Microcosmic numerical simulation method for pore-scale polymer flooding

Abstract

The invention discloses a microcosmic numerical simulation method for pore-scale polymer oil displacement. The method comprises the following steps: obtaining basic data of polymer, oil, water viscosity, oil-polymer and oil-water interfacial tension; initializing partial content data of the basic data; the speed distribution of the polymer, oil and water in the pore space is obtained; adopting a polymer spatial distribution tracking model to obtain distribution of polymers in space; adopting an oil space distribution tracking model to obtain the distribution of oil in the space; obtaining an oil-water interface curvature and an oil-polymer interface curvature; solving the viscoelastic stress tensor of the polymer; and carrying out viscous component and elastic component decomposition on the solved viscoelastic stress, and repeating the steps. According to the method, the strategy of separating and dispersing the viscous component and the elastic component is introduced, the stability of the algorithm is improved, the high-stability numerical simulation method for pore-scale polymer oil displacement is provided, and efficient tracking of pore-scale flow in the polymer oil displacement process is achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of numerical simulation, in particular to a microscopic numerical simulation method for pore-scale polymer flooding. Background Art

[0002] Chemical flooding is an important means of enhancing oil recovery after water flooding. It is a rapidly developing and widely used chemical flooding technology. Unlike water flooding, polymer flooding reduces the viscosity ratio between the oil and the fluid, thereby increasing spatial sweep and mobilizing residual oil. In addition to increasing viscosity, polymers also enhance the elasticity of the flooding fluid. Previous studies have shown that this elasticity can mobilize residual oil in blind spots. In actual field applications, increasing the viscosity of the flooding fluid also increases the displacement pressure, resulting in increased energy consumption during the injection process. Laboratory experiments have shown that increasing polymer viscosity does not necessarily lead to a sustained increase in recovery. The difficulty of polymer-assisted residual oil mobilization is closely related to the residual oil's storage form. The effects of viscosity and elasticity on the mobilization of different types of residual oil vary significantly. Currently, there is a lack of research, both domestically and internationally, on how to evaluate the performance of polymer-assisted residual oil mobilization based on different residual oil storage characteristics. Summary of the Invention

[0003] In response to the above technical problems in the related art, the present invention proposes a microscopic numerical simulation method for pore-scale polymer flooding, which can overcome the above-mentioned shortcomings of the prior art.

[0004] To achieve the above technical objectives, the technical solution of the present invention is implemented as follows:

[0005] In one aspect, a microscopic numerical simulation method for pore-scale polymer flooding is provided, comprising:

[0006] S1: Obtain basic data on polymer, oil, water viscosity, oil-polymer and oil-water interfacial tension;

[0007] S2: Initialize the content data of the basic data;

[0008] S3: The velocity distribution of polymer, oil and water in the pore space is obtained by inputting basic data into the kinetic model, wherein the basic data includes: the basic data in step S1 and the data initialized in step S2; the kinetic model is:

[0009]

[0010] In the above formula, ρ is the average density of polymer, oil and water; ∪ is the volume average velocity of polymer, oil and water; t is time; P is the pressure of the fluid; τ s is the viscous stress tensor; τ p is the viscoelastic stress tensor of the polymer; g is the acceleration due to gravity; σ op is the interfacial tension between oil and polymer; k op is the curvature of the oil-polymer interface; σ ow is the oil-water interfacial tension; k ow is the curvature of the oil-water interface; a o is the oil saturation; is a non-steady-state term that describes the acceleration of the fluid in the spatial position; is the convection term, which describes the momentum increment due to the motion of the surrounding fluid; is the pressure gradient force, which describes the effect of displacement pressure on fluid motion; is the viscous force, which describes the influence of the viscosity of polymers, oils, and water on fluid motion; is the elastic force of the polymer, which describes the influence of the elastic effect of the polymer on the fluid motion; ρg is the gravity, which describes the influence of the gravity effect on the fluid motion; is the interfacial tension between oil and polymer, which describes the effect of the interfacial interaction between oil and polymer on fluid motion; is the tension between oil and water, describing the effect of the interfacial effect between oil and water on fluid motion;

[0011] S4: Using a polymer spatial distribution tracking model to obtain the spatial distribution of the polymer, wherein the polymer spatial distribution tracking model is:

[0012]

[0013] Among them, a p is the saturation of the polymer in the pore space;

[0014] S5: Using an oil spatial distribution tracking model to obtain the spatial distribution of oil, wherein the oil spatial distribution tracking model is:

[0015]

[0016] S6: Track the oil-water interface position and the oil-polymer interface position based on the level set model to obtain the oil-water interface curvature k ow and the oil-polymer interface curvature k op , where the level set model is:

[0017]

[0018] Where S is the distance from the spatial grid point to the oil-water interface or oil-polymer interface;

[0019] S7: Solve the polymer viscoelastic stress tensor τ based on the Oldroyd-B numerical model p , where the Oldroyd-B numerical model is:

[0020]

[0021] Where λ is the relaxation time, which is the ratio of the viscosity and shear modulus of the fluid; η p is the viscosity of the polymer solution; T is the transposition sign; is the upper body derivative;

[0022] S8: The viscoelastic stress τ after solution p Decompose the viscous component and the elastic component, and feed back to step S3, and repeat steps S3-S8.

[0023] Furthermore, the basic data of polymer, oil, and water viscosity, oil-polymer, and oil-water interfacial tension are obtained, including:

[0024] The basic data of polymer, oil, and water viscosity, oil-polymer and oil-water interfacial tension are obtained through physical property measurements.

[0025] Furthermore, the basic data includes:

[0026] The spatial distribution of polymer, oil, and water in the pore space and the pressure, velocity, and elastic stress of the fluids.

[0027] Furthermore, the initialization of the content data of the basic data portion includes:

[0028] Initialize the spatial distribution of polymer, oil, and water in the pore space and the pressure, velocity of the fluid, and elastic stress of the polymer.

[0029] Furthermore, the viscoelastic stress τ after solution is p In the decomposition of viscous and elastic components, the viscous component of the polymer is implicitly processed, where the viscous component τ pv Expressed as:

[0030]

[0031] Furthermore, the viscoelastic stress τ after solution is p In the decomposition of viscous and elastic components, the elastic component of the polymer is explicitly processed, where the elastic component τ pe Expressed as:

[0032] τ pe =τp -τ pv .

[0033] Furthermore, the viscosity component τ pv Expressed as:

[0034]

[0035] Furthermore, the elastic component τ pe Expressed as:

[0036] τ pe =τ p -τ pv .

[0037] Furthermore, the viscoelastic stress is decomposed into viscous components and elastic components, including:

[0038] The viscous component is handled implicitly and the elastic component is handled explicitly.

[0039] Furthermore, the basic data also includes:

[0040] Data after implicit processing of the viscous component and explicit processing of the elastic component.

[0041] In another aspect, the present invention provides a microscopic numerical simulation device for pore-scale polymer flooding, comprising:

[0042] The first acquisition module is used to obtain basic data of polymer, oil, water viscosity, oil-polymer and oil-water interfacial tension;

[0043] Initialization module, used to initialize the content data of basic data;

[0044] The second acquisition module is used to obtain the velocity distribution of polymer, oil and water in the pore space by inputting basic data into the kinetic model, wherein the basic data includes: the basic data in the first acquisition module and the data initialized in the initialization module; the kinetic model is:

[0045]

[0046] In the above formula, ρ is the average density of polymer, oil and water; ∪ is the volume average velocity of polymer, oil and water; t is time; P is the pressure of the fluid; τ s is the viscous stress tensor; τ p is the viscoelastic stress tensor of the polymer; g is the acceleration due to gravity; σ op is the interfacial tension between oil and polymer; k op is the curvature of the oil-polymer interface; σ ow is the oil-water interfacial tension; k owis the curvature of the oil-water interface; a o is the oil saturation; is a non-steady-state term that describes the acceleration of the fluid in the spatial position; is the convection term, which describes the momentum increment due to the motion of the surrounding fluid; is the pressure gradient force, which describes the effect of displacement pressure on fluid motion; is the viscous force, which describes the influence of the viscosity of polymers, oils, and water on fluid motion; is the elastic force of the polymer, which describes the influence of the elastic effect of the polymer on the fluid motion; ρg is the gravity, which describes the influence of the gravity effect on the fluid motion; is the interfacial tension between oil and polymer, which describes the effect of the interfacial interaction between oil and polymer on fluid motion; is the tension between oil and water, describing the effect of the interfacial effect between oil and water on fluid motion;

[0047] The third acquisition module is used to obtain the spatial distribution of the polymer using a polymer spatial distribution tracking model, wherein the polymer spatial distribution tracking model is:

[0048]

[0049] Among them, a p is the saturation of the polymer in the pore space;

[0050] The fourth acquisition module is used to obtain the spatial distribution of oil using an oil spatial distribution tracking model, wherein the oil spatial distribution tracking model is:

[0051]

[0052] The fifth acquisition module is used to track the oil-water interface position and the oil-polymer interface position based on the level set model to obtain the oil-water interface curvature k ow and the oil-polymer interface curvature k op , where the level set model is:

[0053]

[0054] Where S is the distance from the spatial grid point to the oil-water interface or oil-polymer interface;

[0055] Solver module for solving the polymer viscoelastic stress tensor τ based on the Oldroyd-B numerical model p , where the Oldroyd-B numerical model is:

[0056]

[0057] Where λ is the relaxation time, which is the ratio of the viscosity and shear modulus of the fluid; η p is the viscosity of the polymer solution; T is the transposition sign; is the upper body derivative;

[0058] Decomposition module, used to convert the solved viscoelastic stress τ p Decompose the viscous component and the elastic component and feed it back to the second acquisition module, and repeat the steps from the second acquisition module to the decomposition module.

[0059] Furthermore, the basic data of polymer, oil, and water viscosity, oil-polymer, and oil-water interfacial tension are obtained, including:

[0060] The basic data of polymer, oil, and water viscosity, oil-polymer and oil-water interfacial tension are obtained through physical property measurements.

[0061] Furthermore, the basic data includes:

[0062] The spatial distribution of polymer, oil, and water in the pore space and the pressure, velocity, and elastic stress of the fluids.

[0063] Furthermore, the initialization of the content data of the basic data portion includes:

[0064] Initialize the spatial distribution of polymer, oil, and water in the pore space and the pressure, velocity of the fluid, and elastic stress of the polymer.

[0065] Furthermore, the viscoelastic stress τ after solution is p In the decomposition of viscous and elastic components, the viscous component of the polymer is implicitly processed, where the viscous component τ pv Expressed as:

[0066]

[0067] Furthermore, the viscoelastic stress τ after solution is p In the decomposition of viscous and elastic components, the elastic component of the polymer is explicitly processed, where the elastic component τ pe Expressed as:

[0068] τ pe =τ p -τ pv .

[0069] Furthermore, the viscosity component τ pv Expressed as:

[0070]

[0071] Furthermore, the elastic component τpe Expressed as:

[0072] τ pe =τ p -τ pv .

[0073] Beneficial effects of the present invention: The present invention aims to establish a pore-scale numerical simulation method for polymer flooding based on the interaction between polymer, oil, and water, thereby providing a means for exploring the microscopic flow mechanism of polymer flooding and the dynamic process of polymer flooding. The establishment of this method will deepen the understanding of the polymer flooding mechanism and lay the foundation for the adjustment and optimization of polymer flooding reservoir development plans; by analyzing the dynamic characteristics of the interaction between polymer, oil, and water in the polymer flooding process, a dynamic model of polymer flooding is constructed, and a strategy for separating and discretizing the viscous and elastic components is introduced to increase the stability of the algorithm. A highly stable numerical simulation method for pore-scale polymer flooding is proposed, achieving efficient tracking of pore-scale flow in the polymer flooding process. BRIEF DESCRIPTION OF THE DRAWINGS

[0074] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0075] Figure 1 This is a flow chart of a microscopic numerical simulation method for pore-scale polymer flooding according to an embodiment of the present invention;

[0076] Figure 2 This is a schematic structural diagram of a microscopic numerical simulation device for pore-scale polymer flooding according to an embodiment of the present invention;

[0077] Figure 3 It is a porous structure;

[0078] Figure 4 This is the oil-water distribution diagram after water flooding;

[0079] Figure 5 This is a schematic diagram of statistical divisions;

[0080] Figure 6 This is the relationship diagram between pressure, polymer saturation and oil saturation;

[0081] Figure 7 The oil saturation variation diagram along the flow direction at different times;

[0082] Figure 8 This is a graph showing the change of residual oil saturation over time. DETAILED DESCRIPTION

[0083] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention are within the scope of protection of the present invention.

[0084] like Figure 1 As shown: A microscopic numerical simulation method for pore-scale polymer flooding is provided, including:

[0085] S1: Obtain basic data on polymer, oil, water viscosity, oil-polymer and oil-water interfacial tension;

[0086] S2: Initialize the content data of the basic data;

[0087] S3: The velocity distribution of polymer, oil and water in the pore space is obtained by inputting basic data into the kinetic model, wherein the basic data includes: the basic data in step S1 and the data initialized in step S2; the kinetic model is:

[0088]

[0089] In the above formula, ρ is the average density of polymer, oil and water; ∪ is the volume average velocity of polymer, oil and water; t is time; P is the pressure of the fluid; τ s is the viscous stress tensor; τ p is the viscoelastic stress tensor of the polymer; g is the acceleration due to gravity; σ op is the interfacial tension between oil and polymer; k op is the curvature of the oil-polymer interface; σ ow is the oil-water interfacial tension; k ow is the curvature of the oil-water interface; a o is the oil saturation; is a non-steady-state term that describes the acceleration of the fluid in the spatial position; is the convection term, which describes the momentum increment due to the motion of the surrounding fluid; is the pressure gradient force, which describes the effect of displacement pressure on fluid motion; is the viscous force, which describes the influence of the viscosity of polymers, oils, and water on fluid motion; is the elastic force of the polymer, which describes the influence of the elastic effect of the polymer on the fluid motion; ρg is the gravity, which describes the influence of the gravity effect on the fluid motion; is the interfacial tension between oil and polymer, which describes the effect of the interfacial interaction between oil and polymer on fluid motion; is the tension between oil and water, describing the effect of the interfacial effect between oil and water on fluid motion;

[0090] S4: Using a polymer spatial distribution tracking model to obtain the spatial distribution of the polymer, wherein the polymer spatial distribution tracking model is:

[0091]

[0092] Among them, a p is the saturation of the polymer in the pore space;

[0093] S5: Using an oil spatial distribution tracking model to obtain the spatial distribution of oil, wherein the oil spatial distribution tracking model is:

[0094]

[0095] S6: Track the oil-water interface position and the oil-polymer interface position based on the level set model to obtain the oil-water interface curvature k ow and the oil-polymer interface curvature k op , where the level set model is:

[0096]

[0097] Where S is the distance from the spatial grid point to the oil-water interface or oil-polymer interface;

[0098] Among them, the curvature k of the phase interface is solved ow and k op : In order to reduce the false velocity of the phase interface, the level set equation of the present invention tracks the oil-water interface position and the oil-polymer interface position.

[0099]

[0100] Where S is the distance from the spatial grid point to the oil-water interface or oil-polymer interface. The curvature of the oil-water interface k is further solved using the following equation: ow and the oil-polymer interface curvature k op

[0101]

[0102] S7: Solve the polymer viscoelastic stress tensor τ based on the Oldroyd-B numerical model p , where the Oldroyd-B numerical model is:

[0103]

[0104] Where λ is the relaxation time, which is the ratio of the viscosity and shear modulus of the fluid; ηp is the viscosity of the polymer solution; T is the transposition sign; is the upper body derivative;

[0105] The viscoelastic stress of a polymer exhibits a nonlinear relationship with the strain rate or strain amount. In order to track the change in the viscoelastic stress of the polymer, the present invention obtains the change in the viscoelastic stress of the polymer by solving the Oldroyd-B numerical model;

[0106] is the upper body derivative, which is described by the following equation:

[0107]

[0108] S8: The viscoelastic stress τ after solution p The viscous component and the elastic component are decomposed and fed back to step S3, and steps S3-S8 are repeated. The present invention performs implicit processing on the viscous component of the polymer and explicit processing on the elastic component to achieve discrete separation of the viscous component and the elastic component, thereby increasing the stability of the solution.

[0109] In some embodiments of the present invention, obtaining basic data of polymer, oil, and water viscosity, oil-polymer, and oil-water interfacial tensions includes:

[0110] The basic data of polymer, oil, and water viscosity, oil-polymer and oil-water interfacial tension are obtained through physical property measurements.

[0111] In some embodiments of the present invention, the basic data content includes:

[0112] The spatial distribution of polymer, oil, and water in the pore space and the pressure, velocity, and elastic stress of the fluids.

[0113] In some embodiments of the present invention, the viscoelastic stress is decomposed into a viscous component and an elastic component, comprising:

[0114] The viscous component is handled implicitly and the elastic component is handled explicitly.

[0115] In some embodiments of the present invention, the basic data content further includes:

[0116] Data after implicit processing of the viscous component and explicit processing of the elastic component.

[0117] In some embodiments of the present invention, initializing the content data of the basic data portion includes:

[0118] Initialize the spatial distribution of polymer, oil, and water in the pore space and the pressure, velocity of the fluid, and elastic stress of the polymer.

[0119] In some embodiments of the present invention, the viscoelastic stress τ p In the decomposition of viscous and elastic components, the viscous component of the polymer is implicitly processed, where the viscous component τ pv Expressed as:

[0120]

[0121] In some embodiments of the present invention, the viscoelastic stress τ p In the decomposition of viscous and elastic components, the elastic component of the polymer is explicitly processed, where the elastic component τ pe Expressed as:

[0122] τ pe =τ p -τ pv .

[0123] In some embodiments of the present invention, the viscosity component τ pv Expressed as:

[0124]

[0125] In some embodiments of the present invention, the elastic component τ pe Expressed as:

[0126] τ pe =τ p -τ pv .

[0127] On the other hand, Figure 2 As shown, the present invention provides a microscopic numerical simulation device for pore-scale polymer flooding, comprising:

[0128] The first acquisition module is used to obtain basic data of polymer, oil, water viscosity, oil-polymer and oil-water interfacial tension;

[0129] Initialization module, used to initialize the content data of basic data;

[0130] The second acquisition module is used to obtain the velocity distribution of polymer, oil and water in the pore space by inputting basic data into the kinetic model, wherein the basic data includes: the basic data in the first acquisition module and the data initialized in the initialization module; the kinetic model is:

[0131]

[0132] In the above formula, ρ is the average density of polymer, oil and water; ∪ is the volume average velocity of polymer, oil and water; t is time; P is the pressure of the fluid; τ s is the viscous stress tensor; τp is the viscoelastic stress tensor of the polymer; g is the acceleration due to gravity; σ op is the interfacial tension between oil and polymer; k op is the curvature of the oil-polymer interface; σ ow is the oil-water interfacial tension; k ow is the curvature of the oil-water interface; a o is the oil saturation; is a non-steady-state term that describes the acceleration of the fluid in the spatial position; is the convection term, which describes the momentum increment due to the motion of the surrounding fluid; is the pressure gradient force, which describes the effect of displacement pressure on fluid motion; is the viscous force, which describes the influence of the viscosity of polymers, oils, and water on fluid motion; is the elastic force of the polymer, which describes the influence of the elastic effect of the polymer on the fluid motion; ρg is the gravity, which describes the influence of the gravity effect on the fluid motion; is the interfacial tension between oil and polymer, which describes the effect of the interfacial interaction between oil and polymer on fluid motion; is the tension between oil and water, describing the effect of the interfacial effect between oil and water on fluid motion;

[0133] The third acquisition module is used to obtain the spatial distribution of the polymer using a polymer spatial distribution tracking model, wherein the polymer spatial distribution tracking model is:

[0134]

[0135] Among them, a p is the saturation of the polymer in the pore space;

[0136] The fourth acquisition module is used to obtain the spatial distribution of oil using an oil spatial distribution tracking model, wherein the oil spatial distribution tracking model is:

[0137]

[0138] The fifth acquisition module is used to track the oil-water interface position and the oil-polymer interface position based on the level set model to obtain the oil-water interface curvature k ow and the oil-polymer interface curvature k op , where the level set model is:

[0139]

[0140] Where S is the distance from the spatial grid point to the oil-water interface or oil-polymer interface;

[0141] Solver module for solving the polymer viscoelastic stress tensor τ based on the Oldroyd-B numerical model p , where the Oldroyd-B numerical model is:

[0142]

[0143] Where λ is the relaxation time, which is the ratio of the viscosity and shear modulus of the fluid; η p is the viscosity of the polymer solution; T is the transposition sign; is the upper body derivative;

[0144] Decomposition module, used to convert the solved viscoelastic stress τ p Decompose the viscous component and the elastic component and feed it back to the second acquisition module, and repeat the steps from the second acquisition module to the decomposition module.

[0145] In some embodiments of the present invention, obtaining basic data of polymer, oil, and water viscosity, oil-polymer, and oil-water interfacial tensions includes:

[0146] The basic data of polymer, oil, and water viscosity, oil-polymer and oil-water interfacial tension are obtained through physical property measurements.

[0147] In some embodiments of the present invention, the basic data content includes:

[0148] The spatial distribution of polymer, oil, and water in the pore space and the pressure, velocity, and elastic stress of the fluids.

[0149] In some embodiments of the present invention, initializing the content data of the basic data portion includes:

[0150] Initialize the spatial distribution of polymer, oil, and water in the pore space and the pressure, velocity of the fluid, and elastic stress of the polymer.

[0151] In some embodiments of the present invention, the viscoelastic stress τ p In the decomposition of viscous and elastic components, the viscous component of the polymer is implicitly processed, where the viscous component τ pv Expressed as:

[0152]

[0153] In some embodiments of the present invention, the viscoelastic stress τ p In the decomposition of viscous and elastic components, the elastic component of the polymer is explicitly processed, where the elastic component τ pe Expressed as:

[0154] τ pe =τp -τ pv .

[0155] In some embodiments of the present invention, the viscosity component τ pv Expressed as:

[0156]

[0157] In some embodiments of the present invention, the elastic component τ pe Expressed as:

[0158] τ pw =τ p -τ pv .

[0159] The main steps of numerical simulation implementation are as follows:

[0160] (1) During the implementation of polymer flooding at the pore scale, the momentum conservation equation is first solved to obtain the predicted distribution of oil, water, and polymer velocities in the pore space;

[0161] (2) Solve the pressure equation and correct the predicted velocity according to the solved pressure to obtain accurate velocity and pressure distribution;

[0162] (3) Based on the calculated velocity, the spatial distribution of water and polymer saturation is solved. The spatial distribution of oil is equal to 1 minus the sum of water and polymer saturation;

[0163] (4) Solve the rheological model of the polymer to obtain the viscous stress and elastic stress of the polymer, providing data for tracking the momentum equation in the next step (1);

[0164] (5) Based on the spatial distribution of the saturation of oil, water, and polymer obtained in step (3), the average density ρ, average effective viscosity, etc. of the fluid are corrected;

[0165] (6) Repeat the above steps until the preset physical time ends;

[0166] (7) Statistics on velocity, pressure, saturation, etc. are collected to obtain characteristic information of polymer flooding development.

[0167] Example

[0168] Figure 3 The pore structure diagram is given here. This diagram is a digital core constructed by computer tomography scanning of real sandstone. The spatial size of the model is 2mm*2mm, and the number of grids is 432542. The physical model is initially filled with oil. Then water is injected into the model until there is no oil. The remaining oil distribution is as follows: Figure 4As shown in the figure (red is oil and cyan is water). Then inject polymer into the model until no oil is produced. In order to obtain the multiphase motion law during polymer flooding, this example divides the flow area into 8 partitions along the displacement direction, as shown in the figure. Figure 5 By analyzing the statistics of physical quantities in each partition, the dynamic characteristics of the development are obtained.

[0169] Figure 6 A relationship diagram showing the changes in pressure, polymer saturation, and oil saturation is presented. As can be seen from the figure, there is a strict correspondence between the pressure distribution and the spatial distribution of the polymer during injection, with the pressure primarily distributed in the polymer-bearing region. At the same time, there is also a corresponding relationship between the distribution of the polymer and the change in the residual oil. At 0.3 s, the polymer moves to partition 3. Comparing the oil saturation distribution at 0 s and 0.3 s, it can be seen that after 0.3 s, the saturation changes are also primarily concentrated in the region before partition 4, while the oil-water saturation in partitions 5-8 remains unchanged. This phenomenon demonstrates that in the polymer-bearing region, the polymer acts as an oil sink, while in the non-polymer-bearing region, fluid movement is still primarily driven by water drive. Since the injection rate remains constant during water drive, the residual oil does not move in the non-polymer-bearing region.

[0170] Figure 7 The graph of the change of oil saturation along the flow direction at different times is given. It can be seen from the figure that as the displacement progresses, the oil saturation at the polymer front gradually increases, further confirming the oil collection capacity of the polymer flooding.

[0171] Figure 8 The time-varying curve of residual oil saturation and the spatial distribution of oil, water, and polymer saturations at different times are presented. The figures clearly show that polymer flooding progresses through a drainage phase, a recovery phase, and a residual oil phase. Comparing the spatial distribution of polymer and the model's oil content reveals that polymer flooding effectiveness ends once polymer flows out of the outlet.

[0172] Explanation of some of the figures: Figure 1 The black part in the middle is the pore channel; the black part in the pores in the picture is oil, and the white part is water; Figure 3 The black in the mesopores is oil, the white is water, and the streaks are polymers; Figure 6 The black in the mesopores is oil, the white is water, and the stripes are polymers.

[0173] As can be seen from the above examples, the numerical model of the present invention can reproduce the spatial distribution changes of the saturation of each phase during polymer flooding, deepen the understanding of the multiphase movement characteristics and macroscopic development laws during polymer flooding, and provide an important tool for studying the mechanism of polymer flooding.

[0174] In summary, this invention aims to establish a pore-scale numerical simulation method for polymer flooding, based on the interaction between polymer, oil, and water. This method provides a means for exploring the microscopic flow mechanisms and dynamic processes of polymer flooding. This method will deepen our understanding of the mechanisms of polymer flooding and lay the foundation for adjusting and optimizing polymer flooding reservoir development plans. By analyzing the dynamic characteristics of the interaction between polymer, oil, and water during polymer flooding, a dynamic model for polymer flooding is constructed. A strategy for separating and discretizing the viscous and elastic components is introduced, increasing the stability of the algorithm. A highly stable numerical simulation method for pore-scale polymer flooding is proposed, enabling efficient tracking of pore-scale flows during polymer flooding.

[0175] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A microscopic numerical simulation method for pore-scale polymer flooding, characterized in that: include: S1: Obtain basic data on polymer, oil, water viscosity, oil-polymer and oil-water interfacial tension; S2: Initializing the content data of the basic data portion; S3: Obtaining the velocity distribution of polymer, oil, and water in the pore space by inputting the basic data into a kinetic model; S4: Using the polymer spatial distribution tracking model to obtain the spatial distribution of the polymer; S5: Using the oil spatial distribution tracking model to obtain the spatial distribution of oil; S6: Tracking the oil-water interface position and the oil-polymer interface position based on the level set model to obtain the oil-water interface curvature and the oil-polymer interface curvature; S7: Solve the polymer viscoelastic stress tensor based on the Oldroyd-B numerical model; S8: Decompose the solved viscoelastic stress into viscous and elastic components, and feed it back to step S3, and repeat steps S3-S8.

2. The microscopic numerical simulation method for pore-scale polymer flooding according to claim 1, characterized in that: The method of obtaining basic data of polymer, oil, water viscosity, oil-polymer and oil-water interfacial tension includes: The basic data of polymer, oil, and water viscosity, oil-polymer and oil-water interfacial tension are obtained through physical property measurements.

3. The microscopic numerical simulation method for pore-scale polymer flooding according to claim 1, characterized in that: The basic data includes: Spatial distribution of polymer, oil, and water in the pore space.

4. The microscopic numerical simulation method for pore-scale polymer flooding according to claim 3, characterized in that: The basic data also includes: Fluid pressure, velocity, and polymer elastic stress.

5. The microscopic numerical simulation method for pore-scale polymer flooding according to claim 3, characterized in that: The initialization of the basic data content data includes: Initialize the spatial distribution of polymer, oil, and water in the pore space.

6. The microscopic numerical simulation method for pore-scale polymer flooding according to claim 4, characterized in that: The initialization of the basic data content data also includes: Initialize the pressure, velocity, and elastic stress of the fluid in the pore space.

7. The microscopic numerical simulation method for pore-scale polymer flooding according to claim 1, characterized in that: In the decomposition of the solved viscoelastic stress into viscous components and elastic components, the viscous component of the polymer is implicitly processed.

8. The microscopic numerical simulation method for pore-scale polymer flooding according to claim 1, characterized in that: The solved viscoelastic stress is decomposed into viscous components and elastic components, and the elastic component of the polymer is explicitly processed.

9. The microscopic numerical simulation method for pore-scale polymer flooding according to claim 1, characterized in that: The viscoelastic stress is decomposed into viscous components and elastic components, including: The viscous component is handled implicitly and the elastic component is handled explicitly.

10. The microscopic numerical simulation method for pore-scale polymer flooding according to claim 9, characterized in that: The basic data also includes: Data after implicit processing of the viscous component and explicit processing of the elastic component.

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