Low-permeability reservoir gas injection gravity gas drive oil interface stability evaluation method, device, equipment and medium

Abstract

The invention relates to the field of low-permeability reservoir gas injection development, and discloses a low-permeability reservoir gas injection gravity drive gas-oil interface stability evaluation method, device, equipment and medium, which can perform stress analysis on an oil-gas interface in a low-permeability reservoir of gas injection gravity drive to obtain an oil-gas interface flow model, simplify the oil-gas interface flow model, and improve the stability of the oil-gas interface. A plurality of dimensionless criteria is determined. A plurality of dimensionless quasi numbers are used to construct a combined quasi number, and a linear regression relational expression to be fitted is established between the combined quasi number and a set harvesting evaluation parameter. Fitting the linear regression relational expression to be fitted according to low-permeability reservoir sample data of reservoir numerical simulation to obtain a final linear regression relational expression, and evaluating the gas-oil interface stability of the low-permeability reservoir. According to the method, the stability of the gas injection gravity drive gas-oil interface of the low-permeability reservoir can be effectively evaluated, a technical support is provided for evaluation of the development effect of a gas injection gravity drive oil field for producing a thick oil layer, a gas injection development strategy is optimized, and the recovery efficiency is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of gas injection development of low permeability reservoirs, and in particular to a method and device for evaluating gas-oil interface stability in gas injection gravity drainage of low permeability reservoirs, equipment and medium. BACKGROUND

[0002] Low permeability reservoirs are abundant in offshore areas, but due to their small pore throats, water injection development is difficult and the recovery rate is low. Injection media such as natural gas have good injectivity, are easily dissolved in crude oil, and can expand and reduce the viscosity of crude oil, thereby improving the flow capacity of crude oil and enhancing the recovery rate of crude oil.

[0003] In related technologies, for low permeability reservoirs with large dip angle and thick oil layers, gas can be injected at the top of the reservoir to produce crude oil. During gas injection gravity drainage, gravity reduces the viscous fingering of injected gas, thereby improving the sweep efficiency of injected gas. When the gas-oil interface stably advances during gas injection, gas channeling is late, the recovery rate is the highest, and the development effect is the best.

[0004] Therefore, there is an urgent need for a method that can effectively evaluate the stability of the gas-oil interface to optimize the gas injection development strategy. SUMMARY

[0005] The present application provides a method and device for evaluating gas-oil interface stability in gas injection gravity drainage of low permeability reservoirs, equipment and medium, to solve the defect that there is no effective way to evaluate the stability of the gas-oil interface in related technologies, effectively evaluate the stability of the gas-oil interface in gas injection gravity drainage of low permeability reservoirs, and optimize the gas injection development strategy.

[0006] In a first aspect, the present application provides a method for evaluating gas-oil interface stability in gas injection gravity drainage of low permeability reservoirs, comprising: Based on the law of fluid flow, the oil-gas interface in the low permeability reservoir subjected to gas injection gravity drainage is subjected to force analysis, and an oil-gas interface flow model is obtained; According to the balance condition when the oil-gas interface stably moves, the oil-gas interface flow model is simplified to obtain a simplified flow model; Based on the simplified flow model, a plurality of dimensionless numbers for describing the process of gas injection gravity drainage are determined; A combination number is constructed using the plurality of dimensionless numbers, and a linear regression relationship to be fitted is established between the combination number and a set recovery evaluation parameter, wherein the linear regression relationship to be fitted includes the combination number, the recovery evaluation parameter and a plurality of to-be-fitted coefficients; According to the low permeability reservoir sample data obtained by reservoir numerical simulation, the plurality of to-be-fitted coefficients in the linear regression relationship to be fitted are fitted to obtain a plurality of fitted coefficients and a final linear regression relationship; Based on the final linear regression relationship, the gas-oil interface stability of the low permeability reservoir is evaluated.

[0007] Optionally, the oil-gas interface in the low-permeability oil reservoir in the gas injection gravity drainage is analyzed based on the law of fluid flow, and an oil-gas interface flow model is obtained, including: Under the condition that the low-permeability oil reservoir includes oil, gas and water phase fluids, each phase fluid is incompressible, the flow of each phase fluid satisfies the Darcy law and is isothermal seepage, the reservoir is a homogeneous bottom layer, the surface tension and the wetting angle do not change with the movement of the liquid film, and the medium is a porous medium, the oil-gas interface in the low-permeability oil reservoir is analyzed, and the porous medium Darcy equation in three dimensional directions is created; The porous medium Darcy equation in three dimensional directions is determined as the oil-gas interface flow model.

[0008] Optionally, the oil-gas interface flow model is simplified according to the balance condition when the oil-gas interface moves stably, and a simplified flow model is obtained, including: The porous medium Darcy equation in three dimensional directions in the oil-gas interface flow model is simplified to an equation considering only the vertical seepage relationship; According to the parameter prominence influence principle and the balance condition when the oil-gas interface moves stably, the multiple parameter terms in the seepage relationship equation are simplified, and the simplified flow model is obtained.

[0009] Optionally, a plurality of dimensionless numbers for describing the gas injection gravity drainage process are determined based on the simplified flow model, including: The parameters included in the simplified flow model are determined as density, viscosity, permeability, displacement pressure difference and formation dip angle; According to the parameters included in the simplified flow model, the density number, the viscosity number, the capillary number and the gravity number with the largest correlation degree with the density, the viscosity, the permeability, the displacement pressure difference and the formation dip angle are selected from the dimensionless number group of the low-permeability oil reservoir; The selected density number, viscosity number, capillary number and gravity number are determined as the dimensionless numbers.

[0010] Optionally, the combination number is constructed using the plurality of dimensionless numbers, including: The plurality of dimensionless numbers are combined in the form of exponential product, and the corresponding combination number is obtained; The linear regression relationship to be fitted is established between the combination number and the set recovery evaluation parameter, including: The linear regression relationship to be fitted is established between the natural logarithm of the combination number and the recovery evaluation parameter; The low-permeability reservoir sample data according to the numerical simulation of the reservoir is used to fit the plurality of to-be-fitted coefficients in the linear regression relationship to be fitted, so as to obtain a plurality of fitted coefficients and a final linear regression relationship, comprising: numerical simulation is performed on the low-permeability reservoir to obtain a plurality of sample data, each of which comprises corresponding set parameters, each dimensionless criterion and parameter values of the recovery evaluation parameter; The plurality of to-be-fitted coefficients in the linear regression relationship to be fitted are fitted using the plurality of sample data, so as to obtain a plurality of fitted coefficients and a final linear regression relationship.

[0011] Optionally, when the plurality of dimensionless criteria are density number, viscosity number, capillary number and gravity number, the set parameters are formation dip angle, permeability, injection rate or viscosity, and the recovery evaluation parameter is gas recovery.

[0012] Optionally, the gas-oil contact stability of the low-permeability reservoir is evaluated based on the final linear regression relationship, comprising: According to the final linear regression relationship, a curve of the parameter values of the recovery evaluation parameter changing with the logarithmic values of the combined criterion is drawn; According to the curve, it is determined that the parameter values of the recovery evaluation parameter are inversely proportional to the logarithmic values of the combined criterion, and the decrease amplitude of the parameter values of the recovery evaluation parameter increases with the increase of the logarithmic values of the combined criterion; A slope change inflection point is determined in the curve, and a target logarithmic value of the combined criterion corresponding to the slope change inflection point is determined; when the logarithmic value of the combined criterion is greater than the target logarithmic value, the decrease amplitude of the parameter values of the recovery evaluation parameter increases greatly; The target logarithmic value is determined as the gas injection gravity drive gas-oil contact stability limit of the low-permeability reservoir; When the logarithmic value of the combined criterion of the low-permeability reservoir is less than or equal to the target logarithmic value, the gas injection gravity drive gas-oil contact of the low-permeability reservoir is in a stable state; when the logarithmic value of the combined criterion of the low-permeability reservoir is greater than the target logarithmic value, the gas injection gravity drive gas-oil contact of the low-permeability reservoir is in an unstable state.

[0013] In a second aspect, the present application provides a low-permeability reservoir gas injection gravity drive gas-oil contact stability evaluation device, comprising: A force analysis unit is configured to perform force analysis on the oil-gas interface in the low-permeability reservoir subjected to gas injection gravity drive based on fluid flow law, and obtain an oil-gas interface flow model; A model simplification unit is configured to simplify the oil-gas interface flow model according to the balance condition when the oil-gas interface moves stably, and obtain a simplified flow model. a dimensionless number determining unit configured to determine a plurality of dimensionless numbers for describing the gas injection gravity drainage process based on the simplified flow model; a dimensionless number constructing unit configured to construct a combined dimensionless number using the plurality of dimensionless numbers; a relationship establishing unit configured to establish a linear regression relationship to be fitted between the combined dimensionless number and a set recovery evaluation parameter, the linear regression relationship to be fitted including the combined dimensionless number, the recovery evaluation parameter and a plurality of to-be-fitted coefficients; a coefficient fitting unit configured to fit the plurality of to-be-fitted coefficients in the linear regression relationship to be fitted according to low-permeability reservoir sample data of reservoir numerical simulation, to obtain a plurality of fitted coefficients and a final linear regression relationship; an interface evaluation unit configured to evaluate the gas-oil interface stability of the low-permeability reservoir based on the final linear regression relationship.

[0014] In a third aspect, the present application provides a computer device, comprising a memory and a processor, which are communicatively connected with each other, the memory stores computer instructions, and the processor executes the computer instructions to perform the low-permeability reservoir gas injection gravity drainage gas-oil interface stability evaluation method of the first aspect or any of the corresponding embodiments thereof.

[0015] In a fourth aspect, the present application provides a computer readable storage medium, which stores computer instructions, and the computer instructions are used to make a computer perform the low-permeability reservoir gas injection gravity drainage gas-oil interface stability evaluation method of the first aspect or any of the corresponding embodiments thereof.

[0016] The low-permeability oil reservoir gas injection gravity drive gas-oil interface stability evaluation method, device, equipment and medium provided by the application can perform force analysis on the oil-gas interface in the low-permeability oil reservoir subjected to gas injection gravity drive based on the fluid flow law to obtain an oil-gas interface flow model. The oil-gas interface flow model is simplified according to the balance condition when the oil-gas interface stably moves to obtain a simplified flow model. Based on the simplified flow model, a plurality of dimensionless numbers used to describe the gas injection gravity drive process are determined. A combination number is constructed using the plurality of dimensionless numbers, and a linear regression relationship to be fitted is established between the combination number and a set recovery evaluation parameter. The linear regression relationship to be fitted includes the combination number, the recovery evaluation parameter and a plurality of to-be-fitted coefficients. The plurality of to-be-fitted coefficients in the linear regression relationship to be fitted are fitted according to low-permeability oil reservoir sample data obtained through numerical simulation of the oil reservoir to obtain a plurality of fitted coefficients and a final linear regression relationship. The gas-oil interface stability of the low-permeability oil reservoir is evaluated based on the final linear regression relationship. The application can effectively evaluate the gas-oil interface stability of the low-permeability oil reservoir subjected to gas injection gravity drive, provide technical support for development effect evaluation of a thick oil layer gas injection gravity drive oilfield, optimize the gas injection development strategy and improve the recovery rate. BRIEF DESCRIPTION OF DRAWINGS

[0017] In order to more clearly illustrate the technical solutions in the application or the related art, the following will briefly introduce the drawings needed to be used in the embodiments or the related art description. Obviously, the drawings in the following description are some embodiments of the application, and other drawings can be obtained by those skilled in the art without any creative effort.

[0018] Figure 1 A flow chart of a low-permeability oil reservoir gas injection gravity drive gas-oil interface stability evaluation method provided by the embodiment of the application; Figure 2 A tilted stratum gas cap gravity drive oil-gas-water three-phase distribution and oil-gas interface force analysis diagram provided by the embodiment of the application; Figure 3 A gravity stable gas injection profile provided by the embodiment of the application; Figure 4 A sample data table generated by numerical simulation of an oil reservoir provided by the embodiment of the application; Figure 5 A combination number and recovery rate relationship equation undetermined coefficient regression table provided by the embodiment of the application; Figure 6 A combination number and gas drive recovery degree corresponding change relationship diagram provided by the embodiment of the application; Figure 7 A structure schematic diagram of a low-permeability oil reservoir gas injection gravity drive gas-oil interface stability evaluation device provided by the embodiment of the application; Figure 8 This is a schematic diagram of the structure of a computer device provided in an embodiment of the present invention. Detailed Implementation

[0019] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0020] The following is combined with Figures 1-6 This invention describes a method for evaluating the stability of the oil-gas interface in low-permeability reservoirs using gravity-driven gas injection.

[0021] like Figure 1 As shown in the figure, this embodiment proposes a first method for evaluating the stability of the gas-oil interface in gravity-driven gas injection in low-permeability reservoirs. This method may include the following steps: S101. Based on the fluid flow law, the stress analysis of the oil-gas interface in a low-permeability reservoir under gas injection gravity drive is carried out to obtain the oil-gas interface flow model.

[0022] Among them, low-permeability reservoirs can be thick oil-bearing low-permeability reservoirs that are driven by gas injection gravity.

[0023] It should be noted that during gravity-driven gas injection, the gas-oil interface is a curved surface with uneven edges and local areas. Uniform advancement of the gas-oil interface means that the instantaneous rate of change of the forward flow velocity at all points on this curved surface is equal, i.e., the acceleration at all points is 0.

[0024] like Figure 2 As shown, this embodiment can extract a small section of the inclined structure from the three-dimensional formation and actual fluid flow morphology of the reservoir and simplify it into a planar model, and perform a force analysis on the fluid at the oil and gas interface. This model considers several major forces affecting the displacement effect, and also takes into account the dip angle factor affecting the gravity drive effect of the gas cap. Figure 2 middle, The dip angle of the strata. It is the angle between the oil-gas and oil-water interfaces and the opposite direction of fluid flow. h This represents the vertical migration distance at the oil-gas interface.

[0025] Optionally, step S101 may include: In a low-permeability reservoir containing oil, gas, and water phases, where each phase is incompressible, flows according to Darcy's law and is isothermal, the reservoir is a homogeneous sublayer, and the surface tension and wetting angle do not change with the movement of the liquid film, and the medium is porous, stress analysis is performed on the oil-gas interface in the low-permeability reservoir, and Darcy's equations for porous media are established in three dimensions. The Darcy equation for porous media in three dimensions is used as a whole to define the flow model of the oil-gas interface.

[0026] Specifically, in this embodiment, before establishing the mathematical model, basic assumptions are introduced: the process isothermal seepage, the reservoir is a homogeneous formation; the reservoir contains three phases: oil, gas, and water, and the flow of each phase fluid satisfies Darcy's law; all three phase fluids are incompressible; and the surface tension and wetting angle do not change with the movement of the liquid film.

[0027] Darcy's formula for porous media can be derived from the Navier-Stokes equations (NS equations). The NS equations summarize the general laws governing the flow of viscous incompressible fluids and have special significance in fluid mechanics. Therefore, at the microscopic level, when the coordinates ( x , y , z When the medium at location ) is porous, the flow of the oil and gas phases can be described by the Navier-Stokes equations. The Darcy equations for porous media in three dimensions are: ----------Formula (1).

[0028] in, , and For the Laplace operator, x , y and z These represent the coordinates of the fluid in different dimensional directions; For fluid density, p For pressure. Let be the dynamic viscosity, a constant. , and For the fluid in coordinates ( x , y , z The velocity component at the location. This is the acceleration due to gravity.

[0029] S102. Based on the equilibrium conditions during stable migration at the oil-gas interface, the oil-gas interface flow model is simplified to obtain a simplified flow model.

[0030] Specifically, this embodiment simplifies the oil-gas interface flow model to obtain a simplified flow model.

[0031] Optionally, step S102 may include: The Darcy equation for porous media in the three dimensions of the oil-gas interface flow model is simplified to an equation that only considers the seepage relationship in the vertical direction. Based on the principle of highlighting the influence of parameters and the equilibrium conditions during stable migration of oil and gas interfaces, multiple parameter terms in the seepage relationship equation are simplified to obtain a simplified flow model.

[0032] During gravity drive with gas injection, the vertical forces are mainly considered to describe the relationship between forces at the oil-gas interface. The NS equations take into account ( x , y , z The three directions are simplified to only consider... z In the directional seepage model, for the flow within the micropores of the reservoir under this development technology, the main forces to be considered are driving force, gravity, capillary force, and viscous force. The seepage relationship equation can be obtained from formula (1): -------Formula (2).

[0033] The capillary force of oil and gas is poor.

[0034] Divide both sides of equation (2) by the acceleration due to gravity. g We can obtain: -------Formula (3).

[0035] Equation (3) is z The equation of motion in the direction, where the first term is the gravity reference; the second term... It is the ratio of driving pressure difference to gravitational difference, the third term. It is the ratio of capillary force to the difference in gravity. To highlight the effect of density difference, the second term can be simplified to... , h This represents the vertical migration distance at the oil-gas interface. Similarly, the third term can be simplified to... Item 4 Viscous drag represents the ratio of viscous force to gravity. It is proportional to the seepage velocity, therefore the fourth term can be simplified to Item 5 This represents the ratio of the vertical net force (acceleration term) to the gravitational acceleration; this term is 0 when the interface is in stable flow. The dip angle of the oil-gas interface in an oil reservoir may be constantly changing and difficult to measure, but... Figure 1 It can be seen that when the displacement interface progresses stably, it can be approximately considered that... Under this stable condition Therefore, the simplified flow model can be obtained as follows: ----------Formula (4).

[0036] in, Due to the density difference between oil and gas, It is the acceleration due to gravity. This indicates the vertical driving pressure difference during bidirectional air-top and bottom-water drive. The dip angle of the strata. h This represents the vertical migration distance at the oil and gas interface. Due to poor capillary force in oil and gas, This indicates a difference in oil and gas viscosity. This indicates the vertical direction of the fluid at a certain location. The velocity component on, K This refers to penetration rate.

[0037] Where, in the formula , and These are the density of crude oil and the density of injected gas, respectively. , and These are the viscosity of crude oil and the viscosity of injected gas, respectively. . and These are the air top pressure and the bottom water pressure, respectively.

[0038] It is understandable that formula (4) is based on the Navier-Stokes equation and is the equilibrium condition for stable migration of oil and gas interface obtained from the perspective of fluid force analysis. The formula takes into account the influence of factors such as density, viscosity, permeability, displacement pressure difference, and formation dip angle.

[0039] S103. Based on a simplified flow model, determine several dimensionless metric numbers used to describe the gas injection gravity drive process.

[0040] Specifically, this embodiment can use a simplified flow model of a low-permeability reservoir to determine the optimal dimensionless criterion for describing the gas injection gravity drive process.

[0041] Optionally, step S103 may include: The parameters included in the simplified flow model are determined to be density, viscosity, permeability, displacement pressure differential, and formation dip angle. Based on the parameters included in the simplified flow model, namely density, viscosity, permeability, displacement pressure differential, and formation dip angle, the density number, viscosity number, capillary number, and gravity number with the greatest correlation to density, viscosity, permeability, displacement pressure differential, and formation dip angle are selected from the dimensionless quasi-arrays of low-permeability reservoirs. The selected density number, viscosity number, capillary number, and gravity number were determined as dimensionless criterions.

[0042] It should be noted that this embodiment establishes an equilibrium equation based on the forces governing the stability of the gas-oil interface in gas-injection gravity drive. Factors such as density, viscosity, permeability, displacement pressure differential, and formation dip angle affect the development effect of gas-injection gravity drive. To fully consider the influence of each factor, dimensional analysis is employed to reduce the number of experimental variables required to fully describe the relationships between these variables. Reservoir heterogeneity, gas injection rate, viscosity, formation dip angle, wettability, and gas-oil density difference all affect the stability of the gas-oil interface. Therefore, this embodiment can determine that density number, viscosity number, capillary number, and gravity number are the optimal parameters for describing the gas-injection gravity drive process.

[0043] like Figure 3 The gravity-stabilized gas injection profile shown is for this embodiment with an inclination angle of... α When a single layer is subjected to gas displacement, if the displacement is stable, the gas-displacement oil-gas interface should be a horizontal interface. However, if the effect of the tongue advance is considered, the displaced oil-gas interface will have an angle with the horizontal plane, which we can define as... β The stability of its interface is affected by many factors such as gas injection rate, reservoir dip angle, permeability and gas-liquid property differences.

[0044] Assuming that the injected gas per unit time decomposes the fluid at the interface, in x On the axis, combining the potential energy relationship and Darcy's law, we can obtain the following relationship: .

[0045] in, and These are the crude oil flow rate and the injected gas flow rate, respectively. k For gas phase permeability, and These are the potential energy of the crude oil and the potential energy of the injected gas, respectively. The potential energy of the unit fluid is defined as: .

[0046] z The value is positive upwards. Assuming the fluid is incompressible, integrating the above equation yields: .

[0047] C Assuming that the oil-gas contact surface is infinitely large relative to the vertical thickness of the reservoir, then: .

[0048] The oil phase and the gas phase are along the contact surface ac The potential energy difference is: ; .

[0049] In the formula, express a arrive c The unit oil phase fluid pressure energy. express a arrive c The unit gas phase fluid pressure energy.

[0050] Assuming the capillary force at the contact surface remains unchanged, then: .

[0051] Subtracting the two equations, we get: ; Depend on Figure 3 According to geometric relations: ; Assuming a stable gas-oil interface under gravity-driven conditions, the streamline velocity along the reservoir's dip direction is: .

[0052] Solving the simultaneous equations, we get: .

[0053] when β = α At this time, the air-driven interface is extremely unstable. β When the angle decreases, the gas-driven interface stabilizes and shifts downward, resulting in slug-type oil displacement and good recovery. β Approaching the reservoir angle α hour: ; Right now: ; make: ; in, This is due to the difference in oil and gas density.

[0054] The gravity number is the ratio of gravity to capillary force. During the decrease of the interface angle, gas drive exhibits interface stability under certain conditions, meaning a gravity-stabilized gas injection mode can be achieved. Based on equations, the gravity stability condition can be obtained as follows: N G >1.

[0055] The capillary number characterizes the balance between viscous and capillary forces during gravity drive injection. Its value is the product of Darcy velocity and injected gas viscosity divided by the oil-gas interfacial tension. The capillary number is the ratio of viscous force to capillary pressure. .

[0056] The density number characterizes the difference in density between injected gas and crude oil under formation conditions during gravity injection; its value is the density ratio of injected gas to crude oil. The density number is the ratio of injected gas density to crude oil density under formation conditions. .

[0057] The viscosity number characterizes the difference in viscosity between injected gas and crude oil under formation conditions during gravity injection; its value is the density ratio of injected gas to crude oil. The viscosity number is the ratio of the viscosity of injected gas to the viscosity of crude oil under formation conditions. .

[0058] S104. Construct a combined criterion using multiple dimensionless criteria.

[0059] Specifically, in this embodiment, a combined criterion is constructed based on a plurality of determined dimensionless criterions.

[0060] Optionally, step S104 may include: Multiple dimensionless quantiles are combined using the form of an exponential product to obtain the corresponding combined quantile.

[0061] Based on the fundamental metric numbers (Table 4-1) covering various physical and fluid parameters in gas-assisted gravity drive, a combined metric number is established using the form of an exponential product. N com Relationship: .

[0062] in, A , B , C and D All of these are coefficients to be fitted.

[0063] S105. Establish a linear regression relationship to be fitted between the combined criteria and the set harvest evaluation parameters. The linear regression relationship to be fitted includes the combined criteria, the harvest evaluation parameters, and multiple coefficients to be fitted.

[0064] Specifically, in this embodiment, the standard number and harvest evaluation parameters can be combined to establish a linear regression relationship between the two.

[0065] The recovery evaluation parameters can be selected by technicians according to the actual situation, such as gas-driven recovery rate, but this embodiment does not limit them.

[0066] Optionally, step S105 may include: A linear regression relationship to be fitted is established between the natural logarithm of the combined criterion and the harvest evaluation parameters.

[0067] This embodiment can establish a quantitative relationship between the natural logarithm of the combined criterion and the gas-driven recovery rate: .

[0068] in, The gas-driven recovery rate is used as a parameter for evaluating recovery. and The coefficients are to be fitted.

[0069] It is understood that the linear regression equation to be fitted in this embodiment can be: ; .

[0070] S106. Based on the sample data of low-permeability reservoirs from the numerical simulation of the reservoir, fit multiple coefficients in the linear regression equation to obtain the corresponding multiple fitting coefficients and the final linear regression equation.

[0071] Specifically, this embodiment can perform reservoir numerical simulation on low-permeability reservoirs, construct low-permeability reservoir sample data, and use the low-permeability reservoir sample data to fit the coefficients to be fitted in the linear regression relationship to determine all fitting coefficients, thereby obtaining the final linear regression relationship.

[0072] Optionally, step S106 may include: Numerical simulation of low-permeability reservoirs was performed to obtain multiple sample data. Each sample data includes the corresponding set parameters, the parameter values ​​of each dimensionless criterion and the recovery evaluation parameters. Multiple sample data are used to fit multiple coefficients in the linear regression equation to obtain multiple fitting coefficients and the final linear regression equation.

[0073] Optionally, when multiple dimensionless parameters are density number, viscosity number, capillary number and gravity number, the parameters can be set as formation dip angle, permeability, injection rate or viscosity, and the recovery evaluation parameter can be gas-driven recovery rate.

[0074] like Figure 4As shown, this embodiment establishes a reservoir mechanism model based on the typical characteristics of gas-injected gravity-driven reservoirs. Considering geological and fluid uncertainties, different formation dip angles, permeabilities, and crude oil viscosities are set, along with different gas injection rates. For different parameters of the mechanism model, the corresponding density number, viscosity number, capillary number, and gravity number are calculated. Reservoir numerical simulation software is used to calculate the gas-driven recovery rate under different parameters. Results from sensitive schemes such as viscosity, dip angle, gas injection rate, and permeability are screened as sample data for quasi-numerical regression to filter out interference schemes with poor regularity and weak influence, increasing the correlation between the regression scheme and the combined quasi-numericals, improving the correlation coefficient of quasi-numerical regression, and increasing the reliability of the quasi-numerical relationship.

[0075] like Figure 5 As shown, this embodiment can use multiple sample data and the conjugate gradient method to determine the fitting coefficients in the linear regression equation to be fitted. A , B , C , D, a and b At this point, the final linear regression equation can be obtained in this embodiment: .

[0076] S107. Based on the final linear regression equation, evaluate the gas-oil interface stability of low-permeability reservoirs.

[0077] Specifically, this embodiment can use the final linear regression equation to evaluate the gas-oil interface stability of low-permeability reservoirs.

[0078] Optionally, based on the final linear regression equation, plot the curves showing how the parameter values ​​of the harvest evaluation parameters change with the logarithm of the combination criterion. According to the curve, the parameter values ​​of the harvest evaluation parameters are inversely proportional to the parameter values ​​of the combination criterion, and the decrease in the parameter values ​​of the harvest evaluation parameters increases as the parameter values ​​of the combination criterion increase. Identify the inflection point of the slope change in the curve, and determine the target parameter value of the combined criterion corresponding to the inflection point of the slope change; when the parameter value of the combined criterion is greater than the target parameter value, the decrease in the parameter value of the harvest evaluation parameter increases significantly. The target parameter value is determined as the stability limit of the gas-oil interface in the gas injection gravity drive of low-permeability reservoirs. Specifically, when the parameter value of the combination number of a low-permeability reservoir is less than or equal to the target parameter value, the gas-injection gravity-driven gas-oil interface of the low-permeability reservoir is in a stable state; when the parameter value of the combination number of a low-permeability reservoir is greater than the target parameter value, the gas-injection gravity-driven gas-oil interface of the permeable reservoir is in an unstable state.

[0079] like Figure 6 As shown, this embodiment can plot a semi-logarithmic graph of the relationship between the combined criterion and the recovery rate.x The axes are combined metric numbers, using logarithmic coordinates. y The axis represents the recovery rate, expressed as a percentage. The inflection point of the slope change, i.e., the combined criterion, is determined in the semi-logarithmic plot. =0.005. Recovery rate is inversely proportional to the combinatorial index, and the rate of decrease in recovery rate increases with the increase of the combinatorial index. When the logarithm of the combinatorial index exceeds 0.005, the rate of decrease in recovery rate increases significantly, indicating instability in gravity-driven systems. Combination Index A value of 0.005 represents the instability limit of gravity-driven gas injection. When the value is less than or equal to the threshold, gravity drives stability.

[0080] This embodiment can screen out dimensionless parameters crucial for evaluating the stability of the oil-gas interface based on the stress analysis of the oil-gas interface, including density number, capillary number, viscosity number, and gravity number. A combined parameter system comprising these four dimensionless parameters is established. A mechanistic model is built based on field conditions to predict oil recovery. Based on multivariate nonlinear regression, the undetermined regression coefficients of the four dimensionless parameters and two undetermined coefficients of the combined parameter system are determined, thus achieving the evaluation of the oil-gas interface stability.

[0081] This embodiment addresses the technical problem of lacking a method for evaluating the stability of the gas-oil interface in gas injection gravity drive for thick oil reservoirs. It provides important technical basis for the design and optimization of gas injection gravity drive schemes for thick oil reservoirs, and offers technical support for reservoir screening in gas injection gravity drive. It also provides technical support for evaluating the development effect of gas injection gravity drive in producing thick oil reservoirs, and the gas-oil interface stability evaluation results based on this embodiment provide technical support for adjustments to oilfield development.

[0082] The proposed method for evaluating the stability of the gas-oil interface in low-permeability reservoirs undergoing gas injection gravity drive, based on fluid flow laws, performs force analysis on the oil-gas interface in such reservoirs to obtain a flow model. The flow model is simplified according to the equilibrium conditions during stable migration of the oil-gas interface, resulting in a simplified flow model. Based on this simplified model, multiple dimensionless parameters are determined to describe the gas injection gravity drive process. A combined parameter is constructed using these multiple dimensionless parameters, and a linear regression relationship is established between the combined parameter and predetermined recovery evaluation parameters. This linear regression relationship includes the combined parameter, recovery evaluation parameters, and multiple fitting coefficients. Using sample data from low-permeability reservoir numerical simulations, the multiple fitting coefficients in the linear regression relationship are fitted to obtain the corresponding fitting coefficients and the final linear regression relationship. Based on the final linear regression relationship, the stability of the gas-oil interface in the low-permeability reservoir is evaluated. This embodiment can effectively evaluate the stability of the gas-oil interface in gravity-driven gas injection in low-permeability reservoirs, provide technical support for evaluating the development effect of gravity-driven gas injection in thick oil layers, optimize gas injection development strategies, and improve recovery rates.

[0083] like Figure 7 As shown in the figure, this embodiment proposes a device for evaluating the stability of the gas-oil interface in gravity-driven gas injection in low-permeability reservoirs. This device may include: The stress analysis unit 701 is used to perform stress analysis on the oil-gas interface in a low-permeability reservoir under gas injection gravity drive based on the fluid flow law, and to obtain the oil-gas interface flow model. The model simplification unit 702 is used to simplify the oil-gas interface flow model according to the equilibrium conditions during stable migration of the oil-gas interface, so as to obtain a simplified flow model. The criterion number determination unit 703 is used to determine multiple dimensionless criterions for describing the gas injection gravity drive process based on a simplified flow model; The criterion construction unit 704 is used to construct a combined criterion using multiple dimensionless criterions; The relationship establishment unit 705 is used to establish a linear regression relationship to be fitted between the combined criteria and the set harvest evaluation parameters. The linear regression relationship to be fitted includes the combined criteria, the harvest evaluation parameters and multiple coefficients to be fitted. The coefficient fitting unit 706 is used to fit multiple coefficients to be fitted in the linear regression relationship to be fitted based on the sample data of low-permeability reservoirs in the numerical simulation of the reservoir, so as to obtain the corresponding multiple fitting coefficients and the final linear regression relationship. Interface evaluation unit 707 is used to evaluate the gas-oil interface stability of low-permeability reservoirs based on the final linear regression relationship.

[0084] It should be noted that the processing procedures and beneficial effects of the force analysis unit 701, model simplification unit 702, criterion number determination unit 703, criterion number construction unit 704, relationship establishment unit 705, coefficient fitting unit 706, and interface evaluation unit 707 can be referred to respectively. Figure 1 Steps S101 to S107 are not described in detail here.

[0085] Optionally, the force analysis unit 701 is also used for: In a low-permeability reservoir containing oil, gas, and water phases, where each phase is incompressible, flows according to Darcy's law and is isothermal, the reservoir is a homogeneous sublayer, and the surface tension and wetting angle do not change with the movement of the liquid film, and the medium is porous, stress analysis is performed on the oil-gas interface in the low-permeability reservoir, and Darcy's equations for porous media are established in three dimensions. The Darcy equation for porous media in three dimensions is used as a whole to define the flow model of the oil-gas interface.

[0086] Optionally, the model simplification unit 702 is also used for: The Darcy equation for porous media in the three dimensions of the oil-gas interface flow model is simplified to an equation that only considers the seepage relationship in the vertical direction. Based on the principle of prominent parameter influence and the equilibrium condition for stable migration at the oil-gas interface, the multiple parameter terms in the seepage relationship equation are simplified to obtain a simplified flow model, which is: ; in, Due to the density difference between oil and gas, It is the acceleration due to gravity. This indicates the vertical driving pressure difference during bidirectional air-top and bottom-water drive. The dip angle of the strata. h This represents the vertical migration distance at the oil and gas interface. Due to poor capillary force in oil and gas, This indicates a difference in oil and gas viscosity. This indicates the vertical direction of the fluid at a certain location. The velocity component on, K This refers to penetration rate.

[0087] Optionally, the criterion determination unit 703 is also used for: The parameters included in the simplified flow model are determined to be density, viscosity, permeability, displacement pressure differential, and formation dip angle. Based on the parameters included in the simplified flow model, namely density, viscosity, permeability, displacement pressure differential, and formation dip angle, the density number, viscosity number, capillary number, and gravity number with the greatest correlation to density, viscosity, permeability, displacement pressure differential, and formation dip angle are selected from the dimensionless quasi-arrays of low-permeability reservoirs. The selected density number, viscosity number, capillary number, and gravity number were determined as dimensionless criterions.

[0088] Optionally, the quasi-number building block 704 is also used for: Multiple dimensionless criteria are combined using the form of an exponential product to obtain the corresponding combined criteria; Relationship establishment unit 705 is also used for: A linear regression relationship to be fitted is established between the natural logarithm of the combined criterion and the harvest evaluation parameters; The coefficient fitting unit 706 is also used for: Numerical simulation of low-permeability reservoirs was performed to obtain multiple sample data. Each sample data includes the corresponding set parameters, the parameter values ​​of each dimensionless criterion and the recovery evaluation parameters. Multiple sample data are used to fit multiple coefficients in the linear regression equation to obtain multiple fitting coefficients and the final linear regression equation.

[0089] Optionally, when multiple dimensionless parameters are density number, viscosity number, capillary number and gravity number, the parameters can be set as formation dip angle, permeability, injection rate or viscosity, and the recovery evaluation parameter can be gas-driven recovery rate.

[0090] Optionally, the interface evaluation unit 707 is also used for: Based on the final linear regression equation, plot the curves showing how the parameter values ​​of the harvest evaluation parameters change with the logarithm of the combination criterion. According to the curve, the parameter values ​​of the harvest evaluation parameters are inversely proportional to the logarithm of the combination criterion, and the decrease in the parameter values ​​of the harvest evaluation parameters increases as the logarithm of the combination criterion increases. Identify the inflection point of the slope change in the curve, and determine the target logarithmic value of the combined parameters corresponding to the inflection point of the slope change; when the logarithmic value of the combined parameters is greater than the target logarithmic value, the decrease in the parameter value of the harvest evaluation parameters increases significantly. The target logarithmic value is determined as the stability limit of the gas-oil interface in the gas injection gravity drive of low-permeability reservoirs. Specifically, when the logarithm of the combination number of a low-permeability reservoir is less than or equal to the target logarithm, the gas-injection gravity-driven gas-oil interface of the low-permeability reservoir is in a stable state; when the logarithm of the combination number of a low-permeability reservoir is greater than the target logarithm, the gas-injection gravity-driven gas-oil interface of the permeable reservoir is in an unstable state.

[0091] The gas-oil interface stability evaluation device for low-permeability reservoir gas injection gravity drive proposed in this embodiment can perform force analysis on the oil-gas interface in low-permeability reservoirs under gas injection gravity drive based on fluid flow laws, obtaining an oil-gas interface flow model. According to the equilibrium conditions during stable migration of the oil-gas interface, the oil-gas interface flow model is simplified to obtain a simplified flow model. Based on the simplified flow model, multiple dimensionless criterions are determined to describe the gas injection gravity drive process. A combined criterion is constructed using these multiple dimensionless criterions, and a linear regression relationship is established between the combined criterion and the set recovery evaluation parameters. The linear regression relationship includes the combined criterion, the recovery evaluation parameters, and multiple fitting coefficients. Based on the low-permeability reservoir sample data from reservoir numerical simulation, multiple fitting coefficients in the linear regression relationship are fitted to obtain multiple fitting coefficients and the final linear regression relationship. Based on the final linear regression relationship, the gas-oil interface stability of the low-permeability reservoir is evaluated. This embodiment can effectively evaluate the stability of the gas-oil interface in gravity-driven gas injection in low-permeability reservoirs, provide technical support for evaluating the development effect of gravity-driven gas injection in thick oil layers, optimize gas injection development strategies, and improve recovery rates.

[0092] In this embodiment, the low-permeability reservoir gas injection gravity drive gas-oil interface stability evaluation device is presented in the form of a functional unit. Here, a unit refers to an ASIC (Application Specific Integrated Circuit) circuit, a processor and memory that execute one or more software or fixed programs, and / or other devices that can provide the above functions.

[0093] This invention also provides a computer device having the above-described features. Figure 7 The device shown is for evaluating the stability of the gas-oil interface in low-permeability reservoirs using gravity-driven gas injection.

[0094] Please see Figure 8 The present invention provides a schematic diagram of the structure of a computer device according to an optional embodiment. The computer device includes one or more processors 10, a memory 20, and interfaces for connecting the various components, including high-speed interfaces and low-speed interfaces. The various components are interconnected via different buses and can be mounted on a common motherboard or otherwise installed as needed. The processors can process instructions executed within the computer device, including instructions stored in or on memory to display graphical information of a GUI on an external input / output device (such as a display device coupled to the interface). In some optional embodiments, multiple processors and / or multiple buses can be used with multiple memories, if desired. Similarly, multiple computer devices can be connected, each providing some of the necessary operations (e.g., as a server array, a group of blade servers, or a multiprocessor system). Figure 8 Take a processor 10 as an example.

[0095] Processor 10 may be a central processing unit, a network processor, or a combination thereof. Processor 10 may further include a hardware chip. The hardware chip may be an application-specific integrated circuit (ASIC), a programmable logic device (PLD), or a combination thereof. The programmable logic device may be a complex programmable logic device (CAMP), a field-programmable gate array (FPGA), a general-purpose array logic (GDA), or any combination thereof.

[0096] The memory 20 stores instructions executable by at least one processor 10 to cause at least one processor 10 to perform the method shown in the above embodiments.

[0097] The memory 20 may include a program storage area and a data storage area. The program storage area may store the operating system and applications required for at least one function. The data storage area may store data created based on the use of the computer device. Furthermore, the memory 20 may include high-speed random access memory and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some alternative embodiments, the memory 20 may optionally include memory remotely located relative to the processor 10, which can be connected to the computer device via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0098] Memory 20 may include volatile memory, such as random access memory. Memory may also include non-volatile memory, such as flash memory, hard disk, or solid-state drive. Memory 20 may also include combinations of the above types of memory.

[0099] The computer device also includes a communication interface 30 for communicating with other devices or communication networks.

[0100] This invention also provides a computer-readable storage medium. The methods described above according to embodiments of the invention can be implemented in hardware or firmware, or implemented as computer code that can be recorded on a storage medium, or implemented as computer code downloaded via a network and originally stored on a remote storage medium or a non-transitory machine-readable storage medium and then stored on a local storage medium. Thus, the methods described herein can be processed by software stored on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. The storage medium can be a magnetic disk, optical disk, read-only memory, random access memory, flash memory, hard disk, or solid-state drive, etc.; further, the storage medium can also include combinations of the above types of memory. It is understood that computers, processors, microprocessor controllers, or programmable hardware include storage components capable of storing or receiving software or computer code, which, when accessed and executed by the computer, processor, or hardware, implements the methods shown in the above embodiments.

[0101] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for evaluating the stability of the gas-oil interface in gravity-driven gas injection in low-permeability reservoirs, characterized in that, include: Based on fluid flow laws, stress analysis is performed on the oil-gas interface in low-permeability reservoirs under gas injection gravity drive to obtain an oil-gas interface flow model. Based on the equilibrium conditions for stable migration at the oil-gas interface, the oil-gas interface flow model is simplified to obtain a simplified flow model. Based on the simplified flow model, several dimensionless criterions are determined to describe the gas injection gravity drive process. A combined criterion is constructed using the multiple dimensionless criteria, and a linear regression relationship to be fitted is established between the combined criterion and the set harvest evaluation parameters. The linear regression relationship to be fitted includes the combined criterion, the harvest evaluation parameters, and multiple coefficients to be fitted. Based on the low-permeability reservoir sample data from the reservoir numerical simulation, the multiple coefficients to be fitted in the linear regression relationship to be fitted are fitted to obtain the corresponding multiple fitting coefficients and the final linear regression relationship. The stability of the gas-oil interface in the low-permeability reservoir is evaluated based on the final linear regression equation.

2. The method according to claim 1, characterized in that, Based on fluid flow laws, a stress analysis of the hydrocarbon interface in a low-permeability reservoir undergoing gas injection gravity drive is performed to obtain a hydrocarbon interface flow model, including: Given that the low-permeability reservoir contains oil, gas, and water phase fluids, each phase fluid is incompressible, the flow of each phase fluid satisfies Darcy's law and is isothermal, the reservoir is a homogeneous sublayer, the surface tension and wetting angle do not change with the movement of the liquid film, and the medium is a porous medium, a stress analysis is performed on the oil-gas interface in the low-permeability reservoir, and Darcy's equations for porous media are created in three dimensions. The Darcy equations for porous media in three dimensions are used as the overall flow model for the oil-gas interface.

3. The method according to claim 2, characterized in that, The simplified flow model of the oil-gas interface is obtained by simplifying the flow model based on the equilibrium conditions during stable migration at the oil-gas interface, including: The Darcy equation for porous media in the three dimensions of the oil-gas interface flow model is simplified to an equation that only considers the seepage relationship in the vertical direction. Based on the principle of highlighting the influence of parameters and the equilibrium conditions during the stable migration of the oil and gas interface, the multiple parameter terms in the seepage relationship equation are simplified to obtain the simplified flow model.

4. The method according to claim 3, characterized in that, Based on the simplified flow model, several dimensionless metric numbers are determined to describe the gas injection gravity drive process, including: The parameters included in the simplified flow model are determined to be density, viscosity, permeability, displacement pressure differential, and formation dip angle. Based on the parameters included in the simplified flow model, namely density, viscosity, permeability, displacement pressure differential, and formation dip angle, the density number, viscosity number, capillary number, and gravity number with the greatest correlation to density, viscosity, permeability, displacement pressure differential, and formation dip angle are selected from the dimensionless quasi-arrays of low-permeability reservoirs. The selected density number, viscosity number, capillary number, and gravity number are determined as the dimensionless criterion.

5. The method according to claim 1, characterized in that, The construction of a combined criterion using the plurality of dimensionless criteria includes: The multiple dimensionless criteria are combined using the form of an exponential product to obtain the corresponding combined criteria; The step of establishing a linear regression relationship to be fitted between the combined criteria and the set harvest evaluation parameters includes: A linear regression relationship to be fitted is established between the natural logarithm of the combined criterion and the harvest evaluation parameters; The process of fitting multiple coefficients in the linear regression equation to obtain multiple fitting coefficients and the final linear regression equation based on low-permeability reservoir sample data from numerical simulation includes: The low-permeability reservoir was subjected to reservoir numerical simulation to obtain multiple sample data. Each sample data included the corresponding set parameters, the parameter values ​​of each dimensionless criterion and the recovery evaluation parameters. The multiple sample data are used to fit multiple coefficients in the linear regression equation to obtain multiple fitting coefficients and the final linear regression equation.

6. The method according to claim 5, characterized in that, When the multiple dimensionless parameters are density number, viscosity number, capillary number and gravity number, the set parameters are formation dip angle, permeability, injection rate or viscosity, and the recovery evaluation parameter is gas-driven recovery rate.

7. The method according to claim 6, characterized in that, The evaluation of the gas-oil interface stability of the low-permeability reservoir based on the final linear regression relationship includes: Based on the final linear regression equation, plot the curves showing how the parameter values ​​of the harvest evaluation parameters change with the logarithm of the combined criteria. According to the curve, the parameter values ​​of the harvest evaluation parameters are inversely proportional to the logarithm of the combined criterion, and the decrease in the parameter values ​​of the harvest evaluation parameters increases as the logarithm of the combined criterion increases. In the curve, the inflection point of the slope change is determined, and the target logarithmic value of the combined criterion corresponding to the inflection point of the slope change is determined; when the logarithmic value of the combined criterion is greater than the target logarithmic value, the parameter value of the harvest evaluation parameter decreases significantly. The target logarithmic value is determined as the stability limit of the gas-oil interface under gas injection gravity drive in the low-permeability reservoir. Specifically, when the logarithm of the combined criterion of the low-permeability reservoir is less than or equal to the target logarithm, the gas-injection gravity-driven gas-oil interface of the low-permeability reservoir is in a stable state; when the logarithm of the combined criterion of the low-permeability reservoir is greater than the target logarithm, the gas-injection gravity-driven gas-oil interface of the permeable reservoir is in an unstable state.

8. A device for evaluating the stability of the gas-oil interface in gravity-driven gas injection in low-permeability oil reservoirs, characterized in that, include: The stress analysis unit is used to perform stress analysis on the oil-gas interface in low-permeability reservoirs under gas injection gravity drive based on fluid flow laws, and to obtain the oil-gas interface flow model. The model simplification unit is used to simplify the flow model of the oil and gas interface based on the equilibrium conditions during stable migration of the oil and gas interface, so as to obtain a simplified flow model. The criterion number determination unit is used to determine multiple dimensionless criterions for describing the gas injection gravity drive process based on the simplified flow model. A criterion construction unit is used to construct a combined criterion using the plurality of dimensionless criterions; The relationship establishment unit is used to establish a linear regression relationship to be fitted between the combined criteria and the set harvest evaluation parameters, wherein the linear regression relationship to be fitted includes the combined criteria, the harvest evaluation parameters and multiple coefficients to be fitted. The coefficient fitting unit is used to fit multiple coefficients to be fitted in the linear regression relationship to be fitted based on the sample data of low-permeability reservoirs from the numerical simulation of the reservoir, so as to obtain multiple fitting coefficients and the final linear regression relationship. The interface evaluation unit is used to evaluate the gas-oil interface stability of the low-permeability reservoir based on the final linear regression equation.

9. A computer device, characterized in that, include: The system includes a memory and a processor, which are interconnected and communicate with each other. The memory stores computer instructions, and the processor executes the computer instructions to perform the method for evaluating the stability of the gas-oil interface in low-permeability reservoirs via gravity-driven gas injection, as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions for causing the computer to execute the method for evaluating the stability of the gas-oil interface in low-permeability reservoirs via gravity-driven gas injection, as described in any one of claims 1 to 7.

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