004] It can be seen that most of the existing technologies are studied from a macroscopic level, and the few microscopic studies only establish one type of oil displacement agent in the system. In traditional experiments, whether it is the adsorption loss of surfactants or the viscosity loss of alkali, the amount of chemical agents will be increased. This situation requires a large amount of surfactant consumables, and it is difficult to observe obvious oil displacement effects. There are also experimental risks of high temperature and high pressure, and environmental pollution. In the research of microscopic oil displacement systems, there are problems of singleness and poor evaluation results. Summary of the invention

[0005] The purpose of the present invention is to address the deficiencies of the above-mentioned prior art and to provide a method, system and equipment for evaluating the performance of oil-displacing agents in multi-component composite oil displacement, so as to solve the problems in the prior art that a large amount of surfactant consumables are required, it is difficult to observe obvious oil displacement effects, there are experimental risks of high temperature and high pressure, and environmental pollution is caused, and there is a single problem and poor evaluation results in the research of microscopic oil displacement systems.

[0006] The present invention specifically provides the following technical solution: a method for evaluating the performance of an oil displacement agent in a multi-component composite oil displacement, comprising the following steps:

[0007] Constructing a surfactant A model, a surfactant B model, an alkali molecule model, a water model and an oil model, and fusing the water model and the oil model to obtain an oil-water model; wherein the surfactant A model and the surfactant B model use two different types of surfactants;

[0008] Establish a system AC box for multi-component composite simulation calculations at different temperatures, adjust the spatial positions of the oil-water model, the alkali molecule model, the surfactant A model and the surfactant B model, and construct a mixed model through the surfactant A model, the surfactant B model and the alkali molecule model;

[0009] The AC box is divided into three local boxes, and a water model, a mixed model, and an oil-water model are placed in sequence according to their positions, and the structure inside the AC box is optimized to obtain a multi-component composite oil displacement model of surfactants;

[0010] Setting a convergence standard for energy minimization for the multi-component composite flooding model, performing molecular dynamics simulation based on the convergence standard, and obtaining simulation results including molecular dynamics motion state, radial distribution function, relative concentration distribution, mean square displacement and energy;

[0011] Thermodynamic parameters were calculated based on the simulation results, and the oil displacement performance and diffusion capacity of the oil displacement agent in the multi-component composite oil displacement model were evaluated by thermodynamic parameters.

[0012] Preferably, the construction of the surfactant model, the alkali molecule model, the water model and the oil model comprises the following steps:

[0013] Constructing the geometric structures of surfactant molecules, alkali molecules, water molecules and oil molecules, and constructing molecular models of the surfactant molecules, alkali molecules, water molecules and oil molecules according to component ratio, atomic structure, chemical bond type and group type, and saving them as trajectory files in .XSD format;

[0014] Build multiple , select surfactant molecules, alkali molecules, water molecules and oil molecules, construct 15 surfactant A molecules, 10 surfactant B molecules, 10 alkali molecules, 500 water molecules and 50 oil molecules respectively, and then add them into the empty box, use the SMART algorithm for structure optimization, set the convergence standard, number of steps, temperature and pressure, and then perform NVT system simulation for a certain length of time to obtain surfactant A model, surfactant B model, alkali molecule model, water model and oil model.

[0015] Preferably, the water model and the oil model are merged to obtain the oil-water model, comprising the following steps:

[0016] Build Box;

[0017] The oil model and the water model are copied to the In the box, adjust the structural position to obtain the oil-water model.

[0018] Preferably, the construction of multiple When the box is placed in the container, the COMPASS force field is applied and the temperature and energy distribution are calculated.

[0019] Preferably, a convergence criterion for energy minimization is set for the multi-component composite oil displacement model, and molecular dynamics simulation is performed based on the convergence criterion, comprising the following steps:

[0020] A convergence standard of 0.001 kcal / mol is set for the multi-component composite oil displacement model, and a kinetic calculation of the NPT system is performed for at least 100 ns;

[0021] In the dynamic calculation, the temperature was set to 300K, the pressure was set to 0.1GPa, and the step size was set to 1fs; the pressure coupling mode was set to Berendsen pressure coupling, and the pressure coupling mode was set to 1ps;

[0022] The NPT system is isothermal compressed, and periodic boundary conditions are set in the X and Y directions, while the Z direction remains unchanged. The cutoff radii of the two forms of intermolecular forces, Van Der Waals and Lennard-Jones potential, are set to The initial atomic velocities were determined by the Maxwell-Boltzmann distribution, and the motion trajectories were statistically integrated using the Verlet algorithm.

[0023] Preferably, the kinetic calculation of the NPT system for at least 100 ns further comprises the following steps:

[0024] In the dynamic calculation, the temperature is set to 300K and the step size is 1fs; the pressure coupling mode is set to Berendsen pressure coupling and 1ps pressure coupling mode;

[0025] The ensemble is the NVT ensemble, and periodic boundary conditions are set in the X, Y, and Z directions; the cutoff radius of the Van Der Waals and Lennard-Jones potentials is set The initial atomic velocities are determined by the Maxwell-Boltzmann distribution, and the motion trajectories are statistically integrated using the Verlet algorithm.

[0026] Preferably, the obtaining of simulation results including molecular dynamics motion state, radial distribution function, relative concentration distribution, mean square displacement and energy comprises the following steps:

[0027] The MSD module in Forcite analysis is used to obtain the mean square displacement curve in the multi-component composite oil displacement model, and the kinetic motion state of the alkali molecules and the surfactant A molecules and the surfactant B molecules is analyzed through the mean square displacement curve;

[0028] The Forcite analysis module is used to obtain the relative concentration distribution curve of surfactants at the oil-water interface in the multi-component composite flooding model, and the microscopic movement of surfactant molecules is obtained through the change of relative concentration distribution;

[0029] The interaction of surfactant / base with other components of the system is analyzed by radial distribution function to obtain the atomic distribution around a specified atom.

[0030] Preferably, when evaluating the oil displacement performance and diffusion capacity of the oil displacement agent in the multi-component composite oil displacement model by thermodynamic parameters, the oil-water interface is also evaluated by the interface formation energy of the oil-water interface, and the specific expression is:

[0031]

[0032] Where: E total represents the total energy of the system, E blank represents the energy of the blank system without surfactant, E single represents the system energy containing a single surfactant molecule, n represents the number of surfactant molecules in the entire system, and IFE is the evaluation matrix.

[0033] The present invention provides a system for evaluating the performance of an oil displacement agent in a multi-component composite oil displacement, comprising:

[0034] An initial model building module is used to build a surfactant A model, a surfactant B model, an alkali molecule model, a water model and an oil model, and fuse the water model and the oil model to obtain an oil-water model; wherein the surfactant A model and the surfactant B model use two different types of surfactants;

[0035] The adjustment module is used to establish a system AC box for multi-component composite simulation calculations at different temperatures, adjust the spatial positions of the oil-water model, the alkali molecule model, the surfactant A model and the surfactant B model, and construct a mixed model through the surfactant A model, the surfactant B model and the alkali molecule model;

[0036] A composite model building module is used to divide the AC box into three local boxes, place a water model, a mixed model, and an oil-water model in sequence according to their positions, optimize the structure inside the AC box, and obtain a multi-component composite oil displacement model of surfactants;

[0037] A simulation module, used for setting a convergence standard for energy minimization for the multi-component composite flooding model, performing molecular dynamics simulation based on the convergence standard, and obtaining simulation results including molecular dynamics motion state, radial distribution function, relative concentration distribution, mean square displacement and energy;

[0038] The evaluation module is used to calculate thermodynamic parameters based on simulation results and evaluate the oil displacement performance and diffusion capacity of the oil displacement agent in the multi-component composite oil displacement model through thermodynamic parameters.

[0039] The present invention provides a computer device, comprising a memory and a processor, wherein a program is stored in the memory, and when the program is executed by the processor, the processor executes the steps of a method for evaluating the performance of an oil displacement agent in a multi-component composite oil displacement.

[0040] Compared with the prior art, the present invention has the following significant advantages:

[0041] The present invention constructs models of multiple types of surfactant molecules, water molecules, oil molecules and alkali molecules, and obtains an oil-water model by fusing the water model and the oil model. The relationship between the surfactant / alkali and other components of the system is adjusted by establishing a system AC box for multivariate composite simulation calculation at different temperatures to construct a multivariate composite oil displacement model, thereby providing a basis for multivariate analysis and greatly reducing the consumables of the surfactant. At the same time, by setting an energy minimization convergence standard for the multivariate composite oil displacement model, molecular dynamics motion states, radial distribution functions, relative concentration distributions, mean square displacements and energy simulation results are obtained through molecular dynamics simulation, the effects of different types of surfactants on the oil displacement effects of various materials are analyzed, the purpose of revealing the microscopic mechanism of multivariate composite oil displacement under the synergistic action of multiple oil displacement agents is revealed, a multivariate composite flooding visualization result is provided, and a better oil displacement effect is obtained. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Figure 1 It is a schematic diagram of an embodiment of the present invention;

[0043] Figure 2 It is the oil molecule structure diagram of the present invention;

[0044] Figure 3 is a diagram of the water molecule structure of the present invention;

[0045] Figure 4 is a structural diagram of anionic surfactant A of the present invention;

[0046] Figure 5is a structural diagram of a cationic surfactant B of the present invention;

[0047] Figure 6 is a diagram of the molecular structure of the base of the present invention;

[0048] Figure 7 It is the oil-water structure diagram of the present invention;

[0049] Figure 8 This is a structural diagram of the surfactant-alkali multicomponent composite oil displacement model of the present invention;

[0050] Fig. 9 is the structural optimization energy convergence diagram of the present invention;

[0051] Fig.10 is a mean square displacement curve diagram of the multi-component composite oil displacement system of the present invention;

[0052] Fig.11 It is a radial distribution function curve diagram of the multi-component composite oil displacement system of the present invention;

[0053] Fig.12 It is a relative concentration distribution curve diagram of the multi-component composite oil displacement system of the present invention. DETAILED DESCRIPTION

[0054] The following is a clear and complete description of the technical solutions of the embodiments of the present invention in conjunction with the drawings in the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0055] The embodiments of the present invention are as follows Figure 1 As shown; the embodiment of the present invention provides a method for evaluating the performance of an oil displacement agent in a multi-component composite oil displacement, comprising the following steps:

[0056] Step S1: constructing a surfactant A model, a surfactant B model, an alkali molecule model, a water model and an oil model, and fusing the water model with the oil model to obtain an oil-water model.

[0057] In this step, constructing a surfactant A model, a surfactant B model, an alkali molecule model, a water model and an oil model includes the following steps:

[0058] The geometric structures of surfactant molecules, alkali molecules, water molecules and oil molecules are constructed, and the molecular models of surfactant molecules, alkali molecules, water molecules and oil molecules are constructed according to the component ratio, atomic structure, chemical bond type and group type, and saved as trajectory files in .XSD format. The surfactant A model and the surfactant B model use two different types of surfactants.

[0059] Build multiple In the empty box, select surfactant molecules, alkali molecules, water molecules and oil molecules, respectively construct 15 surfactant A molecules, 10 surfactant B molecules, 10 alkali molecules, 500 water molecules and 50 oil molecules and add them to the empty box, use the SMART algorithm for structural optimization, set the convergence standard, number of steps, temperature and pressure, and perform NVT system simulation for a certain length of time to obtain surfactant A model, surfactant B model, alkali molecule model, water model and oil model. Construct multiple When the box is placed in the container, the COMPASS force field is applied and the temperature and energy distribution are calculated.

[0060] In this step, the water model and the oil model are fused to obtain the oil-water model, which includes the following steps:

[0061] Build box; copy the oil model and water model to In the box, optimize the structural position and obtain the oil-water model.

[0062] The specific construction model is as follows:

[0063] (1) Establishing oil molecule model:

[0064] In the molecular dynamics software, construct box, select the oil molecule as n-octadecane C 18 H 38 , add the oil molecules, and then use the Amorphous Cell Calculation module to build 50 oil molecules. Select Construction for the Task option, Medium for the Quality option, C OMPASS for the force field, Ewald for the Electrostatic option, and Atom based for Van der Waals. Use the Forcite module to optimize the structure of the oil molecules using the SMART algorithm, set the convergence standard to 0.001 kcal / mol, the number of steps to 5000, the temperature to 300 K, and the pressure to 0.1 GPa. Then perform a 100 ns NVT system simulation. After completion, the oil molecule model is obtained. The oil molecule model is as follows: Figure 2 shown.

[0065] The hydrocarbons in operation (1) include alkanes; and the alkanes include n-octadecane.

[0066] (2) Establish a water molecule model:

[0067] In the molecular dynamics software, construct box, construct a single water molecule model, the chemical formula of water molecule is H2 O. Then use the Amorphous Cell Calculation module to build 500 water molecules. Select Construction for Task, Medium for Quality, C OMPASS for Force Field, Ewald for Electrostatic, and Atom based for Van der Waals. Use the Forcite module to optimize the structure of water molecules using the SMART algorithm. Set the convergence standard to 0.001 kcal / mol, the number of steps to 5000, the temperature to 300 K, and the pressure to 0.1 GPa. Then perform a 100 ns NVT system simulation. After completion, the water molecule model is as follows: Figure 3 shown.

[0068] (3) Establishing surfactant model:

[0069] In the molecular dynamics software, construct box, construct surfactant molecules, and select the anionic surfactant sodium dodecyl sulfate for oil recovery, with the chemical formula C 12 H 25 SO 4 Na, as surfactant A, and cationic surfactant hexadecyltrimethylammonium bromide, chemical formula C 19 H 42 N Br, as surfactant B. Add surfactant molecules to the empty box, and then use the Amorphous Cell Calculation module to build 15 surfactant A molecules and surfactant B molecules, a total of 25 surfactant molecules, select Construction for the Task option, Medium for the Quality option, COMPASS for the force field, Ewald for the Electrostatic option, and Atombased for Van der Waals. Use the Forcite module and then use the SMART algorithm for structural optimization, set the convergence standard to 0.001 kcal / mol, the number of steps to 5000 steps, set the temperature to 300K, and the pressure to 0.1 GPa, then perform a 100 ns NVT system simulation, and after completion, obtain the surfactant model. The surfactant model is as follows Figure 4 and Figure 5 shown.

[0070] The surfactants in operation (3) are sodium dodecylbenzenesulfonate and hexadecyltrimethylammonium bromide.

[0071] (4) Construction of alkali model:

[0072] In the molecular dynamics software, construct box, construct a base molecule with the molecular formula of NaOH, add the base molecule to the empty box, and then use the Amorphous Cell Calculation module to construct 10 base molecules. Select Construction for the Task option, Medium for the Quality option, COMPASS for the force field, Ewald for the Electrostatic option, and Atom bas ed for Van der Waals. Use the Forcite module and then use the SMART algorithm for structural optimization, set the convergence standard to 0.001 kcal / mol, the number of steps to 5000, the temperature to 300K, and the pressure to 0.1 GPa, and then perform a 100 ns NVT system simulation. After completion, the base model is obtained. The base model is as follows Figure 6 shown.

[0073] (5) Constructing oil-water model:

[0074] In the molecular dynamics software, first build A new empty 3D atomic file is created. The oil model and water model constructed in steps 1 and 2 are copied to the constructed empty box in sequence. The structural position is optimized to obtain the oil-water model. The oil-water model is as follows: Figure 7 shown.

[0075] Step S2: Establish a system AC box for multi-component composite simulation calculations at different temperatures, adjust the spatial positions of the oil-water model, the alkali molecule model, the surfactant A model and the surfactant B model, and construct a mixed model through the surfactant A model, the surfactant B model and the alkali molecule model.

[0076] Step S3: Divide the AC box into three local boxes, place the water model, the mixed model, and the oil-water model in sequence, optimize the structure inside the AC box, and obtain a multi-component composite oil displacement model of surfactants.

[0077] Step S2 and step S3 are specifically as follows:

[0078] (6) Constructing a multi-component composite oil displacement model:

[0079] On the basis of step 5, surfactant molecule model and alkali molecule model are added, and the spatial position of oil-water model and surfactant model is adjusted. The box is divided into three local small boxes. The whole system has three layers. Layer 1 is water box, Layer 2 is surfactant A+surfactant B+alkali, and Layer 3 is oil box. The position is adjusted and the structure is optimized to obtain surfactant multi-composite oil displacement model. The final multi-composite oil displacement model is as follows: Figure 8 shown.

[0080] Step S4: setting a convergence standard for energy minimization for the multi-component composite flooding model, performing molecular dynamics simulation based on the convergence standard, and obtaining simulation results including molecular dynamics motion state, radial distribution function, relative concentration distribution, mean square displacement and energy.

[0081] In this step, the convergence standard of energy minimization is set for the multi-component composite flooding model, and the molecular dynamics simulation is performed based on the convergence standard, including the following steps:

[0082] A convergence standard of 0.001 kcal / mol was set for the multi-component composite flooding model, and the kinetic calculation of the N PT system was performed for at least 100 ns.

[0083] In the dynamic calculation, the temperature is set to 300K, the pressure is set to 0.1GPa, and the step size is set to 1fs; the pressure coupling mode is set to Berendsen pressure coupling and 1ps pressure coupling mode. In the isothermal compression of the NPT system, periodic boundary conditions are set in the X and Y directions, and the Z direction remains unchanged; the cutoff radius of the two forms of intermolecular forces, Van Der Waals and Lennard-Jones potential, is set to The initial atomic velocities were determined by the Maxwell-Boltzmann distribution, and the motion trajectories were statistically integrated using the Verlet algorithm.

[0084] Oil displacement performance evaluation:

[0085] By studying the distribution and motion characteristics of surfactant molecules in a simulated multi-component composite system under equilibrium configuration, the performance of multi-component surfactant flooding in a composite system was evaluated using performance evaluation parameters such as radial distribution function, relative concentration distribution, mean square displacement, and energy.

[0086] The molecular model and structural model established in the present invention have passed energy optimization, which makes the structure reasonable and the simulation results more accurate. The structural optimization convergence diagram is shown in Fig. 9 shown.

[0087] In this step, the simulation results including molecular dynamics motion state, radial distribution function, relative concentration distribution, mean square displacement and energy are obtained, including the following steps:

[0088] The present invention can analyze the interaction between surfactant A / surfactant B / alkali molecules and groups and oil-water molecules, and use the MSD (Mean Square Displacement) module in Forcite analysis. After the simulation, this module is used to select molecules to obtain simulation results, that is, to obtain the mean square displacement curve in the multi-component composite oil displacement model. The mean square displacement curve reflects the curve of molecular flow ability, and the slope reflects the speed of molecular flow ability. The dynamic motion state of the alkali molecule and the anionic surfactant molecule and the cationic surfactant molecule is analyzed by the mean square displacement curve. The mean square displacement refers to the measure of the deviation of the position of the particle after moving over time relative to the reference position. The slope of the mean square displacement curve represents the flow ability of the molecule. The larger the slope of the curve, the stronger the flowability of the molecule and the faster the diffusion. After the alkali and the two types of surfactants are compounded, it is found that the diffusion ability of the anionic surfactant is stronger than that of the cationic surfactant. Compared with the macroscopic experiment, this part provides the flow of each molecule in the oil displacement system during the oil displacement process, reflects the diffusion ability of the oil displacement agent from a microscopic level, and can screen surfactants with strong oil displacement ability through this index, which is difficult to achieve in conventional macroscopic experiments. The mean square displacement curve of the multi-component composite system is as follows: Fig.10 shown.

[0089] According to the trajectory file of the surfactant molecules in the equilibrium configuration of the simulation system, the Forcite analysis module is used to obtain the relative concentration distribution curve of the surfactant at the oil-water interface in the multi-component composite flooding model, and the microscopic movement of the surfactant molecules is obtained through the change of the relative concentration distribution. The relative concentration distribution can quantitatively characterize the distribution and morphological changes of the adsorption of surfactants on the system. It reflects the change of relative particle concentration in the spatial region with position within a given time. Relative concentration is another important structural indicator for evaluating the molecular distribution level by calculating the ratio of the density of molecules in a small unit volume to the density of the entire system. This indicator reflects the dynamic changes of anionic and cationic surfactants and alkali concentrations during the flooding process. When multi-component composite flooding is applied on site, the adsorption loss of surfactants is large, the economic loss is large, and it is difficult to record the optimal concentration of surfactant flooding in each geological block in time. The relative concentration distribution realizes the concentration monitoring of the entire flooding process from a microscopic level. Compared with macroscopic experiments, this evaluation method saves a lot of economic costs. The relative concentration distribution curve is as follows Fig.12 shown.

[0090] The present invention can analyze the movement of a certain component under the multi-component composite oil recovery model, and analyze the interaction between the surfactant / base and other components of the system through the radial distribution function. The radial distribution function can reflect the atomic distribution around the specified atom. This indicator can reflect the interaction ability between the surfactant molecules and the oil and water molecules during the oil recovery process, that is, the aggregation, disturbance, collision, diffusion, adsorption movement and other behaviors between the molecules of each phase. The stronger the interaction force, the stronger the oil recovery potential. The radial distribution function reflects the movement of molecules at the microscopic level. This part makes up for the limitations of macroscopic research and provides microscopic guidance for the on-site application of surfactants. The radial function distribution curve is as follows: Fig.11 shown.

[0091] Step S5: Calculate thermodynamic parameters according to the simulation results, and evaluate the oil displacement performance and diffusion capacity of the oil displacement agent in the multi-component composite oil displacement model by using the thermodynamic parameters.

[0092] In this step, when evaluating the oil displacement performance and diffusion capacity of the oil displacement agent in the multi-component composite oil displacement model by thermodynamic parameters, the oil-water interface is also evaluated by the interface formation energy of the oil-water interface. The specific expression is:

[0093]

[0094] Where: E total represents the total energy of the system, E blank represents the energy of the blank system without surfactant, E single represents the system energy containing a single surfactant molecule, n represents the number of surfactant molecules in the entire system, and IFE is the evaluation matrix.

[0095] Based on the above methods and statements, the present invention provides a system for evaluating the performance of oil displacement agents in multi-component composite oil displacement, comprising: an initial model building module, an adjustment module, a composite model building module, a simulation module and an evaluation module.

[0096] Among them, the initial model construction module is used to construct a surfactant model, an alkali molecule model, a water model and an oil model, and fuse the water model and the oil model to obtain an oil-water model; wherein the surfactant A model and the surfactant B model use two different types of surfactants; the adjustment module is used to establish a system AC box for multi-component composite simulation calculations at different temperatures, adjust the spatial positions of the oil-water model, the alkali molecule model and the surfactant model, and construct a mixed model through the surfactant A model, the surfactant B model and the alkali molecule model; the composite model construction module is used to divide the AC box into three local boxes, place the water model, the mixed model, and the oil model in sequence according to the position, optimize the structure of the AC box, and obtain a multi-component composite oil displacement model of surfactants; the simulation module is used to set the convergence standard of energy minimization for the multi-component composite oil displacement model, perform molecular dynamics simulation based on the convergence standard, and obtain simulation results including molecular dynamics motion state, radial distribution function, relative concentration distribution, mean square displacement and energy; the evaluation module is used to calculate thermodynamic parameters according to the simulation results, and evaluate the oil displacement performance and diffusion capacity of the oil displacement agent in the multi-component composite oil displacement model through thermodynamic parameters.

[0097] The present invention also provides a computer device, including a memory and a processor. The memory stores a program. When the program is executed by the processor, the processor executes the steps of a method for evaluating the performance of an oil displacement agent in a multi-component composite oil displacement.

[0098] The above content is a further detailed description of the present invention in combination with a specific preferred embodiment. For technicians in the technical field to which the present invention belongs, several simple deductions or substitutions can be made without departing from the concept of the present invention, which should be regarded as belonging to the protection scope of the present invention.

Claims

1. A method for evaluating the performance of an oil displacement agent in a multi-component composite oil displacement, characterized in that: The steps include: Constructing a surfactant A model, a surfactant B model, an alkali molecule model, a water model and an oil model, and fusing the water model and the oil model to obtain an oil-water model; wherein the surfactant A model and the surfactant B model use two different types of surfactants; Establish a system AC box for multi-component composite simulation calculations at different temperatures, adjust the spatial positions of the oil-water model, the alkali molecule model, the surfactant A model and the surfactant B model, and construct a mixed model through the surfactant A model, the surfactant B model and the alkali molecule model; The AC box is divided into three local boxes, and a water model, a mixed model, and an oil-water model are placed in sequence according to their positions, and the structure inside the AC box is optimized to obtain a multi-component composite oil displacement model of surfactants; Setting a convergence standard for energy minimization for the multi-component composite flooding model, performing molecular dynamics simulation based on the convergence standard, and obtaining simulation results including molecular dynamics motion state, radial distribution function, relative concentration distribution, mean square displacement and energy; Calculate thermodynamic parameters based on simulation results, and evaluate the oil displacement performance and diffusion capacity of the oil displacement agent in the multi-component composite oil displacement model through thermodynamic parameters; The construction of the surfactant A model, the surfactant B model, the alkali molecule model, the water model and the oil model comprises the following steps: Constructing the geometric structures of surfactant molecules, alkali molecules, water molecules and oil molecules, and constructing molecular models of the surfactant molecules, alkali molecules, water molecules and oil molecules according to component ratio, atomic structure, chemical bond type and group type, and saving them as trajectory files in .XSD format; Build multiple box, select surfactant molecules, alkali molecules, water molecules and oil molecules, construct 15 surfactant A molecules, 10 surfactant B molecules, 10 alkali molecules, 500 water molecules and 50 oil molecules respectively, and then add them into the empty box, use the SMART algorithm for structure optimization, set the convergence standard, number of steps, temperature and pressure, and then perform NVT system simulation for a certain length of time to obtain surfactant model, alkali molecule model, water model and oil model.

2. The method for evaluating the performance of an oil displacement agent in a multi-component composite oil displacement as claimed in claim 1, characterized in that: The water model and the oil model are merged to obtain an oil-water model, comprising the following steps: Build Box; The oil model and the water model are copied to the In the box, adjust the structural position to obtain the oil-water model.

3. The method for evaluating the performance of an oil displacement agent in a multi-component composite oil displacement as claimed in claim 1, characterized in that: The construction of multiple When the box is placed in the container, the COMPASS force field is applied and the temperature and energy distribution are calculated.

4. The method for evaluating the performance of an oil displacement agent in a multi-component composite oil displacement as claimed in claim 1, characterized in that: Setting a convergence standard for energy minimization for the multi-component composite flooding model and performing molecular dynamics simulation based on the convergence standard comprises the following steps: A convergence standard of 0.001 kcal / mol is set for the multi-component composite oil displacement model, and a kinetic calculation of the NPT system is performed for at least 100 ns; In the dynamic calculation, the temperature was set to 300K, the pressure was set to 0.1GPa, and the step size was set to 1fs; the pressure coupling mode was set to Berendsen pressure coupling, and the pressure coupling mode was set to 1ps; The NPT system is isothermal compressed, and periodic boundary conditions are set in the X and Y directions, while the Z direction remains unchanged. The cutoff radii of the two forms of intermolecular forces, Van Der Waals and Lennard-Jones potential, are set to The initial atomic velocities were determined by the Maxwell-Boltzmann distribution, and the motion trajectories were statistically integrated using the Verlet algorithm.

5. The method for evaluating the performance of an oil displacement agent in a multi-component composite oil displacement as claimed in claim 4, characterized in that: The kinetic calculation of the NPT system for at least 100 ns also includes the following steps: In the dynamic calculation, the temperature is set to 300K and the step size is 1fs; the pressure coupling mode is set to Berendsen pressure coupling and 1ps pressure coupling mode; The ensemble is the NVT ensemble, and periodic boundary conditions are set in the X, Y, and Z directions; the cutoff radius of the Van Der Waals and Lennard-Jones potentials is set The initial atomic velocities are determined by the Maxwell-Boltzmann distribution, and the motion trajectories are statistically integrated using the Verlet algorithm.

6. The method for evaluating the performance of an oil displacement agent in a multi-component composite oil displacement as claimed in claim 1, characterized in that: The obtaining of simulation results including molecular dynamics motion state, radial distribution function, relative concentration distribution, mean square displacement and energy comprises the following steps: The MSD module in Forcite analysis is used to select molecules, simulate and obtain the mean square displacement curve in the multi-component composite oil displacement model, and analyze the dynamic motion state of the alkali molecules and the surfactant A molecules and the surfactant B molecules through the mean square displacement curve; The Forcite analysis module is used to obtain the relative concentration distribution curve of surfactants at the oil-water interface in the multi-component composite flooding model, and the microscopic movement of surfactant molecules is obtained through the change of relative concentration distribution; The interaction of surfactant / base with other components of the system is analyzed by radial distribution function to obtain the atomic distribution around a specified atom.

7. The method for evaluating the performance of an oil displacement agent in a multi-component composite oil displacement as claimed in claim 1, characterized in that: When evaluating the oil displacement performance and diffusion capacity of the oil displacement agent in the multi-component composite oil displacement model by thermodynamic parameters, the oil-water interface is also evaluated by the interface formation energy of the oil-water interface. The specific expression is: Where: E total represents the total energy of the system, E blank represents the energy of the blank system without surfactant, E single represents the system energy containing a single surfactant molecule, n represents the number of surfactant molecules in the entire system, and IFE is the evaluation matrix.

8. The system for evaluating the performance of a multi-component composite oil displacement agent in claim 1, characterized in that: include: An initial model building module is used to build a surfactant A model, a surfactant B model, an alkali molecule model, a water model and an oil model, and fuse the water model and the oil model to obtain an oil-water model; wherein the surfactant A model and the surfactant B model use two different types of surfactants; The adjustment module is used to establish a system AC box for multi-component composite simulation calculations at different temperatures, adjust the spatial positions of the oil-water model, the alkali molecule model, the surfactant A model and the surfactant B model, and construct a mixed model through the surfactant A model, the surfactant B model and the alkali molecule model; A composite model building module is used to divide the AC box into three local boxes, place a water model, a mixed model, and an oil-water model in sequence according to their positions, optimize the structure inside the AC box, and obtain a multi-component composite oil displacement model of surfactants; A simulation module, used for setting a convergence standard for energy minimization for the multi-component composite flooding model, performing molecular dynamics simulation based on the convergence standard, and obtaining simulation results including molecular dynamics motion state, radial distribution function, relative concentration distribution, mean square displacement and energy; Evaluation module, used to calculate thermodynamic parameters according to simulation results, and evaluate the oil displacement performance and diffusion capacity of the oil displacement agent in the multi-component composite oil displacement model through thermodynamic parameters; The construction of the surfactant A model, the surfactant B model, the alkali molecule model, the water model and the oil model comprises the following steps: Constructing the geometric structures of surfactant molecules, alkali molecules, water molecules and oil molecules, and constructing molecular models of the surfactant molecules, alkali molecules, water molecules and oil molecules according to component ratio, atomic structure, chemical bond type and group type, and saving them as trajectory files in .XSD format; Build multiple box, select surfactant molecules, alkali molecules, water molecules and oil molecules, construct 15 surfactant A molecules, 10 surfactant B molecules, 10 alkali molecules, 500 water molecules and 50 oil molecules respectively, and then add them into the empty box, use the SMART algorithm for structure optimization, set the convergence standard, number of steps, temperature and pressure, and then perform NVT system simulation for a certain length of time to obtain surfactant model, alkali molecule model, water model and oil model.

9. A computer device, characterized in that: It comprises a memory and a processor, wherein a program is stored in the memory, and when the program is executed by the processor, the processor executes the steps of a method for evaluating the performance of an oil displacement agent in a multi-component composite oil displacement as claimed in any one of claims 1 to 7.

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