Sand production prediction method and system for gas reservoir type compressed air energy storage warehouse

Abstract

The invention discloses a sand production prediction method and system for a gas reservoir type compressed air energy storage warehouse, and relates to the technical field of compressed air energy storage warehouse development. The method comprises the following steps of: substituting cohesive force and an internal friction angle of rock at a preset radius of a shaft of a preset gas storage well of the gas reservoir type compressed air energy storage reservoir under a preset loading frequency, loading times before preset production time and stratum parameters at the preset radius of the shaft into a Mohr-Coulomb criterion; judging whether the Mohr-Coulomb criterion after the data is introduced is true or not, and obtaining a judgment result; and when the judgment result is yes, it is judged that sand flows out at the preset radius of the shaft. According to the method, on the basis of the multiple parameters and the Mohr-Coulomb criterion, whether sand flows out at the preset radius of the shaft of the preset gas storage well of the gas reservoir type compressed air energy storage library or not can be reasonably predicted, and a guarantee is provided for safe operation of the gas reservoir type compressed air energy storage library.

Description

Background Art

[0002] In recent years, the global cumulative wind power curtailment has been serious. CEAS can realize the temporal and spatial transfer of energy and smooth the volatility of new energy. The conversion of depleted gas reservoirs into compressed air energy storage can reduce the electricity cost of oil and gas fields, improve production efficiency, and meet the needs of urban power supply. It is the preferred type of storage construction.

[0003] The injection and production frequency of gas reservoir-type compressed air energy storage is high (twice a day), and the rock skeleton is easily fatigued and damaged under cyclic alternating loads, turning the rock skeleton sand into free sand. The sand production problem is serious, and the formation sand flows into the wellbore, blocking the channel and affecting the production of the gas well. Traditional research on the sand production problem is mainly aimed at oil and gas field development. The injection and production frequency of oil and gas field development is low, and fatigue damage will not occur. The rock strength remains basically unchanged. Sand will only be produced when the critical production pressure difference is exceeded, and the sand production radius is fixed when sand is produced. However, gas reservoir-type compressed air energy storage will produce fatigue damage under high-frequency injection and production, and the rock strength will degrade. When it degrades to meet the strength failure criterion, the rock will be damaged, sand will be produced, and the sand production radius will continue to increase. The particularity of the sand production problem of gas reservoir-type compressed air energy storage.

[0004] At present, there is still a lack of technical solutions for predicting the impact of rock strength degradation on sand production under high-frequency injection and production. Sand production has seriously affected the safe operation of gas reservoir-type compressed air energy storage facilities, and there is an urgent need to form a method for predicting sand production from gas reservoir-type compressed air energy storage facilities. Summary of the invention

[0005] The technical problem to be solved by the present invention is to address the deficiencies of the prior art and specifically provide a method and system for predicting sand production in a gas reservoir type compressed air energy storage reservoir, as follows:

[0006] 1) In the first aspect, the present invention provides a method for predicting sand production in a gas reservoir type compressed air energy storage reservoir, and the specific technical scheme is as follows:

[0007] The cohesion, internal friction angle and the number of loading times before the preset production time of the rock at the preset radius of the wellbore of the preset gas storage well of the gas reservoir type compressed air energy storage reservoir at the preset loading frequency, as well as the formation parameters at the preset radius of the wellbore are brought into the Mohr-Coulomb criterion to determine whether the Mohr-Coulomb criterion after the data is brought in holds true, and obtain a determination result;

[0008] When the judgment result is yes, it is determined that sand is produced at the preset radius of the wellbore.

[0009] The beneficial effects of the sand production prediction method of a gas reservoir type compressed air energy storage provided by the present invention are as follows:

[0010] Based on multiple parameters and the Mohr-Coulomb criterion, it is possible to reasonably predict whether sand is produced at a preset radius of the wellbore of a preset gas storage well of a gas reservoir type compressed air energy storage reservoir, thereby providing a guarantee for the safe operation of the gas reservoir type compressed air energy storage reservoir.

[0011] On the basis of the above scheme, the sand production prediction system of a gas reservoir type compressed air energy storage reservoir of the present invention can also be improved as follows.

[0012] Furthermore, it also includes:

[0013] The cohesion and internal friction angle of the rock at the preset radius of the wellbore under the preset loading frequency, as well as the formation parameters at the preset radius of the wellbore are introduced into the Mohr-Coulomb criterion, and the minimum number of loading times n when the Mohr-Coulomb criterion is established after the data is introduced is calculated. min ;

[0014] According to the relationship between loading frequency and time, and the minimum number of loading times n min , predict the sand production time at a preset radius of the wellbore.

[0015] The beneficial effect of adopting the above further scheme is that it can reasonably predict the sand production time at a preset radius of the wellbore of the preset gas storage well of the gas reservoir type compressed air energy storage reservoir, thereby providing guarantee for the safe operation of the gas reservoir type compressed air energy storage reservoir.

[0016] Furthermore, it also includes:

[0017] The critical sand production radius at the preset production time is determined based on the cohesion and internal friction angle of the rock at the preset radius of the wellbore of the preset gas storage well of the gas reservoir type compressed air energy storage reservoir at the preset loading frequency and the number of loading times before the preset production time, as well as the formation parameters at the preset radius of the wellbore.

[0018] The beneficial effect of adopting the above further scheme is that it can reasonably predict the critical sand production radius at the preset radius of the wellbore of the preset gas storage well of the gas reservoir type compressed air energy storage reservoir, thereby providing guarantee for the safe operation of the gas reservoir type compressed air energy storage reservoir.

[0019] Furthermore, it also includes:

[0020] The sand production amount is predicted by using the sand production prediction model and the critical sand production radius at the preset production time.

[0021] The beneficial effect of adopting the above further scheme is that the amount of sand produced can be reasonably predicted, providing guarantee for the safe operation of the gas reservoir type compressed air energy storage.

[0022] 2) In the second aspect, the present invention also provides a sand production prediction system for a gas reservoir type compressed air energy storage reservoir, and the specific technical scheme is as follows:

[0023] It includes a criterion establishment judgment module and a sand production judgment module;

[0024] The criterion establishment judgment module is used to: bring the cohesion, internal friction angle and the number of loading times before the preset production time of the rock at the preset radius of the wellbore of the preset gas storage well of the gas reservoir type compressed air energy storage reservoir at the preset loading frequency, as well as the formation parameters at the preset radius of the wellbore into the Mohr-Coulomb criterion, judge whether the Mohr-Coulomb criterion after the data is brought in is established, and obtain a judgment result;

[0025] The sand production determination module is used to determine that sand is produced at a preset radius of the wellbore when the determination result is yes.

[0026] On the basis of the above scheme, the sand production prediction system of a gas reservoir type compressed air energy storage reservoir of the present invention can also be improved as follows.

[0027] Furthermore, it also includes a minimum loading times calculation module and a sand production time prediction module;

[0028] The minimum loading times calculation module is used to: bring the cohesion and internal friction angle of the rock at the preset radius of the wellbore under the preset loading frequency, as well as the formation parameters at the preset radius of the wellbore into the Mohr-Coulomb criterion, and calculate the minimum loading times n when the Mohr-Coulomb criterion is established after the data is brought in. min ;

[0029] The sand production time prediction module is used to: According to the relationship between loading frequency and time, and the minimum number of loading times n min , predict the sand production time at a preset radius of the wellbore.

[0030] Furthermore, it also includes a critical sand production radius calculation module;

[0031] The critical sanding radius calculation module is used to determine the critical sanding radius at the preset production time according to the cohesion and internal friction angle of the rock at the preset radius of the wellbore of the preset gas storage well of the gas reservoir type compressed air energy storage reservoir at the preset loading frequency and the number of loadings before the preset production time, as well as the formation parameters at the preset radius of the wellbore.

[0032] Furthermore, it also includes a sand production prediction module, which is used to predict the sand production volume by using a sand production prediction model and a critical sand production radius at a preset production time.

[0033] 3) In a third aspect, the present invention further provides an electronic device, comprising a processor, the processor being coupled to a memory, the memory storing at least one computer program, the at least one computer program being loaded and executed by the processor, so that the electronic device can implement any of the above-mentioned methods for predicting sand production in a gas reservoir-type compressed air energy storage facility.

[0034] 4) In a fourth aspect, the present invention further provides a computer-readable storage medium, in which at least one computer program is stored, and at least one computer program is loaded and executed by a processor so that the computer implements any of the above-mentioned sand production prediction methods for gas reservoir-type compressed air energy storage reservoirs.

[0035] It should be noted that the beneficial effects achieved by the technical solutions of the second to fourth aspects of the present invention and the corresponding possible implementation methods can be found in the above-mentioned technical effects of the first aspect and its corresponding possible implementation methods, and will not be repeated here. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Other features, objects and advantages of the present invention will become more apparent from the detailed description of non-limiting embodiments made with reference to the following drawings:

[0037] Figure 1 A schematic flow chart of a method for predicting sand production in a gas reservoir type compressed air energy storage reservoir according to an embodiment of the present invention;

[0038] Figure 2 It is a schematic diagram of Mohr-Coulomb strength line and Mohr stress circle;

[0039] Figure 3 is the shear strength curve after strength degradation;

[0040] Figure 4 is the rock cohesion curve under different loading times;

[0041] Figure 5 is the rock internal friction angle curve under different loading times;

[0042] Figure 6 The curve of sand output under different production time;

[0043] Figure 7 It is a structural schematic diagram of a sand production prediction system of a gas reservoir type compressed air energy storage reservoir according to an embodiment of the present invention;

[0044] Figure 8 The figure is a schematic diagram of the structure of an electronic device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0045] In order to make the objectives, technical solutions and advantages of the present invention more clear, the embodiments of the present invention will be further described in detail below with reference to the accompanying drawings.

[0046] like Figure 1 As shown, a method for predicting sand production of a gas reservoir type compressed air energy storage reservoir according to an embodiment of the present invention comprises the following steps:

[0047] S1. Substitute the cohesion, internal friction angle and the number of loading times before the preset production time of the rock at the preset radius of the wellbore of the preset gas storage well of the gas reservoir type compressed air energy storage reservoir at the preset loading frequency, as well as the formation parameters at the preset radius of the wellbore into the Mohr-Coulomb criterion, and determine whether the Mohr-Coulomb criterion after the data is entered is established, and obtain a determination result;

[0048] The preset production time may be the current time or any time in the production process specified by the user.

[0049] Among them, the formation parameters include: Boit coefficient and pore pressure of rock.

[0050] Among them, by coupling the underground seepage field with the rock stress field, the Mohr-Coulomb criterion considering the fluid pressure in the pores of the formation rock and expressed by the principal stress is established. The Mohr-Coulomb criterion is:

[0051]

[0052] σ1 represents: the maximum principal stress of rock;

[0053] β b Indicates: Boit coefficient of rock, β b Usually related to the porosity of the rock at any radius r in the wellbore equal;

[0054] P p(r) Indicates: the pore pressure at any radius r in the wellbore, specifically:

[0055] According to the underground seepage theory, in plane radial flow, the pore pressure P at any radius r in the wellbore is p(r) for:

[0056] P w Indicates: the bottom hole pressure of the wellbore, for example, when injecting gas, the bottom hole pressure p w When gas is produced, the bottom hole pressure p w 10MPa;

[0057] P0 represents: distant formation pressure;

[0058] re Indicates: deflation radius;

[0059] r w Represents the radius of the wellbore;

[0060] C(n,f) represents the cohesion of rock under loading frequency f and loading number n.

[0061] τ(n, f) represents the shear strength of rock at loading frequency f and loading number n.

[0062] σ3 represents: the minimum principal stress of rock;

[0063] τ(N(f),f) represents: the shear strength of rock at failure under loading frequency f;

[0064] N(f) represents: the number of loading times when the rock fails under the loading frequency f;

[0065] τ(0, f) represents: the shear strength τ(0, f) of rock under loading frequency f and loading number 0;

[0066] It means: the internal friction angle of rock under loading frequency f and loading number n,

[0067] τ(n, f) represents the shear strength of rock at loading frequency f and loading number f.

[0068] Optionally, obtain and The process includes:

[0069] Through triaxial cyclic loading experiments, under the stress conditions of σ1 and σ3, the number of loading times when the rock fails at different loading frequencies is obtained, represented by N(f): the number of loading times when the rock fails at the loading frequency f, represented by τ(N(f), f): the shear strength when the rock fails at the loading frequency f, τ(N(f), f) is the shear strength after strength degradation.

[0070] Through triaxial monotonic loading experiments, the shear strength τ(0, f) of rock under loading frequency f and loading number 0 is obtained. τ(0, f) is the shear strength when there is no strength degradation.

[0071] The rock is cyclically loaded for multiple times at different loading frequencies through triaxial cyclic loading test, and then the residual shear strength of the rock after multiple cyclic loading is obtained through triaxial monotonic loading test. Specifically, the shear strength (also called residual shear strength) τ(n, f) of the rock under the loading frequency f and the number of loading times n is obtained through data fitting. a represents the rock strength degradation coefficient, which is obtained through data fitting.

[0072] When shear failure occurs in rock, the Mohr-Coulomb strength line is tangent to the Mohr stress circle, and the tangent point is the failure point. The ordinate of the failure point is τ(n, f), as shown in Figure 2 As shown, according to the geometric relationship, the cohesion C(f,n) and internal friction angle of the rock under the loading frequency f and the loading number n can be obtained. as follows:

[0073]

[0074]

[0075] The expression of Mohr-Coulomb intensity line is: C represents: cohesion of rock, in MPa; Indicates: internal friction angle of rock;

[0076] The expression of Mohr stress circle is:

[0077] S2. When the judgment result is yes, it is determined that sand is produced at the preset radius of the wellbore.

[0078] Optionally, when the judgment result is yes, it is determined that no sand is produced at a preset radius of the wellbore.

[0079] Optionally, in the above technical solution, it also includes:

[0080] S3, the cohesion and internal friction angle of the rock at the preset radius of the wellbore at the preset loading frequency, as well as the formation parameters at the preset radius of the wellbore are brought into the Mohr-Coulomb criterion, and the minimum number of loading times n when the Mohr-Coulomb criterion is established after the data are brought in is calculated. min ;

[0081] S4, based on the relationship between loading frequency and time, and the minimum number of loading times n min , predict the sand production time at a preset radius of the wellbore.

[0082] The relationship between loading frequency and time is specifically characterized by the sand production time prediction model, which is: T represents the sand discharge time, and the minimum loading times nmin Substitute into the sand production time prediction model and get T ′ Indicates the sand production time at the preset radius of the wellbore.

[0083] Optionally, in the above technical solution, it also includes:

[0084] S5. According to the cohesion and internal friction angle of the rock at the preset radius of the wellbore of the preset gas storage well of the gas reservoir type compressed air energy storage reservoir at the preset loading frequency and the number of loading times before the preset production time, as well as the formation parameters at the preset radius of the wellbore, the critical sand production radius at the preset production time is determined, which is specifically calculated by the following formula:

[0085]

[0086] Among them, r(f,n) represents: critical sanding radius, let n=n2, and bring other parameters into the formula to calculate the critical sanding radius at the preset production time, and n2 represents the number of loading times before the preset production time.

[0087] Optionally, in the above technical solution, it also includes:

[0088] S6. Predict the amount of sand produced by using the sand production prediction model and the critical sand production radius at the preset production time.

[0089] Among them, the sand volume prediction model is: Where, k is the permeability of the rock, in mD, and h is the reservoir thickness, in m; represents the porosity of the rock, t represents the production time, let n = n2, T = T ′ , t is the preset production time, and other parameters are brought into the sand volume prediction model to predict the sand output Ω(t).

[0090] It should be noted that the cohesion of the rock at a preset radius of the wellbore of the preset gas storage well of the gas reservoir-type compressed air energy storage facility at a preset loading frequency, the internal friction angle, the number of loadings before the preset production time, and the formation parameters at the preset radius of the wellbore, etc., are replaced with the corresponding parameters in the above formula and then calculated.

[0091] Select 8 depleted gas reservoirs in a certain area, the injection and production frequency is 2 times a day, the maximum horizontal principal stress σ1 of the formation is 15MPa, the minimum horizontal principal stress σ3 is 10MPa, and the bottom hole pressure p during gas injection is w The bottom hole pressure p is 14MPa. w is 10MPa, the formation pressure p0 is 12MPa, and the wellbore radius r w is 0.1m, the leakage radius r e 1000m, porosity is 0.23, and the Boit coefficient β b is 0.23, the permeability k is 334mD, and the reservoir thickness h is 10m. The specific implementation process is as follows:

[0092] S101. It was measured that the number of loading times N when the rock was destroyed under cyclic load was 567, the shear strength τ(N) at the time of destruction was 9 MPa, and the shear strength τ(0) when the rock did not undergo strength degradation was 25 MPa.

[0093] S102. Measure the residual shear strength τ(n) of the rock after the strength degradation after loading n times, as Figure 3 As shown in the figure, the rock strength degradation coefficient a is 0.49 obtained through data fitting.

[0094] S103. Obtain the rock cohesion C(n) and rock internal friction angle under different loading times n like Figure 4 and Figure 5 shown.

[0095] S104, the formation parameters p0, r e , production parameter p w 、r w Substituting into the equation, we can obtain the pore pressure P at radius r. p (r).

[0096] S105, the obtained rock cohesion C(n) and rock internal friction angle The pore pressure is P p (r) and formation parameters σ1, σ3, β b Substituting into the equation, we can obtain the failure criterion of the rock in the depleted gas reservoir. If the rock at radius r satisfies the failure criterion after loading n times, the reservoir at radius r begins to produce sand.

[0097] S106. It can be calculated that the sand production time of the gas reservoir is 122 days under the conditions of injection and production frequency twice a day and production pressure difference of 14 MPa.

[0098] S107. The curve of the sand production volume Ω of the gas reservoir changing with the preset production time under the conditions of injection and production frequency twice a day and production pressure difference of 14 MPa can be obtained, such as Figure 6 shown.

[0099] The method for predicting sand production in a gas reservoir type compressed air energy storage reservoir of the present invention obtains the residual strength after strength degradation and the variation law of rock cohesion and internal friction angle with injection and production frequency and number according to the experiment, obtains the Mohr-Coulomb criterion and pore pressure distribution considering the fluid pressure in the pores of the formation rock through theoretical analysis, and finally obtains the prediction model of sand production time and sand production amount, which has a certain guiding role in the safe construction of gas reservoir type compressed air energy storage reservoir. The application process of the present invention is simple and reliable, and the sand production situation under high-frequency injection and production can be predicted. It only needs to adjust the geological parameters, and the present invention has good reliability in use.

[0100] In the above embodiments, although the steps are numbered S1, S2, etc., these are only specific embodiments given by the present invention. Those skilled in the art may adjust the execution order of S1, S2, etc. according to actual conditions, which is also within the protection scope of the present invention. It can be understood that in some embodiments, some or all of the above embodiments may be included.

[0101] like Figure 7 As shown, a sand production prediction system 200 for a gas reservoir type compressed air energy storage reservoir according to an embodiment of the present invention includes a criterion establishment judgment module 201 and a sand production judgment module 202;

[0102] The criterion establishment judgment module 201 is used to: bring the cohesion, internal friction angle and the number of loading times before the preset production time of the rock at the preset radius of the wellbore of the preset gas storage well of the gas reservoir type compressed air energy storage reservoir at the preset loading frequency, as well as the formation parameters at the preset radius of the wellbore into the Mohr-Coulomb criterion, judge whether the Mohr-Coulomb criterion after the data is brought in is established, and obtain a judgment result;

[0103] The sand production determination module 202 is used to determine that sand is produced at a preset radius of the wellbore when the determination result is yes.

[0104] Optionally, in the above technical solution, a minimum loading times calculation module and a sand production time prediction module are also included;

[0105] The minimum loading times calculation module is used to: bring the cohesion and internal friction angle of the rock at the preset radius of the wellbore under the preset loading frequency, as well as the formation parameters at the preset radius of the wellbore into the Mohr-Coulomb criterion, and calculate the minimum loading times n when the Mohr-Coulomb criterion is established after the data is brought in. min ;

[0106] The sand production time prediction module is used to: According to the relationship between loading frequency and time, and the minimum number of loading times n min , predict the sand production time at a preset radius of the wellbore.

[0107] Optionally, in the above technical solution, a critical sand production radius calculation module is also included;

[0108] The critical sanding radius calculation module is used to determine the critical sanding radius at the preset production time according to the cohesion and internal friction angle of the rock at the preset radius of the wellbore of the preset gas storage well of the gas reservoir type compressed air energy storage reservoir at the preset loading frequency and the number of loadings before the preset production time, as well as the formation parameters at the preset radius of the wellbore.

[0109] Optionally, the above technical solution also includes a sand production prediction module, which is used to predict the sand production volume by using a sand production prediction model and a critical sand production radius at a preset production time.

[0110] It should be noted that the beneficial effects of the sand production prediction system for a gas reservoir type compressed air energy storage reservoir provided in the above embodiment are the same as the beneficial effects of the sand production prediction method for the gas reservoir type compressed air energy storage reservoir, which will not be repeated here. In addition, when the system provided in the above embodiment realizes its functions, it only uses the division of the above functional modules as an example. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the system can be divided into different functional modules according to actual conditions to complete all or part of the functions described above. In addition, the system and method embodiments provided in the above embodiment belong to the same concept, and the specific implementation process is detailed in the method embodiment, which will not be repeated here.

[0111] like Figure 8 As shown, an electronic device 300 of an embodiment of the present invention includes a processor 320, the processor 320 is coupled to a memory 310, and the memory 310 stores at least one computer program 330, and the at least one computer program 330 is loaded and executed by the processor 320, so that the electronic device 300 implements any of the above-mentioned methods for predicting sand production in a gas reservoir type compressed air energy storage reservoir, specifically:

[0112] The electronic device 300 may have relatively large differences due to different configurations or performances, and may include one or more processors 320 (Central Processing Units, CPU) and one or more memories 310, wherein at least one computer program 330 is stored in the one or more memories 310, and the at least one computer program 330 is loaded and executed by the one or more processors 320, so that the electronic device 300 implements any one of the gas reservoir type compressed air energy storage reservoir sand production prediction methods provided in the above embodiments. Of course, the electronic device 300 may also have components such as a wired or wireless network interface, a keyboard, and an input and output interface for input and output. The electronic device 300 may also include other components for realizing the functions of the device, which will not be repeated here. The electronic device may specifically be a computer, etc.

[0113] A computer-readable storage medium according to an embodiment of the present invention stores at least one computer program, and the at least one computer program is loaded and executed by a processor so that the computer implements any of the above-mentioned sand production prediction methods for gas reservoir-type compressed air energy storage reservoirs.

[0114] Optionally, the computer-readable storage medium may be a read-only memory (ROM), a random access memory (RAM), a compact disc (CD-ROM), a magnetic tape, a floppy disk, an optical data storage device, and the like.

[0115] In an exemplary embodiment, a computer program product or a computer program is also provided, the computer program product or the computer program comprising computer instructions, the computer instructions being stored in a computer-readable storage medium. A processor of an electronic device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the electronic device executes any of the above-mentioned methods for predicting sand production in a gas reservoir-type compressed air energy storage reservoir.

[0116] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application are used to distinguish similar objects and represent the definition of a specific order or sequence. The order of use of similar objects can be interchanged where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than the order shown or described.

[0117] Those skilled in the art know that the present invention can be implemented as a system, method or computer program product. Therefore, the present invention can be specifically implemented in the following forms, namely: it can be complete hardware, it can be complete software (including firmware, resident software, microcode, etc.), or it can be a combination of hardware and software, which is generally referred to as "circuit", "module" or "system" herein. In addition, in some embodiments, the present invention can also be implemented in the form of a computer program product in one or more computer-readable media, and the computer-readable medium contains computer-readable program code.

[0118] Any combination of one or more computer-readable media can be used. The computer-readable medium can be a computer-readable signal medium or a computer-readable storage medium. The computer-readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media (a non-exhaustive list) include: an electrical connection with one or more wires, a portable computer disk, 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 disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present invention, a computer-readable storage medium can be any tangible medium containing or storing a program, which can be used by an instruction execution system, device or device or used in combination with it.

[0119] Although the embodiments of the present invention have been shown and described above, it is to be understood that the above embodiments are exemplary and are not to be construed as limitations of the present invention. A person skilled in the art may change, modify, replace and vary the above embodiments within the scope of the present invention.

Claims

1. A method for predicting sand production in a gas reservoir type compressed air energy storage reservoir, characterized in that: include: Substitute the cohesion, internal friction angle and the number of loading times before the preset production time of the rock at the preset radius of the wellbore of the preset gas storage well of the gas reservoir type compressed air energy storage reservoir at the preset loading frequency, as well as the formation parameters at the preset radius of the wellbore into the Mohr-Coulomb criterion, determine whether the Mohr-Coulomb criterion after the data is entered is valid, and obtain a determination result; When the judgment result is yes, it is determined that sand is produced at the preset radius of the wellbore.

2. The method for predicting sand production of a gas reservoir type compressed air energy storage reservoir according to claim 1, characterized in that: Also includes: The cohesion and internal friction angle of the rock at the preset radius of the wellbore at the preset loading frequency, as well as the formation parameters at the preset radius of the wellbore are introduced into the Mohr-Coulomb criterion, and the minimum number of loading times n when the Mohr-Coulomb criterion after the data is introduced is calculated. min ; According to the relationship between loading frequency and time, and the minimum number of loading times n min , predicting the sand production time at a preset radius of the wellbore.

3. The method for predicting sand production of a gas reservoir type compressed air energy storage reservoir according to claim 2, characterized in that: Also includes: The critical sand production radius at the preset production time is determined based on the cohesion and internal friction angle of the rock at the preset radius of the wellbore of the preset gas storage well of the gas reservoir type compressed air energy storage reservoir at the preset loading frequency and the number of loading times before the preset production time, as well as the formation parameters at the preset radius of the wellbore.

4. The method for predicting sand production of a gas reservoir type compressed air energy storage reservoir according to claim 3, characterized in that: Also includes: The sand production amount is predicted by using the sand production prediction model and the critical sand production radius at the preset production time.

5. A sand production prediction system for a gas reservoir type compressed air energy storage reservoir, characterized in that: It includes a criterion establishment judgment module and a sand production judgment module; The criterion establishment judgment module is used to: bring the cohesion, internal friction angle and the number of loading times before the preset production time of the rock at the preset radius of the wellbore of the preset gas storage well of the gas reservoir type compressed air energy storage reservoir at the preset loading frequency, as well as the formation parameters at the preset radius of the wellbore, into the Mohr-Coulomb criterion, judge whether the Mohr-Coulomb criterion after the data is brought in is established, and obtain a judgment result; The sand production determination module is used to determine that sand is produced at a preset radius of the wellbore when the determination result is yes.

6. A sand production prediction system for a gas reservoir type compressed air energy storage reservoir according to claim 5, characterized in that: It also includes a minimum loading times calculation module and a sand production time prediction module; The minimum loading times calculation module is used to: bring the cohesion and internal friction angle of the rock at the preset radius of the wellbore under the preset loading frequency, and the formation parameters at the preset radius of the wellbore into the Mohr-Coulomb criterion, and calculate the minimum loading times n when the Mohr-Coulomb criterion is established after the data are brought in. min ; The sand production time prediction module is used to: according to the relationship between loading frequency and time, and the minimum loading number n min , predicting the sand production time at a preset radius of the wellbore.

7. A sand production prediction system for a gas reservoir type compressed air energy storage reservoir according to claim 6, characterized in that: It also includes a critical sanding radius calculation module; The critical sanding radius calculation module is used to determine the critical sanding radius at a preset production time according to the cohesion and internal friction angle of the rock at a preset radius of the wellbore of a preset gas storage well of the gas reservoir type compressed air energy storage reservoir at a preset loading frequency and the number of loading times before a preset production time, as well as the formation parameters at the preset radius of the wellbore.

8. The sand production prediction system for a gas reservoir type compressed air energy storage reservoir according to claim 7, characterized in that: It also includes a sand production prediction module, which is used to predict the sand production volume by using a sand production prediction model and a critical sand production radius at the preset production time.

9. An electronic device, characterized in that: The electronic device includes a processor, the processor is coupled to a memory, at least one computer program is stored in the memory, and the at least one computer program is loaded and executed by the processor so that the electronic device implements a sand production prediction method for a gas reservoir type compressed air energy storage reservoir as described in any one of claims 1 to 4.

10. A computer-readable storage medium, characterized in that: At least one computer program is stored in the computer-readable storage medium, and the at least one computer program is loaded and executed by the processor so that the computer implements the sand production prediction method for a gas reservoir-type compressed air energy storage reservoir as described in any one of claims 1 to 4.

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