Marine loose sandstone reservoir microtransformation simulation method

Abstract

The invention discloses an offshore loose sandstone reservoir microtransformation simulation method which comprises the following steps: establishing an oil reservoir multiphase fluid thermal model, simulating the flowing process of multiphase fluid, and calculating and generating pore pressure, temperature and fluid saturation in real time to achieve the preliminary convergence of a fluid flowing part; establishing a geomechanical numerical model, loading pore pressure and temperature as external loads, executing solid-flow coupling calculation, and generating a stress field, a deformation field and updated porosity and permeability; the porosity and the permeability are transmitted back to the multiphase fluid simulation software in real time, the flow state of the multiphase fluid is recalculated through an iterative algorithm, and the fluid dynamic model is updated; and repeating the above steps, and carrying out multiple iterative loops until all physical field parameters in the coupling process reach stable and convergent conditions. By coupling geomechanics and oil reservoir simulation, the complex coupling effect of multiphase thermal fluid and rock mechanics is accurately simulated, so that the oil and gas yield is increased, and the development efficiency is optimized.

Description

Technical Field

[0001] The invention belongs to the technical field of unconventional oil and gas reservoir exploitation, and in particular relates to a micro-transformation simulation method for an offshore loose sandstone reservoir. Background Art

[0002] In the process of reservoir development, especially in loose sandstone reservoirs offshore, reservoir micro-transformation technology is a common method to improve the recovery rate. Due to the low compressive strength and high porosity of loose sandstone, it is prone to geomechanical deformation and sand production during the mining process. Traditional reservoir simulation methods usually only consider multiphase fluid flow, while ignoring the deformation and stress changes of reservoir rocks. However, changes in fluid pressure in the reservoir will significantly affect the distribution of ground stress, thereby causing rock deformation and even fracture, which is particularly obvious in loose sandstone reservoirs and easily leads to engineering problems such as sand production and well wall collapse. Therefore, a single fluid flow simulation can no longer meet the engineering needs in complex reservoir environments. The complex coupling between multiphase thermal fluids and rock mechanics must be fully considered to ensure that the simulation results can truly reflect the deformation and flow phenomena in the reservoir.

[0003] In recent years, coupled simulation methods have been widely used and studied. By numerically simulating the coupling of geomechanics and thermal recovery processes, the interaction between fluid flow, pressure changes and rock deformation can be described more accurately. Commonly used coupled simulation methods mainly include sequential coupling and full coupling. Sequential coupling is relatively simple and easy to implement, but it may lack accuracy when dealing with highly nonlinear problems. In contrast, the full coupling method can simulate complex interaction processes more accurately, but it has a large amount of calculations and is relatively complex to implement numerically.

[0004] In view of the particularity of offshore loose sandstone reservoirs, it is urgent to develop an efficient and accurate coupling simulation method. Summary of the invention

[0005] The problem to be solved by the present invention is to provide a method for simulating micro-transformation of offshore loose sandstone reservoirs. The method accurately reproduces the two-way coupling process through numerical simulation of coupled geomechanics and thermal recovery processes, covers nonlinear elastoplastic constitutive behavior, stress path, initial stress state and its influence on fluid flow and stress field, and comprehensively considers the coupling effect of reservoir fluid flow and geomechanical deformation, aiming to improve the prediction accuracy and optimization efficiency in the process of micro-transformation of loose sandstone reservoirs.

[0006] In order to solve the above technical problems, the technical solution adopted by the present invention is: a method for simulating micro-transformation of an offshore loose sandstone reservoir, comprising the following steps:

[0007] S1: Use multiphase fluid simulation software to establish a multiphase fluid thermal model of the reservoir, simulate the flow process of the multiphase fluid, generate pore pressure, temperature and fluid saturation through real-time calculation, and achieve preliminary convergence of the fluid flow part;

[0008] S2: dynamically transferring the pore pressure and the temperature to the geomechanical simulation software through a custom interface module, establishing a geomechanical numerical model, loading the pore pressure and the temperature as external loads, performing solid-fluid coupling calculation, and generating stress field, deformation field, and updated porosity and permeability;

[0009] S3: transmitting the porosity and the permeability back to the multiphase fluid simulation software in real time, recalculating the flow state of the multiphase fluid through an iterative algorithm, and updating the fluid dynamics model;

[0010] S4: Repeat S2-S3 for multiple iterations until all physical field parameters in the coupling process reach stable and converged conditions, and finally obtain high-precision simulation results.

[0011] Furthermore, in S1, the multiphase fluid simulation software is CMG software, which performs thermal simulation of multiphase fluid through its built-in STARS module. Its calculation is based on fluid flow equations and energy balance equations, and generates output data containing multi-physical field variables in real time.

[0012] Furthermore, the fluid flow equation includes a water phase mass conservation equation, an oil phase mass conservation equation and a gas phase mass conservation equation.

[0013] The water phase mass conservation equation is as follows,

[0014]

[0015] The oil phase mass conservation equation is as follows:

[0016]

[0017] The gas phase mass conservation equation is as follows,

[0018]

[0019] Among them, q α is the source / sink term of the α phase; S α is the saturation of the α phase; ρ α is the density of the α component in the α phase; c α and β α They represent the compressibility and volume thermal expansion coefficient of the α component respectively; K α and μ α represent the effective permeability and dynamic viscosity of the α phase, respectively.

[0020] Furthermore, the energy balance equation is as follows:

[0021]

[0022] Among them, porous media properties: φ is the dimensionless porosity, which represents the proportion of pore space in the medium, ρ s is the solid phase density, C s is the solid phase heat capacity, H s is the enthalpy of the solid phase;

[0023] Fluid properties: α represents the fluid phase, and its values ​​are w (water phase), o (oil phase), and g (gas phase);

[0024] ρ α is the density of the α component in the α phase, S α is the saturation of the α phase, c α is the compressibility of the α phase, U α is the internal energy of the α component, C α is the heat capacity of the α phase, β α is the volume expansion coefficient of the α phase, K α is the permeability, H α is the enthalpy of the α component, μ α is the α phase dynamic viscosity;

[0025] Field variables: T is the temperature field, p is the pressure field, ε v Volumetric strain rate, dimensionless, represents the deformation rate of porous media, q T , heat source term, represents the rate of heat generation or loss per unit volume;

[0026] Thermal conductivity: λ eff is the effective thermal conductivity of the porous medium;

[0027] Gravity: g is the acceleration due to gravity.

[0028] Further, the S2 comprises the following steps:

[0029] S21: loading the pore pressure and the temperature as external loads into the geomechanical numerical model through a custom interface module, and performing iterative calculation of deformation and stress distribution in combination with a rock mechanics model;

[0030] S22: According to the stress distribution result, the porosity is updated by applying the poroelasticity theory, and the plastic deformation of the formation is calculated by the corresponding stress-strain relationship;

[0031] S23: Based on the updated porosity data, the permeability is calculated using an empirical permeability model.

[0032] Furthermore, the thermoelastic strain of the poroelastic theory in S22 is calculated by the following thermoelastic expansion equation:

[0033] Δ∈ th =α T ΔTI

[0034] Among them, Δ∈ th is the thermoelastic strain, α T is the linear thermal expansion coefficient, ΔT is the temperature change, and I represents the second-order identity tensor.

[0035] Further, in S22, the stress-strain relationship calculation formula is as follows:

[0036] σ′=σ+αpI

[0037] Among them, σ is the total stress tensor, p is the pore pressure, α is the Biot coefficient, and I is the second-order identity tensor.

[0038] Furthermore, the present invention also provides a device for running any of the data processing methods described above.

[0039] Furthermore, the present invention also provides a device, comprising a memory, a processor, and an algorithm stored in the memory and executable on the processor, wherein the processor implements any one of the above-mentioned data processing methods when executing the computer program.

[0040] Furthermore, the present invention also provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer algorithm, and when the computer algorithm is executed by a processor, the data processing described in any one of the above items is implemented.

[0041] The advantages and positive effects of the present invention are:

[0042] 1. During the micro-transformation and production process of heavy oil thermal recovery wells, the injected hot water or steam will cause changes in the pore pressure, saturation and temperature in the reservoir, thereby changing the effective stress state in the reservoir. The porosity and permeability of the reservoir are further affected. Changes in porosity and permeability will affect the fluid flow and heat conduction in the reservoir, and these changes are fed back to the fluid and thermodynamic models through iterative cycles, forming a two-way coupled dynamic process. The present invention conducts analysis by coupling geomechanics with thermal recovery simulation, covering nonlinear elastoplastic constitutive behavior, stress path, initial stress state and its interaction with fluid flow and stress field, significantly improving the prediction accuracy of the reservoir micro-transformation effect.

[0043] 2. The present invention includes the control equations and algorithms for coupling geomechanical simulation and thermal recovery simulation, and reveals the key influencing factors and coupling mechanisms in the thermal recovery process. Through simulation analysis, the influence of changes in geostress field and temperature field on reservoir micro-renovation technology can be determined. According to the results of the coupled numerical model, a set of reservoir micro-renovation technology for heavy oil thermal recovery wells is proposed, and the thermal fluid injection parameters and reservoir micro-renovation scheme of heavy oil thermal recovery wells are optimized to improve the efficiency of reservoir micro-renovation and increase the recovery rate. In order to optimize the development effect of the oil field.

[0044] 3. The present invention proposes an improved coupled reservoir-geomechanics numerical model based on an adaptive multi-physics field coupling algorithm. The model adds a spatiotemporal dynamic adjustment mechanism to the mass conservation and energy conservation equations of multiphase fluids, and can accurately adjust the stress-strain relationship according to real-time changes in temperature, pressure and fluid saturation. In particular, the model introduces a multi-scale feedback mechanism, which enables it to dynamically simulate the physical changes in the reservoir micro-transformation process in a complex thermal-fluid-solid coupling environment, thereby significantly improving the prediction accuracy and optimization effect of reservoir development, and is particularly suitable for the efficient development of heavy oil thermal recovery wells.

[0045] 4. The present invention can identify and predict potential geomechanical problems in the reservoir development process, such as sand production and wellbore collapse, so as to take preventive measures to ensure the safety of the reservoir development process. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Figure 1 It is a schematic diagram of the overall process of an embodiment of the present invention.

[0047] Figure 2 It is a three-dimensional structure diagram of the multiphase fluid thermal model according to an embodiment of the present invention.

[0048] Figure 3 It is a history fitting effect diagram of the multiphase fluid thermal model according to an embodiment of the present invention.

[0049] Figure 4 It is a schematic diagram of stress distribution around the well during reservoir micro-transformation simulation in an embodiment of the present invention.

[0050] Figure 5 3 is a graph showing the change in porosity after transformation according to an embodiment of the present invention.

[0051] Figure 6 This is a diagram of the permeability change after the transformation of an embodiment of the present invention.

[0052] Figure 7 , Figure 8 It is a comparison diagram of the effects of different reservoir micro-transformation methods in the embodiments of the present invention. DETAILED DESCRIPTION

[0053] The technical solution of the present invention will be described clearly and completely below 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. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0054] In the description of the present invention, it should be noted that the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", etc., indicating the orientation or positional relationship, are based on the orientation or positional relationship shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, the terms "first", "second", and "third" are used for descriptive purposes only, and cannot be understood as indicating or implying relative importance.

[0055] In the description of the present invention, it should be noted that, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0056] The embodiments of the present invention are further described below in conjunction with the accompanying drawings:

[0057] like Figure 1 As shown, a method for simulating micro-transformation of an offshore loose sandstone reservoir includes the following steps.

[0058] S1: Based on the geological data of the actual reservoir, a multiphase fluid thermal model of the reservoir is established using multiphase fluid simulation software to simulate the flow process of the multiphase fluid. Through real-time calculation, key field parameters such as pore pressure, temperature and fluid saturation are generated to achieve initial convergence of the fluid flow part.

[0059] Specifically, multiphase fluid flow simulation is performed using CMG software, and thermal simulation of multiphase fluid is performed through its built-in STARS module. The STARS module is based on the finite difference method (FDM) and captures the dynamic behavior of thermal fluids in the reservoir with high precision, thereby ensuring accurate calculation of pore pressure, temperature and fluid saturation.

[0060] When in use, the field parameters of multiphase fluid flow are dynamically calculated by CMG software in each time increment. After the fluid flow part reaches local convergence, key variables such as pore pressure and temperature field are transmitted to the geomechanical simulation software in real time through the custom interface module to ensure data update and iterative optimization of physical field parameters in the coupling process.

[0061] Among them, the solid phase mass conservation equation is used to describe the mass change of solid rock. The specific formula is as follows:

[0062]

[0063] Among them, ρ s is the density of the solid, v s is the velocity of the solid phase, is the solid phase velocity, and the equation is used to simulate the solid phase mass balance when the multiphase fluid interacts with the solid structure in real time.

[0064] When solid minerals are assumed to be incompressible, the solid phase velocity v s The relationship between , porosity φ and volumetric strain rate is expressed by the following equation,

[0065]

[0066] This formula is used to simulate the changes in pore structure caused by fluid flow and stress changes, especially the dynamic effect of solid deformation on porosity in unconsolidated sandstone reservoirs.

[0067] When the pore space is completely occupied by oil, water, and gas, the following saturation constraint equation applies,

[0068] S w +S o +S g =1

[0069] Among them, S w is the water phase saturation, S o is the oil phase saturation, S g is the gas phase saturation. This equation is used to ensure the mass conservation of the three-phase fluid in the porous medium and is dynamically updated in combination with the multiphase fluid flow during thermal recovery.

[0070] When the capillary pressure is ignored, the fluid pressure of each phase in the pore satisfies the following relationship:

[0071] p w =p o =p g =p

[0072] Among them, p w is the water phase pressure, p o is the oil phase pressure, p gis the gas phase pressure. This formula is used to simplify the simulation of the pressure field of multiphase fluids in pores and is particularly suitable for the rapid calculation of the pressure field in high permeability reservoirs.

[0073] By applying the chain rule, the time derivative of fluid density is expressed as a function of pressure and temperature. The mass conservation equation of multiphase fluid in porous media specifically includes the dynamic conservation relationship of water phase, oil phase and gas phase. The equation is as follows,

[0074] Conservation of mass of water phase:

[0075]

[0076] Among them, c w The water phase is the compressibility factor, β w is the volume expansion coefficient of the water phase, K w is the permeability, μ w is the dynamic viscosity of the water phase, g is the acceleration due to gravity, q w is the water phase source term.

[0077] Oil phase mass conservation:

[0078]

[0079] Among them, c o is the oil phase compressibility coefficient, β o is the volume expansion coefficient of the oil phase, K o is the oil phase permeability, μ o is the dynamic viscosity of the oil phase, is the density of the oil phase, q o is the oil phase source term.

[0080] Gas phase mass conservation:

[0081]

[0082] Among them, c g is the gas phase compressibility coefficient, β g is the gas phase volume expansion coefficient, K g is the gas phase permeability, μ g is the gas phase dynamic viscosity, ρ g is the gas phase density, q g is the gas phase source term.

[0083] The equation is used to describe the dynamic mass conservation relationship of water phase, oil phase and gas phase in porous media, and is updated in real time in combination with variables such as porosity, saturation, density, compressibility coefficient, volume expansion coefficient, etc. in the fluid-solid coupling process to ensure the dynamic balance and coupling accuracy of multiple physical fields. It is particularly suitable for thermal recovery processes in loose sandstone reservoirs.

[0084] The equation is expressed by five key variables, including pressure p, temperature T, water saturation S w , oil saturation S o and volumetric strain ∈ v In particular, the present invention introduces a dynamic adjustment coefficient based on pressure gradient and temperature changes, which adjusts porosity and permeability in real time according to fluid-solid interaction, ensuring high-precision fluid-solid coupling simulation under complex geological conditions. Compared with the traditional static strain model, this method dynamically reflects the impact of stress changes on fluid flow behavior by adaptively adjusting parameters, thereby significantly improving simulation accuracy and efficiency, and is particularly suitable for the development of complex offshore loose sandstone reservoirs. Specifically,

[0085] q α is the source / sink term of the α phase;

[0086] S α is the saturation of the α phase;

[0087] ρ α is the density of the α component in the α phase;

[0088] c α and β α represent the compressibility and volumetric thermal expansion coefficient of the α component, respectively;

[0089] K α and μ α represent the effective permeability and dynamic viscosity of the α phase, respectively.

[0090] The equation is used to simulate the interaction between different phases in the reservoir and ensure the coupling calculation accuracy of fluid mechanics and geomechanics of multiphase fluid during thermal recovery.

[0091] The energy balance equation is used to describe the energy transfer and conversion process in porous media. Combining the internal energy, heat conduction and heat convection effects, the specific equation is as follows:

[0092]

[0093] Among them, U α and H α are the internal energy and enthalpy of the α component, λ eff is the effective thermal conductivity of the porous medium. It should be noted that c α and C α The lowercase and uppercase letters represent the compressibility and heat capacity of the α phase, respectively. In the mass and energy balance equations, the volumetric strain rate It plays a key coupling role in the subsequent force balance analysis. This equation is used to simulate the transfer and distribution of energy during thermal recovery of oil reservoirs, especially the effects of temperature changes and stress on energy flow.

[0094] S2: Through the custom interface module, the pore pressure and temperature are dynamically transferred to the geomechanical simulation software to establish a geomechanical numerical model, specifically, including the nonlinear elastic-plastic constitutive relationship of the rock, the stress path and the initial stress state. The pore pressure, temperature field and fluid saturation data are loaded as external loads, and the solid-fluid coupling calculation is performed to generate the stress field, deformation field and updated porosity and permeability. Specifically, the hot water or steam injection process of the heavy oil thermal recovery well is simulated, the diffusion and conduction of the thermal fluid in the reservoir are calculated, and the pore pressure, saturation and temperature field are updated. Based on the pore pressure and temperature field after the thermal fluid injection, the stress field and deformation field in the reservoir are calculated, and the changes in the porosity and permeability of the reservoir are determined.

[0095] Specifically, the custom interface module is used to perform real-time bidirectional data transmission of key parameters between the multiphase fluid simulation software and the geomechanical simulation software. The transmitted parameters include pore pressure, temperature, porosity and permeability. The interface module is based on a unified I / O file system to ensure data format compatibility and transmission efficiency between different software, and ensures the accuracy and integrity of the transmitted data through a data consistency check algorithm.

[0096] Specifically, the calculation of porosity φ and permeability K includes the following steps:

[0097] Use multiphase fluid simulation software to dynamically calculate pore pressure p and temperature field T data. The calculation is based on fluid flow equations and energy balance equations, and output data containing multi-physics field variables is generated in real time;

[0098] Through a custom interface module, the aforementioned pore pressure p and temperature T are loaded into the geomechanical numerical model as external loads, and the deformation and stress distribution are iteratively calculated in combination with the rock mechanics model;

[0099] According to the above stress distribution results, the porosity is updated by applying the poroelasticity theory, and the plastic deformation of the formation is calculated through the corresponding stress-strain relationship;

[0100] Based on the updated porosity φ data, the permeability K is calculated using the empirical permeability model;

[0101] The updated porosity φ and permeability K are transferred back to the multiphase fluid simulation software CMG for recalculation and further optimization of the fluid flow model to achieve coupled iteration of fluid dynamics and geomechanics.

[0102] The force balance equation as a function of the effective stress σ' and the pore pressure p is expressed as follows:

[0103]

[0104] Where I represents the second-order identity tensor, ρb =nρ f +(1-n)ρ s represents the overall density of the fluid-solid mixture, g is the gravitational acceleration, α is the Biot coefficient, ρ b is the overall density of the fluid-solid mixture. This equation is used to simulate the stress distribution and changes during reservoir micro-reconstruction to ensure that the force balance is accurately calculated during the coupling process.

[0105] The present invention is based on the relationship between the improved effective stress tensor and the total stress tensor adjusted by time-dependent stress. This relationship comprehensively considers the mechanical properties of reservoir rocks under different stress paths and strain rates by introducing a multi-scale stress-strain model. Unlike the single Biot coefficient model in the prior art, the present invention dynamically calculates the effective stress by real-time coupling with the change of reservoir porosity, thereby improving the accurate prediction of stress distribution during reservoir micro-transformation, and is particularly suitable for complex loose sandstone reservoirs involving high temperature and high pressure environments:

[0106] σ′=σ+αpI

[0107] Among them, σ is the total stress tensor, p is the pore pressure, α is the Biot coefficient, and I is the second-order identity tensor. This formula is used to simulate the stress adjustment caused by the change of pore pressure during thermal recovery, and is particularly suitable for micro-transformation simulation of loose sandstone reservoirs.

[0108] The present invention proposes an improved incremental relationship model between effective stress and strain components. The model adopts strain localization control technology, combines the anisotropic characteristics of the reservoir, and improves the simulation accuracy of plastic strain by introducing dynamic nonlinear coupling coefficients. In particular, the model corrects the local thermal stress effect caused by temperature changes during micro-transformation, so that it can more accurately predict the plastic deformation behavior in complex reservoir environments and ensure the accuracy and reliability of multi-physics field coupling simulation:

[0109] Δσ'=D(Δ∈-Δ∈th-Δ∈p)

[0110] Where Δ∈ is the total strain increment, Δ∈ th is the thermoelastic strain, Δ∈ p is the plastic strain increment. This formula is used to describe the stress-strain changes caused by thermal expansion and plastic deformation in the reservoir during thermal recovery, ensuring the accuracy of the stress-strain relationship in multi-physics field coupling calculations.

[0111] The thermoelastic strain of the present invention is calculated by the following thermoelastic expansion equation:

[0112] Δ∈ th =Δ T ΔTI

[0113] where Δ∈ th is the thermoelastic strain, α T is the linear thermal expansion coefficient, and ΔT is the temperature change. This equation is used to simulate the volume expansion and stress change caused by the temperature increase during thermal recovery. It is particularly suitable for describing the deformation behavior of oil sand reservoirs in high temperature environments to ensure the accuracy of the thermal and mechanical coupling process.

[0114] During thermal recovery, oil sand formations undergo complex stress trajectories that may lead to reservoir micromodification or compression behavior, depending on the existing stress conditions. Reservoir micromodification phenomena can be accurately characterized by continuum mechanics methods, where the main focus is on macroscopic changes caused by adjustments in microscopic properties (such as particle rolling, sliding, and separation). These macroscopic changes include deformation and destruction of the formation and increased fluid flow capacity. To simulate these phenomena, a constitutive model is based on continuum mechanics, combined with the finite element method, and a soft rock plasticity model is used for solid phase deformation modeling. The model is characterized by a single yield surface and rate-independent non-associated plastic flow rules, which draws on the critical state theory. The yield surface and non-associated plastic flow rules are as follows:

[0115]

[0116] in:

[0117] F(σ') is the yield surface function;

[0118] Ψ(σ') is a function of the non-associative plastic flow rule;

[0119] p' is the mean effective stress;

[0120] q is the Mises deviatoric stress;

[0121] p c is the preconsolidation stress;

[0122] p t is the tensile strength;

[0123] β is the friction angle;

[0124] ny is the material parameter that controls the shape of the yield surface in the p'-q plane;

[0125] e 0 is the parameter that controls the shape of the yield surface;

[0126] g(σ') is the function that transitions from a circular to a rounded triangle shape in the Π plane.

[0127] This formula is used to describe the deformation behavior of reservoirs under complex stress states and is particularly suitable for micro-reconstruction simulation of weakly consolidated oil sand reservoirs.

[0128] These equations describe the behavior of materials under complex stress states, where β represents the friction angle of the material under shear stress and ψ represents the internal friction angle of the material under different stress paths. The mechanical properties of the material under different stress states can be reflected by the different friction angles (tanβ and tanψ). Reservoir micro-modification in weakly consolidated oil sands involves complex reservoir-geomechanical coupling phenomena. The core of this coupling mechanism lies in the poroelastic theory, through which the flow of multiphase fluids, including water, hydrocarbons and steam, is described by a three-phase black oil model.

[0129] In order to accurately capture the unique plastic deformation behavior in weakly consolidated oil sand reservoirs, we used an elastoplastic model of strain hardening and softening. This model can effectively quantify the plastic deformation phenomenon caused by micro-renovation in oil sand reservoirs, ensuring that the deformation of the reservoir and the changes in fluid flow capacity under different stress conditions are accurately described.

[0130] Reservoir micro-reconstruction strain during the elastic-plastic deformation of oil sands mainly occurs in the post-peak deformation stage. The finite element simulation of rock materials in this stage is highly sensitive to mesh characteristics and may introduce artificial effects. In order to accurately capture the strain localization, a regularization scheme is used to solve the mesh dependency problem, especially when the local strain of the material increases with plastic deformation. In addition, the arbitrary Lagrangian-Eulerian (ALE) regridding technique in Abaqus is used to deal with severe mesh distortion areas, and the permeability changes caused by deformation are simulated through user-defined field subroutines.

[0131] Reservoir micro-transformation refers to the rock deformation phenomenon in which the total volume of the porous medium rock mass increases due to the increase of shear stress or pore fluid pressure under the condition of total stress being compressive stress. From a microscopic perspective, the behavior of reservoir micro-transformation is manifested as the rotation, rolling and rearrangement of rock particles. The micro-transformation of the oil sand reservoir forms a large-volume, high-porosity and high-permeability transformation zone around the well, which contains countless microscopic tension-shear fracture networks, forming a high-permeability area. In the numerical simulation process, the complex coupling effect of multiphase thermal fluid and rock mechanics must be fully considered to ensure that the simulation results can truly reflect the deformation and flow phenomena in the reservoir. Due to the complex fluid-solid-thermal coupling behavior of weakly consolidated oil sand reservoirs, the reservoir micro-transformation design must be evaluated by numerical simulation to evaluate the transformation effect under different construction conditions. Coupling geomechanical simulation and thermal recovery simulation is the core technology of micro-transformation of weakly consolidated oil sand reservoirs. In the actual numerical simulation process, the present invention fully considers the complex coupling effect of multiphase thermal fluid and rock mechanics to ensure that the simulation results truly reflect the deformation and fluid flow behavior in the reservoir.

[0132] S3: The updated porosity and permeability data are sent back to the multiphase fluid simulation software in real time, and the flow state of the multiphase fluid is recalculated through an iterative algorithm to update the fluid dynamics model. Specifically, iterative calculations are performed between the reservoir model and the geomechanical model, fully considering the mutual influence of fluid flow and rock deformation. The explicit coupling algorithm is used to gradually update the calculation results of fluid flow and stress deformation until convergence.

[0133] S4: Repeat S2-S3 for multiple iterations until the physical field parameters of the thermal-fluid-geomechanical coupling process reach stable and convergent conditions, and finally obtain high-precision simulation results.

[0134] Specifically, based on the simulation results, the deformation and stress changes of the reservoir during the micro-renovation of the heavy oil thermal recovery well reservoir are analyzed. The thermal fluid injection parameters and reservoir micro-renovation process are optimized, and an efficient reservoir micro-renovation scheme suitable for offshore loose sandstone reservoirs is proposed.

[0135] The present invention is described in detail below by taking a specific embodiment as an example:

[0136] For a steam well in an offshore oil field, which is on the eve of the third round of production, a new round of reservoir micro-transformation is planned. In the second round of production, the reservoir micro-transformation operation was successfully implemented, which significantly improved the porosity and permeability of the area around the well. The offshore loose sandstone reservoir micro-transformation simulation method that couples reservoir simulation and geomechanical simulation includes the following steps:

[0137] S1: Based on the geological data of the actual reservoir, a multiphase fluid thermal model of the reservoir is established using multiphase fluid simulation software to simulate the flow process of the multiphase fluid. Through real-time calculation, key field parameters such as pore pressure, temperature and fluid saturation are generated to achieve initial convergence of the fluid flow part.

[0138] Specifically, the geological data, core analysis data, logging data and production data of the reservoir are collected. These data include parameters such as lithology distribution, porosity, permeability, fluid properties, and initial pressure and temperature distribution.

[0139] The 3D reservoir model was constructed using Petrel software, which included parameters such as the structure of the formation, lithology distribution, initial porosity and permeability. The framework and main parameters of the model were determined by analyzing geological data and well logging data.

[0140] The multiphase flow simulation module in CMG software is used to simulate the multiphase fluid of the reservoir model and simulate the flow of oil, water and gas in the reservoir. The model is fitted with historical production data to ensure the accuracy and reliability of the model. Figure 2 , Figure 3As shown, the 3D reservoir model of the well and the historical fitting effect, including the production time and cumulative oil production curve, are displayed, providing a reliable numerical basis for the subsequent simulation of reservoir micro-transformation.

[0141] S2: Through the custom interface module, the pore pressure and temperature are dynamically transferred to the geomechanical simulation software, a geomechanical numerical model is established, the pore pressure and temperature are loaded as external loads, the solid-fluid coupling calculation is performed, and the stress field, deformation field, and updated porosity and permeability are generated.

[0142] Specifically, based on the geological data of the reservoir model, the initial in-situ stress state and rock mechanical parameters of the formation are determined, including elastic modulus, Poisson's ratio, shear strength, friction angle, cohesion, etc. These parameters are obtained through laboratory tests and field in-situ stress tests.

[0143] A three-dimensional geomechanical model was established using Abaqus software. The initial geostress state of the model included horizontal principal stress, vertical principal stress and minimum horizontal stress. The model also included the rock mechanical parameters and geostress distribution of the stratum.

[0144] A data conversion interface module is developed for data transmission between the reservoir model and the geomechanical model. The interface module is used to transfer the pore pressure and temperature distribution data in the reservoir model to the geomechanical model, and to feed back the stress distribution and deformation data calculated by the geomechanical model to the reservoir model.

[0145] An explicit iterative coupling algorithm is used to exchange data in each time step until the convergence standard is reached. Specifically, the pore pressure and temperature distribution of the current time step are extracted from the reservoir model and transferred to the geomechanical model; reservoir micro-transformation is simulated in the geomechanical model, and the stress distribution and deformation of the transformation area are predicted by applying water injection pressure.

[0146] S3: Feed the stress distribution and deformation data calculated by the geomechanical model back to the reservoir model to update the permeability and porosity in the reservoir model.

[0147] S4: Repeat S2-S3 until the calculation of each time step reaches the convergence standard. Through continuous iteration, the coupling of the reservoir model and the geomechanical model is completed, and accurate simulation results are finally obtained.

[0148] like Figure 1 As shown in FIG, the process of the present invention includes data extraction and transmission, simulation of reservoir micro-transformation process, and data feedback and update. Through continuous iteration, the convergence standard of the model is finally achieved. Figure 4As shown in the figure, by coupling the reservoir model and the geomechanical model, the stress state changes caused by injection pressure and temperature changes during reservoir micro-renovation can be reflected in real time. Our coupling method can accurately capture these changes, including the impact of injection pressure and temperature increases on formation thermal stress, thereby updating the porosity and permeability in the reservoir model in real time, ensuring the accuracy and reliability of the simulation results.

[0149] Specifically, reservoir micro-transformation is simulated in the geomechanical model, and the permeability and porosity changes in the transformation area are predicted by applying a certain water injection pressure. The parameter design of reservoir micro-transformation includes water injection pressure, water injection volume and water injection rate.

[0150] By simulating reservoir micro-transformation, the porosity and permeability changes in the transformed area are predicted. The porosity and permeability distribution after transformation is used to update the parameter settings in the reservoir model. Figure 5 , Figure 6 The figure shows the distribution of porosity and permeability during reservoir micro-renovation. The simulation results show that when the injection volume reaches 950m 3 When the transformation radius is about 10 meters, the porosity increases by 2% on average, and the permeability increases to 10,000 to 15,000 millidarcy (mD). Through the coupling model, the porosity and permeability change diagrams under different transformation radii can be generated to intuitively compare the effects of different reservoir micro-transformation schemes.

[0151] Based on the permeability and porosity change data of the transformed area fed back by the geomechanical model, the steam injection pressure and oil well production after the transformation are predicted.

[0152] Analyze the impact of different transformation radius and water injection volume on reservoir micro-transformation effect. By simulating different transformation schemes, evaluate their impact on reservoir production performance and optimize reservoir micro-transformation design.

[0153] Compare the effects of different reservoir micro-transformation parameters (such as transformation radius and steam injection pressure), analyze their impact on reservoir production performance, and select the optimal reservoir micro-transformation plan.

[0154] By comparing the effects of different reservoir micro-transformation schemes, the best reservoir micro-transformation strategy is determined to achieve the best production performance. Figure 7 , Figure 8 As shown in the figure, the influence of different transformation radius on steam injection speed and the relationship between injection volume and transformation radius are shown. The results show that the larger the transformation radius, the faster the steam injection speed, but it does not mean that the larger the transformation radius, the better the effect. Figure 7 , Figure 8 It can help select the optimal reservoir micro-transformation parameter scheme and improve the overall production performance of the reservoir.

[0155] The advantages and positive effects of the present invention are:

[0156] 1. During the micro-transformation and production process of heavy oil thermal recovery wells, the injected hot water or steam will cause changes in the pore pressure, saturation and temperature in the reservoir, thereby changing the effective stress state in the reservoir. The porosity and permeability of the reservoir are further affected. Changes in porosity and permeability will affect the fluid flow and heat conduction in the reservoir, and these changes are fed back to the fluid and thermodynamic models through iterative cycles, forming a two-way coupled dynamic process. The present invention conducts analysis by coupling geomechanics with thermal recovery simulation, covering nonlinear elastoplastic constitutive behavior, stress path, initial stress state and its interaction with fluid flow and stress field, significantly improving the prediction accuracy of the reservoir micro-transformation effect.

[0157] 2. The present invention includes the control equations and algorithms for coupling geomechanical simulation and thermal recovery simulation, and reveals the key influencing factors and coupling mechanisms in the thermal recovery process. Through simulation analysis, the influence of changes in geostress field and temperature field on reservoir micro-renovation technology can be determined. According to the results of the coupled numerical model, a set of reservoir micro-renovation technology for heavy oil thermal recovery wells is proposed, and the thermal fluid injection parameters and reservoir micro-renovation scheme of heavy oil thermal recovery wells are optimized to improve the efficiency of reservoir micro-renovation and increase the recovery rate. In order to optimize the development effect of the oil field.

[0158] 3. The present invention proposes an improved coupled reservoir-geomechanics numerical model based on an adaptive multi-physics field coupling algorithm. The model adds a spatiotemporal dynamic adjustment mechanism to the mass conservation and energy conservation equations of multiphase fluids, and can accurately adjust the stress-strain relationship according to real-time changes in temperature, pressure and fluid saturation. In particular, the model introduces a multi-scale feedback mechanism, which enables it to dynamically simulate the physical changes in the reservoir micro-transformation process in a complex thermal-fluid-solid coupling environment, thereby significantly improving the prediction accuracy and optimization effect of reservoir development, and is particularly suitable for the efficient development of heavy oil thermal recovery wells.

[0159] 4. The present invention can identify and predict potential geomechanical problems in the reservoir development process, such as sand production and wellbore collapse, so as to take preventive measures to ensure the safety of the reservoir development process.

[0160] The above is a detailed description of an embodiment of the present invention, but the content is only a preferred embodiment of the present invention and cannot be considered to limit the scope of implementation of the present invention. All equivalent changes and improvements made within the scope of the present invention should still fall within the scope of the patent coverage of the present invention.

Claims

1. A method for simulating micro-transformation of an offshore loose sandstone reservoir, characterized in that: The following steps are included: S1: Use multiphase fluid simulation software to establish a multiphase fluid thermal model of the reservoir, simulate the flow process of the multiphase fluid, generate pore pressure, temperature and fluid saturation through real-time calculation, and achieve preliminary convergence of the fluid flow part; S2: dynamically transferring the pore pressure and the temperature to the geomechanical simulation software through a custom interface module, establishing a geomechanical numerical model, loading the pore pressure and the temperature as external loads, performing solid-fluid coupling calculation, and generating stress field, deformation field, and updated porosity and permeability; S3: transmitting the porosity and the permeability back to the multiphase fluid simulation software in real time, recalculating the flow state of the multiphase fluid through an iterative algorithm, and updating the fluid dynamics model; S4: Repeat S2-S3 for multiple iterations until all physical field parameters in the coupling process reach stable and converged conditions, and finally obtain high-precision simulation results.

2. The method for simulating micro-transformation of an offshore loose sandstone reservoir according to claim 1, characterized in that: In S1, the multiphase fluid simulation software is CMG software, which performs thermal simulation of multiphase fluid through its built-in STARS module. Its calculation is based on fluid flow equations and energy balance equations, and generates output data containing multi-physical field variables in real time.

3. The method for simulating micro-transformation of an offshore loose sandstone reservoir according to claim 2, characterized in that: The fluid flow equations include the water phase mass conservation equation, the oil phase mass conservation equation and the gas phase mass conservation equation. The water phase mass conservation equation is as follows, The oil phase mass conservation equation is as follows: The gas phase mass conservation equation is as follows, Among them, q α is the source / sink term of the α phase; S α is the saturation of the α phase; ρ α is the density of the α component in the α phase; c α and β α They represent the compressibility and volume thermal expansion coefficient of the α component respectively; K α and μ α represent the effective permeability and dynamic viscosity of the α phase, respectively.

4. A method for simulating micro-transformation of an offshore loose sandstone reservoir according to claim 2 or 3, characterized in that: The energy balance equation is as follows, Among them, porous media properties: φ is the dimensionless porosity, which represents the proportion of pore space in the medium, ρ s is the solid phase density, C s is the solid phase heat capacity, H s is the enthalpy of the solid phase; Fluid properties: α represents the fluid phase, and its values ​​are w (water phase), o (oil phase), and g (gas phase); ρ α is the density of the α component in the α phase, S α is the saturation of the α phase, c α is the compressibility of the α phase, U α is the internal energy of the α component, C α is the heat capacity of the α phase, β α is the volume expansion coefficient of the α phase, K α is the permeability, H α is the enthalpy of the α component, μ α is the α phase dynamic viscosity; Field variables: T is the temperature field, p is the pressure field, ε v Volumetric strain rate, dimensionless, represents the deformation rate of porous media, q T , heat source term, represents the rate of heat generation or loss per unit volume; Thermal conductivity: λ eff is the effective thermal conductivity of the porous medium; Gravity: g is the acceleration due to gravity.

5. A method for simulating micro-transformation of an offshore loose sandstone reservoir according to claim 1 or 2, characterized in that: The S2 comprises the following steps, S21: loading the pore pressure and the temperature as external loads into the geomechanical numerical model through a custom interface module, and performing iterative calculation of deformation and stress distribution in combination with a rock mechanics model; S22: According to the stress distribution result, the porosity is updated by applying the poroelasticity theory, and the plastic deformation of the formation is calculated by the corresponding stress-strain relationship; S23: Based on the updated porosity data, the permeability is calculated using an empirical permeability model.

6. The method for simulating micro-transformation of an offshore loose sandstone reservoir according to claim 5, characterized in that: The thermoelastic strain in the poroelastic theory of S22 is calculated by the following thermoelastic expansion equation: Δ∈ th =a T ΔTI Among them, Δ∈ th is the thermoelastic strain, α T is the linear thermal expansion coefficient, ΔT is the temperature change, and I represents the second-order identity tensor.

7. The method for simulating micro-transformation of an offshore loose sandstone reservoir according to claim 5, characterized in that: In S22, the stress-strain relationship calculation formula is as follows: σ′=σ+αpI Among them, σ is the total stress tensor, p is the pore pressure, α is the Biot coefficient, and I is the second-order identity tensor.

8. A device, characterized in that: Run the data processing method according to any one of claims 1 to 7.

9. A device comprising a memory, a processor, and an algorithm stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the data processing method according to any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium storing a computer algorithm, characterized in that: When the computer algorithm is executed by a processor, the data processing according to any one of claims 1 to 7 is implemented.

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