Numerical simulation characterization method and system based on low-permeability oilfield pressure flooding oil increment mechanism

Abstract

The application discloses a kind of numerical simulation characterization method and system based on low-permeability oilfield pressure flooding oil-increasing mechanism, it is related to oil and gas field development technical field, including: based on the full stress tensor of target low-permeability oilfield, establish fluid pressure-ground stress-property coupling equation group, calculate the time-varying porosity field, time-varying permeability field and pressure flooding crack dynamic expansion parameter of target low-permeability oilfield;Based on the long-term flow conductivity test experimental data of crack, establish the crack flow conductivity attenuation function of target low-permeability oilfield;Based on the non-steady-state method relative permeability curve test experimental data and mercury injection experimental data, respectively establish the dynamic phase trapping curve control function and dynamic capillary force curve control function of target low-permeability oilfield;Establish the numerical simulation model of target low-permeability oilfield, carry out numerical simulation characterization to the oil-increasing mechanism in the process of pressure flooding of target low-permeability oilfield.The application alleviates the technical problems that the prior art lacks coupling characterization means for multiple pressure flooding oil-increasing mechanisms.

Description

Technical Field

[0001] The present invention relates to the technical field of oil and gas field development, and in particular to a numerical simulation characterization method and system based on a pressure-driven oil-increasing mechanism in a low-permeability oil field. Background Art

[0002] Low-permeability oil reservoirs have abundant reserves, but their reservoir properties are poor and pressure transmission is slow. Conventional fracturing, water flooding, and chemical flooding methods have led to a series of problems, including generally poor inter-well connectivity, slow energy replenishment, low single-well productivity, and poor development results. In response to this situation, domestic oil and gas companies have proposed integrated fracturing and oil recovery technology, also known as "pressure drive," through technical research. Pressure drive technology is an oil reservoir development technology that organically combines single-well fracturing production enhancement technology, conventional water flooding development technology, and chemical oil recovery technology. Through hydraulic fracturing equipment, clean water and oil recovery agents are injected into the formation at high pressure and high speed, rapidly replenishing reservoir energy and increasing reservoir pressure in a short period of time. This allows for the opening of micro-cracks, increased porosity and permeability, imbibition and oil replacement, and oil recovery by oil recovery agents, among other pressure drive mechanisms, to improve the recovery rate of low-permeability oil reservoirs.

[0003] Pressure flooding is a reservoir development and production enhancement technology that utilizes multiple coupled mechanisms to increase oil production. High-volume, high-pressure water injection increases pore fluid pressure around the wellbore, replenishing formation energy, expanding pore size, and improving reservoir permeability. When the injection pressure approaches the formation's fracture pressure, natural microfractures and cracks near the wellbore open, allowing the injected water to penetrate deeper into the reservoir, effectively expanding the affected area and the contact surface between the injected water and the formation crude oil, enhancing the effects of imbibition and oil replacement, as well as the oil displacement agent's oil-washing effect.

[0004] The key to pressure-driven oil production lies in optimizing the injection parameters. Clarifying the applicable scopes and extent of oil production enhancement for different pressure-driven oil production mechanisms plays a crucial role in guiding parameter optimization. Current research on pressure-driven oil production mechanisms lags significantly behind field practice. Pressure-driven process design is primarily based on empirical experience, with no specific numerical simulation methods for pressure-driven oil production, and a lack of coupled characterization tools for multiple pressure-driven oil production mechanisms. Summary of the Invention

[0005] The purpose of the present invention is to provide a numerical simulation characterization method and system based on the pressure-driven oil-increasing mechanism in low-permeability oil fields in order to solve at least one of the above technical problems.

[0006] In the first aspect, an embodiment of the present invention provides a numerical simulation characterization method based on the pressure-driven oil-increasing mechanism of a low-permeability oil field, which is applied to a target low-permeability oil field; the method comprises: establishing a fluid pressure-ground stress-physical property coupling equation group based on the full stress tensor of the target low-permeability oil field; calculating the time-varying porosity field, time-varying permeability field and dynamic expansion parameters of pressure-driven cracks of the target low-permeability oil field based on the fluid pressure-ground stress-physical property coupling equation group; establishing a fracture conductivity attenuation function of the target low-permeability oil field based on the long-term fracture conductivity test experimental data; and calculating the relative permeability curve of the target low-permeability oil field based on the non-steady-state method. The invention relates to a method for establishing a dynamic phase permeability curve control function and a dynamic capillary force curve control function of the target low permeability oilfield based on the line test experimental data and the mercury injection experimental data, respectively. The invention relates to a method for establishing a numerical simulation model of the target low permeability oilfield based on the fluid pressure-ground stress-physical property coupling equation group, the time-varying porosity field, the time-varying permeability field, the dynamic expansion parameter of the pressure-driven fracture, the fracture conductivity attenuation function, the dynamic phase permeability curve control function and the dynamic capillary force curve control function. The invention relates to a method for establishing a numerical simulation model of the target low permeability oilfield based on the line test experimental data and the mercury injection experimental data, respectively. The numerical simulation model is used to characterize the oil increase mechanism during the pressure drive process of the target low permeability oilfield through numerical simulation.

[0007] Furthermore, the fluid pressure-ground stress-physical property coupling equations include:

[0008]

[0009] Where N c is the molar density of component c, S P is the P phase saturation, x c,P is the mole fraction of the c component P phase, ξ P is the molar density of phase P, is the formation displacement vector, ρ r is the rock density at reference pressure, α is the Biot constant, is the total initial stress tensor in the formation, is the initial strain tensor, p0 is the initial pore pressure, λ and μ are functions of Young's modulus and Poisson's ratio, t is time, φ is the time-varying porosity field, O, W, G represent the oil phase, water phase and gas phase respectively, U P represents the seepage velocity vector, q c represents the inflow velocity of the c component P phase, p represents the pore pressure, σ ij is the total formation stress tensor, ∈ ij is the total strain tensor, δ ij is the Kronecker symbol.

[0010] Furthermore, based on the fluid pressure-ground stress-physical property coupling equations, the time-varying porosity field, the time-varying permeability field and the dynamic expansion parameters of the pressure-driven fracture of the target low-permeability oil field are calculated, including: the calculation formula of the time-varying porosity field includes:

[0011]

[0012] Wherein, φ is the time-varying porosity field; the time-varying permeability field is calculated based on the relationship between the permeability retention coefficient and stress obtained from the core pressure drive experiment and the fluid pressure-in-situ stress-physical property coupling equations; wherein, the relationship between the permeability retention coefficient and stress includes:

[0013]

[0014] Wherein, K is permeability, K0 is the initial permeability of the reservoir of the target low-permeability oilfield, σ is the effective stress, and A and B are adjustment variables for fitting the core pressure-flooding experiment. Based on the Mohr-Coulomb strength criterion and the fluid pressure-in-situ stress-physical property coupling equations, the dynamic expansion parameters of the pressure-flooding fractures during the pressure-flooding process of the target low-permeability oilfield are calculated.

[0015] Furthermore, the fracture conductivity attenuation function includes:

[0016]

[0017] Where F is the fracture conductivity, F0 is the initial fracture conductivity, C is the adjustment parameter for fitting the fracture conductivity attenuation experiment, and t is time.

[0018] Furthermore, based on the non-steady-state relative permeability curve test experimental data and the mercury injection test data, a dynamic phase permeability curve control function and a dynamic capillary force curve control function of the target low-permeability oil field are respectively established, including: based on the non-steady-state relative permeability curve test experimental data, a water drive relative permeability curve, a pressure drive relative permeability curve and a surfactant drive relative permeability curve are obtained; based on the water drive relative permeability curve, the pressure drive relative permeability curve and the surfactant drive relative permeability curve, a dynamic phase permeability curve control function with pressure and surfactant concentration as independent variables is established; based on the mercury injection test data, imbibition capillary force data, displacement capillary force data and the relationship between surfactant concentration and oil-water interfacial tension are obtained; based on the imbibition capillary force data, the displacement capillary force data and the relationship between surfactant concentration and oil-water interfacial tension, a dynamic capillary force curve control function with wetting order and surfactant concentration as independent variables is established.

[0019] Furthermore, the dynamic phase permeability curve control function includes:

[0020]

[0021] Where p is pressure, C is surfactant concentration, K ri is the relative permeability of phase i, P surf+p is the pressure of the surfactant pressure drive relative permeability curve, C surf is the surfactant concentration of the relative permeability of surfactant flooding, is the water flooding relative permeability curve, is the relative permeability curve of surfactant flooding, This is the relative permeability curve of surfactant pressure drive.

[0022] Furthermore, the dynamic capillary force curve control function includes a dynamic capillary force curve control function with surfactant concentration as an independent variable and a dynamic capillary force curve control function with wetting order as an independent variable; wherein the dynamic capillary force curve control function with surfactant concentration as an independent variable includes:

[0023]

[0024] Where, P cow is the oil-water capillary force, σ ow is the oil-water interfacial tension with surfactant concentration as the independent variable, σ Hg is the interfacial tension between mercury and air, θ ow is the oil-water contact angle, θ Hg is the contact angle between mercury and air, P Hg is the capillary force between mercury and air; the dynamic capillary force curve control function with the wetting order as the independent variable includes:

[0025] p c =(1-f)p cD +fp cI

[0026]

[0027] Where p c is the capillary force, p cD is the capillary force, p cI is the capillary force of absorption, S w is the water saturation, S wi is the initial water saturation, S w max is the maximum achievable water saturation, and E is the curve parameter.

[0028] In the second aspect, an embodiment of the present invention further provides a numerical simulation characterization system based on the pressure-driven oil-increasing mechanism of a low-permeability oil field, which is applied to a target low-permeability oil field; the system comprises: a first establishment module, a calculation module, a second establishment module, a third establishment module, a fourth establishment module and a simulation characterization module; wherein the first establishment module is used to establish a fluid pressure-ground stress-physical property coupling equation group based on the full stress tensor of the target low-permeability oil field; the calculation module is used to calculate the time-varying porosity field, time-varying permeability field and dynamic expansion parameters of pressure-driven fractures of the target low-permeability oil field based on the fluid pressure-ground stress-physical property coupling equation group; the second establishment module is used to establish the fracture conductivity of the target low-permeability oil field based on the long-term fracture conductivity test experimental data. capacity attenuation function; the third establishment module is used to establish the dynamic phase permeability curve control function and the dynamic capillary force curve control function of the target low permeability oil field based on the non-steady-state relative permeability curve test experimental data and the mercury injection experimental data; the fourth establishment module is used to establish a numerical simulation model of the target low permeability oil field based on the fluid pressure-stress-physical property coupling equation group, the time-varying porosity field, the time-varying permeability field, the pressure-driven fracture dynamic expansion parameter, the fracture conductivity attenuation function, the dynamic phase permeability curve control function and the dynamic capillary force curve control function; the simulation characterization module is used to perform numerical simulation characterization of the oil increase mechanism during the pressure drive process of the target low permeability oil field based on the numerical simulation model.

[0029] In a third aspect, an embodiment of the present invention further provides an electronic device comprising: a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein the processor implements the method provided in the embodiment of the present invention when executing the computer program.

[0030] In a fourth aspect, an embodiment of the present invention further provides a computer-readable storage medium, wherein the computer-readable storage medium stores computer instructions, and when the computer instructions are executed by a processor, the method provided in the embodiment of the present invention is implemented.

[0031] The present invention provides a numerical simulation characterization method and system based on the pressure-driven oil-increasing mechanism of low-permeability oil fields. Based on experimental data such as core pressure-driven experiments, non-steady-state relative permeability curve test experiments, mercury injection experiments, and long-term fracture conductivity test experiments, a control equation is constructed and introduced into a conventional numerical simulation model to perform coupled characterization of the pressure-driven oil-increasing mechanism of low-permeability oil fields, thereby improving the accuracy of pressure-driven simulation and alleviating the technical problem of the existing technology in lacking coupled characterization means for multiple pressure-driven oil-increasing mechanisms. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] In order to more clearly illustrate the implementation methods of the present application or the technical solutions in the prior art, the following is a brief introduction to the drawings required for use in the specific implementation methods or the description of the prior art. Obviously, the drawings described below are some implementation methods of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0033] Figure 1 A flowchart of a numerical simulation characterization method based on the pressure-driven oil-increasing mechanism in a low-permeability oil field provided by an embodiment of the present invention;

[0034] Figure 2 A flowchart of another numerical simulation characterization method based on the pressure-driven oil-increasing mechanism in a low-permeability oil field provided by an embodiment of the present invention;

[0035] Figure 3 A schematic diagram of a fitting curve of the relationship between permeability retention coefficient and stress provided in an embodiment of the present invention;

[0036] Figure 4 A flow chart for calculating the dynamic extension length and orientation of a pressure-driven crack provided in an embodiment of the present invention;

[0037] Figure 5 A schematic diagram of a fracture conductivity attenuation function curve provided by an embodiment of the present invention;

[0038] Figure 6 A schematic diagram of a phase permeability curve under water flooding, pressure flooding, and surfactant flooding conditions provided by an embodiment of the present invention;

[0039] Figure 7 A schematic diagram of a capillary force data curve of imbibition and displacement in a mercury injection experiment provided by an embodiment of the present invention;

[0040] Figure 8 A schematic diagram of a history fitting curve of a numerical simulation model provided by an embodiment of the present invention;

[0041] Figure 9 A schematic diagram of a history fitting curve of a conventional numerical simulation model provided in an embodiment of the present invention that does not consider the characterization of the refined pressure-driven oil-increasing mechanism;

[0042] Figure 10 A schematic diagram of a numerical simulation characterization system based on the pressure-driven oil-increasing mechanism in low-permeability oil fields provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0043] The following will provide a clear and complete description of 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 without making any creative efforts shall fall within the scope of protection of the present invention.

[0044] Example 1

[0045] Figure 1 This is a flow chart of a numerical simulation characterization method based on the pressure-driven oil-increasing mechanism of a low-permeability oil field provided in accordance with an embodiment of the present invention. The method is applied to a target low-permeability oil field. Figure 1 As shown, the method specifically includes the following steps:

[0046] Step S102: establishing a fluid pressure-in-situ stress-physical property coupling equation set based on the full stress tensor of the target low-permeability oilfield.

[0047] Step S104 , based on the fluid pressure-in-situ stress-physical property coupling equations, the time-varying porosity field, the time-varying permeability field and the dynamic expansion parameters of the pressure-driven fracture of the target low-permeability oilfield are calculated.

[0048] Step S106: establishing a fracture conductivity attenuation function for the target low-permeability oilfield based on the long-term fracture conductivity test experimental data.

[0049] Step S108 : Based on the non-steady-state relative permeability curve test data and the mercury injection test data, a dynamic relative permeability curve control function and a dynamic capillary force curve control function of the target low permeability oil field are respectively established.

[0050] Step S110: Establish a numerical simulation model of the target low-permeability oilfield based on the fluid pressure-in-situ stress-physical property coupling equations, the time-varying porosity field, the time-varying permeability field, the pressure-driven fracture dynamic expansion parameters, the fracture conductivity attenuation function, the dynamic phase permeability curve control function, and the dynamic capillary force curve control function.

[0051] Step S112: Based on the numerical simulation model, numerical simulation is performed to characterize the oil-increasing mechanism during the pressure flooding process in the target low-permeability oil field. The characterized oil-increasing mechanisms include time-varying geostress field, time-varying porosity and permeability, time-varying phase permeability, and imbibition replacement.

[0052] Specifically, the fluid pressure-ground stress-physical property coupling equations include:

[0053]

[0054]

[0055] Where N cis the molar density of component c, S P is the P phase saturation, x c,P is the mole fraction of the c component P phase, ξ P is the molar density of phase P, is the formation displacement vector, ρ r is the rock density at reference pressure, α is the Biot constant, is the total initial stress tensor in the formation, is the initial strain tensor, p0 is the initial pore pressure, λ and μ are functions of Young's modulus and Poisson's ratio, φ is the time-varying porosity field, O, W, G represent the oil phase, water phase and gas phase respectively, U P represents the seepage velocity vector, q c represents the inflow velocity of the c component P phase, p represents the pore pressure, σ ij is the total formation stress tensor, ∈ ij is the total strain tensor, δ ij is the Kronecker symbol, when i=j, δ ij =1, i≠j, δ ij =0.

[0056] Optionally, in the embodiment of the present invention, Young's modulus and Poisson's ratio are used to define the elastic characteristics of rock. Specifically,

[0057]

[0058] Where E is Young's modulus and ν is Poisson's ratio.

[0059] Specifically, in step S104, the calculation formula for the time-varying porosity field includes:

[0060]

[0061] Where φ is the time-varying porosity field;

[0062] The time-varying permeability field is calculated based on the relationship between the permeability retention coefficient and stress obtained from core pressure flooding experiments and the fluid pressure-in-situ stress-physical property coupling equations. The relationship between the permeability retention coefficient and stress includes:

[0063]

[0064] Where K is the permeability, K0 is the initial permeability of the target low-permeability oil field, σ is the effective stress, and A and B are the adjustment variables for fitting the core pressure drive experiment.

[0065] Specifically, in step S104, the Mohr-Coulomb strength criterion, the Griffiths criterion, or the expansion criterion is introduced to calculate the dynamic expansion parameters of the pressure-driven crack during the pressure-driven process based on the time-varying in-situ stress field, Young's modulus, Poisson's ratio, etc. The dynamic expansion parameters of the pressure-driven crack include the dynamic expansion length and orientation of the pressure-driven crack.

[0066] Preferably, the dynamic expansion parameters of pressure-driven fractures during the pressure-driven flooding process in the target low-permeability oil field are calculated based on the Mohr-Coulomb strength criterion and the fluid pressure-ground stress-physical property coupling equations. Specifically, the method for determining the dynamic expansion of fractures based on the Mohr-Coulomb strength criterion includes:

[0067] σ1―σ3=(σ1+σ3)sinθ+2c·cosθ

[0068] Where σ1 and σ3 are the maximum and minimum principal stresses in the plane, θ is the friction angle, and c is the cohesion.

[0069] Specifically, the fracture conductivity attenuation function in step S106 includes:

[0070]

[0071] Where F is the fracture conductivity, F0 is the initial fracture conductivity, C is the adjustment parameter for fitting the fracture conductivity attenuation experiment, and t is time.

[0072] Specifically, step S108 further includes the following steps:

[0073] Step S1081: Based on the relative permeability curve test experimental data of the non-steady-state method, a water drive relative permeability curve, a pressure drive relative permeability curve, and a surfactant drive relative permeability curve are obtained.

[0074] Step S1082: Based on the water drive relative permeability curve, the pressure drive relative permeability curve, and the surfactant drive relative permeability curve, a dynamic relative permeability curve control function is established with pressure and surfactant concentration as independent variables. The dynamic relative permeability curve control function includes:

[0075]

[0076] Where p is pressure, C is surfactant concentration, K ri is the relative permeability of phase i, P surf+p is the pressure of the surfactant pressure drive relative permeability curve, C surf is the surfactant concentration of the relative permeability of surfactant flooding, is the water flooding relative permeability curve, is the relative permeability curve of surfactant flooding, This is the relative permeability curve of surfactant pressure drive.

[0077] Step S1083: Based on the mercury intrusion test data, the imbibition capillary force data, the displacement capillary force data, and the relationship between the surfactant concentration and the oil-water interfacial tension are obtained.

[0078] Step S1084: Based on the imbibition capillary force data, the displacement capillary force data, and the relationship between surfactant concentration and oil-water interfacial tension, a dynamic capillary force curve control function is established with the wetting sequence and surfactant concentration as independent variables.

[0079] Specifically, the dynamic capillary force curve control function includes a dynamic capillary force curve control function with surfactant concentration as an independent variable and a dynamic capillary force curve control function with wetting order as an independent variable; wherein,

[0080] The dynamic capillary force curve control function with surfactant concentration as the independent variable includes:

[0081]

[0082] Where, P cow is the oil-water capillary force, σ ow is the oil-water interfacial tension with surfactant concentration as the independent variable, σ Hg is the interfacial tension between mercury and air, θ ow is the oil-water contact angle, θ Hg is the contact angle between mercury and air, P Hg is the capillary force between mercury and air;

[0083] The dynamic capillary force curve control function with wetting order as the independent variable includes:

[0084] p c =(1-f)p cD +fp cI

[0085]

[0086] Where p c is the capillary force, p cD is the capillary force, p cI is the capillary force of absorption, S w is the water saturation, S wi is the initial water saturation, S w max is the maximum achievable water saturation, E is a curve parameter, and in this embodiment, the value is E=0.05.

[0087] Specifically, an embodiment of the present invention provides a numerical simulation characterization method based on the pressure-driven oil production mechanism of a low-permeability oil field. First, based on the geological model and mechanical model of the target low-permeability oil field, numerical simulation and history matching of the reservoir are carried out, so that the constructed numerical simulation model of the reservoir can characterize the production characteristics of the target low-permeability oil field. When simulating the pressure-driven process, the designed pressure-driven injection liquid displacement and total liquid volume are injected. Based on the fluid pressure-ground stress-physical property coupling equation group, the reservoir fluid pressure-ground stress-physical property changes caused by the injected liquid are calculated, and the time-varying ground stress field and porosity-permeability time-varying mechanism are simulated. Based on the Mohr-Coulomb strength criterion and the fluid pressure-ground stress-physical property coupling equation group, the dynamic expansion parameters of the pressure-driven cracks in the pressure-driven process of the target low-permeability oil field are calculated, and the expansion mechanism of the fracturing cracks is simulated. The changes in formation pressure and fluid surfactant concentration caused by the external liquid cause real-time changes in the phase permeability and capillary force curves, thereby simulating the time-varying phase permeability and imbibition replacement mechanism.

[0088] The embodiment of the present invention provides a numerical simulation characterization method based on the pressure-driven oil-increasing mechanism of low-permeability oil fields. According to the pressure-driven characteristics of low-permeability oil layers, a time-varying ground stress field, a time-varying porosity field, a time-varying permeability field, dynamic expansion of pressure-driven cracks, attenuation of fracture conductivity, a dynamic phase permeability curve, and a dynamic capillary force curve model are established. Multiple pressure-driven oil-increasing mechanisms such as time-varying ground stress, time-varying porosity and permeability, time-varying phase permeability, and imbibition and replacement are coupled and characterized to improve the accuracy of pressure-driven simulation. This provides a theoretical basis and numerical simulation method for pressure-driven technology of low-permeability oil reservoirs, and is of great significance to well selection and pressure-driven parameter optimization design for pressure-driven low-permeability oil layers.

[0089] Example 2

[0090] The embodiment of the present invention takes the successful pressure drive test of a well in the existing target low-permeability oil reservoir block A and the need to establish an oil reservoir numerical simulation model as an example to illustrate the application process of the method provided by the embodiment of the present invention.

[0091] Figure 2 FIG. 1 is a flow chart of another numerical simulation characterization method based on the pressure-driven oil-increasing mechanism of low-permeability oil fields provided in accordance with an embodiment of the present invention. Figure 2 As shown, the specific steps include:

[0092] Step 1: Establish a fluid pressure-in-situ stress-physical property coupling equation system based on the full stress tensor; use Young's modulus and Poisson's ratio to define the elastic characteristics of the rock, and calculate the time-varying porosity field based on the time-varying in-situ stress field; use 4 cores to conduct pressure drive experiments, and obtain the relationship between permeability retention coefficient and stress as shown in the following figure: Figure 3 As shown in the figure, the time-varying permeability field is calculated based on the time-varying in-situ stress field; the Mohr-Coulomb strength criterion, Griffiths criterion, expansion criterion, etc. are introduced to calculate the dynamic extension length and orientation of the pressure-driven cracks in the pressure-driven process based on the time-varying in-situ stress field, Young's modulus, Poisson's ratio, etc. The crack calculation flow chart is shown in the figure. Figure 4 shown.

[0093] Step 2: Conduct a long-term fracture conductivity test. The experimental results show that the conductivity decreases rapidly in the early stage of fracture closure and decreases slowly in the later stage. The overall change conforms to the exponential law. Normalize the experimental results and establish a fracture conductivity attenuation function according to the exponential decrease law. The function curve is as follows: Figure 5 shown.

[0094] Step 3: Perform the non-steady-state relative permeability curve test under water flooding / surfactant flooding conditions to obtain the relative permeability curve under water flooding / surfactant flooding conditions as shown in the figure below: Figure 6 As shown in the figure, a dynamic phase permeability curve with surfactant concentration as the independent variable was established; mercury intrusion tests were conducted, and the injection / flowback capillary force data were obtained as shown in the figure. Figure 7 As shown in FIG, the relationship curve between surfactant concentration and interfacial tension obtained by interfacial tension test is used to establish a dynamic capillary force curve that takes into account both surfactant oil enhancement and imbibition displacement oil enhancement.

[0095] Step 4: Based on the existing static geological and fluid data of the mine, combined with the time-varying geostress field, time-varying porosity field, time-varying permeability field, dynamic expansion of pressure-driven fractures, attenuation of fracture conductivity, dynamic phase permeability curve, and dynamic capillary force curve, a pressure-driven fine reservoir numerical simulation model is established.

[0096] Perform history matching such as Figure 8 As shown in the figure, the conventional numerical model fitting results (such as Figure 9 (as shown). A comparison shows that conventional numerical models require extensive human intervention and produce inaccurate fits. The reservoir numerical simulation model developed by this invention incorporates experimental results on time-varying porosity and permeability, couples them with time-varying geostress, sets the fracturing fluid volume according to actual construction parameters, and automatically simulates and generates a fracture network, improving the fitted production rate. The addition of a fracture conductivity attenuation function improves the fitted bottomhole pressure, significantly reducing human intervention. The historical fitting results are more accurate, validating the accuracy of the refined numerical model that couples multiple pressure-driven mechanisms.

[0097] Based on the constructed numerical model, the production capacity contribution of the oil-increasing mechanism was analyzed. The specific simulation scheme design is shown in Table 1, and the numerical simulation results are shown in Table 2.

[0098] Table 1 Simulation scheme design

[0099]

[0100] Table 2 Numerical simulation characterization of oil-increasing mechanism

[0101]

[0102]

[0103] Example 3

[0104] Figure 10 Schematic diagram of a numerical simulation characterization system based on the pressure-driven oil-increasing mechanism of a low-permeability oil field provided in accordance with an embodiment of the present invention, the system is applied to a target low-permeability oil field. Figure 10 As shown, the system includes: a first establishment module 10 , a calculation module 20 , a second establishment module 30 , a third establishment module 40 , a fourth establishment module 50 and a simulation characterization module 60 .

[0105] Specifically, the first establishing module 10 is used to establish a fluid pressure-in-situ stress-physical property coupling equation group based on the full stress tensor of the target low-permeability oil field.

[0106] The calculation module 20 is used to calculate the time-varying porosity field, time-varying permeability field and dynamic expansion parameters of pressure-driven fractures of the target low-permeability oil field based on the fluid pressure-ground stress-physical property coupling equation group.

[0107] The second establishing module 30 is used to establish a fracture conductivity attenuation function of a target low permeability oil field based on the long-term fracture conductivity test experimental data.

[0108] The third establishing module 40 is used to establish a dynamic relative permeability curve control function and a dynamic capillary force curve control function of the target low permeability oil field based on the non-steady-state relative permeability curve test data and the mercury injection test data.

[0109] The fourth establishment module 50 is used to establish a numerical simulation model of the target low-permeability oil field based on the fluid pressure-ground stress-physical property coupling equation group, the time-varying porosity field, the time-varying permeability field, the pressure-driven fracture dynamic expansion parameter, the fracture conductivity attenuation function, the dynamic phase permeability curve control function and the dynamic capillary force curve control function.

[0110] The simulation characterization module 60 is used to perform numerical simulation characterization on the oil-increasing mechanism during the pressure drive process of the target low-permeability oil field based on the numerical simulation model.

[0111] Specifically, the third establishing module 40 is further configured to:

[0112] Based on the relative permeability curve test data of the non-steady-state method, the water drive relative permeability curve, pressure drive relative permeability curve and surfactant drive relative permeability curve are obtained;

[0113] Based on the water drive relative permeability curve, pressure drive relative permeability curve and surfactant drive relative permeability curve, a dynamic relative permeability curve control function with pressure and surfactant concentration as independent variables is established;

[0114] Based on the mercury intrusion test data, the data of the imbibition capillary force, the data of the displacement capillary force and the relationship between the surfactant concentration and the oil-water interfacial tension were obtained;

[0115] Based on the data of imbibition capillary force, displacement capillary force and the relationship between surfactant concentration and oil-water interfacial tension, a dynamic capillary force curve control function with wetting order and surfactant concentration as independent variables was established.

[0116] The present invention also provides an electronic device, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the method provided in the embodiment of the present invention when executing the computer program.

[0117] The present invention also provides a computer-readable storage medium, which stores computer instructions. When the computer instructions are executed by a processor, the method provided in the embodiment of the present invention is implemented.

[0118] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above and that the invention can be embodied in other specific forms without departing from the spirit or essential characteristics of the invention. Therefore, the embodiments should be considered in all respects as illustrative and non-restrictive, and the scope of the invention is defined by the appended claims, not the foregoing description, and all variations within the meaning and range of equivalents of the claims are intended to be included therein. Any reference sign in a claim should not be construed as limiting the claim to which it relates.

[0119] In addition, it should be understood that although this specification is described in terms of implementation methods, not every implementation method contains only one independent technical solution. This narrative method of the specification is only for the sake of clarity. Those skilled in the art should regard the specification as a whole. The technical solutions in each embodiment can also be appropriately combined to form other implementation methods that can be understood by those skilled in the art.

Claims

1. A numerical simulation characterization method based on the pressure-driven oil-increasing mechanism of low-permeability oil fields, characterized in that: Applied to a target low-permeability oil field; the method comprises: Based on the full stress tensor of the target low-permeability oil field, a fluid pressure-in-situ stress-physical property coupling equation system is established; Calculating the time-varying porosity field, time-varying permeability field, and dynamic expansion parameters of pressure-driven fractures of the target low-permeability oilfield based on the fluid pressure-in-situ stress-physical property coupling equations; Based on the experimental data of long-term fracture conductivity test, a fracture conductivity attenuation function of the target low-permeability oil field is established; Based on the non-steady-state relative permeability curve test data and the mercury injection test data, a dynamic relative permeability curve control function and a dynamic capillary force curve control function of the target low permeability oil field are respectively established; Establishing a numerical simulation model of the target low-permeability oilfield based on the fluid pressure-in-situ stress-physical property coupling equations, the time-varying porosity field, the time-varying permeability field, the pressure-driven fracture dynamic expansion parameter, the fracture conductivity attenuation function, the dynamic phase permeability curve control function, and the dynamic capillary force curve control function; Based on the numerical simulation model, a numerical simulation characterization is performed on the oil-increasing mechanism during the pressure drive process of the target low-permeability oil field.

2. The method according to claim 1, wherein: The fluid pressure-ground stress-physical property coupling equations include: Where N c is the molar density of component c, S P is the P phase saturation, x c,P is the mole fraction of the c component P phase, ξ P is the molar density of phase P, is the formation displacement vector, ρ r is the rock density at reference pressure, α is the Biot constant, is the total initial stress tensor in the formation, is the initial strain tensor, p0 is the initial pore pressure, λ and μ are functions of Young's modulus and Poisson's ratio, t is time, φ is the time-varying porosity field, O, W, G represent the oil phase, water phase and gas phase respectively, U P represents the seepage velocity vector, q c represents the inflow velocity of the c component P phase, p represents the pore pressure, σ ij is the total formation stress tensor, ∈ ij is the total strain tensor, δ ij is the Kronecker symbol.

3. The method according to claim 2, wherein: Based on the fluid pressure-in-situ stress-physical property coupled equations, the time-varying porosity field, the time-varying permeability field, and the dynamic expansion parameters of the pressure-driven fractures of the target low-permeability oilfield are calculated, including: The calculation formula for the time-varying porosity field includes: Where φ is the time-varying porosity field; The time-varying permeability field is calculated based on the relationship between the permeability retention coefficient and stress obtained from the core pressure drive experiment and the fluid pressure-in-situ stress-physical property coupling equations. The relationship between the permeability retention coefficient and stress includes: Where K is permeability, K0 is the initial permeability of the reservoir of the target low-permeability oil field, σ is the effective stress, and A and B are the adjustment variables for fitting the core pressure drive experiment; Based on the Mohr-Coulomb strength criterion and the fluid pressure-in-situ stress-physical property coupling equations, the dynamic expansion parameters of the pressure-driven fractures in the pressure-driven process of the target low-permeability oil field are calculated.

4. The method according to claim 1, wherein: The fracture conductivity attenuation function includes: Where F is the fracture conductivity, F0 is the initial fracture conductivity, C is the adjustment parameter for fitting the fracture conductivity attenuation experiment, and t is time.

5. The method according to claim 1, wherein: Based on the non-steady-state relative permeability curve test data and the mercury injection test data, a dynamic relative permeability curve control function and a dynamic capillary force curve control function of the target low permeability oil field are established respectively, including: Based on the relative permeability curve test data of the non-steady-state method, a water drive relative permeability curve, a pressure drive relative permeability curve and a surfactant drive relative permeability curve are obtained; Based on the water drive relative permeability curve, the pressure drive relative permeability curve, and the surfactant drive relative permeability curve, a dynamic relative permeability curve control function is established with pressure and surfactant concentration as independent variables; Based on the mercury injection test data, the imbibition capillary force data, the displacement capillary force data and the relationship between surfactant concentration and oil-water interfacial tension are obtained; Based on the imbibition capillary force data, the displacement capillary force data and the relationship between surfactant concentration and oil-water interfacial tension, a dynamic capillary force curve control function with wetting sequence and surfactant concentration as independent variables is established.

6. The method according to claim 1 or 5, characterized in that: The dynamic phase permeability curve control function includes: Where p is pressure, C is surfactant concentration, K ri () is the relative permeability of phase i, P surf+p is the pressure of the surfactant pressure drive relative permeability curve, C surf is the surfactant concentration of the relative permeability of surfactant flooding, is the water flooding relative permeability curve, is the relative permeability curve of surfactant flooding, is the relative permeability curve of surfactant pressure drive, W and O represent the water phase and oil phase respectively.

7. The method according to claim 5, characterized in that: The dynamic capillary force curve control function includes a dynamic capillary force curve control function with surfactant concentration as an independent variable and a dynamic capillary force curve control function with wetting order as an independent variable; wherein, The dynamic capillary force curve control function with surfactant concentration as an independent variable includes: Where, P cow is the oil-water capillary force, σ ow is the oil-water interfacial tension with surfactant concentration as the independent variable, σ Hg is the interfacial tension between mercury and air, θ ow is the oil-water contact angle, θ Hg is the contact angle between mercury and air, P Hg is the capillary force between mercury and air; The dynamic capillary force curve control function with the wetting order as the independent variable includes: p c =(1-f)p cD +fp cI Where p c is the capillary force, p cD is the capillary force, p cI is the capillary force of absorption, S w is the water saturation, S wi is the initial water saturation, S w max is the maximum achievable water saturation, and E is the curve parameter.

8. A numerical simulation characterization system based on the pressure-driven oil-increasing mechanism of low-permeability oil fields, characterized by: Applied to target low permeability oil fields; including: a first establishment module, a calculation module, a second establishment module, a third establishment module, a fourth establishment module and a simulation characterization module; wherein, The first establishing module is used to establish a fluid pressure-in-situ stress-physical property coupling equation group based on the full stress tensor of the target low-permeability oil field; The calculation module is used to calculate the time-varying porosity field, the time-varying permeability field and the dynamic expansion parameters of the pressure-driven fracture of the target low-permeability oil field based on the fluid pressure-in-situ stress-physical property coupling equation group; The second establishing module is used to establish a fracture conductivity attenuation function of the target low-permeability oilfield based on the long-term fracture conductivity test experimental data; The third establishment module is used to establish a dynamic relative permeability curve control function and a dynamic capillary force curve control function of the target low permeability oil field based on the non-steady-state relative permeability curve test experimental data and the mercury injection experimental data; The fourth establishment module is configured to establish a numerical simulation model of the target low-permeability oilfield based on the fluid pressure-in-situ stress-physical property coupling equations, the time-varying porosity field, the time-varying permeability field, the pressure-driven fracture dynamic expansion parameter, the fracture conductivity attenuation function, the dynamic phase permeability curve control function, and the dynamic capillary force curve control function; The simulation characterization module is used to perform numerical simulation characterization on the oil-increasing mechanism during the pressure drive process of the target low-permeability oil field based on the numerical simulation model.

9. An electronic device, characterized in that: include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the method according to any one of claims 1 to 7 when executing the computer program.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer instructions, and when the computer instructions are executed by a processor, the method according to any one of claims 1 to 7 is implemented.

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