Numerical simulation method based on microbubble flooding

Abstract

The invention discloses a numerical simulation method based on microbubble flooding. The numerical simulation method is implemented according to the following steps: step 1, constructing a microbubble flooding relative permeability correction model; step 2, establishing a microbubble flooding numerical simulation model; and 3, considering influence factors of microbubble flooding numerical simulation, and performing injection-production parameter optimization. According to the method, the microbubbles migrate into the pore space of the low-permeability reservoir and occupy large pores preferentially, so that the seepage resistance is increased, a water flow channel is effectively blocked, the subsequent microbubbles enter small pores, the sweep efficiency is improved, remaining oil in the pores is displaced, and the oil displacement efficiency is improved; the problems that in the prior art, research of a microbubble flooding numerical simulation method is not rich enough, and the recovery efficiency is not obviously improved are solved.

Description

Technical Field

[0001] The invention belongs to the technical field of oil and gas field development and relates to a numerical simulation method based on microbubble flooding. Background Art

[0002] In the process of oil and gas field development, for some oil and gas fields, there are problems such as poor reservoir properties and fine pore throats in low permeability reservoirs, the development of reservoir microcracks, the formation of dominant channels easily by water injection development, high probability of water channeling, and low sweep coefficient, which urgently need to explore new oil recovery technologies. Microbubble flooding, as a new technology that can improve the recovery rate, is a mixed system formed by water and gas. The microbubble flooding technology with this mixed system as the core can achieve the regulation of seepage resistance and energy supplement by adjusting the ratio and dispersion mode of water-gas media, thereby improving the water flooding efficiency of low permeability reservoirs.

[0003] At present, the research on microbubble flooding is basically limited to the microbubble flooding system and operation method, mainly including the innovation of microbubble generation process equipment and preparation method, which belong to the research field of physical model hardware. No relevant research on microbubble flooding using numerical simulation methods has been found. The oil displacement mechanism and sweep characteristics of microbubble flooding are relatively complex, and there is currently no numerical simulation method for improving oil recovery for microbubble flooding. Therefore, the relationship between microbubble concentration and oil recovery efficiency is established through a numerical model. By injecting microbubble concentration to interpolate the gas phase permeability, the gas phase mobility is reduced, and microbubbles migrate into the pore space of low-permeability reservoirs, effectively blocking the water flow channel, increasing the sweep coefficient, displacing the remaining oil in the pores, and improving the oil recovery efficiency. The microbubble flooding method has gradually become a hot topic.

[0004] Therefore, it is urgent to develop a numerical simulation method based on microbubble flooding to realize the numerical simulation of microbubble flooding to enhance oil recovery in low permeability reservoirs. Summary of the invention

[0005] The purpose of the present invention is to provide a numerical simulation method based on microbubble flooding, so as to solve the problem that the research on the numerical simulation method of microbubble flooding in the prior art is not rich enough and the recovery rate is not significantly improved.

[0006] The technical solution adopted by the present invention is a numerical simulation method based on microbubble flooding, which is implemented according to the following steps:

[0007] Step 1, constructing a microbubble flooding phase permeability correction model;

[0008] Step 2, establishing a numerical simulation model for microbubble flooding;

[0009] Step 3: Consider the influencing factors of microbubble flooding numerical simulation and optimize the injection and production parameters.

[0010] The beneficial effect of the present invention is that microbubbles migrate into the pore space of low-permeability oil reservoirs and preferentially occupy large pores, thereby increasing the seepage resistance and effectively blocking the water flow channel. Subsequently, the microbubbles enter the small pores, increasing the sweep coefficient and displacing the remaining oil in the pores, thereby improving the oil recovery efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] Figure 1 It is a microbubble flooding phase permeability correction model established by the method of the present invention;

[0012] Figure 2 It is a numerical simulation model of microbubble flooding established by the method of the present invention;

[0013] Figure 3 It is a comparison of oil production before and after the microbubble concentration interpolation in Example 1 of the method of the present invention;

[0014] Figure 4 It is a comparison of the oil production at different stages of gas-liquid ratios in Example 1 of the method of the present invention;

[0015] Figure 5 It is a comparison of the recovery degree of different gas-liquid ratios in Example 1 of the method of the present invention;

[0016] Figure 6 It is a comparison of the oil production at different injection-production ratios in Example 1 of the method of the present invention;

[0017] Figure 7 It is a comparison of the recovery degree of different injection-production ratios in Example 1 of the method of the present invention;

[0018] Figure 8 It is a comparison of the oil production at different stages of gas-liquid ratios in Example 2 of the method of the present invention;

[0019] Fig. 9 It is a comparison of the recovery degree of different gas-liquid ratios in Example 2 of the method of the present invention;

[0020] Fig.10 It is a comparison of the oil production at different injection-production ratios in Example 2 of the method of the present invention;

[0021] Fig.11 It is a comparison of the recovery degree of different injection-production ratios in Example 2 of the method of the present invention;

[0022] Fig.12 is a comparison of the oil production at different gas-liquid ratios in Example 3 of the method of the present invention;

[0023] Fig.13 It is a comparison of the recovery degree of different gas-liquid ratios in Example 3 of the method of the present invention;

[0024] Fig.14 It is a comparison of the oil production at different stages of injection-production ratios in Example 3 of the method of the present invention;

[0025] Fig.15 It is a comparison of the recovery degree of different injection-production ratios in Example 3 of the method of the present invention;

[0026] Fig.16 is a comparison of the oil production at different gas-liquid ratios in Example 4 of the method of the present invention;

[0027] Fig.17 It is a comparison of the recovery degree of different gas-liquid ratios in Example 4 of the method of the present invention;

[0028] Fig.18 is a comparison of the oil production at different injection-production ratios in Example 4 of the method of the present invention;

[0029] Fig.19 It is a comparison of the recovery degree of different injection-production ratios in Example 4 of the method of the present invention. DETAILED DESCRIPTION

[0030] The present invention is described in detail below with reference to the accompanying drawings and specific embodiments.

[0031] The numerical simulation method of the present invention based on microbubble flooding is implemented according to the following steps:

[0032] Step 1: construct a microbubble flooding phase permeability correction model.

[0033] The numerical simulation of microbubble flooding mainly considers that after microbubbles are injected, they enter more pores in the formation, thereby increasing the sweep efficiency. At the same time, since nanoscale microbubbles enter the pore space of low-permeability reservoirs with the migration of fluids, microbubbles enter small pores and displace the remaining oil in the tiny pores, thereby reducing the residual oil saturation and improving the oil recovery efficiency. Improving the sweep efficiency and reducing the residual oil saturation can be achieved by modifying the phase permeability model in the numerical simulation model. This step draws on the principle of empirical foam flooding, interpolates the relative permeability curve according to the microbubble concentration of different grids, and establishes the relationship between microbubble concentration and oil recovery efficiency, such as Figure 1 shown.

[0034] In this step, the flow characteristics of microbubble flooding are simulated by changing the gas phase fluidity by reducing the gas phase relative permeability. The degree of fluidity reduction is specified by the fluid reduction factor MRF, which is related to the gas phase permeability and viscosity in the microbubble and non-microbubble states. The microbubble system has a high mobility control ability. By changing the microbubble viscosity, the mobility control of the oil layer is realized in different parts and stages, the swept volume is expanded, and the recovery factor is improved.

[0035] The following formulas (1), (2) and (3) are respectively the liquid phase permeability model, the gas phase relative permeability model in the non-microbubble state, and the gas phase relative permeability model in the microbubble state, and the expressions are as follows:

[0036]

[0037] Among them, K rw (S w ) is the liquid relative permeability model, S w is the water saturation, S wc is the bound water saturation, S gr is the residual gas saturation, A and m 1 All are relative permeability parameters of corey-type liquids;

[0038]

[0039] in, is the gas phase relative permeability model in the absence of microbubbles, B and m 2 All are relative permeability parameters of corey-type gases;

[0040]

[0041] in, is the gas phase relative permeability model in the microbubble state, X mb is the microbubble concentration of the flow;

[0042] The following formula (4) is the mobility reduction factor MRF that changes the gas phase permeability after injecting microbubbles. The expression is as follows:

[0043]

[0044] Where MRF is the fluid reduction factor; is the relative permeability of the gas phase in the absence of microbubbles, is the relative permeability of the gas phase in the microbubble state; is the gas phase viscosity in the microbubble state; It is the gas phase viscosity in the absence of microbubbles;

[0045] The following formulas (5) and (6) are important formulas for the correction of gas phase relative permeability in this step, indicating that the gas phase permeability is significantly different when microbubbles (MB) are present and when there are no microbubbles, and the size of the permeability changes according to the concentration of microbubbles. The expressions are as follows:

[0046]

[0047] Among them, K rg (S w ) is the relative permeability of the gas, is the gas phase relative permeability model in the microbubble state, and MRF is the fluid reduction factor;

[0048]

[0049] Among them, Kr is the phase permeability interpolation, is the corresponding phase permeability curve under the microbubble state, is the gas phase relative permeability in the non-microbubble state, X is the equivalent fraction in a certain microbubble state in the injected gas, α(MB)0 is the microbubble equivalent fraction in the non-microbubble state, and α(MB)1 is the microbubble equivalent fraction in the microbubble state.

[0050] The phase permeability model under different microbubble concentrations was established using formula (6), which reveals that under different microbubble concentrations, the corresponding oil-water two-phase phase permeability curves have different residual oil saturations at the phase permeability endpoints, thus establishing the relationship between microbubble concentration and oil recovery efficiency.

[0051] Step 2, establishing a numerical simulation model for microbubble flooding;

[0052] Step 1 modifies the flow model of microbubbles, which can more accurately describe the flow process of microbubbles in the formation; on this basis, the generation and collapse reactions of microbubbles are constructed, thereby establishing a complete numerical simulation model of microbubble flooding.

[0053] Taking the Z well group in the test area as an example, the present invention established a numerical simulation model for microbubble flooding, and the model grid is 13×12×4 (see Figure 2 ), the model includes physical parameters such as porosity, permeability, formation pressure, crude oil density, phase state and related reaction components,

[0054] Among them, the phase states adopt oil, gas and water phases; the model components include H2O, OIL, N2 and microbubbles (MB);

[0055] Formula (7) is the reaction formula for the process of microbubble generation. Microbubbles (MB) are generated by the reaction of injected nitrogen and water. Formula (8) is the reaction formula for the process of microbubble collapse and decomposition into water and nitrogen, which is equivalent to the reverse process of formula (7). They are expressed as follows:

[0056] H2O+N2→MB(7)

[0057] MB→H2O+N2(8)

[0058] The following formula (9) describes the reaction rate of microbubbles, which is expressed as follows:

[0059]

[0060] Among them, k d is the microbubble reaction rate constant; t 1 / 2 is the reaction time of microbubbles.

[0061] In practical applications, the gas phase relative permeability is changed at different microbubble concentrations by adjusting the parameters of the interpolation keyword *DTRAPN corresponding to the fluid reduction factor (MRF), thereby achieving a change in the gas phase relative permeability.

[0062] Table 1. Interpolation table of gas phase relative permeability

[0063]

[0064] The specific implementation process in commercial software is as follows: by setting an interpolation table in the phase permeability correction model of microbubble flooding, the present invention adopts gas phase "MB" component interpolation, and the interpolation parameter is implemented by the keyword *DTRAPN. In the above Table 1, the interpolation table (KRINTTP1, KRINTTP2) of gas phase permeability with different microbubble concentrations in the gas phase is given. In practical applications, by adjusting the value of the interpolation keyword *DTRAPN, the size of the gas phase relative permeability at different microbubble concentrations is changed.

[0065] Step 3: Consider the influencing factors of microbubble flooding numerical simulation and optimize the injection and production parameters;

[0066] Based on the numerical simulation model of microbubble flooding established in step 2, the changes in cumulative oil production calculated by the model under different gas-liquid ratios, microbubble sizes, injection-production ratios and other conditions in the injected microbubbles are compared to optimize the injection-production parameters.

[0067] The present invention takes the Z well group in the test area as an example to carry out numerical simulation research on microbubble flooding, which includes 9 wells, one injection well and 8 production wells. The well group has been put into production since October 2000. After 20 years of production, its water content reaches 60%, which meets the requirements of numerical simulation research on microbubble flooding. The influence of different gas-liquid ratios, injection-production ratios and other factors on the oil recovery effect of low permeability reservoirs is now studied, and injection-production parameters are optimized to verify the feasibility of the method based on numerical simulation of microbubble flooding.

[0068] The working principle of the present invention is:

[0069] By injecting microbubbles into the reservoir, the physical properties of the reservoir are changed, which helps to improve the displacement efficiency. After the microbubbles are injected, they will migrate into the pore space of the low-permeability reservoir and accumulate in the pores to form bubble groups, thereby effectively blocking the water flow channel. This reduces the permeability of the water phase, slows down the migration speed of water, and increases the contact time and area between the microbubbles and the remaining oil, thereby improving the efficiency of displacing the remaining oil.

[0070] Example 1

[0071] In this embodiment 1, based on the numerical simulation model of microbubble flooding, the mechanism of expanding the swept volume, plugging pores and improving oil recovery efficiency is studied by comparing and analyzing the main controlling factors affecting the microbubble flooding effect. According to the microbubble flooding numerical simulation model established in the Z well group of the low permeability reservoir test area, the influence of multiple factors such as microbubble interpolation, gas-liquid ratio and injection-production ratio on microbubble flooding is studied. The main model parameters of this embodiment 1 are shown in Table 2.

[0072] Table 2. Main model parameters

[0073] Porosity 0.04 Crude oil density <![CDATA[812.54kg / m 3 ]]> Permeability 9.3mD Formation water viscosity 0.5cp Formation pressure 29.8MPa Crude oil viscosity 1.5cp Formation water density <![CDATA[1000kg / m 3 ]]> Fluid components <![CDATA[H2O、OIL、N2、MB]]>

[0074] 1) Comparison of recovery degree before and after the change of phase permeability curve.

[0075] The relationship between microbubble concentration and oil recovery efficiency is established. By interpolating the gas permeability by injecting microbubble concentration, the gas phase mobility is reduced, resulting in microbubbles entering the pore space of low-permeability reservoirs better, increasing the sweep coefficient, displacing the remaining oil in the pores, and improving the oil recovery efficiency.

[0076] Refer to Table 3. Figure 3 As shown in the figure, the microbubble flooding effect before and after the phase permeability curve changes is compared and analyzed. After the microbubble concentration is interpolated on the phase permeability curve, the stage oil production of the model is improved. Compared with before interpolation, the stage recovery degree is increased by 0.8%.

[0077] Table 3. Data comparison before and after the phase permeability curve changes

[0078] Phase permeability curve changes <![CDATA[Stage oil production (10 4 m 3 )]]> Stage recovery rate (%) Before the phase permeability curve changes 12.90 13.47 After the phase permeability curve changes 13.66 14.27

[0079] 2) Comparison of recovery degree at different gas-liquid ratios.

[0080] Changes in the number of microbubbles and plugging strength will affect the effect of improving the recovery degree. As the gas-liquid ratio increases, the number of generated microbubbles gradually increases, and the plugging strength of the formation pores gradually increases. The recovery degree increases first and then decreases as the injected gas-liquid ratio increases. When the gas-liquid ratio reaches 3, the apparent viscosity of the microbubbles is high, and the microbubble drive has good injectivity and plugging ability. The stage recovery degree reaches the highest. Continue to increase the gas-liquid ratio, and the stage recovery degree peak begins to decrease. When the gas-liquid ratio is too large, the stability of the microbubbles decreases, the probability of gas channeling during migration increases, the viscosity of the microbubbles decreases, and the plugging ability weakens. Therefore, the microbubbles generated under low gas-liquid ratio conditions can effectively prevent the premature breakthrough of the gas phase, increase the retention time of microbubbles in small pores, and play a more lasting oil displacement effect. Therefore, a large number of microbubbles can be generated under a suitable gas-liquid ratio to ensure good injectivity, effectively plug the water flow channel, and displace the remaining oil.

[0081] In this embodiment 1, different injection gas-liquid ratios are set to compare and analyze the oil recovery effect of microbubble flooding, and the simulated gas-liquid ratios are 1:4, 1:3, 1:2, 1:1, 2:1, and 3:1. As the gas-liquid ratio increases, the recovery rate increases first and then decreases, and the development effect is better when the gas-liquid ratio is 3:1.

[0082] Table 4. Recovery degree under different gas-liquid ratios

[0083] Gas-Liquid Ratio <![CDATA[Stage oil production (10 4 m 3 )]]> Stage recovery rate (%) 1：4 12.01 12.55 1：3 12.36 12.90 1：2 12.60 13.16 1：1 12.94 13.52 2：1 13.25 13.84 3：1 13.66 14.27 4：1 13.14 13.72

[0084] From Table 4, Figure 4 , Figure 5 It can be seen that when the gas-liquid ratio is 3:1, the stage recovery degree is 14.27, and the oil production increases by 13.66×10 4 m 3 The recovery rate is increased by 1.72% (15 years of production) compared with the gas-liquid ratio of 1:4, indicating that the recovery rate increases with the increase of gas-liquid ratio, and then decreases after increasing to a certain extent.

[0085] 3) Comparison of recovery degree under different injection-production ratios.

[0086] The injection-production ratio affects the injectability of microbubbles and their migration in the formation, and thus affects the effect of plugging pores. When the injection-production ratio is small, the number of microbubbles produced is small, the apparent viscosity is low, and the flow resistance is small; when the injection-production ratio increases, the number of microbubbles produced increases, the apparent viscosity of the microbubbles increases, and the flow resistance increases; when a certain injection-production ratio is reached, enough microbubbles are produced, and the shearing effect on the microbubbles increases. Because of the shear thinning of microbubbles, the apparent viscosity of the microbubbles is reduced, the flow resistance gradually decreases, and the oil displacement efficiency of the microbubbles is improved. This shows that a suitable injection-production ratio enhances the water-resistant ability of microbubbles in the reservoir, which is conducive to improving the effect of plugging pores.

[0087] This Example 1 also sets different injection-production ratios and simulates injection-production ratios of 0.8, 0.9, 1.0, 1.1, 1.2, and 1.3. As the value of the injection-production ratio increases, the degree of recovery first increases and then decreases. When the injection-production ratio is 1.0, the degree of recovery is slightly higher and the development effect is slightly better, as shown in Table 5.

[0088] Table 5. Recovery degree under different injection-production ratios

[0089] Injection-production ratio <![CDATA[Stage oil production (10 4 m 3 )]]> Stage recovery rate (%) 0.8 13.35 13.94 0.9 13.54 14.14 1.0 13.67 14.28 1.1 13.66 14.27 1.2 13.64 14.25

[0090] From Table 5, Figure 6 , Figure 7 It can be seen that when the injection-production ratio is 1:1, the stage recovery degree is 14.28, and the oil production increases by 13.67×10 4 m 3, the recovery rate is increased by 0.34% (15 years of production) compared with the injection-production ratio of 0.8. This shows that the recovery rate increases with the increase of the injection-production ratio, and then decreases after increasing to a certain extent.

[0091] It can be seen that the method of the present invention has shown significant effects of plugging pores and expanding the sweep coefficient, and is of great value in optimizing microbubble flooding process parameters and improving the development effect of low permeability reservoirs.

[0092] Example 2

[0093] For a certain oil and gas field No. 2, according to the above three steps of the present invention, with reference to the comparative method of Example 1, the effects of gas-liquid ratio and injection-production ratio on microbubble flooding were simulated, and the simulation results were as follows: when the gas-liquid ratio of injected microbubbles increased, the recovery rate first increased and then decreased, and the development effect was slightly better when the gas-liquid ratio was 3:1 (see Figure 8 , Fig. 9 ); With the increase of the injection-production ratio of microbubble flooding, the recovery rate first increases and then decreases. When the injection-production ratio is 1.0, the recovery rate is slightly higher and the development effect is slightly better (see Fig.10 , Fig.11 ).

[0094] It can be seen that the method of the present invention has shown significant effects of plugging pores and expanding the sweep coefficient, and is of great value in optimizing microbubble flooding process parameters and improving the development effect of low permeability reservoirs.

[0095] Example 3

[0096] For a certain 4# oil and gas field, according to the above three steps of the present invention, with reference to the comparison method of Examples 1 and 2, the influence of the gas-liquid ratio and the injection-production ratio on the microbubble injection effect is studied, and the simulation results are as follows: when the gas-liquid ratio of the injected microbubble is increased, the recovery degree first increases and then decreases. When the gas-liquid ratio is 3:1, the development effect is slightly better (see Fig.12 , Fig.13 ); With the increase of the injection-production ratio of microbubble flooding, the recovery rate first increases and then decreases. When the injection-production ratio is 1.0, the recovery rate is slightly higher and the development effect is slightly better (see Fig.14 , Fig.15 ).

[0097] It can be seen that the patented technology of the present invention has a significant effect of plugging pores and expanding the sweep coefficient, and is of great value in optimizing microbubble flooding process parameters and improving the development effect of low permeability reservoirs.

[0098] Example 4

[0099] For a certain 9# oil and gas field, according to the aforementioned steps and processes, with reference to the comparison methods of Examples 1, 2, and 3, the simulation results are as follows: when the ratio of the gas-liquid ratio of the injected microbubbles is increased, the recovery rate increases first and then decreases. When the gas-liquid ratio is 3:1, the development effect is slightly better (see Fig.16 , Fig.17 ); With the increase of the injection-production ratio of microbubble flooding, the recovery rate first increases and then decreases. When the injection-production ratio is 1.0, the recovery rate is slightly higher and the development effect is slightly better (see Fig.18 , Fig.19 ).

[0100] Therefore, the feasibility of the microbubble flooding numerical simulation method of the present invention is verified by the comparative analysis of the injection and production parameters of the above four embodiments. The principle of the method of the present invention is that microbubbles can enter different pore structures step by step, and they preferentially occupy large pores, thereby increasing the seepage resistance to achieve the plugging effect, reducing the gas phase mobility, and subsequent microbubbles enter small pores, thereby expanding the sweep coefficient, reducing the residual oil saturation, and displacing the remaining oil in the pores. Therefore, the method of the present invention is very suitable for low-permeability reservoirs with medium and high water content, which is of great significance for improving the recovery rate of low-permeability reservoir development.

Claims

1. A numerical simulation method based on microbubble flooding, characterized in that: Follow these steps to implement: Step 1, constructing a microbubble flooding phase permeability correction model; Step 2, establishing a numerical simulation model for microbubble flooding; Step 3: Consider the influencing factors of microbubble flooding numerical simulation and optimize the injection and production parameters.

2. The numerical simulation method based on microbubble flooding according to claim 1, characterized in that: In step 1, the specific process is: The numerical simulation of microbubble flooding takes into account that after microbubbles are injected, they enter more pores in the formation, thus increasing the sweep coefficient. At the same time, since nano-scale microbubbles enter the pore space of low-permeability reservoirs with the migration of fluids, microbubbles enter small pores and displace the remaining oil in the tiny pores, thus reducing the residual oil saturation and improving the oil recovery efficiency. This step draws on the empirical foam flooding principle, interpolates the relative permeability curve according to the microbubble concentration of different grids, and establishes the relationship between microbubble concentration and oil recovery efficiency.

3. The numerical simulation method based on microbubble flooding according to claim 2, characterized in that: In step 1, the specific process is: The flow characteristics of microbubble flooding are simulated by changing the gas phase fluidity by reducing the gas phase relative permeability. The degree of fluidity reduction is specified by the fluid reduction factor MRF, which is related to the gas phase permeability and viscosity in the microbubble and no microbubble states. The following formulas (1), (2) and (3) are respectively the liquid phase permeability model, the gas phase relative permeability model in the non-microbubble state, and the gas phase relative permeability model in the microbubble state, and the expressions are as follows: Among them, K rw (S w ) is the liquid relative permeability model, S w is the water saturation, S wc is the bound water saturation, S gr is the residual gas saturation, A and m 1 All are relative permeability parameters of corey-type liquids; in, is the gas phase relative permeability model in the absence of microbubbles, B and m 2 All are relative permeability parameters of corey-type gases; in, is the gas phase relative permeability model in the microbubble state, X mb is the microbubble concentration of the flow; The following formula (4) is the mobility reduction factor MRF that changes the gas phase permeability after injecting microbubbles. The expression is as follows: Where MRF is the fluid reduction factor; is the relative permeability of the gas phase in the absence of microbubbles, is the relative permeability of the gas phase in the microbubble state; is the gas phase viscosity in the microbubble state; It is the gas phase viscosity in the absence of microbubbles; The following formulas (5) and (6) are important formulas for the correction of gas phase relative permeability in this step, indicating that the gas phase permeability is significantly different when microbubbles (MB) are present and when there are no microbubbles, and the size of the permeability changes according to the concentration of microbubbles. The expressions are as follows: Among them, K rg (S w ) is the relative permeability of the gas, is the gas phase relative permeability model in the microbubble state, and MRF is the fluid reduction factor; Among them, Kr is the phase permeability interpolation, is the corresponding phase permeability curve under the microbubble state, is the relative permeability of the gas phase in the state without microbubbles, X is the equivalent fraction in a certain microbubble state in the injected gas, α(MB)0 is the equivalent fraction of microbubbles in the state without microbubbles, and α(MB)1 is the equivalent fraction of microbubbles in the state with microbubbles; The phase permeability model under different microbubble concentrations was established using formula (6), which reveals that under different microbubble concentrations, the corresponding oil-water two-phase phase permeability curves have different residual oil saturations at the phase permeability endpoints, thus establishing the relationship between microbubble concentration and oil recovery efficiency.

4. The numerical simulation method based on microbubble flooding according to claim 1, characterized in that: In step 2, the specific process is: Step 1 corrects the flow model of microbubbles to more accurately describe the flow process of microbubbles in the formation; on this basis, the generation and collapse reactions of microbubbles are constructed, thereby establishing a complete numerical simulation model of microbubble flooding.

5. The numerical simulation method based on microbubble flooding according to claim 4 is characterized in that: In step 2, the specific process is: A numerical simulation model for microbubble flooding was established with a model grid of 13×12×4. The model includes porosity, permeability, formation pressure, physical parameters of crude oil density, phase state and related reaction components. Among them, the phase states adopt oil, gas and water phases; the model components include H2O, OIL, N2 and microbubbles; Formula (7) is the reaction formula for the process of microbubble generation, where microbubbles are generated by the reaction of injected nitrogen and water; Formula (8) is the reaction formula for the process of microbubble collapse and decomposition into water and nitrogen, which is equivalent to the reverse process of Formula (7), and is expressed as follows: H2O+N2→MB (7) MB→H2O+N2(8) The following formula (9) describes the reaction rate of microbubbles, which is expressed as follows: Among them, k d is the microbubble reaction rate constant; t 1 / 2 is the reaction time of microbubbles.

6. The numerical simulation method based on microbubble flooding according to claim 4, characterized in that: In step 2, the specific process is: By setting an interpolation table in the phase permeability correction model of microbubble flooding, this step uses the gas phase "MB" component interpolation, and the interpolation parameters are implemented by the keyword *DTRAPN. In Table 1 below, an interpolation table of gas phase permeability with different microbubble concentrations in the gas phase is given. By adjusting the value of the interpolation keyword *DTRAPN, the relative permeability of the gas phase at different microbubble concentrations can be changed. Table 1. Interpolation table of gas phase relative permeability 7. The numerical simulation method based on microbubble flooding according to claim 6, characterized in that: In step 3, the specific process is: Based on the numerical simulation model of microbubble flooding established in step 2, the changes in cumulative oil production calculated by the model under different gas-liquid ratios, microbubble sizes, and injection-production ratios in the injected microbubbles are compared to optimize the injection-production parameters.

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