Method and device for determining average formation pressure of reservoir after pressure drive in low-permeability tight oil reservoir

Abstract

The present disclosure provides a method and device for determining the average formation pressure of a reservoir after pressure drive in a low-permeability tight oil reservoir, relating to the technical field of oilfield development, including: determining the control equation and constraint condition equation for the average formation pressure of the target reservoir after pressure drive based on the physical model of the average formation pressure of the target reservoir after pressure drive; determining the prediction relationship between the reservoir pressure, radial distance, and production time in different seepage capacity regions of the target reservoir after pressure drive under stress-sensitive conditions based on the control equation and constraint condition equation for the average formation pressure of the target reservoir after pressure drive; and determining the average formation pressure of the target reservoir after pressure drive based on the prediction relationship between the reservoir pressure, radial distance, and production time in different seepage capacity regions of the target reservoir after pressure drive under stress-sensitive conditions and the production history data of the target reservoir. The method provided by the present disclosure is used to calculate the average formation pressure of the reservoir after pressure drive.

Description

Technical Field

[0001] The present invention relates to the technical field of oilfield development, and particularly to a method and device for determining the average formation pressure of a reservoir after pressure drive in a low-permeability tight oil reservoir. Background Art

[0002] The average formation pressure is an important indicator for measuring formation energy and an important parameter for determining an oilfield development plan. Accurately obtaining the average formation pressure of a reservoir is the basis for production dynamic analysis, reasonably evaluating the productivity of oil wells, predicting stable production years and other indicators, and is an important condition for the oilfield to continuously maintain stable and high production and adjust the later development plan.

[0003] For the problem of "injection failure" of injection wells in low-permeability tight reservoirs, the pressure drive technology can be used to solve it well. However, the pressure drive technology will enhance the heterogeneity of the reservoir around the injection well. At present, there is no calculation method for the average formation pressure for high-intensity injection and reservoir heterogeneity, making it difficult to accurately formulate an oilfield development plan for low-permeability tight reservoirs. Summary of the Invention

[0004] According to one aspect of the present disclosure, there is provided a method for determining the average formation pressure of a reservoir after pressure drive in a low-permeability tight oil reservoir, the method including:

[0005] Based on the physical model of the average formation pressure of the reservoir after pressure drive in the target oil reservoir, determining the control equation and constraint condition equation of the average formation pressure of the reservoir after pressure drive in the target oil reservoir expressed by the seepage partial differential control equation;

[0006] Based on the control equation of the average formation pressure of the reservoir after pressure drive in the target oil reservoir and the constraint condition equation, determining the prediction relationship between the reservoir pressure, radial distance and production time in different seepage capacity regions of the target oil reservoir after pressure drive under stress-sensitive conditions;

[0007] Based on the prediction relationship between the reservoir pressure, radial distance and production time in different seepage capacity regions of the target oil reservoir after pressure drive under stress-sensitive conditions, and the production history data of the target oil reservoir, determining the average formation pressure of the reservoir after pressure drive in the target oil reservoir.

[0008] According to another aspect of the present disclosure, there is provided a device for determining the average formation pressure of a reservoir after pressure drive in a low-permeability tight oil reservoir, the device including:

[0009] A first determination module, configured to determine the control equation and constraint condition equation of the average formation pressure of the reservoir after pressure drive in the target oil reservoir expressed by the seepage partial differential control equation based on the physical model of the average formation pressure of the reservoir after pressure drive in the target oil reservoir;

[0010] The first determination module is further configured to determine a prediction relationship among the reservoir pressure, the radial distance, and the production time in different seepage capacity regions after pressure drive of the target reservoir based on the average reservoir formation pressure control equation after pressure drive of the target reservoir and the constraint condition equation under stress sensitivity conditions;

[0011] A second determination module, configured to determine the average reservoir formation pressure after pressure drive of the target reservoir based on the prediction relationship among the reservoir pressure, the radial distance, and the production time in different seepage capacity regions after pressure drive of the target reservoir under stress sensitivity conditions and the production history data of the target reservoir.

[0012] According to another aspect of the present disclosure, there is provided an electronic device, including:

[0013] A processor; and

[0014] A memory storing a program;

[0015] wherein the program includes instructions that, when executed by the processor, cause the processor to execute the method provided in the embodiments of the present disclosure.

[0016] According to another aspect of the present disclosure, there is provided a non-transitory computer-readable storage medium storing computer instructions for causing a computer to execute the method provided in the embodiments of the present disclosure.

[0017] In one or more technical solutions provided in the embodiments of the present application, through the physical model of the average reservoir formation pressure after pressure drive of the target reservoir, the average reservoir formation pressure control equation and the constraint condition equation (i.e., the mathematical model of the average reservoir formation pressure after pressure drive of the target reservoir) expressed by the seepage partial differential control equation are determined. Then, based on the average reservoir formation pressure control equation and the constraint condition equation after pressure drive of the target reservoir, a prediction relationship among the reservoir pressure, the radial distance, and the production time in different seepage capacity regions after pressure drive of the target reservoir under stress sensitivity conditions can be determined. Based on this, the average reservoir formation pressure after pressure drive of the target reservoir can be determined based on the prediction relationship among the reservoir pressure, the radial distance, and the production time in different seepage capacity regions after pressure drive of the target reservoir under stress sensitivity conditions.

[0018] It can be seen that the exemplary embodiments of the present disclosure can obtain a prediction relationship among the reservoir pressure, radial distance, and production time in different seepage capacity regions after pressure drive of the target reservoir by mathematical modeling and solving of the physical model of the average formation pressure of the reservoir after pressure drive of the target reservoir, and substitute the production history data of the target reservoir into the prediction relationship to determine the average formation pressure of the reservoir after pressure drive of the target reservoir, thereby obtaining an evaluation method for the average formation pressure for high-intensity injection and reservoir heterogeneity. Based on this, the method for determining the average formation pressure of the reservoir after pressure drive of the low-permeability tight oil reservoir provided by the exemplary embodiments of the present disclosure can provide theoretical guidance for the oilfield development plan of the low-permeability tight reservoir. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In the following description of the exemplary embodiments in conjunction with the drawings, more details, features, and advantages of the present disclosure are disclosed. In the drawings:

[0020] Figure 1 The flowchart of the method for determining the average formation pressure of the reservoir after pressure drive of the low-permeability tight oil reservoir provided by the exemplary embodiments of the present disclosure is shown;

[0021] Figure 2 The flowchart of the method for determining the real-domain prediction relationship between the reservoir pressure and the radial distance in different seepage capacity regions provided by the exemplary embodiments of the present disclosure is shown;

[0022] Figure 3 The flowchart of the method for determining the average formation pressure of the reservoir after pressure drive of the target low-permeability tight oil reservoir provided by the exemplary embodiments of the present disclosure is shown;

[0023] Figure 4 The structural schematic diagram of the physical model of the target reservoir provided by the exemplary embodiments of the present disclosure is shown;

[0024] Figure 5A The schematic diagram of the elliptical seepage field before conformal transformation provided by the exemplary embodiments of the present disclosure is shown;

[0025] Figure 5B The schematic diagram of the circular seepage field after conformal transformation provided by the exemplary embodiments of the present disclosure is shown;

[0026] Figure 6 The schematic diagram of the pressure distribution of the injection well and the average formation pressure of the reservoir provided by the exemplary embodiments of the present disclosure is shown;

[0027] Figure 7 The schematic block diagram of the functional modules of the device for determining the average formation pressure of the reservoir after pressure drive of the low-permeability tight oil reservoir provided by the exemplary embodiments of the present disclosure is shown;

[0028] Figure 8Shows a schematic block diagram of a chip according to an exemplary embodiment of the present disclosure;

[0029] Figure 9 Shows a structural block diagram of an exemplary electronic device that can be used to implement the embodiments of the present disclosure. Detailed implementation manners

[0030] Embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although some embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure can be implemented in various forms and should not be construed as limited to the embodiments set forth herein. On the contrary, these embodiments are provided to more thoroughly and completely understand the present disclosure. It should be understood that the drawings and embodiments of the present disclosure are only for exemplary purposes and are not used to limit the protection scope of the present disclosure.

[0031] It should be understood that the various steps recorded in the method embodiments of the present disclosure can be executed in different orders and / or in parallel. In addition, the method embodiments may include additional steps and / or omit the steps shown. The scope of the present disclosure is not limited in this regard.

[0032] As used herein, the term "including" and its variants are open-ended, that is, "including but not limited to". The term "based on" is "at least partially based on". The term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one additional embodiment"; the term "some embodiments" means "at least some embodiments". The relevant definitions of other terms will be given in the following description. It should be noted that the concepts such as "first" and "second" mentioned in the present disclosure are only used to distinguish different devices, modules or units, and are not used to limit the order of the functions executed by these devices, modules or units or their interdependent relationships.

[0033] It should be noted that the modifications of "one" and "multiple" mentioned in the present disclosure are illustrative rather than restrictive. Those skilled in the art should understand that, unless otherwise clearly specified in the context, it should be understood as "one or more".

[0034] The names of the messages or information exchanged between multiple devices in the embodiments of the present disclosure are only for illustrative purposes and are not used to limit the scope of these messages or information.

[0035] Before introducing the embodiments of the present disclosure, the following interpretations are first made for the relevant terms involved in the embodiments of the present disclosure:

[0036] Area-weighted method is a method commonly used to calculate averages. It weights each data point based on its area, rather than simply giving all data points equal weights. In area-weighted method, the weighting factor of each data point is the ratio of the area of ​​its region to the total area.

[0037] The MDH method is a well test analysis method proposed by Miller, Dyes and Hutchinson in 1950. It is mainly used to analyze the radial flow section of the pressure recovery data to obtain data such as formation permeability and skin coefficient. It is suitable for situations where the shut-in time is much longer than the test time.

[0038] The MBH method is a well test analysis method proposed by Mathews, Brons and Hazebroke in 1954. It mainly uses the pressure recovery data in the bounded oil supply area to calculate the average formation pressure.

[0039] Average formation pressure is an important indicator for measuring formation energy and an important parameter for determining oilfield development plans. Accurately obtaining the average formation pressure of the reservoir is the basis for production dynamic analysis, reasonable evaluation of oil well productivity, prediction of stable production years and other indicators. It is an important condition for the oilfield to maintain stable and high production and implement later production adjustment measures. For low-permeability and tight reservoirs, their physical properties are poor and their permeability is low (<10mD), so there is a problem that water injection wells cannot be injected. Pressure-driven technology can effectively solve the problem of difficult injection of low-permeability and tight oil reservoirs by injecting a large amount of energy-replenishing fluid into the reservoir in a short time through high-pump pressure and large-volume water injection. However, pressure-driven technology will change the properties of the reservoir around the water injection well and enhance heterogeneity. However, there is currently a lack of methods for calculating the average formation pressure under conditions of high-intensity injection and reservoir heterogeneity.

[0040] At present, the formation pressure is mainly determined by well test interpretation in oil field development. The well test interpretation method and pressure calculation method used in the oil field will directly affect the reliability of reservoir pressure evaluation. Commonly used methods for determining average formation pressure include MDH method, MBH method and Dietz method, but these methods are only applicable to homogeneous reservoirs and do not consider the effects of high-intensity injection and reservoir heterogeneity. Therefore, it is urgent to propose a method for calculating the average formation pressure of the reservoir after pressure drive in low-permeability tight oil reservoirs, which is of great significance for accurately obtaining the average formation pressure of the reservoir and determining the oil field development plan.

[0041] In view of the above problems, an exemplary embodiment of the present disclosure provides a method for determining the average formation pressure of a reservoir after pressure drive in a low-permeability tight reservoir. It can solve the mathematical model of the average formation pressure of the reservoir after pressure drive in the target reservoir, and determine the prediction relationship between the reservoir pressure, radial distance, and production time in different seepage capacity regions after pressure drive in the target reservoir based on the stress-sensitive condition. Based on this relationship, the average formation pressure of the reservoir after pressure drive in the target reservoir can be accurately predicted, providing a theoretical basis for formulating the development plan of the target reservoir.

[0042] In practical applications, the method of the exemplary embodiment of the present disclosure can be executed by an electronic device or a chip applied to an electronic device. The electronic device can be a server or a terminal device, and the terminal device includes but is not limited to desktop computers, laptop computers, mobile phones, etc.

[0043] Figure 1 The flowchart of the method for determining the average formation pressure of a reservoir after pressure drive in a low-permeability tight reservoir provided by an exemplary embodiment of the present disclosure is shown. As Figure 1 shown, the method for determining the average formation pressure of a reservoir after pressure drive in a low-permeability tight reservoir of an exemplary embodiment of the present disclosure includes:

[0044] Step 110: Based on the physical model of the average formation pressure of the reservoir after pressure drive in the target reservoir, determine the control equation and constraint condition equation of the average formation pressure of the reservoir after pressure drive in the target reservoir expressed by the seepage partial differential control equation. It should be understood that the target reservoir in the exemplary embodiment of the present disclosure may refer to a low-permeability tight reservoir after high-intensity fluid injection by the pressure drive technology, and the reservoir has strong heterogeneity.

[0045] Exemplarily, the physical model of the average formation pressure of the reservoir after pressure drive in the injection well of the above target reservoir is determined by the reservoir parameters of the target reservoir, the fluid parameters of the target reservoir, the water injection parameters of the target reservoir, and the well parameters of the injection well of the target reservoir. For example, the reservoir parameters may include: the thickness of the target reservoir, the porosity of the target reservoir, the total compressibility of the target reservoir, the initial pressure of the target reservoir, the permeability of the target reservoir, etc., and are not limited thereto. The fluid parameters of the target reservoir may include: the fluid viscosity of the target reservoir, etc., and are not limited thereto. The water injection parameters of the target reservoir may include: the water injection rate of the target reservoir, the water injection time of the target reservoir, etc., and are not limited thereto. The well parameters of the injection well of the target reservoir may include: the boundary distance of the target reservoir, the well diameter of the target reservoir, etc., and are not limited thereto.

[0046] Step 120: Based on the control equation and constraint condition equation of the average formation pressure of the reservoir after pressure drive in the target reservoir, determine the prediction relationship between the reservoir pressure, radial distance, and production time in different seepage capacity regions after pressure drive in the target reservoir based on the stress-sensitive condition.

[0047] In practical applications, due to the significant impact of stress sensitivity on the reservoir, specifically reflected in the impact on the permeability of the reservoir, it leads to difficulties in reservoir water injection. Therefore, the exemplary embodiments of the present disclosure can determine the real-domain prediction relationship between the reservoir pressure and the radial distance in different seepage capacity regions based on the control equation of the average formation pressure of the reservoir after pressure drive in the target reservoir and the constraint condition equation. Then, based on the real-domain prediction relationship between the reservoir pressure and the radial distance in different seepage capacity regions and the stress sensitivity condition, determine the dimensionless prediction relationship between the reservoir pressure, radial distance, and production time in different seepage capacity regions of the target reservoir after pressure drive under the stress sensitivity condition.

[0048] Step 130: Based on the prediction relationship between the reservoir pressure, radial distance, and production time in different seepage capacity regions of the target reservoir after pressure drive under the stress sensitivity condition, and the production history data of the target reservoir, determine the average formation pressure of the reservoir after pressure drive in the target reservoir.

[0049] When the production history data of the target reservoir is known, the production history data of the target reservoir can be substituted into the prediction relationship between the reservoir pressure, radial distance, and production time in different seepage capacity regions of the target reservoir after pressure drive under the stress sensitivity condition to obtain the average formation pressure of the reservoir after pressure drive in the target reservoir.

[0050] In summary, through the physical model of the average formation pressure of the reservoir after pressure drive in the target reservoir, the control equation and constraint condition equation of the average formation pressure of the reservoir after pressure drive in the target reservoir expressed by the seepage partial differential control equation (i.e., the mathematical model of the average formation pressure of the reservoir after pressure drive in the target reservoir) are determined. Then, based on the control equation of the average formation pressure of the reservoir after pressure drive in the target reservoir and the constraint condition equation, the prediction relationship between the reservoir pressure, radial distance, and production time in different seepage capacity regions of the target reservoir after pressure drive under the stress sensitivity condition can be determined. Based on this, the average formation pressure of the reservoir after pressure drive in the target reservoir can be determined based on the prediction relationship between the reservoir pressure, radial distance, and production time in different seepage capacity regions of the target reservoir after pressure drive under the stress sensitivity condition.

[0051] It can be seen that the exemplary embodiments of the present disclosure can obtain the prediction relationship between the reservoir pressure, radial distance, and production time in different seepage capacity regions of the target reservoir after pressure drive under the stress sensitivity condition by mathematical modeling and solving the physical model of the average formation pressure of the reservoir after pressure drive in the target reservoir, and substitute the production history data of the target reservoir into the prediction relationship to determine the average formation pressure of the reservoir after pressure drive in the target reservoir, thereby obtaining an evaluation method for the average formation pressure for high-intensity injection and reservoir heterogeneity. Based on this, the method for determining the average formation pressure of the reservoir after pressure drive in the low-permeability tight oil reservoir provided by the exemplary embodiments of the present disclosure can provide theoretical guidance for the oilfield development plan of low-permeability tight reservoirs.

[0052] As a possible implementation, the physical model of the average formation pressure of the reservoir after pressure drive in the above target reservoir satisfies the following conditions: the reservoir physical property assumption conditions of the target reservoir, the well assumption conditions of the injection wells in the target reservoir, and the reservoir fluid assumption conditions of the target reservoir.

[0053] In some optional aspects, the reservoir physical property assumption conditions of the above target reservoir include: the simplified seepage field conditions formed during the pressure drive water injection process in the target reservoir, the horizontal homogeneity conditions of the reservoir in the target reservoir, and the initial pressure conditions at various positions in the reservoir of the target reservoir.

[0054] Exemplarily, the reservoir physical property assumption conditions satisfied by the physical model of the average formation pressure of the reservoir after pressure drive in the above target reservoir include:

[0055] (1) The seepage field formed during the pressure drive water injection process is simplified into two seepage zones, namely: Zone I - the elliptical transformation zone with stronger seepage ability; Zone II - the matrix zone (original formation area) with lower seepage ability;

[0056] (2) The reservoir is horizontally homogeneous and of equal thickness, and the initial pressures at various positions in the reservoir are the same.

[0057] The well assumption conditions of the injection wells in the above target reservoir include: the completion assumption conditions of the injection wells in the target reservoir and the production assumption conditions of the injection wells in the target reservoir.

[0058] Exemplarily, the well assumption conditions satisfied by the physical model of the average formation pressure of the reservoir after pressure drive in the above target reservoir include:

[0059] (1) The injection well completely penetrates the reservoir;

[0060] (2) The pressure drive water injection rate is constant.

[0061] The reservoir fluid assumption conditions of the above target reservoir include: the reservoir fluid influencing factor assumption conditions of the target reservoir and the reservoir fluid state assumption conditions of the target reservoir.

[0062] Exemplarily, the reservoir fluid assumption conditions satisfied by the physical model of the average formation pressure of the reservoir after pressure drive in the above target reservoir include:

[0063] (1) The influence of gravity and temperature on the fluid flow in the reservoir is ignored;

[0064] (2) During the pressure drive water injection process, it is mainly single-phase fluid flow and satisfies Darcy's law.

[0065] As a possible implementation, the above-mentioned control equation for the average formation pressure of the reservoir after pressure drive in the target reservoir includes: the partial differential control equation of reservoir seepage in the transformed area after pressure drive in the target reservoir and the partial differential control equation of reservoir seepage in the matrix area after pressure drive in the target reservoir.

[0066] The above-mentioned constraint condition equations include: the reservoir boundary condition equation in the transformed area after pressure drive in the target reservoir, the reservoir boundary condition equation in the matrix area after pressure drive in the target reservoir, the interface condition equation of the reservoir in the transformed area after pressure drive in the target reservoir, and the interface condition equation of the reservoir in the matrix area after pressure drive in the target reservoir.

[0067] In some optional aspects, Figure 2 The flowchart of the determination method of the real-domain prediction relationship between the reservoir pressure and the radial distance in different seepage capacity regions provided according to an exemplary embodiment of the present disclosure is shown. As Figure 2 shown, based on the above-mentioned control equation for the average formation pressure of the reservoir after pressure drive in the target reservoir and the constraint condition equations, determining the real-domain prediction relationship between the reservoir pressure and the radial distance in different seepage capacity regions may include:

[0068] Step 210: Make the control equation for the average formation pressure of the reservoir after pressure drive in the target reservoir and the constraint condition equations dimensionless to obtain the dimensionless pressure control equation and dimensionless constraint condition equation of the reservoir after pressure drive in the target reservoir.

[0069] In practical applications, a physical model of the calculation model of the average formation pressure of the reservoir after pressure drive in the target reservoir can be established according to the production history data such as the reservoir parameters, fluid parameters, and water injection parameters of the target reservoir. Then, using the conformal transformation method, the elliptical seepage field is converted into a circular seepage field, dimensionless variables are defined, and finally, the control equation for the average formation pressure of the reservoir after pressure drive in the target reservoir and the constraint condition equations are made dimensionless to obtain the dimensionless pressure control equation and dimensionless constraint condition equation of the reservoir after pressure drive in the target reservoir.

[0070] The above-mentioned dimensionless variables may include:

[0071] Dimensionless pressure:

[0072]

[0073] where: k is the permeability, μ is the fluid viscosity, B is the volume coefficient of the fluid, p i is the initial pressure of the reservoir, h is the reservoir thickness, p is the reservoir pressure, q is the water injection rate, and the subscripts 1 and 2 represent the inner area and the outer area respectively. The inner area refers to the internal area of the circular seepage field after conformal transformation (the area with stronger seepage capacity), and the outer area refers to the external area of the circular seepage field after conformal transformation (the area with weaker seepage capacity).

[0074] Dimensionless production time:

[0075]

[0076] Where: C t is the total compressibility, t is the production time, r w is the wellbore diameter, and φ is the reservoir porosity.

[0077] Dimensionless composite radius:

[0078]

[0079] Where: r w is the wellbore radius, and r f is the inner zone radius.

[0080] Dimensionless radial distance:

[0081]

[0082] Where: r is the dimensional radial distance.

[0083] Mobility ratio:

[0084]

[0085] Conductivity ratio:

[0086]

[0087] Dimensionless stress sensitivity coefficient:

[0088]

[0089] Where: α is the stress sensitivity coefficient, and B is the formation volume factor of the fluid.

[0090] Based on this, the above dimensionless pressure control equation can include Equation 8 and Equation 9:

[0091] The above dimensionless constraint condition equation can include:

[0092] Initial condition:

[0093] p 1D (r D , 0) = p 2D (r D , 0) = 0(10)

[0094] Outer boundary condition:

[0095]

[0096] Inner boundary condition:

[0097]

[0098] Interface conditions:

[0099] p 1D (r fD ,t D ) = p 2D (r fD ,t D )(13)

[0100]

[0101] Step 220: Based on the dimensionless pressure control equation and dimensionless constraint condition equation of the reservoir after pressure drive in the target reservoir, determine the dimensionless prediction relationship between the reservoir pressure and the radial distance in different seepage capacity regions.

[0102] In practical applications, the dimensionless pressure control equation and dimensionless constraint condition equation of the reservoir after pressure drive in the target reservoir can be simplified by the perturbation transformation method to eliminate the influence of non - linear terms. The simplified dimensionless pressure control equation of the reservoir after pressure drive in the target reservoir can include Formula 15 and Formula 16:

[0103]

[0104] The simplified dimensionless constraint condition equation can include:

[0105] Initial conditions:

[0106]

[0107] Outer boundary conditions:

[0108]

[0109] Inner boundary conditions:

[0110]

[0111] Interface conditions:

[0112]

[0113]

[0114] Where: are the dimensionless pressures in the inner and outer regions after perturbation transformation.

[0115] Then, through the Laplace transform technique and Bessel function theory, the dimensionless pressure control equation and dimensionless constraint condition equation of the reservoir after pressure drive in the target reservoir can be solved to obtain the dimensionless prediction relationship between the reservoir pressure and the radial distance in different seepage capacity regions.

[0116] The dimensionless pressure control equation in the Laplace space can include Equation 22 and Equation 23:

[0117]

[0118] The dimensionless constraint condition equation in the Laplace space can include:

[0119] Outer boundary condition:

[0120]

[0121] Interface condition:

[0122]

[0123] Inner boundary condition:

[0124]

[0125] Based on the Bessel function theory, the pressure solutions in the inner region and the outer region can be obtained. Among them, Equation 28 and Equation 29 are the dimensionless prediction relationships between the reservoir pressure and the radial distance in different seepage capacity regions:

[0126]

[0127] Where:

[0128]

[0129]

[0130] Where: I 0 , I 1 is the Bessel function of the first kind, K 0 , K 1 is the Bessel function of the second kind.

[0131] Step 230: Based on the dimensionless prediction relationship between the reservoir pressure and the radial distance in different seepage capacity regions, determine the real-domain prediction relationship between the reservoir pressure and the production time in different seepage capacity regions.

[0132] In practical applications, the Laplace inverse transform can be first performed on the production solutions of the average formation pressure control equation and the dimensionless constraint condition equation of the reservoir after pressure drive in the target reservoir in the Laplace domain, that is:

[0133]

[0134] Where: N is an empirical constant, generally taken as 8, 10, 12. By giving an i value and a t value, V is calculated. i The value of V, by calculating the value of V within each time step, the pressure solution of the control equation and the constraint equation of the average formation pressure of the reservoir after pressure drive in the real domain of the target reservoir can be obtained. Among them, Equation 30 is the real-domain prediction relationship between the reservoir pressure and the production time in different seepage capacity regions. i As a possible implementation,

[0135] As a possible implementation, Figure 3 shows a flowchart of a method for determining the average formation pressure of a reservoir after pressure drive of a target low-permeability tight oil reservoir provided according to an exemplary embodiment of the present disclosure. As Figure 3 shown, the above-mentioned prediction relationships between the pressure, radial distance, and production time of the reservoir in different seepage capacity regions after pressure drive of the target reservoir based on the stress-sensitive condition, and the production history data of the target reservoir are used to determine the average formation pressure of the reservoir after pressure drive of the target reservoir, including:

[0136] Step 310: Based on the prediction relationships between the pressure, radial distance, and production time of the reservoir in different seepage capacity regions after pressure drive of the target reservoir based on the stress-sensitive condition, and the production history data of the target reservoir, determine the pressure distribution data of the reservoir after pressure drive of the target reservoir.

[0137] In practical applications, after obtaining the real-domain prediction relationship between the reservoir pressure and the production time in different seepage capacity regions, considering the exact solution and the dimensionless zero-order perturbation solution approximation of the control equation and the constraint equation of the average formation pressure of the reservoir after pressure drive of the target reservoir affected by stress sensitivity, the dimensionless pressure solution of the target reservoir affected by stress sensitivity can be expressed as:

[0138]

[0139] Substitute the production history data such as the porosity, initial pressure, permeability, and fluid viscosity of the target reservoir into Equation 32, and the pressure distribution data of the reservoir after pressure drive of the target reservoir affected by stress sensitivity can be obtained.

[0140] Step 320: Based on the pressure distribution data of the reservoir after pressure drive of the target reservoir, determine the average formation pressure of the reservoir after pressure drive of the target reservoir.

[0141] In practical applications, according to the pressure distribution data of the reservoir after pressure drive of the target reservoir affected by stress sensitivity, the area-weighted method can be used to calculate the average formation pressure of the reservoir, and its formula can be:

[0142]

[0143] The present disclosure will be further described below by way of examples, but the present disclosure is not limited to the scope of the examples accordingly.

[0144] Example 1

[0145] The target reservoir is located in the Shanjiasi Oilfield, on the southwestern slope of the Lijin Sag in the northwestern part of the Dongying Sag in terms of tectonic position, adjacent to the Binxian Uplift in the west, the Chenjiazhuang Uplift in the north, and the Lijin Oil Generation Sag in the south. The main oil-bearing formation is the Shahejie Formation, with an oil-bearing area of 36.84 km 2 , the target reservoir has a buried depth of 2700 m, a porosity of 8.5%, a permeability of 3.7 mD, and a reservoir thickness of 9.5 m.

[0146] Step 1: Obtain basic parameter production history data such as geological parameters and fluid physical property parameters, as shown in Table 1 specifically.

[0147] Table 1 Geological parameter and fluid physical property parameter table

[0148]

[0149]

[0150] Step 2: Figure 4 The structural schematic diagram of the physical model of the target reservoir provided according to an exemplary embodiment of the present disclosure is shown.

[0151] As Figure 4 shown, a physical model of the calculation model of the average formation pressure of the reservoir after pressure drive of the target reservoir is established according to the above production history data. Among them, the assumption conditions of the physical model include: (1) The seepage field formed during the pressure drive water injection process is simplified into 2 seepage zones, namely: Zone I - the elliptical transformation zone with stronger seepage capacity; Zone II - the original formation area with lower seepage capacity; (2) The reservoir is horizontally homogeneous and of equal thickness, and the initial pressure at each position of the reservoir is the same; (3) The influence of gravity and temperature on the fluid flow in the reservoir is ignored; (4) The injection well completely penetrates the reservoir; (5) During the pressure drive water injection process, it is mainly single-phase fluid flow and satisfies Darcy's law; (6) The pressure drive water injection speed is constant.

[0152] Step 3: Figure 5A The schematic diagram of the elliptical seepage field before conformal transformation provided according to an exemplary embodiment of the present disclosure is shown, Figure 5B and the schematic diagram of the circular seepage field after conformal transformation provided according to an exemplary embodiment of the present disclosure is shown. As Figure 5A and Figure 5B shown, the elliptical seepage field of the physical model of the calculation model of the average formation pressure of the reservoir after pressure drive of the target reservoir is converted into a circular seepage field by using the conformal transformation method. After conformal transformation, the outer boundary of the transformed zone is mapped to a circle with a radius of r in the w-plane fThe outer boundary of the matrix region is mapped to a circle with a radius of r in the w-plane. e circle.

[0153] Step 4: Define dimensionless variables such as dimensionless time and dimensionless pressure, and obtain the dimensionless pressure control equation and dimensionless constraint condition equation for the reservoir after pressure drive in the target reservoir.

[0154] Dimensionless pressure:

[0155] where: k is the permeability, μ is the fluid viscosity, B is the fluid volume coefficient, p i is the initial pressure of the reservoir, h is the reservoir thickness, p is the reservoir pressure, q is the water injection rate, and the subscripts 1 and 2 represent the inner region and the outer region respectively. The inner region refers to the inner region of the circular seepage field after conformal transformation (i.e., the region of the circle with a radius of r f circle), and the outer region refers to the outer region of the circular seepage field after conformal transformation (i.e., the region outside the circle with a radius of r e circle excluding the circle with a radius of r f circle).

[0156] Dimensionless production time:

[0157] where: C t is the total compressibility, t is the production time, r w is the wellbore radius, and φ is the reservoir porosity.

[0158] Dimensionless composite radius:

[0159] where: r w is the wellbore radius, and r f is the inner region radius.

[0160] Dimensionless radial distance:

[0161] where: r is the dimensional radial distance.

[0162] Mobility ratio:

[0163] Conductive pressure coefficient ratio:

[0164] Dimensionless stress sensitivity coefficient:

[0165] where: α is the stress sensitivity coefficient, and B is the fluid volume coefficient.

[0166] Based on this, the dimensionless pressure control equation for the reservoir after pressure drive in the above target reservoir can include:

[0167]

[0168] The dimensionless constraint condition equations of the reservoir after pressure drive in the target reservoir can include:

[0169] Initial condition:

[0170] p 1D (r D , 0) = p 2D (r D , 0) = 0

[0171] Outer boundary condition:

[0172]

[0173] Inner boundary condition:

[0174]

[0175] Interface condition:

[0176] p 1D (r fD , t D ) = p 2D (r fD , t D )

[0177]

[0178] Step 5: Simplify the dimensionless pressure control equation and dimensionless constraint condition equation of the reservoir after pressure drive in the target reservoir by using the perturbation transformation method.

[0179] The simplified dimensionless pressure control equation of the reservoir after pressure drive in the target reservoir can include:

[0180]

[0181] The simplified dimensionless constraint condition equation can include:

[0182] Initial condition:

[0183]

[0184] Outer boundary condition:

[0185]

[0186] Inner boundary condition:

[0187]

[0188] Interface condition:

[0189]

[0190]

[0191] where: ζ 1D and ζ 2D are the dimensionless pressures in the inner and outer regions after perturbation transformation.

[0192] Step 6: Using Laplace transform technology and Bessel function theory, solve the dimensionless pressure control equation and dimensionless constraint condition equation of the reservoir after pressure drive in the target reservoir to obtain the dimensionless pressure solution of the target well.

[0193] The dimensionless pressure control equation in Laplace space can include:

[0194]

[0195] The dimensionless constraint condition equation in Laplace space can include:

[0196] Outer boundary condition:

[0197]

[0198] Interface condition:

[0199]

[0200] Inner boundary condition:

[0201]

[0202] Based on Bessel function theory, the pressure solutions in the inner and outer regions are obtained:

[0203]

[0204] where:

[0205]

[0206]

[0207] where: I 0 and I 1 are the Bessel functions of the first kind, and K 0 and K 1 are the Bessel functions of the second kind.

[0208] Step 7: Process the pressure solution in the Laplace domain using the Stehfest numerical inversion method to obtain the pressure solutions in the real domain for the control equation of the average formation pressure of the reservoir after pressure drive in the target reservoir and the dimensionless constraint condition equation. First, perform the Laplace inverse transform on the production rate solutions of the control equation of the average formation pressure of the reservoir after pressure drive in the target reservoir and the dimensionless constraint condition equation in the Laplace domain, that is:

[0209]

[0210] where: N is an empirical constant, generally taking 8, 10, or 12. By giving an i value and a t value, calculate the value of V i value. By calculating the value of V i value in each time step, the pressure solutions in the real domain for the control equation of the average formation pressure of the reservoir after pressure drive in the target reservoir and the constraint condition equation are obtained.

[0211] Step 8: If the exact solution and the dimensionless zero-order perturbation solution of the control equation of the average formation pressure of the reservoir after pressure drive in the target reservoir and the constraint condition equation considering the stress sensitivity effect are approximated, then the dimensionless pressure solution of the target well considering the stress sensitivity effect can be expressed as:

[0212]

[0213] Step 9: Based on the dimensionless pressure solution considering the stress sensitivity effect, the pressure distribution of the reservoir is obtained, and the area-weighted method is used to calculate the average formation pressure of the reservoir. Its formula can be:

[0214]

[0215] Figure 6 shows a schematic diagram of the pressure distribution of the injection well and the average formation pressure of the reservoir provided according to an exemplary embodiment of the present disclosure. As Figure 6 shown, the average formation pressure of the reservoir after pressure drive injection is 48.02 MPa. It should be understood that Figure 6 is drawn and calculated according to a production time of 30 days, and schematic diagrams of different production times can also be drawn according to actual situations.

[0216] The above mainly introduces the solution provided by the embodiments of the present disclosure from the perspective of the server. It can be understood that in order for the server to implement the above functions, it includes the corresponding hardware structure and / or software module for executing each function. Those skilled in the art should easily realize that, in combination with the units and algorithm steps of each example described in the embodiments disclosed herein, the present disclosure can be implemented in the form of hardware or a combination of hardware and computer software. Whether a certain function is executed in the way of hardware or computer software driving hardware depends on the specific application and design constraints of the technical solution. Professional technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the present disclosure.

[0217] The embodiments of the present disclosure can divide the functions of the server according to the above method examples. For example, each function module can be divided corresponding to each function, or two or more functions can be integrated into one processing module. The above integrated module can be implemented in the form of hardware or in the form of a software function module. It should be noted that the division of modules in the embodiments of the present disclosure is illustrative, only a logical function division, and there may be other division methods in actual implementation.

[0218] In the case of dividing each function module corresponding to each function, the exemplary embodiments of the present disclosure provide a device for determining the average formation pressure of a reservoir after pressure drive in a low-permeability tight oil reservoir. The device for determining the average formation pressure of a reservoir after pressure drive in a low-permeability tight oil reservoir can be a server or a chip applied to the server. Figure 7 The schematic block diagram of the function modules of the device for determining the average formation pressure of a reservoir after pressure drive in a low-permeability tight oil reservoir according to the exemplary embodiments of the present disclosure is shown. As Figure 7 shown, the device 700 for determining the average formation pressure of a reservoir after pressure drive in a low-permeability tight oil reservoir includes:

[0219] A first determination module 710, configured to determine a control equation and a constraint equation for the average formation pressure of the target reservoir after pressure drive expressed by a seepage partial differential equation based on a physical model of the average formation pressure of the target reservoir after pressure drive;

[0220] The first determination module 710 is further configured to determine a prediction relationship between the reservoir pressure, radial distance, and production time in different seepage capacity regions of the target reservoir after pressure drive under stress-sensitive conditions based on the control equation and the constraint equation for the average formation pressure of the target reservoir after pressure drive;

[0221] A second determination module 720, configured to determine the average formation pressure of the target reservoir after pressure drive based on the prediction relationship between the reservoir pressure, radial distance, and production time in different seepage capacity regions of the target reservoir after pressure drive under stress-sensitive conditions, and the production history data of the target reservoir.

[0222] As a possible implementation, the physical model of the average formation pressure of the reservoir after pressure drive in the above-mentioned target reservoir satisfies the reservoir physical property assumption conditions of the target reservoir, the well assumption conditions of the injection wells in the target reservoir, and the reservoir fluid assumption conditions of the target reservoir.

[0223] In some optional ways, the reservoir physical property assumption conditions of the above-mentioned target reservoir include: the simplified conditions of the seepage field formed during the pressure drive water injection process in the target reservoir, the horizontal homogeneity conditions of the reservoir in the target reservoir, and the initial pressure conditions at each position of the reservoir in the target reservoir;

[0224] The well assumption conditions of the injection wells in the target reservoir include: the completion assumption conditions of the injection wells in the target reservoir and the production assumption conditions of the injection wells in the target reservoir;

[0225] The reservoir fluid assumption conditions of the target reservoir include: the assumption conditions of the influencing factors of the reservoir fluid in the target reservoir and the assumption conditions of the reservoir fluid state in the target reservoir.

[0226] As a possible implementation, the physical model of the average formation pressure of the reservoir after pressure drive of the above-mentioned injection wells in the target reservoir is determined by the reservoir parameters of the target reservoir, the fluid parameters of the target reservoir, the water injection parameters of the target reservoir, and the well parameters of the injection wells in the target reservoir.

[0227] As a possible implementation, the above-mentioned control equation for the average formation pressure of the reservoir after pressure drive in the target reservoir includes: the partial differential control equation of reservoir seepage in the reformed area after pressure drive in the target reservoir and the partial differential control equation of reservoir seepage in the matrix area after pressure drive in the target reservoir;

[0228] The constraint condition equations include: the reservoir boundary condition equations in the reformed area after pressure drive in the target reservoir, the reservoir boundary condition equations in the matrix area after pressure drive in the target reservoir, as well as the interface condition equations of the reservoir in the reformed area after pressure drive in the target reservoir and the interface condition equations of the reservoir in the matrix area after pressure drive in the target reservoir.

[0229] As a possible implementation, the above-mentioned first determination module 710 is further configured to determine the real-domain prediction relationship between the reservoir pressure and the radial distance in different seepage capacity regions based on the control equation for the average formation pressure of the reservoir after pressure drive in the target reservoir and the constraint condition equations; and determine the dimensionless prediction relationship between the reservoir pressure, the radial distance, and the production time in different seepage capacity regions after pressure drive in the target reservoir based on the stress sensitivity condition and the real-domain prediction relationship between the reservoir pressure and the radial distance in different seepage capacity regions.

[0230] In some alternative embodiments, the apparatus for determining the average formation pressure of the reservoir after pressure drive in the above-mentioned low-permeability tight reservoir further includes an obtaining module 730, configured to nondimensionalize the control equation of the average formation pressure of the reservoir after pressure drive in the target reservoir and the constraint condition equation, so as to obtain the nondimensional pressure control equation and the nondimensional constraint condition equation of the reservoir after pressure drive in the target reservoir;

[0231] The first determination module 710 is further configured to determine a nondimensional prediction relationship between the reservoir pressure and the radial distance in different seepage capacity regions based on the nondimensional pressure control equation and the nondimensional constraint condition equation of the reservoir after pressure drive in the target reservoir; and determine a real-domain prediction relationship between the reservoir pressure and the production time in different seepage capacity regions based on the nondimensional prediction relationship between the reservoir pressure and the radial distance in different seepage capacity regions.

[0232] As a possible implementation manner, the above-mentioned second determination module 720 is further configured to determine the pressure distribution data of the reservoir after pressure drive in the target reservoir based on the prediction relationships of the pressure, radial distance, and production time of the reservoir in different seepage capacity regions after pressure drive in the target reservoir under stress-sensitive conditions, and the production history data of the target reservoir; and determine the average formation pressure of the reservoir after pressure drive in the target reservoir based on the pressure distribution data of the reservoir after pressure drive in the target reservoir.

[0233] Figure 8 FIG. shows a schematic block diagram of a chip according to an exemplary embodiment of the present disclosure. As Figure 8 shown, the chip 800 includes one or more (including two) processors 801 and a communication interface 802. The communication interface 802 can support the server to execute the data sending and receiving steps in the above-mentioned image processing method, and the processor 801 can support the server to execute the data processing steps in the above-mentioned image processing method.

[0234] Optionally, as Figure 8 shown, the chip 800 further includes a memory 803. The memory 803 can include a read-only memory and a random access memory, and provide operation instructions and data to the processor. A part of the memory can also include a non-volatile random access memory (NVRAM).

[0235] In some embodiments, as Figure 8As shown, the processor 801 executes corresponding operations by calling the operation instructions stored in the memory (the operation instructions can be stored in the operating system). The processor 801 controls the processing operations of any one of the terminal devices, and the processor can also be referred to as a central processing unit (CPU). The memory 803 can include a read-only memory and a random access memory, and provides instructions and data to the processor 801. A part of the memory 803 can also include NVRAM. For example, in an application, the memory, the communication interface, and the memory are coupled together through a bus system, where the bus system can include a power bus, a control bus, a status signal bus, etc. in addition to the data bus. However, for the sake of clear illustration, in Figure 8 all kinds of buses are labeled as the bus system 804.

[0236] The method disclosed in the above embodiments of the present disclosure can be applied to a processor or implemented by a processor. The processor may be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the above method can be completed by the integrated logic circuit in the hardware of the processor or the instructions in the form of software. The above processor can be a general-purpose processor, a digital signal processor (DSP), an ASIC, a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components. It can implement or execute the various methods, steps, and logic block diagrams disclosed in the embodiments of the present disclosure. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor, etc. The steps of the method disclosed in combination with the embodiments of the present disclosure can be directly embodied as being executed and completed by a hardware decoding processor, or executed and completed by a combination of the hardware and software modules in the decoding processor. The software module can be located in a mature storage medium in the art such as a random access memory, a flash memory, a read-only memory, a programmable read-only memory, or an electrically erasable programmable memory, a register, etc. The storage medium is located in the memory, and the processor reads the information in the memory and combines its hardware to complete the steps of the above method.

[0237] The exemplary embodiments of the present disclosure also provide an electronic device, including: at least one processor; and a memory communicatively connected to the at least one processor. The memory stores a computer program that can be executed by the at least one processor, and the computer program, when executed by the at least one processor, is used to cause the electronic device to execute the method according to the embodiments of the present disclosure.

[0238] The exemplary embodiments of the present disclosure also provide a non-transitory computer-readable storage medium storing a computer program, wherein the computer program, when executed by a processor of a computer, is configured to cause the computer to execute the method according to the embodiments of the present disclosure.

[0239] The exemplary embodiments of the present disclosure also provide a computer program product, including a computer program, wherein the computer program, when executed by a processor of a computer, is configured to cause the computer to execute the method according to the embodiments of the present disclosure.

[0240] Reference Figure 9 , the following will describe a block diagram of an electronic device 900 that can be a server or a client of the present disclosure, which is an example of a hardware device applicable to various aspects of the present disclosure. The electronic device is intended to represent various forms of digital electronic computer devices, such as, a laptop computer, a desktop computer, a workbench, a personal digital assistant, a server, a blade server, a mainframe computer, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as, a personal digital processor, a cellular phone, a smart phone, a wearable device, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present disclosure described and / or claimed herein.

[0241] As Figure 9 shown, the electronic device 900 includes a computing unit 901, which can execute various appropriate actions and processes according to the computer program stored in a read-only memory (ROM) 902 or the computer program loaded from a storage unit 908 into a random access memory (RAM) 903. In the RAM 903, various programs and data required for the operation of the electronic device 900 can also be stored. The computing unit 901, the ROM 902, and the RAM 903 are connected to each other through a bus 904. An input / output (I / O) interface 905 is also connected to the bus 904.

[0242] Multiple components in the electronic device 900 are connected to the I / O interface 905, including: an input unit 906, an output unit 907, a storage unit 908, and a communication unit 909. The input unit 906 can be any type of device capable of inputting information into the electronic device 900. The input unit 906 can receive input digital or character information and generate key signal inputs related to user settings and / or function controls of the electronic device. The output unit 907 can be any type of device capable of presenting information and can include, but is not limited to, a display, a speaker, a video / audio output terminal, a vibrator, and / or a printer. The storage unit 908 can include, but is not limited to, magnetic disks and optical disks. The communication unit 909 allows the electronic device 900 to exchange information / data with other devices via a computer network such as the Internet and / or various telecommunication networks and can include, but is not limited to, a modem, a network card, an infrared communication device, a wireless communication transceiver, and / or a chipset, such as a Bluetooth™ device, a WiFi device, a WiMax device, a cellular communication device, and / or the like.

[0243] The computing unit 901 can be various general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the computing unit 901 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. The computing unit 901 executes the various methods and processes described above. For example, in some embodiments, the methods of the exemplary embodiments of the present disclosure can be implemented as a computer software program tangibly embodied in a machine-readable medium, such as the storage unit 908. In some embodiments, part or all of the computer program can be loaded and / or installed onto the electronic device 900 via the ROM 902 and / or the communication unit 909. In some embodiments, the computing unit 901 can be configured to execute the methods of the exemplary embodiments of the present disclosure in any other suitable manner (e.g., by means of firmware).

[0244] The program code for implementing the methods of the present disclosure can be written in any combination of one or more programming languages. These program codes can be provided to a processor or controller of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when the program codes are executed by the processor or controller, the functions / operations specified in the flowcharts and / or block diagrams are implemented. The program codes can be executed entirely on the machine, partially on the machine, executed partially on the machine as an independent software package and partially on a remote machine, or executed entirely on a remote machine or server.

[0245] In the context of this disclosure, a machine-readable medium can be a tangible medium that can contain or store a program for use by or in connection with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0246] As used in this disclosure, the terms “machine-readable medium” and “computer-readable medium” refer to any computer program product, apparatus, and / or device (e.g., a disk, optical disk, memory, programmable logic device (PLD)) used to provide machine instructions and / or data to a programmable processor, including a machine-readable medium that receives machine instructions as a machine-readable signal. The term “machine-readable signal” refers to any signal used to provide machine instructions and / or data to a programmable processor.

[0247] In order to provide an interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or a trackball) by which the user can provide input to the computer. Other kinds of devices can also be used to provide an interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0248] The systems and techniques described herein can be implemented in a computing system including backend components (e.g., as a data server), or a computing system including middleware components (e.g., an application server), or a computing system including frontend components (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described herein), or a computing system including any combination of such backend components, middleware components, or frontend components. The components of the system can be interconnected to each other by digital data communication in any form or medium (e.g., a communication network). Examples of communication networks include: local area network (LAN), wide area network (WAN), and the Internet.

[0249] A computer system can include a client and a server. The client and the server are generally remote from each other and typically interact through a communication network. The client - server relationship is created by computer programs running on the respective computers and having a client - server relationship with each other.

[0250] In the above - mentioned embodiments, it can be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer programs or instructions. When the computer program or instructions are loaded and executed on a computer, the processes or functions described in the embodiments of the present disclosure are executed in whole or in part. The computer can be a general - purpose computer, a special - purpose computer, a computer network, a terminal, a user device, or other programmable devices. The computer program or instructions can be stored in a computer - readable storage medium, or transmitted from one computer - readable storage medium to another computer - readable storage medium. For example, the computer program or instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center in a wired or wireless manner. The computer - readable storage medium can be any available medium that a computer can access, or a data storage device such as a server or a data center integrating one or more available media. The available medium can be a magnetic medium, such as a floppy disk, a hard disk, or a magnetic tape; it can also be an optical medium, such as a digital video disc (DVD); or it can be a semiconductor medium, such as a solid - state drive (SSD).

[0251] Although the present disclosure has been described in connection with specific features and their embodiments, it will be apparent that various modifications and combinations can be made without departing from the spirit and scope of the present disclosure. Accordingly, the present specification and the drawings are merely illustrative descriptions of the present disclosure defined by the appended claims and are considered to cover any and all modifications, variations, combinations, or equivalents within the scope of the present disclosure. Obviously, those skilled in the art can make various changes and modifications to the present disclosure without departing from the spirit and scope of the present disclosure. Thus, if these modifications and variations of the present disclosure fall within the scope of the claims of the present disclosure and their equivalent technologies, the present disclosure is also intended to include these changes and modifications.

Claims

1. A method for determining the average formation pressure of a low-permeability tight oil reservoir after pressure flooding, characterized in that: The method comprises: Based on the physical model of the average formation pressure of the target oil reservoir after pressure drive, the control equation and constraint equation of the average formation pressure of the target oil reservoir after pressure drive expressed by the partial differential control equation of seepage are determined, wherein the physical model of the average formation pressure of the target oil reservoir after pressure drive of the water injection well is determined by the reservoir parameters of the target oil reservoir, the fluid parameters of the target oil reservoir, the water injection parameters of the target oil reservoir and the well parameters of the water injection well of the target oil reservoir; Based on the control equation of the average formation pressure of the target reservoir after pressure drive and the constraint condition equation, a prediction relationship between the reservoir pressure, radial distance and production time of different seepage capacity areas of the target reservoir after pressure drive under stress sensitive conditions is determined. The formula for calculating the prediction relationship includes formula (1), formula (2) and formula (3), wherein formula (1) is a real domain prediction relationship between the reservoir pressure and production time in different seepage capacity areas, and formula (2) is used to solve the variable V in formula (1). i , Formula (3) is the prediction relationship between reservoir pressure, radial distance and production time of different permeability areas after pressure drive of the target reservoir under stress-sensitive conditions; Where: D (t D ) is the pressure value of the average formation pressure calculation model of the low permeability tight oil reservoir after pressure flooding in the real domain, t D is the dimensionless production time, N is an empirical constant, generally 8, 10, 12, V i is the intermediate variable of the inverse Laplace transform, i represents the area with different seepage capacity, and takes 1 or 2, m is the summation index in the numerical inversion formula, and m takes values ​​from 1 to N, and p iD (r D ,t D ) is the dimensionless pressure value corresponding to the radial distance and production time of the target reservoir considering the influence of stress sensitivity, r D is the dimensionless radial distance, α D is the dimensionless stress sensitivity coefficient, ζ iD (r D ,u) is the production history data of the target reservoir considering the influence of stress sensitivity and the dimensionless pressure value of different permeability areas corresponding to the dimensionless radial distance; Based on the predicted relationship between the reservoir pressure, radial distance and production time of different seepage capacity areas of the target oil reservoir after pressure driving under the stress sensitive condition, and the production history data of the target oil reservoir, the average reservoir formation pressure of the target oil reservoir after pressure driving is determined, and the formula for calculating the average reservoir formation pressure of the target oil reservoir after pressure driving is formula (4); Where: is the average formation pressure of the target reservoir after pressure drive, p is the formation pressure of any point in the reservoir after pressure drive, A is the area selected in the reservoir for calculating the average pressure, r w is the well diameter.

2. The method for determining the average formation pressure of a low-permeability tight oil reservoir after pressure flooding according to claim 1, characterized in that: The physical model of the average formation pressure of the target oil reservoir after pressure drive satisfies: the reservoir physical property assumption conditions of the target oil reservoir, the well assumption conditions of the water injection wells of the target oil reservoir and the reservoir fluid assumption conditions of the target oil reservoir.

3. The method for determining the average formation pressure of a low-permeability tight oil reservoir after pressure flooding according to claim 2, characterized in that: The reservoir physical property assumptions of the target oil reservoir include: simplified seepage field conditions formed in the pressure-driven water injection process of the target oil reservoir, reservoir water level uniformity conditions of the target oil reservoir, and initial pressure conditions at various positions of the reservoir of the target oil reservoir; The well assumption conditions of the target oil reservoir water injection well include: the completion assumption conditions of the target oil reservoir water injection well and the production assumption conditions of the target oil reservoir water injection well; The reservoir fluid assumption conditions of the target oil reservoir include: reservoir fluid influencing factor assumption conditions of the target oil reservoir and reservoir fluid state assumption conditions of the target oil reservoir.

4. The method for determining the average formation pressure of a low-permeability tight oil reservoir after pressure flooding according to claim 1, characterized in that: The control equation of the average formation pressure of the target oil reservoir after pressure drive includes: the partial differential control equation of the reservoir seepage in the reformed area of ​​the target oil reservoir after pressure drive and the partial differential control equation of the reservoir seepage in the matrix area of ​​the target oil reservoir after pressure drive; The constraint condition equations include: a reservoir boundary condition equation for the reformed area of ​​the target oil reservoir after pressure drive, a reservoir boundary condition equation for the matrix area of ​​the target oil reservoir after pressure drive, an interface condition equation for the reservoir in the reformed area of ​​the target oil reservoir after pressure drive, and an interface condition equation for the reservoir in the matrix area of ​​the target oil reservoir after pressure drive.

5. The method for determining the average formation pressure of a low-permeability tight oil reservoir after pressure flooding according to claim 1, characterized in that: The prediction relationship between reservoir pressure, radial distance and production time of different permeability areas of the target oil reservoir after pressure drive based on the control equation of the average formation pressure of the target oil reservoir after pressure drive and the constraint condition equation is determined under stress-sensitive conditions, including: Based on the control equation of the average formation pressure of the target reservoir after pressure drive and the constraint condition equation, a real-domain prediction relationship between the reservoir pressure and the radial distance in different seepage capacity areas is determined; Based on the real domain prediction relationship between reservoir pressure and radial distance in different seepage capacity areas and stress sensitivity conditions, a dimensionless prediction relationship between reservoir pressure, radial distance and production time in different seepage capacity areas after pressure drive of the target reservoir under stress sensitivity conditions is determined.

6. The method for determining the average formation pressure of a low-permeability tight oil reservoir after pressure flooding according to claim 5, characterized in that: The method of determining the real domain prediction relationship between the reservoir pressure and the radial distance in different permeability regions based on the control equation of the average formation pressure of the target reservoir after pressure drive and the constraint condition equation includes: Non-dimensionalizing the reservoir average formation pressure control equation and the constraint condition equation after the pressure drive of the target oil reservoir to obtain the reservoir dimensionless pressure control equation and dimensionless constraint condition equation after the pressure drive of the target oil reservoir; Determine a dimensionless prediction relationship between reservoir pressure and radial distance in different permeability regions based on a dimensionless pressure control equation and a dimensionless constraint condition equation of the target oil reservoir after pressure drive; Based on the dimensionless prediction relationship between the reservoir pressure and radial distance in the different seepage capacity areas, a real domain prediction relationship between the reservoir pressure and production time in the different seepage capacity areas is determined.

7. The method for determining the average formation pressure of a low-permeability tight oil reservoir after pressure flooding according to any one of claims 1 to 6, characterized in that: The method of determining the average formation pressure of the target oil reservoir after pressure driving based on the prediction relationship between the pressure, radial distance and production time of the reservoir in different seepage capacity areas after pressure driving of the target oil reservoir under the stress sensitive condition and the production history data of the target oil reservoir comprises: Determine the pressure distribution data of the reservoir after pressure drive of the target oil reservoir based on the prediction relationship between the pressure, radial distance and production time of the reservoir in different seepage capacity areas after pressure drive of the target oil reservoir under the stress sensitive condition and the production history data of the target oil reservoir; Based on the pressure distribution data of the reservoir after the pressure drive of the target oil reservoir, the average formation pressure of the reservoir after the pressure drive of the target oil reservoir is determined.

8. A device for determining the average formation pressure of a low-permeability tight oil reservoir after pressure flooding, characterized in that: The device comprises: A first determination module is used to determine a control equation and a constraint condition equation for the average formation pressure of the target oil reservoir after pressure drive expressed by a partial differential control equation for seepage based on a physical model of the average formation pressure of the target oil reservoir after pressure drive, wherein the physical model of the average formation pressure of the target oil reservoir after pressure drive of the water injection well is determined by reservoir parameters of the target oil reservoir, fluid parameters of the target oil reservoir, water injection parameters of the target oil reservoir, and well parameters of the water injection well of the target oil reservoir; The first determination module is also used to determine the prediction relationship between the reservoir pressure, radial distance and production time of different seepage capacity areas of the target reservoir after pressure drive under stress sensitive conditions based on the reservoir average formation pressure control equation after pressure drive of the target reservoir and the constraint condition equation. The formula for calculating the prediction relationship includes formula (1), formula (2) and formula (3), wherein formula (1) is the real domain prediction relationship between the reservoir pressure and production time in different seepage capacity areas, and formula (2) is used to solve the variable V in formula (1). i , Formula (3) is the prediction relationship between reservoir pressure, radial distance and production time of different permeability areas after pressure drive of the target reservoir under stress-sensitive conditions; Where: D (t D ) is the pressure value of the average formation pressure calculation model of the low permeability tight oil reservoir after pressure flooding in the real domain, t D is the dimensionless production time, N is an empirical constant, generally 8, 10, 12, V i is the intermediate variable of the inverse Laplace transform, i represents the area with different seepage capacity, and takes 1 or 2, m is the summation index in the numerical inversion formula, and m takes values ​​from 1 to N, and p iD (r D ,t D ) is the dimensionless pressure value corresponding to the radial distance and production time of the target reservoir considering the influence of stress sensitivity, r D is the dimensionless radial distance, α D is the dimensionless stress sensitivity coefficient, ζ iD (r D ,u) is the production history data of the target reservoir considering the influence of stress sensitivity and the dimensionless pressure value of different permeability areas corresponding to the dimensionless radial distance; The second determination module is used to determine the average formation pressure of the target oil reservoir after pressure driving based on the predicted relationship between the reservoir pressure, radial distance and production time of different seepage capacity areas of the target oil reservoir after pressure driving under the stress sensitive condition, and the production history data of the target oil reservoir. The formula for calculating the average formation pressure of the target oil reservoir after pressure driving is formula (4); Where: is the average formation pressure of the target reservoir after pressure drive, p is the formation pressure of any point in the reservoir after pressure drive, A is the area selected in the reservoir for calculating the average pressure, r w is the well diameter.

9. An electronic device, characterized in that: The electronic device comprises: processor; and, A memory for storing programs; The program includes instructions, which, when executed by the processor, cause the processor to perform the method according to any one of claims 1 to 7.

10. A non-transitory computer-readable storage medium, characterized in that The non-transitory computer-readable storage medium stores computer instructions for causing the computer to execute the method according to any one of claims 1-7.

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