Method for predicting direct well productivity of gas storage under interwell interference and high injection and high production conditions

Abstract

The present disclosure provides a method for predicting the productivity of a direct well of a gas storage under the conditions of interwell interference and strong injection and production, comprising: obtaining basic data of a target formation of a natural gas underground gas storage; based on the basic data of the target formation of the natural gas underground gas storage and a direct well productivity prediction mathematical model, using the superposition principle to calculate the pressure superposition solution of the target direct well under the conditions of interwell interference and strong injection and production, and obtaining the bottom hole pressure solution of the target direct well of the direct well productivity prediction mathematical model; based on the bottom hole pressure solution, obtaining the production solution of the target direct well, and predicting the productivity of the target direct well in the natural gas underground gas storage. On the basis of the existing productivity prediction method, the superposition principle is used to solve the influence of interwell interference and strong injection and production on the calculation of the productivity of the direct well of the gas storage, improve the accuracy of the direct well productivity prediction mathematical model, reduce the error in the productivity calculation process, and accurately predict the productivity of the direct well of the gas storage.

Description

TECHNICAL FIELD

[0001] The present disclosure relates to the technical field of gas storage, and in particular to a method for predicting the productivity of a vertical well of a gas storage under the conditions of interwell interference and strong injection and production. BACKGROUND

[0002] Efficient utilization of natural gas resources is an important means, but its supply and demand has seasonal and regional characteristics, so large-scale energy storage technology is needed. Underground gas storage is one of the most effective energy storage methods, which can optimize the supply system, meet the needs of natural gas peak shaving, emergency and reserve, and solve the imbalance of gas consumption by adjusting injection and production time, so that natural gas resources can be reasonably utilized to obtain the best economic benefit. The productivity prediction method can help technical personnel accurately predict the productivity of the vertical well of the gas storage, which is of great significance to ensure the emergency peak shaving capacity of the gas storage. Since the underground gas storage is a typical multi-vertical well injection and production system, strong injection and production and periodic injection and production often occur during injection and production peak shaving, making the interwell interference phenomenon more prominent during the operation of the gas storage, which brings difficulties to the accurate productivity prediction of the vertical well of the gas storage.

[0003] Current productivity prediction methods for underground gas storage have achieved many obvious research results, but there are still many problems to be solved. For example, the existing productivity prediction method only considers single well, and ignores the influence of interwell interference and strong injection and production on the productivity of the vertical well of the gas storage, which is difficult to accurately predict the productivity of the vertical well of the gas storage. SUMMARY

[0004] According to an aspect of the present disclosure, a method for predicting the productivity of a vertical well of a gas storage under the conditions of interwell interference and strong injection and production is provided, comprising:

[0005] obtaining basic data of a target formation of a natural gas underground gas storage; the basic data of the target formation of the natural gas underground gas storage includes: geological parameters of the target formation, basic physical property parameters of injection and production gas, injection and production gas data of a target vertical well, and injection and production gas data of adjacent vertical wells, the adjacent vertical wells and the target vertical well are located in the same gas storage layer of the natural gas underground gas storage;

[0006] based on the basic data of the target formation of the natural gas underground gas storage and the vertical well productivity prediction mathematical model, the pressure superposition solution of the target vertical well under the conditions of interwell interference and strong injection and production is calculated by using the superposition principle, and the bottom hole pressure solution of the target vertical well of the vertical well productivity prediction mathematical model is obtained;

[0007] based on the bottom hole pressure solution, the production solution of the target vertical well is obtained, and the productivity of the target vertical well in the natural gas underground gas storage is predicted.

[0008] According to another aspect of the present disclosure, there is provided a device for predicting the productivity of a direct well of a gas storage under the conditions of interwell interference and strong injection and production, comprising:

[0009] a data acquisition module configured to acquire basic data of a target formation of a natural gas underground gas storage, wherein the basic data of the target formation of the natural gas underground gas storage comprises geological parameters of the target formation, basic physical parameters of injection and production of gas, injection and production data of a target direct well, and injection and production data of adjacent direct wells located in the same gas storage layer of the natural gas underground gas storage as the target direct well;

[0010] a pressure solution acquisition module configured to calculate, based on the basic data of the target formation of the natural gas underground gas storage and a direct well productivity prediction mathematical model, a pressure superposition solution of the target direct well under the conditions of interwell interference and strong injection and production by using the superposition principle, and to obtain a bottom hole pressure solution of the direct well productivity prediction mathematical model target direct well;

[0011] a productivity prediction module configured to obtain a production solution of the target direct well based on the bottom hole pressure solution, and to predict the productivity of the target direct well in the natural gas underground gas storage.

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

[0013] a processor; and

[0014] a memory storing a program;

[0015] wherein the program comprises instructions that, when executed by the processor, cause the processor to perform the method according to the exemplary 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 perform the method according to the exemplary embodiments of the present disclosure.

[0017] One or more technical solutions provided in the embodiments of the present disclosure acquire basic data of a target formation of a natural gas underground gas storage, and obtain a bottom hole pressure solution of a direct well productivity prediction mathematical model target direct well under the conditions of interwell interference and strong injection and production by using the superposition principle to consider the interference effect of adjacent direct wells of the gas storage on the target direct well based on the basic data of the target formation of the natural gas underground gas storage and the direct well productivity prediction mathematical model. Finally, a production solution of the direct well productivity prediction mathematical model target direct well under the conditions of interwell interference and strong injection and production is calculated based on the bottom hole pressure solution, and the productivity of the direct well of the underground gas storage is predicted.

[0018] Because the underground gas storage adopts the production mode of multiple straight wells for simultaneous injection and production, obvious well interference phenomenon occurs, and in the solving process of the straight well productivity prediction mathematical model, the superposition principle is used to consider the interference effect of adjacent straight wells of the gas storage on the target straight well, so as to obtain the bottom hole pressure solution of the target straight well of the straight well productivity prediction mathematical model under the conditions of considering well interference and strong injection and strong production. Finally, based on the bottom hole pressure solution, the yield solution of the straight well productivity prediction mathematical model is calculated, and the yield solution has considered the influence of well interference and strong injection and strong production, and is closer to the real injection and production situation of the straight well of the underground gas storage.

[0019] Therefore, the method of the example embodiment of the present disclosure can solve the technical problem that the existing productivity prediction method has a large error in productivity prediction calculation because the influence of well interference and strong injection and strong production is not considered, the straight well productivity prediction mathematical model of the example embodiment of the present disclosure can truly simulate the real situation of the underground gas storage, and the technical personnel can accurately predict the productivity of the straight well of the underground gas storage by using the method for predicting the productivity of the straight well of the gas storage under the conditions of well interference and strong injection and strong production. BRIEF DESCRIPTION OF DRAWINGS

[0020] In the following description of the example embodiment in conjunction with the drawings, more details, features and advantages of the present disclosure are disclosed, and in the drawings:

[0021] Figure 1 A flow chart of the method for predicting the productivity of the straight well of the gas storage under the conditions of well interference and strong injection and strong production according to the example embodiment of the present disclosure is shown;

[0022] Figure 2 A physical model of the method for predicting the productivity of the straight well of the gas storage under the conditions of well interference and strong injection and strong production according to the example embodiment of the present disclosure is shown;

[0023] Figure 3 A yield curve predicted by the method for predicting the productivity of the straight well of the gas storage under the conditions of well interference and strong injection and strong production according to the example embodiment of the present disclosure is shown;

[0024] Figure 4 A flow principle diagram of the method for predicting the productivity of the straight well of the gas storage under the conditions of well interference and strong injection and strong production according to the example embodiment of the present disclosure is shown;

[0025] Figure 5 A functional module schematic block diagram of the device for predicting the productivity of the straight well of the gas storage under the conditions of well interference and strong injection and strong production according to the example embodiment of the present disclosure is shown;

[0026] Figure 6 A schematic block diagram of a chip according to the example embodiment of the present disclosure is shown;

[0027] Figure 7A structural block diagram of an exemplary electronic device that can be used to implement embodiments of the present disclosure is shown. DETAILED DESCRIPTION

[0028] Embodiments of the present disclosure will be described in more detail with reference to the 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 being limited to the embodiments set forth herein, but rather the embodiments are provided so that the present disclosure can be more thoroughly and completely understood. It should be understood that the drawings and embodiments of the present disclosure are for exemplary purposes only and are not intended to limit the scope of protection of the present disclosure.

[0029] It should be understood that each of the steps recited in the method embodiments of the present disclosure can be performed in different orders and / or in parallel. In addition, the method embodiments can include additional steps and / or omit performing the steps shown. The scope of the present disclosure is not limited in this respect.

[0030] The term "comprising" and variations thereof as used herein are open-ended, that is, "including but not limited to". The term "based on" is "based, at least in part, 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". Related definitions are given throughout the detailed description. It should be noted that the concepts mentioned in the present disclosure are merely for distinguishing different apparatuses, modules or units, and do not limit the functions performed by these apparatuses, modules or units.

[0031] It should be noted that the modification of "one", "multiple" mentioned in the present disclosure is illustrative and not restrictive, and those skilled in the art should understand that unless the context clearly indicates otherwise, it should be understood as "one or more".

[0032] The productivity prediction method is an important means to predict the productivity of the gas storage vertical well, but the existing productivity prediction method has a large error when calculating the productivity, because the number of injection and production wells in the underground gas storage is large and the well spacing is small, and at the same time, due to the seasonal peak shaving demand, the production characteristics of strong injection and strong production are accompanied, which makes the well interference phenomenon more obvious. Since the existing productivity prediction method usually only considers a single well and ignores the influence of adjacent vertical wells, technicians cannot accurately predict the productivity of the gas storage vertical well by using the existing productivity prediction method.

[0033] Therefore, in order to accurately predict the productivity of the gas storage vertical well and ensure the safe operation of the gas storage, the embodiments of the present disclosure first provide a gas storage vertical well productivity prediction method for well interference and strong injection and strong production conditions, Figure 1A flow chart of a method for predicting the productivity of a direct well of a gas storage under the conditions of interwell interference and strong injection and production is shown. As shown in Figure 1 the method can include the following steps:

[0034] Step S110: Obtain basic data of a target formation of a natural gas underground gas storage. The basic data of the target formation of the natural gas underground gas storage can include geological parameters of the target formation, basic physical parameters of injection and production of gas, injection and production data of the target direct well, and injection and production data of adjacent direct wells, but is not limited thereto. The above-mentioned basic data of the target formation of the natural gas underground gas storage can be obtained by consulting microseismic data, drilling and completion data, and logging and geological data. Here, the adjacent direct well and the target direct well are located in the gas storage layer of the same natural gas underground gas storage.

[0035] For example, in one embodiment provided by the present disclosure, the target gas storage is located in the southern margin of the Junggar Basin in China, which is a near-east-west faulted anticline, about 20 km long from east to west, about 3.5 km wide from north to south, and about 180 m in structural closure height. The thicknesses of the reservoir and the direct cap rock are 120 m and 150 m, respectively, and the thickness of the regional cap rock is about 870 m. The lithology is mainly sandstone, which has good trap conditions. The basic parameters such as geological parameters and fluid physical parameters are shown in Table 1 as follows:

[0036] Table 1 Input parameter table for the method for predicting the productivity of a direct well of a gas storage under the conditions of interwell interference and strong injection and production

[0037] Parameter Value Reservoir thickness m 22 Porosity 0.2 Total compressibility MPa -1 ]] 4.35 x 10 -4 ]]> Initial pressure MPa 32.45 Permeability md 40.5 Mobility ratio 10 Dispersion ratio 10 Composite radius m 830 Skin factor -4.75 Wellbore storage coefficient m 3 / MPa 0.15 Viscosity mPa.s 0.02 Gas compressibility 0.019 Production speed m 3 / d]] 5 x 10 5 ]] Wellbore diameter m 0.1

[0038] Step S120: Obtain a productivity prediction physical model based on the conditions of interwell interference and strong injection and production. The productivity prediction physical model is obtained at least according to the basic data of the target formation of the natural gas underground gas storage and the positions of the direct wells in the gas storage; in actual application, a productivity prediction physical model considering the conditions of interwell interference and strong injection and production is constructed according to the parameters such as the geological parameters of the target formation, the basic physical parameters of injection and production of gas, and the positions of the direct wells in the gas storage.

[0039] Figure 2 A physical model of a method for predicting the productivity of a direct well of a gas storage under the conditions of interwell interference and strong injection and production is shown. As shown in Figure 2 a rectangular coordinate system is established for each direct well in the gas storage to describe the positions of the direct wells in the gas storage, thereby constructing a physical model of a method for predicting the productivity of a direct well of a gas storage under the conditions of interwell interference and strong injection and production. Wherein, 1, 2, 3, 4, 5, and 6 represent the numbers of the direct wells in the gas storage; r f is the inner zone radius of the gas storage direct well; the outer boundary is represented by a curve with nodes, and the boundary of the inner zone of the gas storage direct well is represented by a dashed line.

[0040] Step S130: obtaining a straight well productivity prediction mathematical model based on the control equation and the target assumption condition under the conditions of interwell interference and strong injection and strong production. The construction method of the straight well productivity prediction mathematical model includes the following steps:

[0041] Step S131: defining the target assumption condition. The target assumption condition includes at least one of the following: ① the average quality of the gas storage layer is equal in thickness, and the initial pressure of each position of the reservoir is the same; ② the effects of gravity and temperature on the gas flow in the gas storage are ignored; ③ the gas storage has a closed top and bottom interface, and the gas storage has an irregular outer boundary; ④ the straight well of the gas storage completely penetrates the reservoir; ⑤ the fluid in the reservoir is a single-phase slightly compressible fluid satisfying Darcy's law; and ⑥ the gas injection rate and the gas production rate of the straight well of the gas storage are constant. The target assumption condition is a prerequisite for constructing the straight well productivity prediction mathematical model.

[0042] Step S132: defining the dimensionless variable and establishing the control equation under the condition of strong injection and strong production, and establishing the straight well productivity prediction mathematical model under the conditions of interwell interference and strong injection and strong production based on the dimensionless variable. The straight well productivity prediction mathematical model refers to simplifying the strong injection and strong production problem of the gas storage into a mathematical relationship structure of two flow regions with different permeability or a mathematical expression of the relationship between the variables in a system by using mathematical language, and then modeling and solving. The dimensionless variable includes but is not limited to the dimensionless production time, the dimensionless pseudo-pressure, the dimensionless wellbore storage coefficient, and the dimensionless production.

[0043] For example, the dimensionless production time can be represented by the following formula (1):

[0044]

[0045] wherein k represents the reservoir permeability, μ represents the fluid viscosity, C t represents the total compressibility, h represents the reservoir thickness, t represents the production time, q sc represents the production under standard conditions, represents the reservoir porosity.

[0046] For example, the dimensionless pseudo-pressure of the gas storage can be represented by the following formulas (2) and (3):

[0047]

[0048]

[0049] wherein m represents the reservoir pseudo-pressure, m i represents the initial pseudo-pressure of the gas storage, k represents the reservoir permeability, T represents the reservoir temperature, D represents the dimensionless, and Tsc : indicates the temperature of the standard state, P sc : indicates the pressure of the standard state, n = 1 : indicates the inner zone of the gas storage straight well, n = 2 : indicates the outer zone of the gas storage straight well, P a : indicates an arbitrarily selected reference pressure, P : indicates pressure, μ : indicates gas viscosity, Z : indicates gas compressibility factor.

[0050] Exemplarily, the dimensionless production rate can be expressed by the following equation (4) :

[0051]

[0052] wherein, m wf : indicates the bottom hole pseudo pressure of the target straight well, m i : indicates the initial pseudo pressure of the gas storage, k : indicates the reservoir permeability, T : indicates the reservoir temperature, T sc : indicates the temperature of the standard state, P sc : indicates the pressure of the standard state, q sc : indicates the production rate under the standard condition, h : indicates the reservoir thickness.

[0053] Exemplarily, the dimensionless wellbore storage coefficient can be expressed by the following equation (5) :

[0054]

[0055] wherein, C : indicates the wellbore storage coefficient, L : indicates the reference length, C t : indicates the total compressibility factor, h : indicates the reservoir thickness, : indicates the reservoir porosity.

[0056] Exemplarily, the dimensionless well spacing can be expressed by the following equation (6) :

[0057]

[0058] wherein, d : indicates the distance from the adjacent straight well to the target straight well, L : indicates the reference length.

[0059] Exemplarily, the dimensionless mobility ratio can be expressed by the following equation (7) :

[0060]

[0061] wherein, k : indicates the reservoir permeability, u : indicates the Laplace variable, and subscripts 1 and 2 respectively represent the inner zone and the outer zone of the gas storage straight well.

[0062] Exemplarily, the dimensionless storage capacity ratio can be expressed by the following equation (8) :

[0063]

[0064] wherein, φ represents the reservoir porosity, C t : represents the total compressibility, the subscripts 1, 2 represent the inner region and the outer region of the gas storage vertical well, respectively.

[0065] Exemplarily, the dimensionless composite radius can be represented by the following formula (9):

[0066]

[0067] wherein, r w : represents the wellbore radius, r f : represents the inner region radius of the gas storage vertical well.

[0068] Exemplarily, the dimensionless distance can be represented by the following formula (10):

[0069]

[0070] wherein, r: represents the radial distance, x, y: represents the rectangular coordinate system distance, L: represents the reference length.

[0071] Exemplarily, the dimensionless rectangular coordinate system target vertical well position can be represented by the following formula (11):

[0072]

[0073] wherein, r w : represents the wellbore radius, x w , y w : represents the rectangular coordinate system target vertical well position, L: represents the reference length.

[0074] Exemplarily, in the present embodiment, the vertical well productivity prediction mathematical model used is a radial composite model, which is applied to the present embodiment to solve the problem of strong injection and strong production. Since the production solution in the real domain space is not easy to obtain, it is necessary to first obtain the production solution in the Laplace domain. Under the condition of strong injection and strong production, the control equation of the vertical well productivity prediction mathematical model can be represented by the following formulas (12) and (13):

[0075]

[0076]

[0077] wherein, u: represents the Laplace variable, t D : represents the dimensionless production time, : represents the dimensionless pseudo-pressure of the inner region of the gas storage vertical well, : represents the dimensionless pseudo-pressure of the outer region of the gas storage vertical well, M 12 : represents the dimensionless mobility ratio, ω12 : represents a dimensionless storage ratio, r D : represents a dimensionless radial distance, represents a variable in Laplace domain.

[0078] Step S133: defining the inner boundary condition, the inner-outer zone interface condition and the outer boundary condition of the mathematical model for predicting the productivity of the straight well.

[0079] Exemplarily, the inner boundary condition can be represented by the following formulas (14) and (15):

[0080]

[0081]

[0082] wherein u represents a Laplace variable, C D : represents a dimensionless wellbore storage coefficient, represents a dimensionless pseudo-pressure of the inner zone of the gas storage straight well, r D : represents a dimensionless radial distance, S represents a skin factor.

[0083] Exemplarily, the inner-outer zone interface condition can be represented by the following formulas (16) and (17):

[0084]

[0085]

[0086] wherein u represents a Laplace variable, C D : represents a dimensionless wellbore storage coefficient, represents a dimensionless pseudo-pressure of the inner zone of the gas storage straight well, r D : represents a dimensionless radial distance.

[0087] Exemplarily, the outer boundary condition can be represented by the following formula (18):

[0088]

[0089] wherein, a dimensionless pseudo-pressure of the outer zone of the gas storage straight well, r D : represents a dimensionless radial distance, t D : represents a dimensionless production time.

[0090] Step S140: Based on the basic data of the target formation of the natural gas underground storage and the mathematical model of the straight well productivity prediction, the pressure superposition solution of the target straight well under the conditions of well interference and strong injection and production is calculated by using the superposition principle, and the bottom hole pressure solution of the target straight well in the mathematical model of the straight well productivity prediction under the conditions of well interference and strong injection and production is obtained. Among them, the dimensionless bottom hole pressure solution of the target straight well is obtained by using Laplace transform method to solve the mathematical model of the straight well productivity prediction, and the pressure interference of the adjacent straight well to the target straight well is considered by using the superposition principle, and finally the bottom hole pressure solution of the target straight well in the mathematical model of the straight well productivity prediction under the conditions of well interference and strong injection and production is obtained.

[0091] Step S141: The bottom hole pressure solution of the target straight well in the mathematical model of the straight well productivity prediction under the Laplace domain is calculated.

[0092] For example, the bottom hole pressure solution of the target straight well considering the wellbore storage effect and the skin factor can be represented by the following formula groups (19)-(21):

[0093]

[0094]

[0095]

[0096] Wherein, I0, I1: represent the first kind of virtual quantity Bessel function, K0, K1: represent the second kind of Bessel function, R D And KI: represent the intermediate variable, u: represent the Laplace variable, M 12 : represent the dimensionless mobility ratio, ω 12 : represent the dimensionless storage ratio, r D : represent the dimensionless radial distance, C D : represent the dimensionless wellbore storage coefficient, r fD : represent the dimensionless composite radius.

[0097] Step S142: The pressure solution of the adjacent straight well in the mathematical model of the straight well productivity prediction under the Laplace domain is calculated.

[0098] For example, the pressure solution of the adjacent straight well can be represented by the following formula groups (22)-(23):

[0099]

[0100]

[0101] Wherein, j: represents the serial number of the adjacent straight well, represents the injection and production capacity of the adjacent straight well, r D,j: represents the dimensionless distance from other adjacent vertical wells to the target vertical well in the multi-well system, x wD wD : both represent the position of the target vertical well in the dimensionless rectangular coordinate system, x D，j D，j : represents the position of the adjacent well in the gas storage in the dimensionless rectangular coordinate system.

[0102] Step S143: calculating the pressure interference of the adjacent vertical wells on the target vertical well by using the superposition principle to obtain the pressure superposition solution of the target vertical well.

[0103] Illustratively, the influence of the adjacent vertical wells on the target vertical well in the multi-well system is considered by using the superposition principle, and this step can be represented by the following formula (24):

[0104]

[0105] wherein j: represents the serial number of the adjacent vertical well, N m : represents the total number of vertical wells in the multi-well system of the gas storage, : represents the injection and production capacity of the adjacent vertical well, r D,j : represents the dimensionless distance from other adjacent vertical wells to the target vertical well in the multi-well system, K0: represents the second kind of Bessel function, and u: represents the Laplace variable.

[0106] Step S144: calculating the bottom hole pressure solution of the target vertical well in the mathematical model for predicting the productivity of the vertical well of the gas storage under the conditions of interwell interference and strong injection and production.

[0107] Illustratively, the bottom hole pressure solution of the target vertical well in the Laplace domain under the conditions of interwell interference and strong injection and production in the multi-well system of the gas storage can be represented by the following formula (25):

[0108]

[0109] wherein : represents the pressure superposition solution of the pressure interference of the adjacent vertical wells on the target vertical well, : represents the bottom hole pressure solution of the target vertical well under the conditions of considering the wellbore storage effect and the skin factor.

[0110] Step S150: obtaining the production solution of the target vertical well based on the bottom hole pressure solution to predict the productivity of the target vertical well in the underground gas storage.

[0111] Illustratively, the production solution of the target vertical well is calculated based on the bottom hole pressure solution of the target vertical well in the Laplace domain under the conditions of interwell interference and strong injection and production, and this step can be represented by the following formula (26):

[0112]

[0113] ​​wherein, represents the solution of the bottom hole pressure of the target vertical well in the Laplace domain under the condition of interwell interference and strong injection and production in the multi-well system of the gas storage, and u represents the Laplace variable.

[0114] The Stehfest numerical inversion method is used to obtain the production solution of the vertical well in the Laplace domain.

[0115] For example, the production solution of the vertical well in the Laplace domain is first subjected to the inverse Laplace transform. Then, the value of V i is calculated by giving an i value and a t value. The production solution of the underground gas storage in the real domain is obtained by calculating the value of V i at each time step. This step can be represented by the following formula groups (27)-(29):

[0116]

[0117]

[0118]

[0119] wherein N represents an empirical constant, generally 8, 10, 12, represents the production solution of the target vertical well, u represents the Laplace variable, i represents the cycle variable, and l represents the cycle variable.

[0120] Figure 3 The production curve predicted by the vertical well productivity prediction method for the interwell interference and strong injection and production conditions of the gas storage according to the exemplary embodiments of the present disclosure is shown. As shown in FIG. 6, the production curve of the target vertical well of the gas storage under the interwell interference and strong injection and production conditions is plotted with the production time as the horizontal coordinate and the daily production as the vertical coordinate by using the production solution of the target vertical well in the real domain. Figure 3

[0121] Based on the above embodiments, in another embodiment provided by the present disclosure, a vertical well productivity prediction method for the interwell interference and strong injection and production conditions of the gas storage is also provided, Figure 4 The flow principle diagram of the vertical well productivity prediction method for the interwell interference and strong injection and production conditions of the gas storage according to the exemplary embodiments of the present disclosure is shown. As shown in FIG. 7, the method comprises the following steps: Figure 4

[0122] Step 410: Obtain the basic data of the target formation of the underground gas storage.

[0123] ​​In the exemplary embodiments of the present disclosure, the basic data of the target formation of the natural gas underground storage reservoir includes, but is not limited to, geological parameters of the target formation, basic physical parameters of injection and production of gas, injection and production data of the target vertical well and injection and production data of adjacent vertical wells, and the adjacent vertical wells and the target vertical well are located in the same gas storage layer of the natural gas underground storage reservoir.

[0124] Step 420: based on the basic data of the target formation of the natural gas underground storage reservoir and the vertical well productivity prediction mathematical model, the pressure superposition solution of the target vertical well under the conditions of well interference and strong injection and production is calculated by using the superposition principle, and the bottom hole pressure solution of the target vertical well of the vertical well productivity prediction mathematical model is obtained.

[0125] Step 430: based on the bottom hole pressure solution, the production solution of the target vertical well is obtained, and the productivity of the target vertical well in the natural gas underground storage reservoir is predicted.

[0126] In one or more of the technical solutions provided in the embodiments of the present disclosure, the basic data of the target formation of the natural gas underground storage reservoir is obtained, based on the basic data of the target formation of the natural gas underground storage reservoir and the vertical well productivity prediction mathematical model, the interference effect of adjacent vertical wells of the storage reservoir on the target vertical well is considered by using the superposition principle, the bottom hole pressure solution of the target vertical well of the vertical well productivity prediction mathematical model under the conditions of well interference and strong injection and production is obtained. Finally, based on the bottom hole pressure solution of the target vertical well of the vertical well productivity prediction mathematical model under the conditions of well interference and strong injection and production, the production solution of the target vertical well is calculated, and the productivity of the vertical well of the underground storage reservoir is predicted.

[0127] Experiments prove that, compared with the existing productivity prediction method which does not consider well interference, the method for predicting the productivity of the vertical well of the storage reservoir under the conditions of well interference and strong injection and production in the exemplary embodiments of the present disclosure can solve the problem that the existing productivity prediction method has a large error in productivity prediction calculation due to not considering the influence of well interference, and accurately predicts the productivity of the vertical well of the underground storage reservoir.

[0128] The above mainly introduces the solutions provided by the embodiments of the present disclosure from the perspective of method. It can be understood that, in order to realize the above functions, the device corresponding to the method of the exemplary embodiments of the present disclosure 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 the examples described in the embodiments disclosed herein, the present disclosure can be realized in the form of hardware or a combination of hardware and computer software. Whether a certain function is realized by 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 realize the described functions for each specific application, but such implementation should not be considered beyond the scope of the present disclosure.

[0129] 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 according to each function, or two or more functions can be integrated into one processing module. The 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 the modules in the embodiments of the present disclosure is illustrative, and is only a logical function division. When actually implemented, another division method can be used.

[0130] In the case of dividing each function module according to each function, the exemplary embodiments of the present disclosure provide a device for predicting the productivity of a direct well of a gas storage under interwell interference and strong injection and production conditions. The device for predicting the productivity of the direct well of the gas storage can be a server or a chip applied to the server. Figure 5 A functional module schematic block diagram of the device for predicting the productivity of the direct well of the gas storage under interwell interference and strong injection and production conditions according to the exemplary embodiments of the present disclosure is shown. As shown in the figure, the device 500 for predicting the productivity of the direct well includes: Figure 5

[0131] The data acquisition module 510 is configured to acquire basic data of a target formation of a natural gas underground gas storage. The basic data of the target formation of the natural gas underground gas storage includes geological parameters of the target formation, basic physical property parameters of injection and production of gas, target direct well injection and production data, and injection and production data of adjacent direct wells. The adjacent direct wells and the target direct well are located in the same gas storage layer of the natural gas underground gas storage.

[0132] The pressure solution acquisition module 520 is configured to calculate, based on the basic data of the target formation of the natural gas underground gas storage and a direct well productivity prediction mathematical model, a pressure superposition solution of the target direct well under the interwell interference and strong injection and production conditions by using the superposition principle, and obtain a bottom hole pressure solution of the target direct well of the direct well productivity prediction mathematical model.

[0133] The productivity prediction module 530 is configured to obtain a production solution of the target direct well based on the bottom hole pressure solution, and predict the productivity of the target direct well in the natural gas underground gas storage, including:

[0134]

[0135] wherein, represents the bottom hole pressure solution of the target direct well in the Laplace domain considering the interwell interference and strong injection and production in the multi-well system of the gas storage, and u represents a Laplace variable.

[0136] The pressure solution acquisition module 520 is further configured to acquire a productivity prediction physical model based on the interwell interference and strong injection and production conditions. The productivity prediction physical model is obtained according to at least the basic data of the target formation of the natural gas underground gas storage and the positions of the direct wells in the natural gas underground gas storage.​

[0137] The control equation of the straight well productivity prediction mathematical model under the conditions of interwell interference and strong injection and production is established, and the straight well productivity prediction mathematical model under the conditions of interwell interference and strong injection and production is obtained based on the control equation and target assumption conditions;

[0138] The target assumption conditions include at least one of the following: the average quality of the gas storage layer is equal in thickness, the initial pressure of each position of the reservoir is the same, the effects of gravity and temperature on the gas flow in the gas storage are ignored, the gas storage has a closed top and bottom interface, and the gas storage has an irregular outer boundary, the straight well of the gas storage completely penetrates the reservoir, the gas flow in the reservoir satisfies Darcy's law, and the gas injection rate and the gas production rate of the straight well of the gas storage are constant.

[0139] The pressure solution acquisition module 520 is further configured to establish a control equation of the straight well productivity prediction mathematical model under the conditions of interwell interference and strong injection and production.

[0140]

[0141]

[0142] wherein, u: represents a Laplace variable, t D : represents a dimensionless production time, represents a dimensionless pseudo-pressure in an inner zone of the gas storage straight well, represents a dimensionless pseudo-pressure in an outer zone of the gas storage straight well, M 12 : represents a dimensionless mobility ratio, ω 12 : represents a dimensionless storage capacity ratio, r D : represents a dimensionless radial distance, represents a variable in the Laplace domain.

[0143] The pressure solution acquisition module 520 is further configured to calculate the pressure solution of the adjacent straight well.

[0144]

[0145]

[0146] wherein, j: represents an adjacent straight well serial number, represents injection and production of the adjacent straight well, r D,j : represents a dimensionless distance from other adjacent straight wells to the target straight well in the multi-well system, x wD , y wD : both represent positions of the target straight well in a dimensionless rectangular coordinate system, x D，j , y D，j : both represent positions of the adjacent well in the gas storage in a dimensionless rectangular coordinate system;

[0147] The pressure interference of the adjacent vertical wells on the target vertical well is calculated using the superposition principle, and the pressure superposition solution of the target vertical well is obtained:

[0148]

[0149] Where j: represents the ordinal number of the adjacent vertical well, N m : Indicates the total number of vertical wells in a multi-vertical-well system of a gas storage facility. The gas injection and production volume of adjacent vertical wells, r D,j : represents the dimensionless distance from other adjacent vertical wells to the target vertical well in a multi-well system, K0: represents the second kind of Bessel function, u: represents the Laplace variable;

[0150] Calculate the bottom hole pressure solution of the target vertical well in the mathematical model for predicting the production capacity of the vertical well under the conditions of inter-well interference and intensive injection and production:

[0151]

[0152] in, This represents the superposition solution of pressures that cause pressure disturbance to the target vertical well from adjacent vertical wells. This represents the bottom hole pressure solution for a target vertical well considering wellbore storage effect and skin coefficient conditions.

[0153] Figure 6 A schematic block diagram of a chip according to an exemplary embodiment of the present disclosure is shown. Figure 6 As shown, the chip 600 includes one or more (including two) processors 601 and a communication interface 602. The communication interface 602 can support the server in performing the data transmission and reception steps in the above method, and the processor 601 can support the server in performing the data processing steps in the above method.

[0154] Optional, such as Figure 6 As shown, the chip 600 also includes a memory 603, which may include read-only memory and random access memory, and provides operation instructions and data to the processor. A portion of the memory may also include non-volatile random access memory (NVRAM).

[0155] In some implementations, such as Figure 6As shown, the processor 601 executes various processing operations according to its computer program instructions. The processor 601 can also include a central processing unit (CPU), a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field programmable gate array (FPGA), or other processing logic that can constitute a processing unit. The memory 603 can include read-only memory (ROM) and random access memory (RAM) that can store computer program instructions and data for the processor 601. A portion of the memory 603 can also include non-volatile memory, such as a non-volatile memory express (NVME). For example, the memory, the communication interface, and the bus system can be coupled together via a bus system, which can include a data bus, a power bus, a control bus, and a state signal bus, etc. For clarity, however, the various buses are represented as the bus system 604 in the Figure 6

[0156] The method disclosed in the embodiments of the present disclosure can be applied to a processor or implemented by the processor. The processor can be an integrated circuit chip with a signal processing capability. In the implementation process, the steps of the above method can be completed by hardware integrated logic circuit or software form of instructions in the processor. The processor mentioned above can be a general processor, a digital signal processor (DSP), an ASIC, a field programmable gate array (FPGA) or other programmable logic device, a discrete gate or transistor logic device, a discrete hardware component. The disclosed methods, steps and logic block diagrams in the embodiments of the present disclosure can be implemented or executed. The general processor can be a microprocessor or the processor can also be any conventional processor. The steps of the method disclosed in conjunction with the embodiments of the present disclosure can be directly embodied as a hardware code processor for execution, or a combination of hardware and software modules in the code processor. The software module can be located in a random access memory, a flash memory, a read only memory, a programmable read only memory or an electrically erasable programmable memory, a register, or other mature storage medium in the art. The storage medium is located in the memory, and the processor reads the information in the memory and combines the hardware to complete the steps of the above method.

[0157] The exemplary embodiments of the present disclosure also provide an electronic device, including at least one processor, and a memory connected with the at least one processor in communication. The memory stores a computer program capable of being executed by the at least one processor, and the computer program, when executed by the at least one processor, is configured to cause the electronic device to perform the method according to the embodiments of the present disclosure.

[0158] ​The exemplary embodiments of the present disclosure further provide a non-transitory computer readable storage medium storing a computer program, wherein the computer program, when executed by a processor of a computer, causes the computer to perform the method according to the embodiments of the present disclosure.

[0159] The exemplary embodiments of the present disclosure further provide a computer program product comprising a computer program, wherein the computer program, when executed by a processor of a computer, causes the computer to perform the method according to the embodiments of the present disclosure.

[0160] Reference Figure 7 will now be described, which is an example of a hardware device that can be applied to various aspects of the present disclosure. The electronic device is intended to represent a wide variety of digital electronic computer devices such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computer devices. The electronic device can also represent a variety of mobile devices such as personal digital processors, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown here, their connections and relationships, and their functions, are meant to be examples only, and are not meant to limit implementations of the present disclosure described and / or claimed in this document.

[0161] As Figure 7 shown, the electronic device 700 includes a computing unit 701 that can perform various appropriate actions and processes in accordance with a computer program stored in a read-only memory (ROM) 702 or a computer program loaded into a random access memory (RAM) 703 from a storage unit 708. In the RAM 703, various programs and data required for the operation of the device 700 can also be stored. The computing unit 701, the ROM 702, and the RAM 703 are connected to each other through a bus 704. An input / output (I / O) interface 705 is also connected to the bus 704.

[0162] A plurality of components in the electronic device 700 are connected to the I / O interface 705, including: an input unit 706, an output unit 707, a storage unit 708, and a communication unit 709. The input unit 706 can be any type of device that can input information to the electronic device 700, and can receive inputted digital or character information, and generate key signal inputs related to user settings and / or function controls of the electronic device. The output unit 707 can be any type of device that can present 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 708 can include, but is not limited to, a magnetic disk, an optical disk. The communication unit 709 allows the electronic device 700 to exchange information / data with other devices through 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.

[0163] The computing unit 701 can be various general and / or special purpose processing components having processing and computing capabilities. Some examples of the computing unit 701 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various specialized artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The computing unit 701 performs various methods and processes described above. Each of the various methods described above can be implemented as a computer software program tangibly embodied in a machine-readable medium, such as the storage unit 708. In some embodiments, part or all of the computer program can be loaded and / or installed onto the electronic device 700 via the ROM 702 and / or the communication unit 709.

[0164] Program code for carrying out methods of the present disclosure can be written in any combination of one or more programming languages. The program code can be provided to a processor or controller of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the program code, when executed by the processor or controller, produces the functions / operations specified in the flowcharts and / or the block diagrams. The program code can be executed entirely on a machine, partially on a machine, partially on a machine and partially on a remote machine or entirely on a remote machine or server.

[0165] In the context of this disclosure, a machine-readable medium can be a tangible medium that contains or stores a program for use by or in connection with an instruction execution system, apparatus, or device. The 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 an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of the machine-readable storage medium will include one or more lines of electrical connections, portable computer disks, hard disk drives, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or Flash memory), optical fibers, portable compact disc read-only memories (CD-ROMs), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0166] 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., magnetic discs, optical disks, memory, Programmable Logic Devices (PLDs)) 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 that can be used to provide machine instructions and / or data to a programmable processor.

[0167] To provide for interaction with a user, the systems and techniques described here 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 be used to provide for interaction with a user as well; for example, 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, speech, or tactile input.

[0168] The systems and techniques described here can be implemented in a computing system that includes a back end component, e.g., as a data server, or that includes a middleware component, e.g., an application server, or that includes a front end component, 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 here, or any combination of such back end, middleware, or front end components. The components of the system can be interconnected by any form or medium of digital data communication, e.g., a communication network. Examples of communication networks include a local area network (LAN), a wide area network (WAN), and the Internet.

[0169] The computer system can include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other.

[0170] In the embodiments described above, all or some of the steps can be implemented by software, hardware or firmware, or any combination thereof. When implemented by software, all or some of the steps can be implemented by one or more computer program or instructions. When loaded on a computer, the computer program or instructions can execute on the computer and perform all or some of the steps described in the embodiments of the present disclosure. The computer can be a general purpose computer, a special purpose computer, a computer network, a terminal, a user device, or other programmable apparatus. The computer program or instructions can be stored in a computer readable storage medium or transmitted from one computer readable storage medium to another, e.g., from a website, a computer, a server or a data center to another website, computer, server or data center through a wired or wireless way. The computer readable storage medium can be any available medium or a combination of one or more of the available media that is accessible by a computer. The available medium can be a magnetic medium, e.g., a floppy diskette, a hard disk, a magnetic tape; an optical medium, e.g., a compact disk (CD), a digital video disk (DVD); a semiconductor medium, e.g., a solid state disk (SSD).

[0171] Although the present disclosure has been described in connection with certain specific features and embodiments thereof, it is to be understood that it is provided as an exemplification of the principles of the present disclosure and the features set forth herein are intended to be illustrative rather than limiting, and that numerous modifications and variations therein can be expected by those skilled in the art. Accordingly, it should be understood that the description and drawings are illustrative of the present disclosure and are not intended to be limiting. It should be understood that various changes can be made to the implementations described and the embodiments presented herein without departing from the spirit and scope of the present disclosure. It is intended that all such changes be considered as within the scope of the present disclosure.

Claims

1. A method for predicting the production capacity of vertical wells in gas storage facilities under conditions of inter-well interference and intensive injection and extraction, characterized in that, include: Obtain basic data on the target formation of the underground natural gas storage facility; The basic data of the target formation of the underground natural gas storage facility include: geological parameters of the target formation, basic physical property parameters of gas injection and production, gas injection and production data of the target vertical well and the gas injection and production data of adjacent vertical wells, wherein the adjacent vertical wells and the target vertical well are located in the same gas storage layer of the underground natural gas storage facility; Based on the basic data of the target formation of the underground natural gas storage facility and the mathematical model for predicting the production capacity of vertical wells, the pressure superposition solution of the target vertical well under the conditions of inter-well interference and strong injection and strong production is calculated using the superposition principle, and the bottom hole pressure solution of the target vertical well in the mathematical model for predicting the production capacity of vertical wells is obtained. Based on the bottom hole pressure solution, the production solution of the target vertical well is obtained, and the production capacity of the target vertical well in the underground natural gas storage is predicted. The method for constructing the mathematical model for predicting the production capacity of vertical wells includes: A physical model for production capacity prediction based on inter-well interference and strong injection and extraction conditions is obtained. The physical model for production capacity prediction is obtained at least based on the basic data of the target formation of the underground natural gas storage and the location of each vertical well in the underground natural gas storage. The control equations of the vertical well production capacity prediction mathematical model under the conditions of inter-well interference and strong injection and extraction are established. Based on the control equations and the target assumptions, the vertical well production capacity prediction mathematical model under the conditions of inter-well interference and strong injection and extraction is obtained. The governing equations for establishing the mathematical model of vertical well productivity prediction under inter-well interference and intensive injection / production conditions include: Where u represents the Laplace variable, t d : Indicates dimensionless production time. This represents the dimensionless pseudo-pressure within the vertical well of the gas storage facility. M represents the dimensionless pseudo-pressure in the outer zone of the gas storage vertical well. 12 : Represents the dimensionless mobility ratio, ω 12 : Represents the dimensionless storage capacity ratio, r D : Indicates dimensionless radial distance, Represents a variable in the Laplace domain; The calculation of the pressure superposition solution of the target vertical well under the conditions of inter-well interference and strong injection and production using the superposition principle, and the obtaining of the bottom hole pressure solution of the target vertical well in the mathematical model for predicting the vertical well production capacity, includes: Calculate the pressure solution for the adjacent vertical wells: Where j: represents the ordinal number of the adjacent vertical well. The gas injection and production volume of adjacent vertical wells, r D,j : Represents the dimensionless distance from other adjacent vertical wells to the target vertical well in a multi-well system, x wD y wD Both x and y represent the position of the target vertical well in a dimensionless rectangular coordinate system. D，j y D，j : Both represent the positions of adjacent wells in a gas storage facility in a dimensionless rectangular coordinate system; The pressure interference of the adjacent vertical wells on the target vertical well is calculated using the superposition principle, and the pressure superposition solution of the target vertical well is obtained: Where j: represents the ordinal number of the adjacent vertical well, N m : Indicates the total number of vertical wells in a multi-vertical-well system of a gas storage facility. The gas injection and production volume of adjacent vertical wells, r D,j : represents the dimensionless distance from other adjacent vertical wells to the target vertical well in a multi-well system, K0: represents the Bessel function of the second kind, u: represents the Laplace variable; Calculate the bottom hole pressure solution of the target vertical well in the mathematical model for predicting the production capacity of the vertical well under conditions of inter-well disturbance and strong injection and production: in, This represents the superposition solution of pressures that cause pressure disturbance to the target vertical well from adjacent vertical wells. This represents the bottom hole pressure solution for a target vertical well considering wellbore storage effect and skin coefficient conditions.

2. The method according to claim 1, characterized in that, The target assumptions include at least one of the following: the gas reservoir is homogeneous and of uniform thickness, and the initial pressure is the same at all locations in the reservoir; the effects of gravity and temperature on gas flow in the gas reservoir are ignored; the gas reservoir has a closed top and bottom interface and an irregular outer boundary; the gas reservoir vertical well completely penetrates the reservoir; the gas flow in the reservoir satisfies Darcy's law; and the gas injection rate and gas production rate of the gas reservoir vertical well are constant.

3. The method according to claim 1, characterized in that, The process of obtaining the production solution of the target vertical well based on the bottom hole pressure solution includes: in, denoted as the bottom hole pressure solution of the target vertical well in the Laplace domain of a multi-well gas storage system, considering inter-well interference and intensive injection and production, where u represents the Laplace variable.

4. A device for predicting the production capacity of vertical wells in gas storage facilities under conditions of inter-well interference and intensive injection and extraction, characterized in that, include: The data acquisition module is used to acquire basic data of the target strata in the underground natural gas storage facility. The basic data of the target formation of the underground natural gas storage facility include: geological parameters of the target formation, basic physical property parameters of gas injection and production, gas injection and production data of the target vertical well and the gas injection and production data of adjacent vertical wells, wherein the adjacent vertical wells and the target vertical well are located in the same gas storage layer of the underground natural gas storage facility; The pressure solution acquisition module is used to calculate the pressure superposition solution of the target vertical well under the conditions of inter-well interference and strong injection and strong production based on the basic data of the target formation of the underground natural gas storage and the vertical well production prediction mathematical model, and to obtain the bottom hole pressure solution of the target vertical well of the vertical well production prediction mathematical model. The method for constructing the mathematical model for predicting the production capacity of vertical wells includes: A physical model for production capacity prediction based on inter-well interference and strong injection and extraction conditions is obtained. The physical model for production capacity prediction is obtained at least based on the basic data of the target formation of the underground natural gas storage and the location of each vertical well in the underground natural gas storage. The control equations of the vertical well production capacity prediction mathematical model under the conditions of inter-well interference and strong injection and extraction are established. Based on the control equations and the target assumptions, the vertical well production capacity prediction mathematical model under the conditions of inter-well interference and strong injection and extraction is obtained. The governing equations for establishing the mathematical model of vertical well productivity prediction under inter-well interference and intensive injection / production conditions include: Where u represents the Laplace variable, t D : Indicates dimensionless production time. This represents the dimensionless pseudo-pressure within the vertical well of the gas storage facility. M represents the dimensionless pseudo-pressure in the outer zone of the gas storage vertical well. 12 : Represents the dimensionless mobility ratio, ω 12 : Represents the dimensionless storage capacity ratio, r D : Indicates dimensionless radial distance, Represents a variable in the Laplace domain; The calculation of the pressure superposition solution of the target vertical well under the conditions of inter-well interference and strong injection and production using the superposition principle, and the obtaining of the bottom hole pressure solution of the target vertical well in the mathematical model for predicting the vertical well production capacity, includes: Calculate the pressure solution for the adjacent vertical wells: Where j: represents the ordinal number of the adjacent vertical well. The gas injection and production volume of adjacent vertical wells, r D,j : Represents the dimensionless distance from other adjacent vertical wells to the target vertical well in a multi-well system, x wD y wD Both x and y represent the position of the target vertical well in a dimensionless rectangular coordinate system. D,j y D,j : Both represent the positions of adjacent wells in a gas storage facility in a dimensionless rectangular coordinate system; The pressure interference of the adjacent vertical wells on the target vertical well is calculated using the superposition principle, and the pressure superposition solution of the target vertical well is obtained: Where j: represents the ordinal number of the adjacent vertical well, N m : Indicates the total number of vertical wells in a multi-vertical-well system of a gas storage facility. The gas injection and production volume of adjacent vertical wells, r D,j : represents the dimensionless distance from other adjacent vertical wells to the target vertical well in a multi-well system, K0: represents the Bessel function of the second kind, u: represents the Laplace variable; Calculate the bottom hole pressure solution of the target vertical well in the mathematical model for predicting the production capacity of the vertical well under conditions of inter-well disturbance and strong injection and production: in, This represents the superposition solution of pressures that cause pressure disturbance to the target vertical well from adjacent vertical wells. This represents the bottom hole pressure solution for a target vertical well considering wellbore storage effect and skin coefficient conditions; The production capacity prediction module is used to obtain the production capacity of the target vertical well based on the bottom hole pressure solution, and to predict the production capacity of the target vertical well in the underground natural gas storage facility.

5. An electronic device, characterized in that, include: processor; as well as, Memory for stored programs; The program includes instructions that, when executed by the processor, cause the processor to perform the method according to any one of claims 1-3.

6. 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 perform the method according to any one of claims 1-3.

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