Parameter selection method and device based on gas injection migration rule of condensate gas reservoir

Abstract

The invention relates to the field of oil exploration, in particular to a parameter selection method and device based on a gas injection migration rule of a condensate gas reservoir. The method comprises the following steps: constructing a mathematical model of injected fluid flow diffusion according to an injection condition set; numeralizing the mathematical model to obtain a relation curve between the injected gas breakthrough time and Pecklet; constructing a physical simulation model for injecting the fluid to displace the condensate gas reservoir, and performing a condensate gas reservoir simulation experiment according to injection conditions to obtain a simulation result; according to a simulation result, verifying and fitting a relation curve among the injected gas breakthrough time, the fluidity ratio and the Peclet number, and determining a breakthrough time calculation formula; performing condensate gas reservoir gas injection experiments by utilizing the injection parameter sets, and calculating breakthrough time of the condensate gas reservoir gas injection experiments corresponding to each group of injection parameter sets; and determining an optimal injection parameter according to the injection parameter set corresponding to the gas injection experiment of the condensate gas reservoir with the shortest breakthrough time. The scheme solves the problem that the condensate gas reservoir blocks an oil-gas seepage channel, and normal operation of an oil-gas well is prevented from being affected.

Description

Technical Field

[0001] This article relates to the field of petroleum exploration, and in particular to a parameter selection method and device based on the migration law of gas injection in condensate gas reservoirs. Background Art

[0002] Condensate gas reservoirs are a common phenomenon in the exploration and exploitation of oil and gas reservoirs. Specifically, after hydrocarbon gases under high temperature and high pressure conditions deep underground are extracted to the surface, liquid petroleum will condense due to the decrease in temperature and pressure. This liquid light oil is condensate oil, and this gas reservoir is a condensate gas reservoir.

[0003] At present, condensate gas reservoirs containing high-saturation condensate oil accumulate near the wellbore, which easily causes oil and gas seepage channels to be blocked, seriously affecting oil and gas production efficiency. In addition, condensate gas reservoirs usually have high-temperature and high-pressure reservoir characteristics, making it difficult to visualize the seepage of gas in porous media through intuitive means.

[0004] At present, the industry generally uses dry gas without condensate oil as an injectant for condensate gas reservoirs to dredge the oil and gas seepage channels near the wellbore. To inject gas into condensate gas reservoirs, the gas injection parameters must be determined first. Existing methods usually determine the gas injection parameters based on actual gas injection operation experience. The operation process is complicated and the determined parameters are inaccurate, which seriously affects the dredging efficiency of the oil and gas seepage channels. Summary of the invention

[0005] In order to solve the problem in the prior art that the gas injection parameters are determined based on operational experience, which affects the dredging efficiency of the oil and gas seepage channel, the embodiments of this article provide a parameter selection method and device based on the migration law of gas injection in condensate gas reservoirs.

[0006] According to one aspect of the embodiments of the present specification, the method includes: constructing a mathematical model of injected fluid flow and diffusion according to an injection condition set; digitizing the mathematical model of injected fluid flow and diffusion to obtain a relationship curve between injected gas breakthrough time, mobility ratio and Péclet number; constructing a physical simulation model of injected fluid to displace condensate gas reservoirs, and based on the physical simulation model, conducting a condensate gas reservoir simulation experiment according to the injection conditions to obtain simulation results; based on the simulation results, verifying and fitting the relationship curve between the injected gas breakthrough time, mobility ratio and Péclet number to determine a breakthrough time calculation formula; using an injection parameter set, conducting a condensate gas reservoir injection experiment based on the physical simulation model of injected fluid to displace condensate gas reservoirs, and using the breakthrough time calculation formula to calculate the breakthrough time of the condensate gas reservoir injection experiment corresponding to each set of injection parameter sets; determining the injection parameter set corresponding to the condensate gas reservoir injection experiment with the shortest breakthrough time as the optimal injection parameter.

[0007] According to one aspect of an embodiment of the present specification, the injection condition set includes the fluid velocity, viscosity, diffusion coefficient, concentration, and flow function of the injected fluid. Constructing the injected gas flow diffusion model based on the injection condition set includes: constructing a kinetic equation of the injected fluid based on the fluid velocity of the injected fluid, the viscosity of the injected fluid and the diffusion coefficient; constructing a convection-diffusion equation of the fluid concentration based on the concentration and flow function of the injected fluid; performing a dimensionless analysis on the kinetic equation and the convection-diffusion equation; performing a Hartley transform on the flow variables in the kinetic equation and the diffusion equation after the dimensionless analysis to obtain a mathematical model of the injected gas flow diffusion.

[0008] According to one aspect of the embodiments of this specification, based on the fluid velocity of the injected fluid, the viscosity of the injected fluid and the diffusion coefficient, constructing the kinetic equation of the injected fluid includes a kinetic equation represented by the following formula:

[0009] Among them, p'=p / (μ1·D·K-1), represents pressure, U represents the velocity field of the injected fluid; D represents the diffusion coefficient tensor, μ'=μ / μ1 represents the dimensionless fluid viscosity, u'=u / U represents the dimensionless fluid velocity, μ1· represents, K represents, and μ represents the fluid viscosity; according to the concentration and flow function of the injected fluid, the convection-diffusion equation of the fluid concentration is constructed, including the convection-diffusion equation represented by the following formula: Where c represents the concentration of the injected fluid, ψ is the flow rate function, x and y represent the two-dimensional horizontal and vertical coordinates, t represents time, and c' represents the dimensionless concentration.

[0010] According to one aspect of an embodiment of the present specification, digitizing the mathematical model of the flow and diffusion of the injected fluid to obtain a relationship curve between the breakthrough time of the injected gas and the mobility ratio and the Péclet number includes: numerically solving the mathematical model of the flow and diffusion of the injected fluid, and determining the viscosity index diameter of the mathematical model of the flow and diffusion of the injected fluid at a constant diffusion coefficient at different times and the viscosity index diameter at a constant mobility ratio at different times; determining the relationship curve between the breakthrough time and the mobility ratio and the Péclet number based on the viscosity index diameter at the constant diffusion coefficient at different times and the viscosity index diameter at the constant mobility ratio at different times.

[0011] According to one aspect of the embodiments of the present specification, constructing a physical simulation model for injecting fluid to displace a condensate gas reservoir includes: determining the condensate gas required for physical simulation based on the composition of the on-site well flow; determining the physical simulation injection-production pressure difference based on the state of the on-site well and the principle of similarity in the proportion of gravity and displacement force; determining the injection rate of the injected fluid based on the injection-production pressure difference and Darcy's formula; and selecting different gas injection methods, injection fluid types, injection timing, injection pressure, and injection rate to complete the construction of the physical simulation model.

[0012] According to one aspect of the embodiments of this specification, the dynamic equation considering the gravity factor is as follows:

[0013]

[0014] Among them, x and y are the horizontal and vertical coordinates of the fluid in the two-dimensional coordinates; u represents the injection velocity, g represents gravity, μ / K represents the fluid mobility, P represents the pressure, μ represents the fluid viscosity, K represents the permeability of the injected fluid, ρ represents the fluid density, and g represents the acceleration due to gravity.

[0015] According to one aspect of the embodiment of this specification, based on the simulation results and the relationship curve, the relationship between the fitting breakthrough time, mobility ratio and Peclet number is verified, and the breakthrough time calculation formula is determined: The relationship between the dimensionless breakthrough time, mobility ratio and Peclet number is determined by fitting using the following formula: t BT =e 0.793419 ×e -0.231092R ×Pe 0.899608 ; where t BT represents dimensionless breakthrough time; R represents mobility ratio, Pe represents Peclet number; the breakthrough time is determined according to the following formula:

[0016] Among them, t BT represents the dimensionless breakthrough time, t represents the breakthrough time, D represents the diffusion coefficient tensor, and U represents the injection velocity.

[0017] The embodiment of the present specification also provides a parameter selection device based on the law of gas injection and migration of condensate gas reservoirs, the device comprising: a mathematical model construction unit, used to construct a mathematical model of injection fluid flow and diffusion according to injection conditions, wherein the injection conditions include: injection medium properties, diffusion convection of injection fluid; a relationship curve determination unit, used to digitize the mathematical model of injection fluid flow and diffusion, and obtain the injection gas breakthrough time and mobility ratio and Peclet relationship curve; a physical simulation model construction unit, used to construct a physical simulation model of injection fluid displacement of condensate gas reservoirs, and based on the physical simulation model, conduct condensate gas reservoir experiments under the injection conditions to obtain simulation results; a breakthrough time calculation unit, used to verify the fitting of the mobility ratio and Peclet number according to the simulation results and the relationship curve, and determine the breakthrough time calculation formula; an experimental unit, used to conduct condensate gas reservoir injection experiments using an injection parameter set, and use the breakthrough time calculation formula to calculate the breakthrough time of the condensate gas reservoir injection experiment corresponding to each set of injection parameter sets; an optimal injection parameter determination unit, used to determine the injection parameter set corresponding to the condensate gas reservoir injection experiment with the shortest breakthrough time as the optimal injection parameter.

[0018] The embodiment of the present invention provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the method for measuring the breakthrough pressure of dense rock is implemented when the processor executes the computer program.

[0019] The embodiments of the present invention further provide a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method for measuring the breakthrough pressure of dense rock is implemented.

[0020] This solution solves the problem of condensate gas reservoirs blocking the oil and gas seepage channels to avoid affecting the normal operation of oil and gas wells, reduces the decline in old areas, increases recoverable reserves, converts underground resources into production, and produces better economic benefits. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] In order to more clearly illustrate the technical solutions in the embodiments of this article or the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of this article. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0022] Figure 1 It is a flow chart of a parameter selection method based on the migration law of gas injection in condensate gas reservoir according to an embodiment of this specification;

[0023] Figure 2 Shown is a flow chart of a method for constructing an injected gas flow diffusion model in this specification;

[0024] Figure 3 The figure is a flow chart of a method for determining a relationship curve between the breakthrough time of injected gas and the mobility ratio and the Peclet number according to an embodiment of the present specification;

[0025] Figure 4 The figure shows a flow chart of a method for constructing a physical simulation model for injecting fluid to displace a condensate gas reservoir according to an embodiment of the present specification;

[0026] Figure 5 The flowchart of a method for verifying the relationship between the fitting breakthrough time and the mobility ratio and the Peclet number in the embodiment of this specification is shown;

[0027] Figure 6 It is a structural schematic diagram of a parameter selection device based on the migration law of gas injection in a condensate gas reservoir according to an embodiment of this invention;

[0028] Fig. 7A and Figure 7B It is a schematic diagram of a mathematical model of flow and diffusion of injected fluid according to an embodiment of this specification;

[0029] Figure 8 The figure shows a schematic diagram of the viscosity finger diameter under a constant diffusion coefficient in an embodiment of this specification;

[0030] Fig. 9 The figure shows a schematic diagram of the viscosity finger diameter when the mobility ratio is 1.5 in an embodiment of this specification;

[0031] Fig.10 The figure shows a schematic diagram of the viscosity finger diameter when the mobility ratio is 2 in an embodiment of this specification;

[0032] Fig.11 The figure shows a schematic diagram of the viscosity finger diameter when the mobility ratio is 2.5 in an embodiment of this specification;

[0033] Fig.12 The figure shows a schematic diagram of the viscosity finger diameter when the Péclet number is 300 in an embodiment of the present specification;

[0034] Fig.13 The figure shows a schematic diagram of the viscosity finger diameter when the Péclet number is 500 in an embodiment of the present specification;

[0035] Fig.14 The figure shows a schematic diagram of the viscosity finger diameter when the Péclet number is 900 in an embodiment of the present specification;

[0036] Fig.15 The figure shows a curve diagram of the relationship between breakthrough time and Peclet in an embodiment of the present specification;

[0037] Fig.16 Shown is a schematic diagram of the structure of a computer device according to an embodiment of this invention.

[0038] Description of the accompanying symbols:

[0039] 601, Mathematical model building unit;

[0040] 602, relationship curve determination unit;

[0041] 603. Physical simulation model building unit;

[0042] 604. Breakthrough time calculation unit;

[0043] 605, Experimental Unit;

[0044] 606. Optimal injection parameter determination unit;

[0045] 1602. Computer equipment;

[0046] 1604, processor;

[0047] 1606. Memory;

[0048] 1608, driving mechanism;

[0049] 1610, input / output module;

[0050] 1612. Input devices;

[0051] 1614. Output device;

[0052] 1616. Presentation equipment;

[0053] 1618. Graphical user interface;

[0054] 1620, network interface;

[0055] 1622, communication link;

[0056] 1624. Communication bus. DETAILED DESCRIPTION

[0057] In order to enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below in conjunction with the drawings in the embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this specification, not all of the embodiments. Based on the embodiments of this specification, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this specification.

[0058] It should be noted that the terms "first", "second", etc. in the specification and claims of this article and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of this article described here can be implemented in an order other than those illustrated or described here. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, device, product or equipment that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or equipment.

[0059] This specification provides method operation steps as described in the embodiments or flow charts, but more or fewer operation steps may be included based on routine or non-creative work. The order of steps listed in the embodiments is only one way of executing the order of many steps and does not represent the only execution order. When the system or device product is executed in practice, it can be executed in the order of the method shown in the embodiments or the drawings or in parallel.

[0060] It should be noted that the parameter selection method based on the gas injection and migration law of condensate gas reservoirs in this article can be used in the field of oil and gas field exploration, and this article does not limit the application field of the parameter selection method and device based on the gas injection and migration law of condensate gas reservoirs.

[0061] Figure 1 The flowchart of a parameter selection method based on the migration law of gas injection in condensate gas reservoirs according to an embodiment of this specification is shown, which specifically includes the following steps:

[0062] Step 101, injecting a mathematical model of fluid flow and diffusion according to an injection condition set. In this step, the injection condition set includes: properties of the injected fluid and the diffusion and convection state of the injected fluid. The injected fluid properties include but are not limited to: injected fluid type, injected fluid viscosity, and injected fluid density.

[0063] In this step, a mathematical model of the flow and diffusion of the injected fluid is constructed by considering factors such as gravity, the medium type of the injected fluid, and the convection and diffusion of the injected fluid. In this step, the injected fluid can be a gas, including but not limited to: methane, nitrogen, field gas, carbon dioxide, etc.

[0064] In the embodiments of this specification, since the migration of the injected gas in the condensate gas field is mainly affected by the displacement force and gravity, the basic model of the mathematical model of the flow and diffusion of the injected fluid adopts the Hele-Shaw model.

[0065] In the embodiments of this specification, if the influence of gravity on the migration of injected gas is not considered, and the basic model is a two-dimensional homogeneous medium, there is no phase change and heat conduction, the diffusion coefficient is constant, it is completely miscible, single-phase flow, and the velocity at the outlet and inlet is the same. In the case of an incompressible Newtonian fluid, the migration of injected gas is described by the continuity equation, the momentum equation in the form of Darcy's law, and the convection-diffusion equation of concentration.

[0066] Furthermore, after obtaining the basic model, due to the actual injection situation of the condensate gas field, it is necessary to consider the gravity overburden caused by gravity and establish the injection fluid motion equation containing gravity. The injection medium motion equation containing gravity is more in line with the actual migration of injected gas in the condensate gas field. Therefore, according to the momentum equation based on Darcy's law, the convection diffusion equation of concentration and the gravity factor, a mathematical model of injection fluid flow and diffusion is constructed.

[0067] In this step, numerical simulation is used to describe the complex displacement process. The displacement process is that the fluid with lower viscosity replaces the fluid with higher viscosity, and a viscous finger-in area is formed when the two fluids come into contact. Through the mathematical model of this step, the width and state of the viscous finger-in area formed by the contact of the two fluids at each moment can be calculated. Further, according to the width and state of the viscous finger-in area at each moment, the diffusion convection state of the injected fluid is determined, and finally the displacement breakthrough time of the injected fluid is determined.

[0068] Step 102, digitizing the mathematical model of the flow and diffusion of the injected fluid to obtain a relationship curve between the injection gas breakthrough time and the mobility ratio and the Peclet.

[0069] In this step, the two key parameters that describe the flow state of the injected fluid are: mobility ratio and Péclet number. In this step, the momentum equation, the convection-diffusion equation of concentration, and the boundary conditions in the mathematical model of the injected fluid flow and diffusion are calculated to solve the migration of the injected gas under different injection speed conditions. Specifically, numerical calculations can calculate the viscosity index at different times under a constant diffusion coefficient, the viscosity index at different times under different mobility ratios, and the viscosity index at different times with different Péclet numbers. Figures 8 to 14 shown.

[0070] Step 103, construct a physical simulation model for injecting fluid to displace the condensate gas reservoir, based on the physical simulation model, perform a condensate gas reservoir simulation experiment according to the injection conditions, and obtain a simulation result. In the embodiment of this specification, the physical simulation model for injecting fluid to displace the condensate gas reservoir is used to simulate a scene containing a condensate gas reservoir in a real well, and the experiment is performed by the injection condition set to finally obtain the simulation result of the experiment. The experimental simulation result indicates the breakthrough time taken by the injected fluid to complete the displacement of the condensate gas after injecting different types of fluids.

[0071] In the examples of this specification, a displacement experiment is performed by injecting fluid into the experimental device to determine the injection conditions such as the injection speed, injection pressure, temperature, type of injected fluid, fluid viscosity, etc. at the initial moment. Displacement is achieved by convection diffusion of the injected fluid and the originally existing condensate gas, and the time it takes for the injected fluid to break through the entire device is recorded. Therefore, the simulation result is the breakthrough time of the injected fluid in the experiment.

[0072] Step 104: verify the relationship between the breakthrough time of the injected fluid and the mobility ratio and the Péclet number according to the simulation result and the relationship curve, and determine a breakthrough time calculation formula.

[0073] In the embodiments of this specification, under normal circumstances, the breakthrough time of the injected fluid obtained by numerical simulation calculation through the mathematical model of the flow and diffusion of the injected fluid and the breakthrough time of the actual experiment obtained through physical simulation should be consistent or have a small difference. Therefore, the physical simulation model of the injected fluid displacement condensate gas reservoir and the simulation results obtained by the experiment are fitted with the relationship between the breakthrough time calculated by the mathematical model of the flow and diffusion of the injected fluid and the mobility ratio and the Peclet number, so as to obtain an accurate calculation formula for the breakthrough time.

[0074] In the embodiments of this specification, a mathematical model of injected fluid flow and diffusion is used to numerically simulate the complex displacement process, and a physical simulation model of injected fluid displacement of condensate gas reservoirs is combined to verify the numerical simulation results of the mathematical model, thereby improving the prediction capability of the displacement process.

[0075] In the embodiments of this specification, the calculation formula of the breakthrough time of the injected gas can also be used to determine the value of the reasonable mobility ratio or Peclet number in order to obtain the expected ideal breakthrough time. The mobility ratio and the Peclet number can be converted into other adjustable injection parameters. Therefore, the optimal injection parameters can be determined based on the inverted mobility ratio or Peclet number.

[0076] Step 105, using the injection parameter set, based on the physical simulation model of the injected fluid displacing the condensate gas reservoir, perform a gas injection experiment in the condensate gas reservoir, and using the breakthrough time calculation formula to calculate the breakthrough time of the gas injection experiment in the condensate gas reservoir corresponding to each set of injection parameter sets. In this step, the injection parameter set in step 101 can be used to perform an actual experiment of injecting gas to displace the condensate gas reservoir. According to the breakthrough time calculation formula of the injected gas determined in the previous step, calculate the breakthrough time of the injected gas corresponding to each physical simulation test. In some other embodiments of the present specification, other injection parameter sets can also be selected to perform physical simulation experiments.

[0077] Step 106, determining the injection parameter set corresponding to the condensate gas reservoir experiment with the shortest breakthrough time as the optimal injection parameter. In this step, the condensate gas reservoir physical time with the shortest breakthrough time is determined as the optimal experiment, and the injection parameter set corresponding to the experiment is determined as the optimal parameter set.

[0078] Figure 2 The flowchart of a method for constructing an injected gas flow diffusion model is shown in this specification. In the embodiment of this specification, the injection condition set includes: fluid velocity, viscosity, diffusion coefficient, concentration, flow function, etc. of the injected fluid. The method specifically includes the following steps:

[0079] Step 201, construct a kinetic equation of the injected fluid according to the fluid velocity, viscosity and diffusion coefficient of the injected fluid. Specifically, the kinetic equation is expressed as follows:

[0080] Among them, p'=p / (μ1·D·K-1) represents pressure, U represents the velocity field of the injected fluid, D represents the diffusion coefficient tensor, μ'=μ / μ1 represents the dimensionless fluid viscosity, u'=u / U represents the dimensionless fluid velocity, μ1 represents the viscosity of the injected fluid, K represents the permeability of the injected fluid, and μ represents the fluid viscosity.

[0081] In the embodiments of this specification, in the application process of gas injection in condensate gas reservoirs with obvious gravity differentiation, the gravity effect cannot be ignored, so the kinetic equation of the embodiments of this specification takes the gravity factor into account. When the gravity factor is taken into account, the kinetic equation is constructed as shown in the following formula:

[0082] p represents pressure, u represents the velocity field of the injected fluid, μ / K represents the fluid mobility of the injected fluid, ρ represents density, g represents the acceleration of gravity, and x and y represent the two-dimensional coordinate system in the mathematical model. Among them, the velocity field of the fluid refers to the vector velocity distribution of the fluid flow front. The fluid velocity vector distribution state at all points in space at the same time.

[0083] In addition, the mathematical model for the flow and diffusion of injected gas also includes: constructing a continuity equation according to the injection velocity of the injected fluid, which is expressed as follows: Wherein, u represents the injection velocity of the injected fluid, and x and y represent the two-dimensional coordinate system in the mathematical model.

[0084] Step 202, construct the convection diffusion equation of fluid concentration according to the concentration and flow function of the injected fluid. In the embodiment of this specification, the convection diffusion equation of fluid concentration is expressed as follows:

[0085]

[0086] Among them, c represents concentration, D represents diffusion coefficient, t represents time, and x and y represent the two-dimensional coordinate system in the mathematical model.

[0087] In some other embodiments of the present specification, the mathematical model of injected fluid flow and diffusion also includes Poisson's equation: Among them, ω is the vorticity and ψ is the flow function.

[0088] Step 203, dimensionless analysis is performed on the kinetic equation and convection-diffusion equation. Since the above kinetic equation and convection-diffusion equation cannot distinguish the influence of each parameter well, the velocity, length and time are dimensionlessly quantified as u'=u / U, L'=L / (D / U) and t'=t / (D / U2 square), and the viscosity, density and pressure are processed as μ'=μ / μ1, ρ'=ρ / ρ1, p'=p / (μ1·D·K-1), and dimensionless analysis is performed on the mathematical model. ρ1

[0089] In this step, dimensionless processing is used to obtain the dimensionless equation of vorticity, as expressed by the following formula: Among them, u represents the velocity of the injected fluid, c' represents the dimensionless concentration of the injected fluid, μ represents the fluid viscosity, U represents the velocity field of the injected fluid, K represents the permeability of the injected fluid, x, y represent the abscissa and ordinate of the mathematical model of the flow and diffusion of the injected fluid, ρ1 represents the density of the injected fluid, ψ is the flow function, and g represents the acceleration of gravity.

[0090] After considering the total concentration in space and the one-dimensional convection-diffusion equation and the interference concentration, the dimensionless equation obtained becomes:

[0091]

[0092] Step 204, Hartley transformation is performed on the flow variables in the kinetic equation and diffusion equation after dimensionless analysis to obtain the mathematical model of the injected gas flow diffusion. After the Hartley transformation, the alternating implicit method is introduced to solve the concentrated concentration c and iterative pressure in the x-direction of the horizontal coordinate, so that both the concentration c and the pressure p converge, and dt / 2 is iterated in the y-direction of the vertical coordinate. After the iterations in the x-direction and the y-direction are completed, the construction of the mathematical model of the injected gas flow diffusion is completed.

[0093] Figure 3 The flowchart of a method for determining the relationship curve between the breakthrough time of injected gas and the mobility ratio and the Péclet number according to an embodiment of the present specification is shown, which specifically includes the following steps:

[0094] Step 301, numerically solving the mathematical model of injected fluid flow diffusion, and determining the viscosity index diameter of the mathematical model of injected fluid flow diffusion at constant diffusion coefficients at different times and the viscosity index diameter at constant mobility ratios at different times.

[0095] In this step, the viscosity index of each grid of the two-dimensional plane of the mathematical model is numerically solved and calculated, and based on the correlation between each grid and other grids, a schematic diagram of the viscosity index of the entire two-dimensional plane of the mathematical model is finally drawn.

[0096] like Fig. 7AAs shown in the figure, the concentration field of the flow displacement with a constant diffusion coefficient has no obvious instability at first, and there is a stable diffusion area at the contact. The width of the area of ​​the two components increases with time. This period is called the diffusion-dominated period. In the diffusion-dominated period, the unstable part is the smallest. However, in the dimensionless time such as t = 100 to 150, some small wave disturbances begin to develop. At t = 200, the identifiable contact area of ​​the viscous finger diameter becomes unstable. The evolution of the mixing area thereafter switches to a period dominated by convection with a characteristic time Tc. In the subsequent time, the initial finger diameter undergoes a series of mechanisms, resulting in the development of the finger diameter and the fusion of other finger diameters. Finally, several main finger diameters are formed and reach the far right, with the boundary indicated by t = 500. During the entire displacement diffusion process, the viscous finger diameter always grows in the transition area with a relatively thick contact area in the diffusion area.

[0097] Step 302, determining a relationship curve between breakthrough time, mobility ratio and Péclet number according to the viscosity index diameter under constant diffusion coefficient at different times and the viscosity index diameter under constant mobility ratio at different times.

[0098] like Fig.11 It can be seen that as the mobility ratio R increases, the instability of the displacement front occurs earlier and the movement of the viscous fingering becomes more complex. For example, when the mobility ratio R is 1.5, the initial instability of the displacement front occurs at around time 400, while when the mobility ratio R is 3.0, the initial instability of the displacement front occurs at around time 200. For the case of a constant diffusion coefficient D, the change in R does not affect the diffusion coefficient, so it will be superimposed on the same P e It can be seen that the larger the R, the shorter the diffusion range and the earlier the instability is triggered.

[0099] as follows Figure 12 to Figure 14 The viscosity finger diameter results under the same mobility ratio and different Peclet numbers are shown. The mobility ratio R is 3. Fig.12 , Fig.13 and Fig.14 It can be seen that as the Peclet number P e As the mobility ratio R increases, the front edge breakthrough time decreases.

[0100] For a fixed diffusion coefficient D and the length L of the porous medium, the larger Péclet number P e Indicates that higher injection rates and more unstable flow rates make the viscous finger reach the downstream boundary faster. Breakthrough time and Peclet relationship curve, such as Fig.15 shown.

[0101] Figure 4The flowchart of a method for constructing a physical simulation model for injecting fluid to displace a condensate gas reservoir in an embodiment of this specification is shown, which specifically includes the following steps:

[0102] Step 401, determining the condensate gas required for physical simulation according to the on-site well flow composition.

[0103] In the embodiments of this specification, in order to ensure the effect of experimental simulation of gas reservoirs, the injection volume of condensate gas in a single experiment shall not be less than 1.5 times the experimental amount. Use an injection pump to inject formation water into the two-dimensional model, and the injection volume is 1.5 times the pore volume to ensure that the formation water of the gas reservoir is configured in the container tank according to the ion concentration. Furthermore, according to the logistics components of the actual wells in the target work area, determine the compound condensate gas of the physical simulation model of the injected fluid to displace the condensate gas reservoir. Among them, the compound condensate gas includes: components in the condensate gas and the molar fraction of each component. As shown in Table 1 below:

[0104] Table 1 YH23-2-10 well flow composition and small model compound gas composition

[0105]

[0106]

[0107] Step 402, according to the state of the on-site well, based on the principle of similarity between gravity and displacement force ratio, determine the physical simulation injection-production pressure difference.

[0108] In this step, it is necessary to design a reasonable injection-production pressure difference for the physical simulation model. Specifically, according to the cyclic gas injection development mechanism of condensate gas reservoirs, molecular diffusion is only related to temperature and pressure. According to the method that the gravity and displacement force ratios of the oil field and the laboratory are similar, the injection-production pressure difference of the physical simulation model is determined, and the calculation formula is as follows:

[0109]

[0110] Among them, ρ is the gas density of condensate gas, the unit is kg / m3, g represents the acceleration of gravity, h represents the height, and p represents the pressure. The injection-production pressure difference in the laboratory is further determined according to the height of the actual well in the oil field, the downhole pressure in the oil field, and the height of the laboratory physical simulation model.

[0111]

[0112] In the embodiments of this specification, the density of condensate gas can be calculated according to an empirical formula, which is expressed as follows:

[0113] Where p is pressure; γg is gas specific gravity; T is temperature; and z is the gas deviation coefficient, dimensionless.

[0114] The above formula calculates that the density of condensate gas at 138°C and 54.94MPa is 0.279g / cm 3 The injection-production pressure difference of the physical simulation model is calculated based on the similarity ratio formula to be 6.94 kPa.

[0115] Step 403, determine the injection rate of the injected fluid according to the injection-production pressure difference and Darcy's formula. After determining the injection-production pressure difference, the injection rate is calculated according to Darcy's formula to be 1.5cc / min.

[0116] Step 404 , select different gas injection methods, injection fluid types, injection timings, injection pressures, and injection speeds to complete the construction of the physical simulation model.

[0117] In the embodiments of this specification, different gas injection methods for condensate gas reservoirs will have a serious impact on the recovery rate and final recovery rate of condensate gas and condensate oil. In order to study the best gas injection method for a condensate gas reservoir in a well in a certain work area, axial gas injection, top gas injection and bottom gas injection are selected for comparative analysis.

[0118] In the examples of this specification, the migration law of injected gas in the formation needs to be studied, and the important factor of injected fluid characteristics needs to be considered. Since the properties of reservoir fluid and injected fluid (gas) are quite different, the interaction between the two will seriously affect the migration of injected gas. Therefore, three gas injection media are selected for comparative analysis, and the injection media are methane, carbon dioxide, and field gas.

[0119] In the examples of this specification, in order to analyze the impact of injection timing on the recovery effect of condensate gas reservoirs, three gas injection methods were selected for comparative analysis, namely, depletion production, depletion to 38 MPa and then pressure increase to 58 MPa production, and depletion to 38 MPa and then pressure increase to 46 MPa production.

[0120] In the examples of this specification, in order to analyze the influence of injection pressure on the recovery effect of condensate gas reservoirs, three injection pressures are selected for comparative analysis, namely 58 MPa, 46 MPa and 38 MPa.

[0121] In the examples of this specification, in order to analyze the influence of injection rate on the recovery effect of condensate gas reservoir, three gas injection pressures are selected for comparative analysis, namely 0.05 ml / min, 0.1 ml / min and 0.15 ml / min.

[0122] Experiments were conducted based on the physical simulation model of fluid displacement of condensate gas reservoirs by selecting different gas injection methods, injection media, injection timing, injection pressure and injection rate.

[0123] Figure 5The flowchart of a method for verifying the relationship between the fitting breakthrough time, mobility ratio and Péclet number in an embodiment of this specification is shown, which specifically includes the following steps:

[0124] Step 501, determine the relationship between dimensionless breakthrough time, mobility ratio and Peclet number by fitting. Specifically, the following formula is used: BT =e 0.793419 ×e -0.231092R ×Pe 0.899608 ; where t BT represents the dimensionless breakthrough time; R represents the mobility ratio, and Pe represents the Péclet number.

[0125] In this step, the mobility ratio R and Peclet number Pe corresponding to each time point calculated by the mathematical model, each mobility ratio R and Peclet number Pe time t constitute a point, and a curve is formed in the two-dimensional coordinate. The curve is fitted with the test results obtained by the condensate gas reservoir simulation experiment based on the physical simulation model and injection conditions to obtain the relationship formula between the dimensionless breakthrough time and the mobility ratio and Peclet number.

[0126] According to the description in step 104, based on the physical simulation model of the injected fluid to displace the condensate gas reservoir, the relationship between the injected gas breakthrough time, the mobility ratio and the Peclet number is verified and fitted, and the relationship between the injected gas breakthrough time, the mobility ratio and the Peclet number is adjusted so that the relationship between the gas breakthrough time, the mobility ratio and the Peclet number corresponds to the simulation result of the physical simulation model.

[0127] Step 502, determine the breakthrough time. Specifically, the breakthrough time is determined according to the following formula:

[0128] Among them, t BT represents the dimensionless breakthrough time, t represents the breakthrough time, D represents the diffusion coefficient tensor, and U represents the injection velocity.

[0129] like Figure 6 The figure shows a schematic diagram of a parameter selection device based on the migration law of gas injection in a condensate gas reservoir according to an embodiment of the present invention. The figure describes the basic structure of the parameter selection device based on the migration law of gas injection in a condensate gas reservoir. The functional units and modules therein can be implemented in software, or can be implemented in a general chip or a specific chip based on the parameter selection of the migration law of gas injection in a condensate gas reservoir. The device specifically includes:

[0130] The mathematical model building unit 601 is used to build a mathematical model of flow diffusion of the injected fluid according to the injection conditions, wherein the injection conditions include: properties of the injected medium and diffusion convection of the injected fluid;

[0131] A relationship curve determination unit 602 is used to digitize the mathematical model of the flow and diffusion of the injected fluid to obtain the injection gas breakthrough time and mobility ratio and the Peclet relationship curve;

[0132] A physical simulation model building unit 603 is used to build a physical simulation model for injecting fluid to displace a condensate gas reservoir, and to perform a condensate gas reservoir experiment under the injection conditions based on the physical simulation model to obtain a simulation result;

[0133] A breakthrough time calculation unit 604 is used to verify and fit the mobility ratio and the Péclet number according to the simulation result and the relationship curve, and determine a breakthrough time calculation formula;

[0134] The experimental unit 605 is used to perform a gas injection experiment in a condensate gas reservoir using the injection parameter set, and calculate the breakthrough time of the gas injection experiment in the condensate gas reservoir corresponding to each set of injection parameter sets using the breakthrough time calculation formula;

[0135] The optimal injection parameter determination unit 606 is used to determine the injection parameter set corresponding to the condensate gas reservoir injection experiment with the shortest breakthrough time as the optimal injection parameter.

[0136] This plan aims to continuously and efficiently develop the developed condensate oil and gas fields, reduce the decline of old areas, increase recoverable reserves, convert underground resources into production, and generate good economic benefits; at the same time, comprehensively improve the technical level of condensate gas reservoir development. Improve the recovery rate technology of circulating gas injection in the middle and late stages, innovate and break through the technology of improving the condensate oil recovery rate of condensate gas reservoirs with oil rings in the middle and late stages of depletion development, and explore how to improve the condensate oil recovery rate under the condition of near-abandonment pressure in the late stage of reserve development.

[0137] Fig. 7A and Figure 7B Shown is a schematic diagram of a mathematical model of injected fluid flow and diffusion in an embodiment of this specification. The mathematical model shown in the figure is a two-dimensional mathematical model. The length of the two-dimensional mathematical model is L and the height is H. Among them, the injected fluid of the mathematical model is a two-dimensional horizontal flow uniform porous medium, and its displacement length can reach L. The injected fluid injects condensate gas with a viscosity of μ1 and a displacement viscosity of μ2 at a slow and stable speed U. The concentration of the injected gas is c1 and the viscosity is μ1, and the concentration of the condensate gas is c2 and the viscosity is μ2. The velocity field of the injected gas is U, which changes with time, and the velocity field is expressed as U(t).

[0138] Figure 8 The figure shows a schematic diagram of the viscosity finger diameter under a constant diffusion coefficient in an embodiment of this specification. It can be seen from the figure that the concentration field of the flow displacement with a constant diffusion coefficient has no obvious instability at first, and there is a stable diffusion area at the contact point. The width of the area of ​​the two components increases over time, forming a diffusion-dominated period. The unstable part of the diffusion-dominated period is the smallest.

[0139] Fig. 9 The figure shows a schematic diagram of the viscosity finger diameter when the mobility ratio is 1.5 in an embodiment of this specification. Fig.10 The figure shows a schematic diagram of the viscosity finger diameter when the mobility ratio is 2 in an embodiment of this specification. Fig.11 The figure shows a schematic diagram of the viscosity finger diameter when the flow ratio is 2.5 in an embodiment of this specification. Fig. 9 , Fig.10 , Fig.11 It can be seen that as the mobility ratio R increases, the instability of the displacement front occurs earlier and the movement of the viscous fingering becomes more complicated.

[0140] Fig.12 The figure shows a schematic diagram of the viscosity finger diameter when the Péclet number is 300 in an embodiment of this specification. Fig.13 The figure shows a schematic diagram of the viscosity finger diameter when the Péclet number is 500 in an embodiment of this specification. Fig.14 The figure shows a schematic diagram of the viscosity finger diameter when the Péclet number is 900 in an embodiment of this specification. Fig.12 , Fig.13 , Fig.14 In the figure, the mobility ratio R is 3. As the Peclet number P e With the increase of , the leading edge breakthrough time has a general trend of increasing.

[0141] Fig.15 The figure shows a curve diagram of the relationship between the breakthrough time and the Peclet number in an embodiment of the present specification. It can be seen from the figure that when the mobility ratio remains unchanged, the larger the Peclet number, the longer the breakthrough time.

[0142] like Fig.16As shown, a computer device provided in an embodiment of the present invention is provided, and the parameter selection method based on the migration law of gas injection in condensate gas reservoir is executed by the computer device. The computer device 1602 may include one or more processors 1604, such as one or more central processing units (CPUs), and each processing unit may implement one or more hardware threads. The computer device 1602 may also include any memory 1606, which is used to store any kind of information such as code, settings, data, etc. Non-limitingly, for example, the memory 1606 may include any one or more combinations of the following: any type of RAM, any type of ROM, flash memory device, hard disk, optical disk, etc. More generally, any memory may use any technology to store information. Further, any memory may provide volatile or non-volatile retention of information. Further, any memory may represent a fixed or removable component of the computer device 1602. In one case, when the processor 1604 executes an associated instruction stored in any memory or combination of memories, the computer device 1602 may perform any operation of the associated instruction. The computer device 1602 also includes one or more drive mechanisms 1608 for interacting with any storage, such as a hard disk drive mechanism, an optical disk drive mechanism, etc.

[0143] The computer device 1602 may also include an input / output module 1610 (I / O) for receiving various inputs (via input devices 1612) and for providing various outputs (via output devices 1614). A specific output mechanism may include a presentation device 1616 and an associated graphical user interface (GUI) 1618. In other embodiments, the input / output module 1610 (I / O), input device 1612, and output device 1614 may not be included, and the computer device 1602 may be used as a computer device in a network. The computer device 1602 may also include one or more network interfaces 1620 for exchanging data with other devices via one or more communication links 1622. One or more communication buses 1622 couple the components described above together.

[0144] The communication link 1623 may be implemented in any manner, for example, through a local area network, a wide area network (e.g., the Internet), a point-to-point connection, etc., or any combination thereof. The communication link 1622 may include any combination of hardwired links, wireless links, routers, gateway functions, name servers, etc. governed by any protocol or combination of protocols.

[0145] Corresponds to Figures 1 to 5 The method in this article also provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the steps of the above method are executed.

[0146] The embodiment of the present invention also provides a computer readable instruction, wherein when the processor executes the instruction, the program therein causes the processor to execute the following Figures 1 to 5 The method shown.

[0147] It should be understood that in the various embodiments of this document, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this document.

[0148] It should also be understood that in the embodiments of this article, the term "and / or" is only a description of the association relationship of the associated objects, indicating that three relationships may exist. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in this article generally indicates that the associated objects before and after are in an "or" relationship.

[0149] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the composition and steps of each example have been generally described in terms of function in the above description. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this article.

[0150] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0151] In the several embodiments provided herein, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic, for example, the division of the units is only a logical function division, and there may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or units, or can be electrical, mechanical or other forms of connection.

[0152] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the embodiments of this article.

[0153] In addition, each functional unit in each embodiment of this invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above integrated unit may be implemented in the form of hardware or in the form of software functional unit.

[0154] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this article is essentially or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of this article. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk and other media that can store program codes.

[0155] Specific embodiments are used in this article to illustrate the principles and implementation methods of this article. The description of the above embodiments is only used to help understand the methods and core ideas of this article. At the same time, for general technicians in this field, according to the ideas of this article, there will be changes in the specific implementation methods and application scopes. In summary, the content of this specification should not be understood as a limitation on this article.

Claims

1. A parameter selection method based on the migration law of gas injection in condensate gas reservoirs, characterized in that: The method comprises: Constructing a mathematical model of injected fluid flow and diffusion according to the injection condition set; Numerically quantifying the mathematical model of the flow and diffusion of the injected fluid to obtain the relationship curve between the breakthrough time of the injected gas and the mobility ratio and the Peclet curve; Constructing a physical simulation model for injecting fluid to displace a condensate gas reservoir, and conducting a condensate gas reservoir simulation experiment based on the physical simulation model and the injection conditions to obtain a simulation result; According to the simulation results, verify and fit the relationship curve between the breakthrough time of the injected gas and the mobility ratio and the Péclet number, and determine the breakthrough time calculation formula; Using the injection parameter set, a gas injection experiment of a condensate gas reservoir is performed based on the physical simulation model of the injected fluid displacing the condensate gas reservoir, and using the breakthrough time calculation formula, the breakthrough time of the gas injection experiment of the condensate gas reservoir corresponding to each group of injection parameter sets is calculated; The injection parameter set corresponding to the gas injection experiment of the condensate gas reservoir with the shortest breakthrough time is determined as the optimal injection parameter.

2. The parameter selection method based on the gas injection migration law of condensate gas reservoir according to claim 1 is characterized in that: The injection condition set includes the fluid velocity, viscosity, diffusion coefficient, concentration, and flow function of the injected fluid. Constructing the injected gas flow diffusion model based on the injection condition set includes: A kinetic equation of the injected fluid is constructed based on the fluid velocity, viscosity and diffusion coefficient of the injected fluid; According to the concentration and flow rate function of the injected fluid, the convection-diffusion equation of the fluid concentration is constructed; Performing dimensionless analysis on the kinetic equation and the convection-diffusion equation; The flow variables in the kinetic equation and diffusion equation after dimensionless analysis are subjected to Hartley transformation to obtain a mathematical model of the flow and diffusion of the injected gas.

3. The parameter selection method based on the gas injection migration law of condensate gas reservoir according to claim 2 is characterized in that: According to the fluid velocity of the injected fluid, the viscosity of the injected fluid and the diffusion coefficient, the kinetic equation of the injected fluid is constructed, including the kinetic equation represented by the following formula: Wherein, p'=p / (μ1·D·K-1), represents pressure, U represents velocity field of injected fluid; D represents diffusion coefficient tensor, μ'=μ / μ1 represents dimensionless fluid viscosity, u'=u / U represents dimensionless fluid velocity, μ1· represents, K represents permeability of injected fluid, μ represents fluid viscosity; According to the concentration and flow function of the injected fluid, the convection-diffusion equation of the fluid concentration is constructed, including the convection-diffusion equation expressed by the following formula: Where c represents the concentration of the injected fluid, ψ is the flow rate function, x and y represent the two-dimensional horizontal and vertical coordinates, t' represents the dimensionless time, and c' represents the dimensionless concentration.

4. The parameter selection method based on the gas injection migration law of condensate gas reservoir according to claim 3 is characterized in that: The mathematical model of the flow and diffusion of the injected fluid is numerically quantified to obtain the relationship curve between the injected gas breakthrough time, mobility ratio and Péclet number, including: Numerically solving a mathematical model of the flow and diffusion of the injected fluid, and respectively determining a viscosity index diameter of the mathematical model of the flow and diffusion of the injected fluid at a constant diffusion coefficient at different times and a viscosity index diameter at a constant mobility ratio at different times; According to the viscosity index diameter under constant diffusion coefficient at different times and the viscosity index diameter under constant mobility ratio at different times, the relationship curve between breakthrough time, mobility ratio and Péclet number is determined.

5. The parameter selection method based on the gas injection migration law of condensate gas reservoir according to claim 1 is characterized in that: The physical simulation model for injecting fluid to displace condensate gas reservoirs includes: Determine the condensate gas required for physical simulation based on the on-site well flow composition; According to the status of the on-site wells, based on the principle of similarity between gravity and displacement force ratio, the physical simulation injection-production pressure difference is determined; Determine the injection rate of the injected fluid based on the injection-production pressure difference and Darcy's formula; Select different gas injection methods, injection fluid types, injection timing, injection pressure, and injection speed to complete the construction of the physical simulation model.

6. The parameter selection method based on the gas injection migration law of condensate gas reservoir according to claim 5 is characterized in that: The dynamic equation considering gravity is as follows: Among them, x and y are the horizontal and vertical coordinates of the fluid in the two-dimensional coordinates; u represents the injection velocity, g represents gravity, μ / K represents the fluid mobility, P represents the pressure, μ represents the fluid viscosity, K represents the permeability of the injected fluid, ρ represents the fluid density, and g represents the acceleration due to gravity.

7. The parameter selection method based on the migration law of gas injection in condensate gas reservoir according to claim 1 is characterized in that: According to the simulation results and the relationship curve, the relationship between the fitting breakthrough time, mobility ratio and Péclet number was verified, and the breakthrough time calculation formula was determined: The relationship between dimensionless breakthrough time, mobility ratio and Péclet number is determined by fitting using the following formula: t BT =e 0.793419 ×e -0.231092R ×Pe 0.899608 ; where t BT represents dimensionless breakthrough time; R represents mobility ratio, P e represents the Péclet number; The breakthrough time is determined according to the following formula: Among them, t BT represents the dimensionless breakthrough time; t represents the breakthrough time, D represents the diffusion coefficient tensor, and U represents the injection velocity.

8. A parameter selection device based on the migration law of gas injection in condensate gas reservoir, characterized in that: The device comprises: A mathematical model building unit, used to build a mathematical model of flow diffusion of the injected fluid according to the injection conditions, wherein the injection conditions include: properties of the injected medium, diffusion convection of the injected fluid; A relationship curve determination unit, used for digitizing the mathematical model of the flow and diffusion of the injected fluid, and obtaining the injection gas breakthrough time and mobility ratio and the Peclet relationship curve; A physical simulation model building unit is used to build a physical simulation model for injecting fluid to displace a condensate gas reservoir, and to perform a condensate gas reservoir experiment under the injection conditions based on the physical simulation model to obtain a simulation result; A breakthrough time calculation unit, used to verify and fit the mobility ratio and the Péclet number according to the simulation result and the relationship curve, and determine a breakthrough time calculation formula; An experimental unit, used to perform a gas injection experiment in a condensate gas reservoir using an injection parameter set, and to calculate the breakthrough time of the gas injection experiment in the condensate gas reservoir corresponding to each injection parameter set using the breakthrough time calculation formula; The optimal injection parameter determination unit is used to determine the injection parameter set corresponding to the condensate gas reservoir injection experiment with the shortest breakthrough time as the optimal injection parameter.

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

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

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