Numerical simulation method for viscosity reduction and pressure drive of heavy oil reservoir

Abstract

This invention provides a numerical modeling method for viscosity-reducing pressure flooding in heavy oil reservoirs. The method includes: Step 1: determining the relationship between the viscosity-reducing rate and the concentration of the viscosity-reducing agent; Step 2: performing numerical modeling characterization of the viscosity-reducing agent's performance; Step 3: characterizing the microfracture characteristics of the reservoir; Step 4: fitting the fracturing data to obtain the relative permeability curves corresponding to the microfracture opening and closing pressures; Step 5: calculating the current reservoir pressure, and then interpolating the relative permeability curves based on the reservoir pressure value to determine the relative permeability curves of the current reservoir state; Step 6: calculating the flow and distribution of oil and water in the reservoir during viscosity-reducing pressure flooding, thus achieving numerical modeling characterization of viscosity-reducing pressure flooding in heavy oil reservoirs. This numerical modeling method for viscosity-reducing pressure flooding in heavy oil reservoirs provides support for the numerical modeling optimization of injection parameters for the development of viscosity-reducing pressure flooding in heavy oil reservoirs.

Description

Technical Field

[0001] This invention relates to the field of oilfield development technology, and in particular to a numerical model characterization method for viscosity-reducing pressure drive of heavy oil reservoirs. Background Technology

[0002] Shengli Oilfield has abundant heavy oil reservoir resources, but problems such as "small affected area, rapid increase in water cut, and low oil well fluid volume" seriously restrict the development effect of heavy oil reservoirs.

[0003] In the development of heavy oil reservoirs using viscosity reduction and displacement, the displacement phase is prone to migrate along deep bands due to the viscosity ratio between the displacing and substitutable phases. This results in a small effective sweep area, rapid water cut increase in wells, and poor displacement effect. Furthermore, heavy oil reservoirs have high start-up pressures, requiring the loss of some pressure differential between injection and production wells to overcome these pressures. This leads to a smaller effective displacement pressure differential, lower well fluid volume, and consequently, reduced well productivity. Therefore, in-depth research is needed to explore methods to significantly improve the utilization rate of heavy oil reservoirs and achieve economical and efficient development.

[0004] Viscosity-reducing pressure drive involves injecting a large amount of water-soluble viscosity-reducing agent solution into a heavy oil reservoir at extremely high injection rates within a short period. This rapidly increases the formation pressure coefficient while simultaneously reducing the viscosity of the heavy oil, creating artificial high pressure within the reservoir to overcome the initiation pressure between injection and production wells. This, in turn, increases the effective displacement pressure differential and improves the well fluid volume. Because the injection pressure of viscosity-reducing pressure drive is close to the formation fracturing pressure, numerous network-like microfractures form near the injection well during the injection process and continuously and uniformly extend into the formation. The viscosity-reducing agent solution penetrates deeper into the reservoir along with these microfractures, expanding the reach of the viscosity-reducing system. Furthermore, the microfractures formed by viscosity-reducing pressure drive effectively reduce the adverse effects of reservoir heterogeneity, promoting the balanced advancement of the viscosity-reducing system.

[0005] Chinese patent application CN201710615404.5 relates to a numerical simulation method for chemical flooding in heavy oil reservoirs, including: parameter collection; calculation and processing methods for establishing numerical model parameters characterizing the oil displacement mechanism of heavy oil chemical flooding; defining a multi-component, multi-phase model; establishing an indoor experimental-scale numerical simulation model for heavy oil chemical composite flooding using the size, physical properties, and fluid properties of core or sand-filled models from indoor physical simulation experiments, and correcting the parameters of the numerical model characterizing the oil displacement mechanism of heavy oil chemical flooding; importing the three-dimensional reservoir geological model and actual mine production data into the pre-fitted indoor experimental-scale numerical simulation model for heavy oil chemical composite flooding, and establishing a mine-scale three-dimensional numerical simulation model for heavy oil chemical composite flooding. This invention lays the foundation for conducting numerical simulations to predict the field application effects of heavy oil reservoir chemical composite flooding, and while improving the quantitative characterization model of the oil displacement mechanism of heavy oil chemical composite flooding, it provides a theoretical basis for exploring the application of heavy oil chemical composite flooding.

[0006] Chinese patent application CN201310668360.4 discloses a numerical simulation method for a heterogeneous composite flooding system. This method includes: solving the water phase pressure equation and the oil phase pressure equation; solving the phase saturation equation and the mass conservation equation for each component, calculating the concentration of pre-crosslinked gel particles at the current time step; interpolating the residual drag coefficient curve of the pre-crosslinked gel particles to calculate the residual drag coefficient of the pre-crosslinked gel particles at the current time step; calculating the viscosity of the pre-crosslinked gel particle suspension; and correcting Darcy's law for the mobility coefficient, calculating the water phase flow velocity according to Darcy's law, then proceeding to the next time step to calculate the phase pressure equation, until the heterogeneous composite flooding simulation ends. This numerical simulation method for a heterogeneous composite flooding system establishes a mathematical model describing the plugging and profile control, and migration and displacement characteristics of heterogeneous composite flooding, and proposes a numerical simulation method to effectively characterize the displacement mechanism of pre-crosslinked gel particles.

[0007] Chinese patent application CN202010176052.X discloses a numerical simulation method for multi-element thermal fluid reservoir recovery. The method involves three steps: Step 1: Conducting a PVT experiment to obtain the PR-EOS equation of state for the multi-element thermal fluid; deriving the phase diagram of the multi-element thermal fluid-heavy oil system based on this equation; Step 2: Conducting a reservoir damage assessment experiment to establish a mathematical model of reservoir damage using the multi-element thermal fluid; Step 3: Using the novel PR-EOS equation of state and reservoir damage mathematical model obtained in Steps 1 and 2, establishing a numerical simulation method for the multi-element thermal fluid, and implementing it through programming to obtain a multi-element thermal fluid numerical simulator; obtaining multiple construction schemes for multi-element thermal fluid recovery under different conditions through the numerical simulator, comparing them, and obtaining the optimal scheme. Using this method, the problem that existing numerical simulation methods for multi-element thermal fluid reservoir recovery cannot accurately describe the phase characteristics of multi-element thermal fluids and the damage caused by multi-element thermal fluids to the reservoir can be effectively solved.

[0008] In the development of viscosity-reducing pressure-driven flooding, numerical simulation is the most important means to predict the dynamics of viscosity-reducing pressure-driven flooding. However, there is currently no mature method for numerical modeling characterization of viscosity-reducing pressure-driven flooding. To address this, we have invented a numerical modeling characterization method for viscosity-reducing pressure-driven flooding in heavy oil reservoirs, which solves the aforementioned technical problem. Summary of the Invention

[0009] The purpose of this invention is to provide a numerical modeling method for viscosity-reducing pressure drive of heavy oil reservoirs, which determines the flow and distribution of oil and water in the reservoir and predicts the production dynamics of the reservoir.

[0010] The objective of this invention can be achieved through the following technical measures: a method for calculating the optimal water injection rate for reservoir pressure flooding development, wherein the numerical model characterization method for viscosity-reducing pressure flooding of heavy oil reservoirs includes:

[0011] Step 1: Determine the relationship between the viscosity reduction rate of the viscosity reducer and the concentration of the viscosity reducer;

[0012] Step 2: Perform numerical model characterization on the performance of the viscosity reducer;

[0013] Step 3: Characterize the features of microfractures in the reservoir;

[0014] Step 4: Fit the fracturing data to obtain the relative permeability curves corresponding to the microcrack opening pressure and closing pressure;

[0015] Step 5: Calculate the current reservoir pressure, and then interpolate the relative permeability curve based on the reservoir pressure value to determine the relative permeability curve of the current reservoir state;

[0016] Step 6: Calculate the flow and distribution of oil and water in the reservoir during the viscosity reduction pressure drive process to achieve numerical model characterization of viscosity reduction pressure drive in heavy oil reservoirs.

[0017] The objective of this invention can also be achieved through the following technical measures:

[0018] In step 1, the relationship between the viscosity reduction rate and the concentration of the viscosity reducer needs to be determined experimentally; the relationship between the viscosity reduction rate and the concentration of the viscosity reducer has the following form:

[0019] F = a × ln(c) + b

[0020] Where F is the viscosity reduction rate of the viscosity reducer, c is the concentration of the viscosity reducer, and a and b are coefficients.

[0021] In step 2, the experimental results from step 1 are fitted, and the fitting results are converted into a nonlinear viscosity reduction coefficient table to characterize the viscosity reducer performance using a numerical model.

[0022] In step 2, the nonlinear viscosity reduction coefficient table has the following form:

[0023] Viscosity reduction <![CDATA[F1]]> <![CDATA[F2]]> …… <![CDATA[F 10 ]]> <![CDATA[F 11 ]]>

[0024] In step 3, based on the small-scale fracturing data from the oilfield, the fracture opening pressure and fracture closing pressure when microfractures are generated in the reservoir, as well as the reservoir permeability under the open and closed states of microfractures, are obtained.

[0025] In step 3, the opening pressure Pmax, closing pressure Pmin, and reservoir permeability, which characterize the microfracture state, are obtained from small-scale fracturing data in this block.

[0026] In step 4, the small-scale fracturing data from step 3 are fitted to obtain the relative permeability curves corresponding to the fracture open state and the fracture closed state, respectively.

[0027] In step 5, the current reservoir pressure is calculated based on the viscosity-reducing pressure drive parameters. Then, the relative permeability curve is interpolated based on the reservoir pressure value to determine the relative permeability curve of the current reservoir state.

[0028] In step 5, the current reservoir pressure Pr is calculated based on the viscosity-reducing pressure drive parameters. Based on the relationship between the calculated Pr and the opening pressure Pmax and closing pressure Pmin, as well as the relative permeability curves under fracture opening and fracture closing conditions, the relative permeability curve corresponding to the current reservoir pressure Pr is calculated by interpolation.

[0029] In step 5, the relationship between the current reservoir pressure Pr and the opening pressure Pmax and closing pressure Pmin is as follows:

[0030] α=(Pr-Pmin) / (Pmax-Pmin)

[0031] Where α is the dimensionless coefficient corresponding to the current reservoir pressure.

[0032] In step 6, by coupling the viscosity reducer performance parameters in step 2 and the current reservoir phase permeability curve in step 5, the flow and distribution of oil and water in the reservoir during the viscosity reduction pressure drive process are calculated, thereby realizing the numerical model characterization of the viscosity reduction pressure drive of heavy oil reservoir.

[0033] This invention discloses a numerical modeling method for viscosity-reducing pressure-driven heavy oil reservoirs. The method determines the performance parameters of a viscosity reducer through experiments and then uses numerical simulation to characterize the viscosity reducer's performance. Based on small-scale fracturing data from the oilfield, it determines the opening and closing pressures of microfractures and the permeability under different conditions, describing the characteristics of the microfractures. Furthermore, it obtains relative permeability curves under different conditions through numerical simulation. The viscosity-reducing pressure-driven flooding parameters are input into the numerical modeling software to calculate the reservoir pressure. The relative permeability curves are then interpolated based on the pressure to determine the seepage parameters. Finally, the viscosity reducer performance parameters and seepage parameters are coupled in the numerical model to calculate the flow and distribution of oil and water in the reservoir during viscosity-reducing pressure-driven flooding, thus achieving numerical modeling characterization of viscosity-reducing pressure-driven flooding in heavy oil reservoirs. This provides support for the numerical modeling optimization of injection parameters for viscosity-reducing pressure-driven flooding development in heavy oil reservoirs. Attached Figure Description

[0034] Figure 1 This is a flowchart illustrating a specific example of a numerical model characterization method for viscosity-reducing pressure flooding of heavy oil reservoirs according to the present invention;

[0035] Figure 2 This is a graph showing the relationship between the viscosity reduction rate of the viscosity reducer and the viscosity reducer concentration in a specific embodiment of the present invention.

[0036] Figure 3 In a specific embodiment of the present invention, a schematic diagram of the relative permeability curves corresponding to the microfracture closure pressure and the microfracture opening pressure, and the relative permeability curve calculated by reservoir pressure interpolation is shown.

[0037] Figure 4 This is a graph showing the relationship between the viscosity reduction rate of the viscosity reducer and the viscosity reducer concentration in another specific embodiment of the present invention;

[0038] Figure 5 In another specific embodiment of the present invention, a schematic diagram of the relative permeability curves corresponding to the microcrack closure pressure and the microcrack opening pressure, and the relative permeability curve calculated by reservoir pressure interpolation. Detailed Implementation

[0039] To make the above and other objects, features and advantages of the present invention more apparent and understandable, preferred embodiments are described below in detail with reference to the accompanying drawings:

[0040] This invention provides a numerical model characterization method for viscosity-reducing pressure flooding in heavy oil reservoirs, comprising:

[0041] Step 1: Experimentally determine the relationship between the viscosity reduction rate of the viscosity reducer and the concentration of the viscosity reducer;

[0042] Step 2: Fit the experimental results from Step 1 using reservoir numerical simulation software, and convert the fitting results into a nonlinear viscosity reduction coefficient table to characterize the viscosity reducer performance using numerical modeling.

[0043] Step 3: Based on the small-scale fracturing data from the oilfield, obtain the fracture opening pressure and fracture closing pressure when microfractures are generated in the reservoir, as well as the reservoir permeability under the conditions of microfracture opening and closing.

[0044] Step 4: Fit the fracturing data using reservoir numerical simulation software to obtain the relative permeability curves corresponding to the microfracture opening pressure and closing pressure;

[0045] Step 5: Input the viscosity-reducing pressure drive parameters into the numerical simulation software, calculate the current reservoir pressure, and then interpolate the relative permeability curve based on the reservoir pressure value to determine the relative permeability curve of the current reservoir state.

[0046] Step 6: By coupling the viscosity reducer performance parameters in Step 2 and the reservoir phase permeability curve in Step 5 with numerical simulation software, calculate the flow and distribution of oil and water in the reservoir during the viscosity reduction pressure drive process, and realize the numerical model characterization of viscosity reduction pressure drive in heavy oil reservoirs.

[0047] This numerical modeling method for viscosity-reducing pressure-driven heavy oil reservoirs determines the performance parameters of viscosity reducers experimentally and then uses numerical simulations to characterize the viscosity reducer performance. Based on small-scale fracturing data from the oilfield, the opening and closing pressures of microfractures and the permeability under different conditions are determined to describe the characteristics of microfractures. Relative permeability curves under different conditions are then obtained through numerical simulations. Viscosity-reducing pressure-driven flooding parameters are input into the numerical modeling software to calculate the reservoir pressure. The relative permeability curves are then interpolated based on the pressure to determine the seepage parameters. Finally, the viscosity reducer performance parameters and seepage parameters are coupled in the numerical model to calculate the flow and distribution of oil and water in the reservoir during viscosity-reducing pressure-driven flooding, thus achieving numerical modeling characterization of viscosity-reducing pressure-driven flooding in heavy oil reservoirs. This provides support for the numerical modeling optimization of reasonable injection parameters in the development of viscosity-reducing pressure-driven flooding in heavy oil reservoirs.

[0048] The following are several specific embodiments of the application of the present invention.

[0049] Example 1

[0050] In a specific embodiment 1 of the present invention, the numerical model characterization method for viscosity-reducing pressure drive of heavy oil reservoir includes the following steps:

[0051] In step 1, the relationship between the viscosity reduction rate and the viscosity reducer concentration was experimentally determined. The relationship between the viscosity reduction rate and the viscosity reducer concentration has the following form:

[0052] F = a × ln(c) + b

[0053] Where F is the viscosity reduction rate of the viscosity reducer, c is the concentration of the viscosity reducer, and a and b are coefficients.

[0054] In step 2, the experimental results from step 1 are fitted using reservoir numerical simulation software, and the fitting results are converted into a nonlinear viscosity reduction coefficient table to numerically characterize the viscosity reducer's performance. The nonlinear viscosity reduction coefficient table has the following form:

[0055] Viscosity reduction <![CDATA[F1]]> <![CDATA[F2]]> …… <![CDATA[F 10 ]]> <![CDATA[F 11 ]]>

[0056] In step 3, based on the small-scale fracturing data of the oilfield, the fracture opening pressure Pmax and fracture closing pressure Pmin when the reservoir microfractures are generated, as well as the reservoir permeability under the open and closed states of the microfractures, are obtained to characterize the reservoir microfractures.

[0057] In step 4, the fracturing data is fitted using reservoir numerical simulation software to obtain the relative permeability curves corresponding to the microfracture opening pressure and closing pressure.

[0058] In step 5, the viscosity-reducing pressure drive parameters are input into the numerical modeling software to calculate the current reservoir pressure Pr, and the relationship between Pr and the opening pressure Pmax and closing pressure Pmin is determined:

[0059] α=(Pr-Pmin) / (Pmax-Pmin)

[0060] Then, the Krow relative permeability curve corresponding to the current reservoir pressure is calculated by interpolation:

[0061] Krow = Kmin + α × (Kmax - Kmin)

[0062] Wherein, Krow is the relative permeability curve under the current reservoir pressure, Kmin is the relative permeability curve corresponding to the microfracture closure pressure Pmin, and Kmax is the relative permeability curve corresponding to the microfracture initiation pressure Pmax.

[0063] In step 6, the viscosity reducer performance parameters in step 2 and the current reservoir phase permeability curve in step 5 are coupled using numerical simulation software to calculate the flow and distribution of oil and water in the reservoir during the viscosity reduction pressure drive process, thereby realizing the numerical model characterization of the viscosity reduction pressure drive of heavy oil reservoirs.

[0064] Example 2

[0065] In a specific embodiment 2 of the present invention, such as Figure 1 As shown, Figure 1 This is a flowchart of a numerical model characterization method for viscosity-reducing pressure flooding in heavy oil reservoirs. The numerical model characterization method for viscosity-reducing pressure flooding in heavy oil reservoirs of this invention includes:

[0066] In step 101, the relationship between the viscosity reduction rate and the viscosity reducer concentration was experimentally determined. The relationship between the viscosity reduction rate and the viscosity reducer concentration is as follows: Figure 2 As shown, there is a relationship between the viscosity reduction rate and the viscosity reducer concentration:

[0067] F = 43.56 × ln(c) + 101.51

[0068] Where F is the viscosity reduction rate of the viscosity reducer, and c is the concentration of the viscosity reducer.

[0069] In step 102, the experimental results from step 1 are fitted using reservoir numerical simulation software, and the fitting results are converted into a nonlinear viscosity reduction coefficient table to characterize the viscosity reducer's performance using numerical modeling. The nonlinear viscosity reduction coefficient table is shown in Table 1.

[0070] Table 1 shows the nonlinear viscosity reduction coefficients obtained from the combined numerical simulation and experimental results.

[0071] Viscosity reduction rate (frac) 0.000 0.421 0.486 0.656 0.689 0.728 0.801 0.890 0.927 0.965 1.000

[0072] In step 103, based on the small-scale fracturing data of the oilfield, the fracture opening pressure Pmax when the oil reservoir microfractures are generated is 42 MPa, the fracture closing pressure Pmin is 27 MPa, and the oil reservoir permeability under the microfracture opening state is 3720 mD, and the oil reservoir permeability under the microfracture closing state is 670 mD.

[0073] In step 104, the fracturing data is fitted using reservoir numerical simulation software to obtain the relative permeability curves corresponding to the microfracture opening and closing pressures, such as... Figure 3 As shown.

[0074] In step 105, the viscosity-reducing pressure drive parameters are input into the numerical modeling software to calculate the current reservoir pressure of 36 MPa, and the relationship between the current reservoir pressure and the opening pressure of 42 MPa and the closing pressure of 27 MPa is determined:

[0075] α=(Pr-Pmin) / (Pmax-Pmin)=(36-27) / (42-27)=0.6

[0076] Then, interpolation is used to calculate the relative permeability curve corresponding to the current reservoir pressure. The calculated relative permeability curve is as follows: Figure 3 As shown.

[0077] In step 106, the viscosity reducer performance parameters in step 102 and the current reservoir phase permeability curve in step 105 are coupled using numerical simulation software to calculate the flow and distribution of oil and water in the reservoir during viscosity reduction pressure drive, thereby realizing the numerical model characterization of viscosity reduction pressure drive in heavy oil reservoirs.

[0078] Example 3

[0079] In a specific embodiment 3 of the present invention, such as Figure 1 As shown, Figure 1 This is a flowchart of a numerical model characterization method for viscosity-reducing pressure flooding in heavy oil reservoirs. The numerical model characterization method for viscosity-reducing pressure flooding in heavy oil reservoirs of this invention includes:

[0080] In step 101, the relationship between the viscosity reduction rate and the viscosity reducer concentration was experimentally determined. The relationship between the viscosity reduction rate and the viscosity reducer concentration is as follows: Figure 4 As shown, there is a relationship between the viscosity reduction rate and the viscosity reducer concentration:

[0081] F = 26.45 × ln(c) + 101.64

[0082] Where F is the viscosity reduction rate of the viscosity reducer, and c is the concentration of the viscosity reducer.

[0083] In step 102, the experimental results from step 1 are fitted using reservoir numerical simulation software, and the fitting results are converted into a nonlinear viscosity reduction coefficient table to characterize the viscosity reducer's performance using numerical modeling. The nonlinear viscosity reduction coefficient table is shown in Table 2.

[0084] Table 2 shows the nonlinear viscosity reduction coefficients obtained from the combined numerical simulation and experimental results.

[0085] Viscosity reduction rate (frac) 0.000 0.378 0.594 0.699 0.813 0.857 0.901 0.933 0.946 0.965 0.983

[0086] In step 103, based on the small-scale fracturing data of the oilfield, the fracture opening pressure Pmax when the oil reservoir microfractures are generated is 48.2 MPa, the fracture closing pressure Pmin is 30.7 MPa, and the oil reservoir permeability under the microfracture opening state is 2880 mD, and the oil reservoir permeability under the microfracture closing state is 420 mD.

[0087] In step 104, the fracturing data is fitted using reservoir numerical simulation software to obtain the relative permeability curves corresponding to the microfracture opening and closing pressures, such as... Figure 5 As shown.

[0088] In step 105, the viscosity-reducing pressure drive parameters are input into the numerical simulation software to calculate the current reservoir pressure of 42.4 MPa, and the relationship between the current reservoir pressure and the opening pressure of 48.2 MPa and the closing pressure of 30.7 MPa is determined:

[0089] α=(Pr-Pmin) / (Pmax-Pmin)=(42.4-30.7) / (48.2-30.7)=0.67

[0090] Then, interpolation is used to calculate the relative permeability curve corresponding to the current reservoir pressure. The calculated relative permeability curve is as follows: Figure 5 As shown.

[0091] In step 106, the viscosity reducer performance parameters in step 102 and the current reservoir phase permeability curve in step 105 are coupled using numerical simulation software to calculate the flow and distribution of oil and water in the reservoir during viscosity reduction pressure drive, thereby realizing the numerical model characterization of viscosity reduction pressure drive in heavy oil reservoirs.

[0092] Based on viscosity reducer performance evaluation experiments and small-scale fracturing data in the oilfield, this invention calculates the reservoir pressure during the viscosity reduction and pressure drive process, combines the relative permeability curves under the opening and closing states of microfractures, and obtains the relative permeability curve of the current state of the reservoir by interpolation calculation. Coupled with the nonlinear viscosity reduction coefficient that characterizes the viscosity reducer performance, the flow and distribution state of oil and water in the reservoir is determined, and the production dynamics of the reservoir are predicted.

[0093] Finally, it should be noted that the above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

[0094] Except for the technical features described in the specification, all other technologies are known to those skilled in the art.

Claims

1. A numerical model characterization method for viscosity-reducing pressure flooding in heavy oil reservoirs, characterized in that, The numerical model characterization method for viscosity reduction and pressure flooding of heavy oil reservoirs includes: Step 1: Determine the relationship between the viscosity reduction rate of the viscosity reducer and the concentration of the viscosity reducer; Step 2: Perform numerical model characterization on the performance of the viscosity reducer; Step 3: Characterize the features of microfractures in the reservoir; Step 4: Fit the fracturing data to obtain the relative permeability curves corresponding to the microcrack opening pressure and closing pressure; Step 5: Calculate the current reservoir pressure, and then interpolate the relative permeability curve based on the reservoir pressure value to determine the relative permeability curve of the current reservoir state; Step 6: Calculate the flow and distribution of oil and water in the reservoir during the viscosity reduction pressure drive process to achieve numerical model characterization of viscosity reduction pressure drive in heavy oil reservoirs; In step 1, the relationship between the viscosity reduction rate and the concentration of the viscosity reducer needs to be determined experimentally. The relationship between the viscosity reduction rate and the concentration of the viscosity reducer has the following form: F = a × ln(c) + b; Where F is the viscosity reduction rate of the viscosity reducer, c is the concentration of the viscosity reducer, and a and b are coefficients; In step 2, the experimental results from step 1 are fitted, and the fitting results are converted into a nonlinear viscosity reduction coefficient table to characterize the viscosity reducer's performance using numerical modeling. The nonlinear viscosity reduction coefficient table has the following form: ； In step 3, based on the small-scale fracturing data of the oilfield, the fracture opening pressure Pmax and fracture closing pressure Pmin when the reservoir microfractures are generated are obtained, as well as the reservoir permeability under the microfracture opening and closing states. In step 4, the small-scale fracturing data from step 3 are fitted to obtain the relative permeability curves corresponding to the fracture open state and the fracture closed state, respectively. In step 5, the current reservoir pressure Pr is calculated based on the viscosity-reducing pressure drive parameters. Based on the relationship between the calculated Pr and the opening pressure Pmax and closing pressure Pmin, as well as the relative permeability curves under fracture open and closed conditions, the relative permeability curve corresponding to the current reservoir pressure Pr is calculated through interpolation. The relationship between the current reservoir pressure Pr and the opening pressure Pmax and closing pressure Pmin is as follows: α = (Pr - Pmin) / (Pmax - Pmin); Where α is the dimensionless coefficient corresponding to the current reservoir pressure; In step 6, by coupling the viscosity reducer performance parameters in step 2 and the current reservoir phase permeability curve in step 5, the flow and distribution of oil and water in the reservoir during the viscosity reduction pressure drive process are calculated, thereby realizing the numerical model characterization of the viscosity reduction pressure drive of heavy oil reservoir.

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