Acid etching fracture conductivity prediction method, system, equipment and medium

Abstract

The invention discloses a method, a system, equipment and a medium for predicting the flow conductivity of an acid etching fracture, and particularly relates to the technical field of oil and gas field development, and the method is technically characterized by comprising the following steps: scanning the surface morphology of a rock plate fracture under different acid etching conditions to obtain fracture surface width distribution data under different acid etching conditions; inputting the crack surface width distribution data under different acid etching conditions into the acid etching model, and calculating to obtain crack pressure field data; according to the rock elastic deformation theory and in combination with the rock Young modulus, determining rock deformation characteristics under the action of the closing pressure, and updating the fracture pressure field data based on the rock deformation characteristics to obtain updated fracture pressure field data; and inputting the updated fracture pressure field data, the combined acid liquor concentration change rate and the acid etching fracture width change rate into a flow conductivity prediction model, and predicting to obtain an acid etching fracture flow conductivity prediction result.

Description

Technical Field

[0001] The invention relates to the technical field of oil and gas field development, and in particular to a method, system, equipment and medium for predicting the conductivity of an acid-etched fracture. Background Art

[0002] In the process of oil and gas field exploitation, the production of carbonate reservoirs decreases in the later stage of production, and acid fracturing is required to improve the production capacity of the reservoir. The effect of fracture acid fracturing mainly depends on two aspects: one is to produce a certain acid erosion distance, and the other is the conductivity of the fracture; the conductivity is used to measure the size of the resistance to the flow of oil and gas in the fracture;

[0003] In the prior art, the conductivity is mainly measured by closed acid injection in the laboratory, and the conductivity of the crack is measured after a period of acid etching. However, after the above technical solution adds different closing stresses to the rock plate, the rock plate will be almost broken and cannot be reused. At the same time, when different rock plates are used for repeated experiments, the differences between the rock plates (such as rock heterogeneity, initial morphological characteristics, etc.) will affect the results of the acid etching measurement, and the accuracy of the measurement results cannot be guaranteed.

[0004] Therefore, the present invention aims to solve the above-mentioned related problems through a method, system, equipment and medium for predicting the conductivity of acid-etched fractures. Summary of the invention

[0005] The technical problem to be solved by the present invention is that the non-repeatability and universality of the use of laboratory rock slabs in the prior art lead to the impact on the results of acid etching measurements, and the accuracy of the measurement results cannot be guaranteed. The purpose is to provide a method, system, equipment and medium for predicting the conductivity of acid-etched fractures. By utilizing the characteristics of acid etching that are ultimately reflected in the crack width distribution, the crack width distribution is obtained by experimentally scanning the rock slabs, and the conductivity of different closing pressures is simulated and calculated by considering the rock deformation characteristics, thereby realizing multi-factor simulation analysis of the same rock core, and forming a conductivity prediction method that can connect experimental measurement and numerical simulation, thereby solving the non-repeatability and universality of the use of laboratory rock slabs in the prior art, which lead to the impact on the results of acid etching measurements, and the accuracy of the measurement results cannot be guaranteed.

[0006] The present invention is achieved through the following technical solutions:

[0007] A method for predicting conductivity of acid-etched cracks, the method comprising:

[0008] Scan the surface morphology of the cracks in the rock slab under different acid etching conditions to obtain the crack surface width distribution data under different acid etching conditions;

[0009] The crack surface width distribution data under different acid etching conditions are input into the acid etching model to calculate the crack pressure field data;

[0010] According to the rock elastic deformation theory combined with the rock Young's modulus, the rock deformation characteristics under the action of closing pressure are determined, and the fracture pressure field data is updated based on the rock deformation characteristics to obtain updated fracture pressure field data;

[0011] The updated fracture pressure field data, combined with the acid concentration change rate and the acid-etched fracture width change rate, are input into the conductivity prediction model to obtain the conductivity prediction results of the acid-etched fractures.

[0012] Furthermore, before scanning the surface morphology of the cracks of the rock plate under different acid etching conditions to obtain the crack surface width distribution data under different acid etching conditions, it also includes:

[0013] The stress-strain curves of the rock slabs before and after acid etching were measured by triaxial compression test, and the Young's modulus of the rock was calculated by using the stress-strain curves.

[0014] Furthermore, the acid etching model includes a pressure field distribution function, an acid concentration variation function, and an acid etching crack width variation function, specifically:

[0015]

[0016] Where, μ represents the viscosity of the acid; p represents the pressure; p e It is expressed as reservoir pressure; represents the average acid concentration; k g represents the mass transfer coefficient; k represents the permeability of the matrix rock; w m represents the length of the acid-etched wormhole; t represents the acid injection time; b represents the crack width.

[0017] Furthermore, the flow conductivity prediction model is specifically as follows:

[0018]

[0019] Among them, C f represents the conductivity of the acid-etched fracture; q represents the acid injection rate; μ represents the acid viscosity; x f Indicates the crack length; h f represents the fracture height; Δp represents the injection pressure difference.

[0020] The present invention also provides a system for predicting conductivity of acid-etched cracks, which is used in any one of the above-mentioned methods for predicting conductivity of acid-etched cracks, and the system comprises:

[0021] A data acquisition module is used to scan the surface morphology of cracks in rock slabs under different acid etching conditions and obtain the distribution data of crack surface width under different acid etching conditions;

[0022] A pressure field data calculation module is used to input the crack surface width distribution data under different acid etching conditions into the acid etching model to calculate the crack pressure field data;

[0023] The pressure field data updating module is used to determine the rock deformation characteristics under the action of closing pressure according to the rock elastic deformation theory combined with the rock Young's modulus, and to update the fracture pressure field data based on the rock deformation characteristics to obtain updated fracture pressure field data;

[0024] The conductivity prediction module is used to input the updated fracture pressure field data and the acid concentration change rate and the acid-etched fracture width change rate into the conductivity prediction model to predict the conductivity prediction result of the acid-etched fracture.

[0025] Furthermore, the system also includes:

[0026] The rock property calculation module is used to obtain the stress-strain curve of the rock plate before and after acid etching using triaxial compression test measurements, and to calculate the Young's modulus of the rock using the stress-strain curve.

[0027] Furthermore, the acid etching model includes a pressure field distribution function, an acid concentration variation function, and an acid etching crack width variation function, specifically:

[0028]

[0029] Where, μ represents the viscosity of the acid; p represents the pressure; p e It is expressed as reservoir pressure; represents the average acid concentration; k g represents the mass transfer coefficient; k represents the permeability of the matrix rock; w m represents the length of the acid-etched wormhole; t represents the acid injection time; b represents the crack width.

[0030] The present invention also provides a computer device, comprising a system memory and a processor, wherein the system memory stores a computer program, and the processor implements the steps of any one of the above-mentioned methods when executing the computer program.

[0031] The present invention also provides a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the steps of any one of the methods described above are implemented.

[0032] The present invention also provides a computer program product comprising instructions, when the instructions are executed by a computer device cluster, the computer device cluster executes any of the above methods.

[0033] Compared with the prior art, the present invention has the following advantages and beneficial effects:

[0034] In the present invention, by utilizing the characteristics of acid etching that are ultimately reflected in the crack width distribution, the crack width distribution is obtained by experimentally scanning the rock plate, and the rock deformation characteristics are taken into consideration to simulate and calculate the conductivity of different closure pressures, thereby realizing multi-factor simulation analysis of the same rock core, and forming a conductivity prediction method that can connect experimental measurement and numerical simulation, thereby solving the non-repeatability and universality of the use of laboratory rock plates in the prior art, which leads to the impact on the results of acid etching measurements and the inability to guarantee the accuracy of the measurement results. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] In order to more clearly illustrate the technical solutions of the exemplary embodiments of the present invention, the following briefly introduces the drawings required for use in the embodiments. It should be understood that the following drawings only illustrate certain embodiments of the present invention and should not be regarded as limiting the scope. For those of ordinary skill in the art, other relevant drawings can be obtained based on these drawings without creative work. In the drawings:

[0036] Figure 1 This is a schematic diagram of a method flow chart of a method for predicting conductivity of acid-etched cracks in this embodiment;

[0037] Figure 2 Schematic diagram of stress-strain curve in a method for predicting conductivity of acid-etched cracks in this embodiment;

[0038] Figure 3 A schematic diagram of the surface morphology of an acid-etched groove-shaped crack in a method for predicting conductivity of an acid-etched crack in this embodiment;

[0039] Figure 4 A schematic diagram of the surface morphology of acid-etched natural cracks in a method for predicting the conductivity of acid-etched cracks in this embodiment;

[0040] Figure 5 It is a schematic diagram of the conductivity experiment and numerical model prediction fitting of the conductivity of acid-etched groove cracks in a method for predicting the conductivity of acid-etched cracks in this embodiment;

[0041] Figure 6 It is a schematic diagram of the fitting of the acid-etched conductivity experiment and the numerical model prediction of the surface acid-etched conductivity of natural fractures in a method for predicting the conductivity of acid-etched fractures in this embodiment;

[0042] Figure 7Schematic diagram of the structure of a system for predicting conductivity of acid-etched cracks in this embodiment;

[0043] Figure 8 A schematic diagram of the structure of a computer device. DETAILED DESCRIPTION

[0044] The following is a description of exemplary embodiments of the present disclosure in conjunction with the accompanying drawings, including various details of the embodiments of the present disclosure to facilitate understanding, which should be considered as merely exemplary. Therefore, it should be recognized by those of ordinary skill in the art that various changes and modifications may be made to the embodiments described herein without departing from the scope of the present disclosure. Similarly, for the sake of clarity and conciseness, the description of well-known functions and structures is omitted in the following description.

[0045] In the present disclosure, unless otherwise specified, the use of the terms "first", "second", etc. to describe various elements is not intended to limit the positional relationship, timing relationship, or importance relationship of these elements, and such terms are only used to distinguish one element from another element. In some examples, the first element and the second element may refer to the same instance of the element, and in some cases, based on the description of the context, they may also refer to different instances.

[0046] The terms used in the description of various examples in this disclosure are only for the purpose of describing specific examples and are not intended to be limiting. Unless the context clearly indicates otherwise, if the number of elements is not specifically limited, the element can be one or more. In addition, the term "and / or" used in this disclosure covers any one of the listed items and all possible combinations.

[0047] Example 1

[0048] See also Figure 1 The present embodiment provides a method for predicting conductivity of acid-etched cracks, the method comprising:

[0049] S1: The stress-strain curve of the rock plate before and after acid etching is measured by triaxial compression test, and the Young's modulus of the rock is calculated by stress-strain curve;

[0050] Specifically, in the present embodiment, the triaxial compression test is a conventional technical means in this field, and the experimental process is as follows: first, the experimental sample is packed in a heat shrink tube, and strain sensors are installed in the axial and radial directions; then, the relevant valves are opened or closed according to the drainage requirements of the experiment; then, air pressure or hydraulic pressure is injected into the pressure chamber to make the sample withstand the surrounding pressure and keep the pressure unchanged during the entire experiment; then, axial pressure is applied to the rock sample through the piston. As the axial pressure gradually increases, the sample is eventually destroyed due to shear force, and the experiment is finally terminated to obtain the stress-strain curve of the rock plate before and after acid etching; finally, according to the stress-strain data obtained in the triaxial compression experiment, the rock modulus and other attribute parameters are calculated.

[0051] S2: Scan the surface morphology of the cracks in the rock slab under different acid etching conditions to obtain the crack surface width distribution data under different acid etching conditions;

[0052] S3: input the crack surface width distribution data under different acid etching conditions into the acid etching model to calculate the crack pressure field data;

[0053] It should be noted that, in this embodiment, the acid etching model includes a pressure field distribution function, an acid concentration variation function, and an acid etching crack width variation function, specifically:

[0054]

[0055] Where, μ represents the viscosity of the acid; p represents the pressure; p e It is expressed as reservoir pressure; represents the average acid concentration; k g represents the mass transfer coefficient; k represents the permeability of the matrix rock; w m represents the length of the acid-etched wormhole; t represents the acid injection time; b represents the crack width.

[0056] S4: According to the rock elastic deformation theory and the rock Young's modulus, the rock deformation characteristics under the closure pressure are determined, and the fracture pressure field data is updated based on the rock deformation characteristics to obtain updated fracture pressure field data;

[0057] Specifically, in this embodiment, according to the rock elastic deformation theory: σ = Eε, b=b i -Δb, where σ represents the applied stress, MPa, E is the Young's modulus of the rock, GPa, ε is the rock strain, which is the ratio of the deformation of the rock to the maximum height of the roughness protruding from the rock surface; σ' is the stress on the support point, MPa; α is the rock contact ratio under different closing pressures, which is the ratio of the contact area between the two fracture surfaces under a certain closing pressure to the entire fracture surface; b is the fracture width, m; b iis the initial crack width, m; Δb is the rock deformation caused by the closing stress, m; b max is the maximum crack width, m; b min is the minimum crack width; m;

[0058] At the same time, the initial crack is given, and it is judged whether the two crack surfaces are in contact under zero closing pressure. When the contact ratio of the two crack surfaces reaches a certain value, it is determined that the crack is about to close. When it is determined that the crack is about to close, the proportion of the rock foundation supporting the crack surface can be calculated, thus laying the foundation for the pressure field calculation.

[0059] When the rock is pressurized and closed, it deforms and the crack width changes, which causes the pressure field to change. The fracture pressure field data is recalculated and updated based on the rock deformation characteristics to obtain updated fracture pressure field data.

[0060] The pressure boundary conditions are as follows: Among them, p inlet is the net pressure at the inlet, which is a constant value p i , MPa; p outlet is the net pressure at the outlet, which is 0.

[0061] S5: The updated fracture pressure field data and the acid concentration change rate and the acid-etched fracture width change rate are input into the conductivity prediction model to obtain the acid-etched fracture conductivity prediction result.

[0062] It should be noted that, in this embodiment, the flow conductivity prediction model is specifically:

[0063]

[0064] Among them, C f represents the conductivity of the acid-etched fracture; q represents the acid injection rate; μ represents the acid viscosity; x f Indicates the crack length; h f represents the fracture height; Δp represents the injection pressure difference.

[0065] Specifically, in this embodiment, the updated fracture pressure field data and the acid concentration change rate and the acid-etched crack width change rate are input into the conductivity prediction model to predict the conductivity of the same rock plate under different acid types, acid injection rates, closure stresses, rock mechanical properties and fracture openings.

[0066] For example, see Figure 2-Figure 6 As shown, the changes in fracture conductivity under closure pressures of 10MPa, 20MPa, 30MPa, 40MPa, 50MPa, 60MPa, 70MPa and 80MPa were calculated and compared with the conductivity measured in the laboratory.

[0067] Specifically, in this embodiment, by utilizing the characteristics of acid etching that are ultimately reflected in the crack width distribution, the crack width distribution is obtained by experimentally scanning the rock plate, and combined with the rock deformation characteristics, the conductivity of different closure pressures is simulated and calculated, thereby realizing multi-factor simulation analysis of the same rock core, and forming a conductivity prediction method that can connect experimental measurement and numerical simulation, thereby solving the non-repeatability and universality of the use of laboratory rock plates in the prior art, which leads to the impact of the acid etching measurement results and the inability to guarantee the accuracy of the measurement results.

[0068] Example 2

[0069] See also Figure 7 As shown, the present invention also provides an acid-etched fracture conductivity prediction system, which is used in any one of the above-mentioned acid-etched fracture conductivity prediction methods, and the system includes:

[0070] The rock property calculation module 100 is used to obtain the stress-strain curve of the rock plate before and after acid etching by using triaxial compression test measurement, and calculate the rock Young's modulus by using the stress-strain curve;

[0071] The data acquisition module 200 is used to scan the surface morphology of the cracks in the rock plate under different acid etching conditions and obtain the crack surface width distribution data under different acid etching conditions;

[0072] The pressure field data calculation module 300 is used to input the crack surface width distribution data under different acid etching conditions into the acid etching model to calculate the crack pressure field data;

[0073] The pressure field data updating module 400 is used to determine the rock deformation characteristics under the closure pressure according to the rock elastic deformation theory combined with the rock Young's modulus, and to update the fracture pressure field data based on the rock deformation characteristics to obtain updated fracture pressure field data;

[0074] The conductivity prediction module 500 is used to input the updated fracture pressure field data and the acid concentration change rate and the acid-etched fracture width change rate into the conductivity prediction model to predict the conductivity prediction result of the acid-etched fracture.

[0075] Furthermore, the acid etching model includes a pressure field distribution function, an acid concentration variation function, and an acid etching crack width variation function, specifically:

[0076]

[0077] Where, μ represents the viscosity of the acid; p represents the pressure; p e It is expressed as reservoir pressure; represents the average acid concentration; kg represents the mass transfer coefficient; k represents the permeability of the matrix rock; w m represents the length of the acid-etched wormhole; t represents the acid injection time; b represents the crack width.

[0078] It should be noted that the modules in the system of Example 2 correspond to the steps in the method of Example 1. The steps in the method of Example 1 have been described in detail in Example 1. In this Example 2, the contents of the modules in the system will not be described in detail.

[0079] Example 3

[0080] See also Figure 8 As shown, this embodiment further provides a computer device, including a system memory 1005 and a processor 1001, wherein the system memory 1005 stores a computer program, and the processor 1001 implements the steps of any of the above methods when executing the computer program.

[0081] It should be noted that the processor 1001 is used to execute the steps in the above method embodiments according to the instructions in the program code. Alternatively, the processor 1001 implements the functions of each module / unit in the above system / device embodiments when executing the computer program.

[0082] Specifically, in this embodiment, the computer program may be divided into one or more modules / units, one or more modules / units are stored in the system memory 1005, and are executed by the processor 1001 to complete the present application. One or more modules / units may be a series of computer program instruction segments that can complete specific functions, and the instruction segments are used to describe the execution process of the computer program in the terminal device.

[0083] The terminal device may be a computing device such as a desktop computer, a notebook, a PDA, a cloud server, etc. The terminal device may include, but is not limited to, a processor 1001 and a system memory 1005. Those skilled in the art will appreciate that this does not constitute a limitation on the terminal device, and may include more or fewer components than shown in the figure, or a combination of certain components, or different components. For example, the terminal device may also include an input / output device 1003, a network access device 1002, a bus 1006, etc.

[0084] The processor 1001 may be a central processing unit (CPU), or other general-purpose processors 1001, digital signal processors 1001 (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor 1001 may be a microprocessor or any conventional processor, etc.

[0085] The system memory 1005 may be an internal storage unit of the terminal device, such as a hard disk or memory of the terminal device. The system memory 1005 may also be a storage device 1004 of the terminal device, such as a plug-in hard disk, a smart memory card (SmartMedia Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (FlashCard), etc. equipped on the terminal device. Further, the system memory 1005 may also include both the internal storage unit of the terminal device and the storage device 1004. The system memory 1005 is used to store computer programs and other programs and data required by the terminal device. The system memory 1005 may also be used to temporarily store data that has been output or is to be output.

[0086] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described systems, systems and units can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0087] Example 4

[0088] This embodiment provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the steps of any one of the above methods are implemented.

[0089] Among them, the computer-readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared or semiconductor system, system 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. Random Access Memory (RAM), Read-Only Memory (ROM), Erasable Programmable Read Only Memory (EPROM), registers, hard disks, optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the above, or any other form of computer-readable storage medium known in the art.

[0090] An exemplary storage medium is coupled to a processor so that the processor can read information from the storage medium and write information to the storage medium. Of course, the storage medium can also be a component of the processor. The processor and the storage medium can be located in an application-specific integrated circuit (ASIC). In an embodiment of the present invention, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, system, or device.

[0091] Example 5

[0092] This embodiment also provides a computer program product including instructions. When the instructions are executed by a computer device cluster, the computer device cluster executes the method described in Embodiment 1.

[0093] The specific implementation methods described above further illustrate the objectives, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above description is only a specific implementation method of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A method for predicting the conductivity of acid-etched cracks, characterized in that: Methods include: Scan the surface morphology of the cracks in the rock slab under different acid etching conditions to obtain the crack surface width distribution data under different acid etching conditions; The crack surface width distribution data under different acid etching conditions are input into the acid etching model to calculate the crack pressure field data; According to the rock elastic deformation theory combined with the rock Young's modulus, the rock deformation characteristics under the action of closing pressure are determined, and the fracture pressure field data is updated based on the rock deformation characteristics to obtain updated fracture pressure field data; The updated fracture pressure field data, combined with the acid concentration change rate and the acid-etched fracture width change rate, are input into the conductivity prediction model to obtain the conductivity prediction results of the acid-etched fractures.

2. The method for predicting conductivity of acid-etched cracks according to claim 1, characterized in that: Before scanning the surface morphology of cracks in rock slabs under different acid etching conditions and obtaining the crack surface width distribution data under different acid etching conditions, the following steps are also included: The stress-strain curves of the rock slabs before and after acid etching were measured by triaxial compression test, and the Young's modulus of the rock was calculated by using the stress-strain curves.

3. The method for predicting conductivity of acid-etched cracks according to claim 1, characterized in that: The acid etching model includes the pressure field distribution function, the acid concentration change function and the acid etching crack width change function, which are as follows: Where, μ represents the viscosity of the acid; p represents the pressure; p e It is expressed as reservoir pressure; represents the average acid concentration; k g represents the mass transfer coefficient; k represents the permeability of the matrix rock; w m represents the length of the acid-etched wormhole; t represents the acid injection time; b represents the crack width.

4. The method for predicting conductivity of acid-etched cracks according to claim 1, characterized in that: The specific flow capacity prediction model is: Among them, C f represents the conductivity of the acid-etched fracture; q represents the acid injection rate; μ represents the acid viscosity; x f Indicates the crack length; h f represents the fracture height; Δp represents the injection pressure difference.

5. A system for predicting conductivity of acid-etched cracks, characterized in that: The system is used in a method for predicting conductivity of acid-etched fractures according to any one of claims 1 to 4, and the system comprises: A data acquisition module is used to scan the surface morphology of cracks in rock slabs under different acid etching conditions and obtain the distribution data of crack surface width under different acid etching conditions; A pressure field data calculation module is used to input the crack surface width distribution data under different acid etching conditions into the acid etching model to calculate the crack pressure field data; The pressure field data updating module is used to determine the rock deformation characteristics under the action of closing pressure according to the rock elastic deformation theory combined with the rock Young's modulus, and to update the fracture pressure field data based on the rock deformation characteristics to obtain updated fracture pressure field data; The conductivity prediction module is used to input the updated fracture pressure field data and the acid concentration change rate and the acid-etched fracture width change rate into the conductivity prediction model to predict the conductivity prediction result of the acid-etched fracture.

6. The acid-etched crack conductivity prediction system according to claim 5, characterized in that: The system also includes: The rock property calculation module is used to obtain the stress-strain curve of the rock plate before and after acid etching using triaxial compression test measurements, and to calculate the Young's modulus of the rock using the stress-strain curve.

7. The acid-etched fracture conductivity prediction system according to claim 5, characterized in that: The acid etching model includes the pressure field distribution function, the acid concentration change function and the acid etching crack width change function, which are as follows: Where, μ represents the viscosity of the acid; p represents the pressure; p e It is expressed as reservoir pressure; represents the average acid concentration; k g represents the mass transfer coefficient; k represents the permeability of the matrix rock; w m represents the length of the acid-etched wormhole; t represents the acid injection time; b represents the crack width.

8. A computer device comprising a system memory and a processor, wherein the system memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 4 are implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 4 are implemented.

10. A computer program product comprising instructions, characterized in that When the instructions are executed by a computer device cluster, the computer device cluster executes the method according to any one of claims 1 to 4.

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