Geological engineering integrated numerical simulation method for response of low permeability reservoir pressure drive water injection

Abstract

The application provides a low-permeability oil reservoir pressure drive water injection response geology engineering integrated numerical simulation method, which comprises the following steps: step 1, a seepage-stress-damage coupling model is established; step 2, after the seepage field is calculated, the stress field is calculated by coupling the stress-strain relationship of the rock matrix; step 3, the stress-strain parameters of the reservoir rock are solved; step 4, a micro-fracture damage zone caused by pressure drive water injection is obtained; step 5, a heterogeneous refined three-dimensional pressure drive water injection reservoir black oil geology model of a target block is established; and step 6, the pressure drive water injection response range is obtained by simulating the pressure drive water injection water saturation distribution. The low-permeability oil reservoir pressure drive water injection response geology engineering integrated numerical simulation method can provide theoretical guidance for controlling the pressure drive injection parameters, fracturing scheme design and other pressure drive-fracturing injection-production well reservoir development, and can provide theoretical guidance for the field low-permeability oil reservoir pressure drive injection-production development.

Description

Technical Field

[0001] This invention relates to the field of oil and gas production enhancement and geotechnical engineering technology, and in particular to an integrated numerical simulation method for the geological engineering of pressure-driven water injection in low-permeability oil reservoirs. Background Technology

[0002] my country's low-permeability and ultra-low-permeability reservoirs have relatively low utilization rates and poor development results, indicating significant remaining development potential. To address the "injection failure and extraction failure" problem in water injection development of low-permeability reservoirs, Shengli Oilfield has proposed pressure-driven fracturing technology. This technology transforms the traditional hydraulic fracturing approach of "promoting fracture extension" into "slowing fracture extension," breaking the conventional understanding that water injection cannot exceed the fracture pressure. By rapidly and continuously injecting large amounts of clean water and oil displacement agents near the fracture pressure, followed by well shut-in, well simmering for seepage, and pressure diffusion, it achieves rapid replenishment of formation energy and increases reservoir pressure within a short period.

[0003] In water injection during pressure-driven hydraulic injection, the most important aspects are understanding the effective range of water-driven oil and controlling the velocity of the water-driven front. This allows for adjustments to the injection method, parameters, and medium to improve the water-driven swept volume and efficiency, ultimately enhancing the water injection development effect. Research has revealed methods for determining the effective range of pressure-driven hydraulic injection and the location of the water-driven front, including the Berkeley-Lewelt method, well test analysis, numerical simulation, and microseismic testing. However, most models in these methods do not consider important characteristics of low-permeability tight reservoirs, such as heterogeneity and capillary forces. The presence of heterogeneity causes significant differences in water absorption in different directions around the injection well, thus affecting the movement direction of the water-driven front. Specifically, conventional mathematical analytical methods suffer from cumbersome solution processes and high costs. Microseismic monitoring technology is currently the most widely used water-driven front monitoring technology. While simple to implement, its accuracy is low, limiting its effectiveness in actual production. Therefore, there is an urgent need to invent an integrated numerical simulation method for the geological and engineering effects of water injection in pressure-driven reservoirs, which can accurately describe the oil-water movement law and the distribution of the water drive front during the pressure-driven process, and provide technical support for the development description of water injection in pressure-driven reservoirs.

[0004] Patent document CN115875030A discloses a method for designing injection volume and optimizing well fracture parameters under water injection well pressure-driven conditions. This method includes determining the formation micro-fracture pressure based on formation pore pressure and formation fracturing pressure; calculating the wellhead injection pressure; calculating the maximum injection volume of the water injection well; classifying and setting the daily injection volume based on the maximum injection volume and changes in formation pressure coefficient during injection; establishing a heterogeneous three-dimensional pressure-driven water injection reservoir black oil geological model for the target block; adding surfactant components to the injection water using reservoir numerical simulation software; simulating water injection and then shutting down the injection well; opening the production well to simulate production capacity; and optimizing the optimal fracture half-length of the production well through a three-year cumulative oil production comparison to obtain the final cumulative oil production. This invention simulates the formation of the fracture network in water injection wells using numerical simulation software, optimizing the fracture parameters under the premise of water injection well pressure-driven conditions. However, it does not consider the dynamic changes in formation and reservoir properties during actual pressure-driven processes, making it difficult to apply effectively.

[0005] Patent document CN115841083A discloses a method for determining the injection volume of a water injection well under pressure-driven flooding, comprising: Step 1, calculating the relationship between water injection volume and formation pressure recovery using a material balance equation; Step 2, drawing a chart of formation pressure drop changes under different injection-production ratios based on Step 1; Step 3, drawing a profile of inter-well pressure changes before pressure-driven flooding; Step 4, determining the limiting free-flow radius of the water well and the limiting drainage radius of the oil well during pressure-driven flooding; Step 5, drawing a schematic diagram of the water drive sweep range between oil and water wells during pressure-driven flooding, and calculating the maximum water drive front sweep radius corresponding to the establishment of an effective displacement relationship using a fluid connection method; Step 6, calculating the pore volume within the water drive sweep radius using an ellipsoidal model to determine the water injection volume for pressure-driven flooding; Step 7, comparing and optimizing the water injection volume calculated in Step 6 with the material balance method to determine a suitable displacement radius and water injection volume for pressure-driven flooding. This invention determines the injection rate of water at the pressure-driven water injection front based on the seepage characteristics of low-permeability reservoirs and the pressure change characteristics between oil and water wells. However, this method only considers the injection rate for mean reservoirs based on the material balance equation, which has poor adaptability.

[0006] Patent document CN118429560A discloses a simulation method for improving the pressure distribution in deep reservoir development through integrated pressure-drive, relating to the field of oil and gas reservoir development technology. The simulation method is as follows: Step S1, collect and organize the data required to establish the simulation model; Step S2, establish the simulation model and import the initial integrated pressure-drive scheme; Step S3, run the three-dimensional geological model, seepage model, geostress model, and discrete fracture network model to optimize the pressure-drive parameters; Step S4, after the simulation is completed, output and analyze the simulation data. This invention simulates the response and changes of oil and gas reservoirs under different pressure distributions by establishing a three-dimensional geological model, seepage model, geostress model, and discrete fracture network model, solving the problem of a single pressure simulation method. However, it does not consider the damage caused by the propagation of microfractures during water injection pressure drive under conditions exceeding the fracturing pressure, and it lacks a description of the water drive front.

[0007] In summary, the technical solutions, problems solved, and beneficial effects of the disclosed technologies are all different from those of this invention. Furthermore, none of the disclosed technical documents offer any technical inspiration for the more advanced technical features, problems solved, and beneficial effects of this invention. A search reveals no literature of the XY category, indicating that this invention possesses originality. Since there is no solution in the existing technology to address the technical problem we seek to solve, we have invented a novel integrated numerical simulation method for the geological engineering of pressure-driven water injection in low-permeability oil reservoirs. Summary of the Invention

[0008] The purpose of this invention is to provide an integrated numerical simulation method for the geological engineering of water injection effect in low-permeability reservoirs, which can provide theoretical guidance for the field control of injection parameters and fracturing scheme design in pressure-driven injection-production wells, and provide theoretical guidance for the field development of pressure-driven injection-production in low-permeability reservoirs.

[0009] The objective of this invention can be achieved through the following technical measures: an integrated numerical simulation method for the geological engineering of water injection-driven pressure ...

[0010] Step 1: Establish a seepage-stress-damage coupling model;

[0011] Step 2: After calculating the seepage field, the stress field is calculated by coupling the stress-strain relationship of the rock matrix;

[0012] Step 3: Solve for the stress-strain parameters of the reservoir rock;

[0013] Step 4: Obtain the microcrack damage zone caused by pressure-driven water injection;

[0014] Step 5: Establish a detailed three-dimensional geological model of the heterogeneous water-injected pressure-driven oil reservoir in the target block;

[0015] Step 6: Simulate the water saturation distribution of the pressure drive to obtain the effective range of water injection for pressure drive.

[0016] The objective of this invention can also be achieved through the following technical measures:

[0017] In step 1, based on the interaction between rock and fluid, and combining the seepage model, Biot linear elastic theory and continuous damage model, a seepage-stress-damage fluid-structure coupling mathematical model is constructed, and a seepage-stress-damage coupling model is established.

[0018] In step 1, the constitutive equation for the interaction between the matrix rock and the fluid is: Based on Boit's linear elastic stress theory, the constitutive relationship equation between the fluid and the matrix is ​​established. According to the effective stress, the equilibrium equation between the rock and the fluid can be obtained:

[0019] σ=σ′-α·p m I (1)

[0020] Where: σ`—effective stress tensor of rock, Pa; σ—total stress tensor of rock, Pa; p m — Rock pore fluid pressure, Pa; α—Biot coefficient, ranging from 0 to 1; I—Identity matrix;

[0021] Based on the effective stress of rock and the stress-strain linear elastic relationship, the relationship between the effective stress of rock and the rock displacement can be obtained:

[0022] σ′=λ(▽·u)I+2Gε(u) (2)

[0023] Where: u—rock displacement tensor, m; ε—rock strain tensor, dimensionless; λ—Lamé's first coefficient in the formula of the continuum mechanics theory, dimensionless; G—Lamé's second coefficient in the formula of the continuum mechanics theory, dimensionless;

[0024] The rock strain tensor can be expressed as:

[0025]

[0026] During pressure displacement, injected water seeps into the formation, increasing reservoir pore pressure and thus affecting the reservoir stress field distribution. Simultaneously, changes in reservoir stress cause reservoir volume deformation, further influencing the reservoir porosity-permeability coefficient. Assuming infinitesimal elastic deformation of the reservoir, the expressions for permeability and porosity within the rock matrix can be obtained:

[0027]

[0028] Where: p, p0—reservoir pressure and reference pressure, Pa; ε, ε0—rock strain under p and p0 pressure conditions, dimensionless; φ, φ0—matrix porosity under p and p0 pressure conditions, dimensionless; M—reference coefficient in Biot theory, dimensionless; K—reservoir matrix permeability, mD; c—Kozeny-Carman constant, dimensionless; S—rock specific surface area, cm 2 / cm 3 .

[0029] In step 1, the differential equation for the two-phase flow of oil and water within the rock matrix is:

[0030]

[0031]

[0032] In the formula, K is the absolute permeability, k ro and k rw These are the relative permeabilities of the oil and water phases, in μm. 2 B o And B w These are the volume coefficients of the oil and water phases, respectively; as well as These represent the pressure gradients at the oil and water phases, respectively, in MPa·m. -1 ;ρ o and ρ w These are the densities of the oil phase and the water phase, respectively, in kg·m³. -3 ;q o and q w These represent the oil and water phase production under standard conditions, with positive values ​​for injection wells and negative values ​​for production wells. The unit is m³. 3 S o and S w These represent the saturation levels of the oil phase and the water phase, respectively.

[0033] In step 2, considering the actual physical process of pressure-driven water injection, the injected water flows in the reservoir, causing changes in the stress field of the reservoir rock. These changes in the stress field cause rock damage. Therefore, the seepage field is calculated first, and then the stress field is calculated by coupling the stress-strain relationship of the rock matrix.

[0034] In step 3, the seepage equation is first discretized and solved using the finite volume method. Based on this, the rock stress and strain field is projected and calculated using the virtual element method. Finally, the fluid seepage field and rock stress field are solved by automatic differentiation to obtain the reservoir rock stress and strain parameters.

[0035] In step 3, when performing fluid-structure interaction (FSI) solutions for the fluid seepage field and rock stress field, the model is first spatially discretized and assembled, and then the rock mechanical parameters and fluid parameters in each element grid are initialized. Next, the time domain is discretized, and the seepage-stress-damage model is calculated under different time steps. Finally, considering the influence of low-velocity non-Darcy seepage in low-permeability reservoirs and Biot's linear elastic theory, the coupling relationship between reservoir rock deformation and fluid seepage is established.

[0036]

[0037] Where p, p0—reservoir pressure and reference pressure, Pa; ε, ε0—rock strain under p and p0 pressure conditions, dimensionless; φ, φ0—matrix porosity under p and p0 pressure conditions, dimensionless; M—reference coefficient in Biot theory, dimensionless;

[0038] An automatic differentiation method is used to compute coupled numerical models. Complex functions are broken down into multiple simpler functions, which are computed and stored separately. Differentiation is performed at a specific point in the multi-layered composite function, automatically returning the derivative at any point in the original function. This reduces the difficulty of differentiating complex functions. The algorithm's rules are as follows:

[0039]

[0040] In the formula: a, b — two variables in the computational domain;

[0041] a`, b` — the derivatives of variables a and b;

[0042] The Jacobian matrix of the fluid-structure interaction equations is obtained through an automatic differentiation algorithm, and then the nonlinear equations are calculated using Newton's iteration method, as follows:

[0043] J -1 ×δV=-R (9)

[0044] δV=V n+1 -V n (10)

[0045] Where: J — Jacobi matrix;

[0046] V n V n+1 Unknown variables at times n and n+1 include the fluid saturation S of the cell grid, the rock displacement u, and the pore pressure p;

[0047] R—Residual vector, dimensionless.

[0048] In step 4, the cell damage factor is calculated and the degree of cell damage is determined by the continuous damage model. Then, the reservoir rock mechanical parameters, including effective stress and Young's modulus, and physical property parameters, including porosity and permeability, are corrected. After iterative calculation, the corrected reservoir seepage field and stress-strain field are obtained, and the micro-crack damage zone caused by pressure-driven water injection is obtained.

[0049] In step 4, a damage factor d is introduced, which physically represents the degree of rock damage. Its value ranges from 0 to 1, where 0 indicates the rock is not fractured and 1 indicates complete rock failure. Based on the damage factor, the actual stress and effective stress of the formation are expressed as follows:

[0050]

[0051] Where: σ`—effective formation stress, Pa; σ—actual formation stress, Pa.

[0052] In step 5, collect the relative permeability curves, geological parameters, fluid parameters, and core experimental data of low-permeability sandstone reservoirs in the actual mining field, and establish a heterogeneous, refined three-dimensional pressure-driven water-injection reservoir black oil geological model for the target block.

[0053] In step 6, the micro-fracture damage zone attribute parameters, including permeability and mechanical properties, are extracted from step 4 and imported into the three-dimensional pressure-driven water injection reservoir black oil geological model. The oil-water two-phase process of water-driven oil is simulated using reservoir software to obtain the water saturation distribution of pressure-driven oil injection and finally obtain the effective range of pressure-driven water injection.

[0054] The objective of this invention can also be achieved through the following technical measures: an integrated numerical simulation system for the geological engineering of water injection-induced pressure drive in low-permeability reservoirs. This integrated numerical simulation system for water injection-induced pressure drive in low-permeability reservoirs uses an integrated numerical simulation method to describe the oil-water movement patterns and water front distribution during the pressure drive process.

[0055] The integrated numerical simulation method for the geological and engineering aspects of water injection-pressure driven reservoirs in low-permeability reservoirs, as presented in this invention, solves the problem that traditional reservoir numerical simulation methods in the prior art cannot describe the coupled influence of pressure drive injection, fracture propagation, and the water drive front, and are difficult to accurately simulate the unclear effective range of water drive during pressure drive. The integrated numerical simulation method for water injection-pressure driven reservoirs in low-permeability reservoirs provided by this invention can provide theoretical guidance for field control of pressure drive injection parameters, fracturing scheme design, and other aspects of pressure drive-fracture injection-production well reservoir development, and provides theoretical guidance for field pressure drive injection-production development of low-permeability reservoirs. Compared with the prior art, this invention has the following beneficial effects:

[0056] 1. It can solve the problem that traditional reservoir numerical simulation methods are difficult to accurately simulate the dynamic changes in reservoir properties during pressure drive;

[0057] 2. It can accurately depict the challenges of dynamic expansion, physical property evolution, and fluid seepage capacity changes in the seam mesh modification zone during pressure driving;

[0058] 3. It can simultaneously simulate the damage caused by pressure-driven injection into cracks and the effective range of water-driven injection. Attached Figure Description

[0059] Figure 1 A flowchart of a specific embodiment of the integrated numerical simulation method for the geological and engineering effects of water injection and pressure-driven oil reservoirs according to the present invention;

[0060] Figure 2 This is a flowchart of the seepage-stress-damage coupling solution of the present invention;

[0061] Figure 3 This is a simulated well network diagram of pressure-driven fracture damage according to a specific embodiment of the present invention;

[0062] Figure 4 This is a diagram showing the damage zone of the pressure-driven crack in a specific embodiment of the present invention.

[0063] Figure 5 This is a three-dimensional geological model of the target block Petre l in a specific embodiment of the present invention;

[0064] Figure 6 This is a diagram showing the effective range of pressure drive in a specific embodiment of the present invention. Detailed Implementation

[0065] It should be noted that the following detailed descriptions are exemplary and intended to provide further illustration of the invention. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0066] It should be noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the exemplary embodiments of the present invention. As used herein, the singular form is intended to include the plural form as well, unless the context clearly indicates otherwise. Furthermore, it should be understood that when the terms "comprising" and / or "including" are used in this specification, they indicate the presence of features, steps, operations, and / or combinations thereof.

[0067] like Figure 1 As shown, Figure 1 This is a flowchart of the integrated numerical simulation method for the geological engineering of water injection-driven pressure ...

[0068] Step 1: Based on the interaction between rock and fluid, and combining the seepage model, Biot linear elastic theory and continuous damage model, construct a seepage-stress-damage (HMD) fluid-structure coupling mathematical model and establish a seepage-stress-damage coupling model.

[0069] Step 2: Consider the actual physical process of pressure-driven water injection. The injected water flows in the reservoir, causing changes in the stress field of the reservoir rock. These changes in stress field cause rock damage. Therefore, the seepage field is calculated first, and then the stress field is calculated by coupling the stress-strain relationship of the rock matrix.

[0070] Step 3: First, the seepage equation is discretized and solved using the finite volume method. Then, the rock stress and strain field is projected and calculated using the virtual element method. Finally, the fluid seepage field and rock stress field are solved by automatic differentiation to obtain the reservoir rock stress and strain parameters.

[0071] Step 4: Calculate cell damage factors and determine cell damage degree through continuous damage model, and then correct reservoir rock mechanical parameters (effective stress, Young's modulus) and physical property parameters (porosity, permeability). After iterative calculation, obtain the corrected reservoir seepage field and stress-strain field, and obtain the micro-fracture damage zone caused by pressure-driven water injection.

[0072] Step 5: Collect relative permeability curves, geological parameters, fluid parameters, and core experimental data of low-permeability sandstone reservoirs in actual mining areas, and establish a heterogeneous, refined three-dimensional pressure-driven water-injection reservoir black oil geological model for the target block.

[0073] Step 6: Extract the attribute parameters (permeability, mechanical properties, etc.) of the micro-fracture damage zone from Step 4 as input parameters and import them into the three-dimensional geological model. Then, use reservoir software to simulate the oil-water two-phase process of water-driven oil to obtain the water saturation distribution of pressure-driven oil and finally obtain the effective range of water injection for pressure-driven oil.

[0074] A further technical solution is that, in step 1, the constitutive equation for the interaction between the matrix rock and the fluid is: based on Boit's linear elastic stress theory, the constitutive relationship equation between the fluid and the matrix is ​​established; and according to the effective stress, the equilibrium equation between the rock and the fluid can be obtained.

[0075] σ=σ′-α·p m I (1)

[0076] Where: σ`—effective stress tensor of rock, Pa; σ—total stress tensor of rock, Pa; p m — Rock pore fluid pressure, Pa; α—Biot coefficient, ranging from 0 to 1;

[0077] I—Identity matrix.

[0078] Based on the effective stress of rock and the stress-strain linear elastic relationship, the relationship between the effective stress of rock and the rock displacement can be obtained:

[0079] σ′=λ(▽·u)I+2Gε(u) (2)

[0080] Where: u—rock displacement tensor, m; ε—rock strain tensor, dimensionless; λ—Lamé's first coefficient in the formula of the continuum mechanics theory, dimensionless; G—Lamé's second coefficient in the formula of the continuum mechanics theory, dimensionless.

[0081] The rock strain tensor can be expressed as:

[0082]

[0083] During pressure displacement, injected water seeps into the formation, increasing reservoir pore pressure and thus affecting the reservoir stress field distribution. Simultaneously, changes in reservoir stress cause reservoir volume deformation, further influencing the reservoir porosity-permeability coefficient. Assuming infinitesimal elastic deformation of the reservoir, the expressions for permeability and porosity within the rock matrix can be obtained:

[0084]

[0085] Where: p, p0—reservoir pressure and reference pressure, Pa; ε, ε0—rock strain under p and p0 pressure conditions, dimensionless; φ, φ0—matrix porosity under p and p0 pressure conditions, dimensionless; M—reference coefficient in Biot theory, dimensionless; K—reservoir matrix permeability, mD; c—Kozeny-Carman constant, dimensionless; S—rock specific surface area, cm 2 / cm 3 .

[0086] A further technical solution is that the differential equation for the two-phase flow of oil and water within the rock matrix in step 1 is:

[0087]

[0088]

[0089] In the formula, K is the absolute permeability, k ro and k rw These are the relative permeabilities of the oil and water phases, in μm. 2 B o And B w These are the volume coefficients of the oil and water phases, respectively; as well as These represent the pressure gradients at the oil and water phases, respectively, in MPa·m. -1 ;ρ o and ρ wThese are the densities of the oil phase and the water phase, respectively, in kg·m³. -3 ;q o and q w These represent the oil and water phase production under standard conditions (positive for injection wells, negative for production wells), in cubic meters (m³). 3 S o and S w These represent the saturation levels of the oil phase and the water phase, respectively.

[0090] A further technical solution is that the seepage-stress-damage coupling solution method in step 3 is as follows:

[0091] First, the model is spatially discretized and assembled. Then, the rock mechanics parameters and fluid parameters in each cell grid are initialized. Next, the time domain is discretized, and the seepage-stress-damage model is calculated under different time steps. Finally, considering the influence of low-velocity non-Darcy flow in low-permeability reservoirs and Biot's linear elasticity theory, the coupling relationship between reservoir rock deformation and fluid seepage is established.

[0092]

[0093] Where p, p0—reservoir pressure and reference pressure, Pa; ε, ε0—rock strain under p and p0 pressure conditions, dimensionless; φ, φ0—matrix porosity under p and p0 pressure conditions, dimensionless; M—reference coefficient in Biot theory, dimensionless;

[0094] An automatic differentiation method is used to compute coupled numerical models. This method decomposes complex functions into multiple simpler functions, calculates and stores them separately, and automatically returns the derivative of the original function at any point in the multi-layered composite function. This reduces the difficulty of differentiating complex functions. The algorithm's rules are as follows:

[0095]

[0096] In the formula: a, b — two variables in the computational domain;

[0097] a`, b` — the derivatives of variables a and b.

[0098] This invention uses an automatic differentiation algorithm to obtain the Jacobian matrix of the fluid-structure interaction equations, and then calculates the nonlinear equations using Newton's iteration method, as follows:

[0099] J -1 ×δV=-R (9)

[0100] δV=V n+1 -V n (10)

[0101] Where: J — Jacobi matrix;

[0102] V n V n+1 Unknown variables at times n and n+1, such as the fluid saturation S of the element mesh, rock displacement u, and pore pressure p.

[0103] A further technical solution is to introduce a damage factor d in step 4. Its physical meaning represents the degree of rock damage, with a value ranging from 0 to 1. A value of 0 indicates that the rock is not fractured, and a value of 1 indicates that the rock is completely destroyed. Based on the damage factor, the actual stress and effective stress of the formation are expressed as follows:

[0104]

[0105] Where: σ`—effective formation stress, Pa; σ—actual formation stress, Pa.

[0106] This invention establishes a coupled seepage-stress-damage (HMD) mathematical model for hydraulic fracturing and oil displacement in low-permeability reservoirs based on a nonlinear seepage model, Biot linear elastic theory, and a continuous damage model. Coupled with the Petrel three-dimensional geological model, it realizes integrated numerical simulation of hydraulic fracturing and geological engineering, accurately describing the effective range of hydraulic fracturing and water injection.

[0107] The following are several specific embodiments of the application of the present invention.

[0108] Example 1

[0109] In a specific embodiment 1 of the present invention, the integrated numerical simulation method for the geological and engineering effects of pressure-driven water injection in low-permeability reservoirs includes the following steps:

[0110] Step 1: Simulate reservoir dimensions of 808*808*40m, with a five-point injection-production well pattern (1 injection, 4 production). Figure 3 As shown, this includes one hydraulically driven water injection well (W5) and four hydraulically fractured oil production wells (W2, W4, W6, and W9). The hydraulic injection parameters are set as shown in Table 1, with a single injection volume of 30,000 m³ / s for each hydraulically driven water injection well. 3 The injection rate is 1000m. 3 The flow rate was 0.95 m / min, with an initial concentration of 0.2% for the accompanying oil displacement agent.

[0111] Table 1 Basic Engineering Parameters of the Reservoir

[0112]

[0113] Step 2: Based on the established seepage-stress-damage coupling model and numerical solution method, simulate and obtain the microcrack damage zone caused by pressure-driven water injection, such as... Figure 4 As shown.

[0114] Step 3: The target area includes 8 production wells (W1, W2, W3, W4, W6, W8, W9, W10) and 2 injection wells (W5, W7), distributed in a nine-point diamond well network. Pressure-driven water injection is planned for W5 and W7. Geological parameters such as well logging, fluid parameters, reservoir relative permeability curves, and core experimental data from actual low-permeability sandstone reservoirs in the area are collected from 10 wells (W1-W10). Based on these, reservoir parameters are controlled, and considering the influence of faults, a refined three-dimensional pressure-driven water injection reservoir geological model of the target block is established, such as... Figure 5 As shown. The model is 1347m long × 1234m wide × 266m high, with 8 × 151 planar grids and 34 vertical grids.

[0115] Step 4: Extract the attribute parameters (permeability, mechanical properties, etc.) of the micro-fracture damage zone from Step 2 and import them into the three-dimensional geological model. Then, use reservoir software to simulate the oil-water two-phase process of water-driven oil recovery to obtain the water saturation distribution during pressure flooding. Figure 6 As shown in Table 2, the effective range of pressure-driven water injection was finally obtained.

[0116] Table 2 Simulation results of the effective range of pressure-driven water injection

[0117]

[0118] Example 2

[0119] In a specific embodiment 2 of the present invention, such as Figure 2 As shown, Figure 2 This is a flowchart of the seepage-stress-damage coupling solution process of the present invention. The seepage-stress-damage coupling solution process includes:

[0120] Step 1: Based on the interaction between rock and fluid, and combining the seepage model, Biot linear elastic theory and continuous damage model, establish a fracturing oil displacement physical model and perform discrete element mesh generation.

[0121] Step 2: Based on the finite volume method, the differential equation of the control volume of each node is integrated to obtain the corresponding discrete equation. The volumes controlled by the nodes of the computational grid do not overlap, so the discrete local conservation performance effectively ensures the conservation of the overall computational field, and can efficiently solve the nonlinear seepage equation of tight oil reservoirs.

[0122] Step 3: Based on the virtual element method, first analyze the virtual element space, then use the projection operator to solve the mass and stiffness matrices, and then calculate the stress and strain field of the tight reservoir element.

[0123] Step 4: Based on the Mohr-Coulomb criterion, the principle of energy conservation, the rock damage constitutive tensor and the linear elastic constitutive tensor, a damage factor is introduced to obtain the damage evolution function, thereby determining the degree of damage to the tight reservoir rock.

[0124] Step 5: Determine whether the convergence condition of the calculation process is met. If not, return to step 2 for iterative calculation until the convergence condition is met, then end the calculation and output the result.

[0125] This invention is applied to the production enhancement and stimulation of low-permeability oil reservoirs, specifically to the design of pressure-driven water injection well schemes. It accurately reflects the development effect of pressure-driven production enhancement and injection, provides technical means for the study of development mechanisms such as the effect law of pressure-driven operation, and supports the whole-process optimization and control of development schemes such as balanced development strategy, post-pressure-driven energy replenishment method, and differentiated pressure-driven operation.

[0126] 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.

[0127] Except for the technical features described in the specification, all other technologies are known to those skilled in the art.

Claims

1. A numerical simulation method integrating geology and engineering for pressure-driven water injection in low-permeability oil reservoirs, characterized in that, The integrated numerical simulation method for the geological and engineering effects of water injection pressure drive in low-permeability oil reservoirs includes: Step 1: Establish a seepage-stress-damage coupling model; Step 2: After calculating the seepage field, the stress field is calculated by coupling the stress-strain relationship of the rock matrix; Step 3: Solve for the stress-strain parameters of the reservoir rock; Step 4: Obtain the microcrack damage zone caused by pressure-driven water injection; Step 5: Establish a detailed three-dimensional geological model of the heterogeneous water-injected pressure-driven oil reservoir in the target block; Step 6: Simulate the water saturation distribution of the pressure drive to obtain the effective range of water injection for pressure drive.

2. The integrated numerical simulation method for the geological and engineering effects of pressure-driven water injection in low-permeability reservoirs according to claim 1, characterized in that, In step 1, based on the interaction between rock and fluid, and combining the seepage model, Biot linear elastic theory and continuous damage model, a seepage-stress-damage fluid-structure coupling mathematical model is constructed, and a seepage-stress-damage coupling model is established.

3. The integrated numerical simulation method for the geological and engineering effects of pressure-driven water injection in low-permeability reservoirs according to claim 2, characterized in that, In step 1, the constitutive equation for the interaction between the matrix rock and the fluid is: Based on Boit's linear elastic stress theory, the constitutive relationship equation between the fluid and the matrix is ​​established. According to the effective stress, the equilibrium equation between the rock and the fluid can be obtained: σ=σ′-α·p m I (1) Where: σ`—effective stress tensor of rock, Pa; σ—total stress tensor of rock, Pa; p m — Rock pore fluid pressure, Pa; α—Biot coefficient, ranging from 0 to 1; I—Identity matrix; Based on the effective stress of rock and the stress-strain linear elastic relationship, the relationship between the effective stress of rock and the rock displacement can be obtained: σ′=λ(▽·u)I+2Gε(u) (2) Where: u—rock displacement tensor, m; ε—rock strain tensor, dimensionless; λ—Lamé's first coefficient in the formula of the continuum mechanics theory, dimensionless; G—Lamé's second coefficient in the formula of the continuum mechanics theory, dimensionless; The rock strain tensor can be expressed as: During pressure displacement, injected water seeps into the formation, increasing reservoir pore pressure and thus affecting the reservoir stress field distribution. Simultaneously, changes in reservoir stress cause reservoir volume deformation, further influencing the reservoir porosity-permeability coefficient. Assuming infinitesimal elastic deformation of the reservoir, the expressions for permeability and porosity within the rock matrix can be obtained: Where: p, p0—reservoir pressure and reference pressure, respectively, in Pa; Rock strain under pressures ε, ε0—p and p0, dimensionless; φ, φ0—matrix porosity under pressures p and p0, dimensionless; M—reference coefficient in Biot theory, dimensionless; K—reservoir matrix permeability, mD; c—Kozeny-Carman constant, dimensionless; S—rock specific surface area, cm 2 / cm 3 .

4. The integrated numerical simulation method for the geological and engineering effects of pressure-driven water injection in low-permeability reservoirs according to claim 3, characterized in that, In step 1, the differential equation for the two-phase flow of oil and water within the rock matrix is: In the formula, K is the absolute permeability, k ro and k rw These are the relative permeabilities of the oil and water phases, in μm. 2 ; B o And B w These are the volume coefficients of the oil and water phases, respectively; as well as These represent the pressure gradients at the oil and water phases, respectively, in MPa·m. -1 ; ρ o and ρ w These are the densities of the oil phase and the water phase, respectively, in kg·m³. -3 ;q o and q w These represent the oil and water phase production under standard conditions, with positive values ​​for injection wells and negative values ​​for production wells. The unit is m³. 3 ; S o and S w These represent the saturation levels of the oil phase and the water phase, respectively.

5. The integrated numerical simulation method for the geological and engineering effects of pressure-driven water injection in low-permeability reservoirs according to claim 1, characterized in that, In step 2, considering the actual physical process of pressure-driven water injection, the injected water flows in the reservoir, causing changes in the stress field of the reservoir rock. These changes in the stress field cause rock damage. Therefore, the seepage field is calculated first, and then the stress field is calculated by coupling the stress-strain relationship of the rock matrix.

6. The integrated numerical simulation method for the geological and engineering effects of pressure-driven water injection in low-permeability reservoirs according to claim 1, characterized in that, In step 3, the seepage equation is first discretized and solved using the finite volume method. Based on this, the rock stress and strain field is projected and calculated using the virtual element method. Finally, the fluid seepage field and rock stress field are solved by automatic differentiation to obtain the reservoir rock stress and strain parameters.

7. The integrated numerical simulation method for the geological and engineering effects of pressure-driven water injection in low-permeability reservoirs according to claim 6, characterized in that, In step 3, when performing fluid-structure interaction (FSI) solutions for the fluid seepage field and rock stress field, the model is first spatially discretized and assembled, and then the rock mechanical parameters and fluid parameters in each element grid are initialized. Next, the time domain is discretized, and the seepage-stress-damage model is calculated under different time steps. Finally, considering the influence of low-velocity non-Darcy seepage in low-permeability reservoirs and Biot's linear elastic theory, the coupling relationship between reservoir rock deformation and fluid seepage is established. Where p, p0—reservoir pressure and reference pressure, Pa; ε, ε0—rock strain under p and p0 pressure conditions, dimensionless; φ, φ0—matrix porosity under p and p0 pressure conditions, dimensionless; M—reference coefficient in Biot theory, dimensionless; An automatic differentiation method is used to compute coupled numerical models. Complex functions are broken down into multiple simpler functions, which are computed and stored separately. Differentiation is performed at a specific point in the multi-layered composite function, automatically returning the derivative at any point in the original function. This reduces the difficulty of differentiating complex functions. The algorithm's rules are as follows: In the formula: a, b — two variables in the computational domain; a`, b` — the derivatives of variables a and b; The Jacobian matrix of the fluid-structure interaction equations is obtained through an automatic differentiation algorithm, and then the nonlinear equations are calculated using Newton's iteration method, as follows: J -1 ×δV=-R (9) δV=V n+1 -V n (10) Where: J — Jacobi matrix; V n V n+1 Unknown variables at times n and n+1 include the fluid saturation S of the cell grid, the rock displacement u, and the pore pressure p; R—Residual vector, dimensionless.

8. The integrated numerical simulation method for the geological and engineering effects of pressure-driven water injection in low-permeability reservoirs according to claim 1, characterized in that, In step 4, the cell damage factor is calculated and the degree of cell damage is determined by the continuous damage model. Then, the reservoir rock mechanical parameters, including effective stress and Young's modulus, and physical property parameters, including porosity and permeability, are corrected. After iterative calculation, the corrected reservoir seepage field and stress-strain field are obtained, and the micro-crack damage zone caused by pressure-driven water injection is obtained.

9. The integrated numerical simulation method for the geological and engineering effects of pressure-driven water injection in low-permeability reservoirs according to claim 8, characterized in that, In step 4, a damage factor d is introduced, which physically represents the degree of rock damage. Its value ranges from 0 to 1, where 0 indicates the rock is not fractured and 1 indicates complete rock failure. Based on the damage factor, the actual stress and effective stress of the formation are expressed as follows: Where: σ`—effective formation stress, Pa; σ—actual formation stress, Pa.

10. The integrated numerical simulation method for the geological and engineering effects of pressure-driven water injection in low-permeability reservoirs according to claim 1, characterized in that, In step 5, collect the relative permeability curves, geological parameters, fluid parameters, and core experimental data of low-permeability sandstone reservoirs in the actual mining field, and establish a heterogeneous, refined three-dimensional pressure-driven water-injection reservoir black oil geological model for the target block.

11. The integrated numerical simulation method for the geological and engineering effects of pressure-driven water injection in low-permeability reservoirs according to claim 1, characterized in that, In step 6, the micro-fracture damage zone attribute parameters, including permeability and mechanical properties, are extracted from step 4 and imported into the three-dimensional pressure-driven water injection reservoir black oil geological model. The oil-water two-phase process of water-driven oil is simulated using reservoir software to obtain the water saturation distribution of pressure-driven oil injection and finally obtain the effective range of pressure-driven water injection.

12. An integrated numerical simulation system for the geological engineering of low-permeability reservoir pressure-driven water injection, characterized in that: The integrated numerical simulation system for the geological and engineering aspects of water injection-induced pressure drive in low-permeability reservoirs uses the integrated numerical simulation method for water injection-induced pressure drive in low-permeability reservoirs as described in any one of claims 1-11 to describe the oil-water movement patterns and water front distribution during the pressure drive process.

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