Rock core permeability prediction method and device, electronic equipment and medium

Abstract

The invention discloses a core permeability prediction method and device, electronic equipment and a medium. Relates to the field of petroleum and natural gas exploration and development, and comprises the following steps: establishing a simulation observation system of a digital core, the simulation observation system comprising a skeleton solid layer and a liquid layer; setting attribute parameter information of the liquid layer and the skeleton solid layer; constructing a velocity field according to the skeleton solid layer and the liquid layer after setting the attribute parameter information; an elastic wave model is combined with the velocity field, and a wave equation of the liquid layer is obtained; and solving the wave equation through a rotary staggered finite difference method so as to predict the permeability of the rock core. According to the invention, the technical problems of large error and unstable calculation result of the traditional experimental measurement method in the prior art are solved.

Description

Technical Field

[0001] The present invention relates to the field of oil and gas exploration and development, and particularly to a method, device, electronic device and medium for predicting core permeability. Background Art

[0002] In oil and gas exploration and development, the permeability of rocks is an important parameter. Core permeability refers to the ability of fluids (such as water, oil and gas, etc.) in rocks to pass through rock pores, and it is one of the important parameters for evaluating the properties of rock reservoirs. The size of permeability directly affects the reservoir quality of rocks and the fluid migration ability, and it is a key indicator for evaluating the development potential of oil and gas fields. At present, core permeability is generally measured in the laboratory, with large data errors and instability. Summary of the Invention

[0003] In view of this, it is necessary to provide a method, device, electronic device and medium for predicting core permeability to solve the problems of large data errors and instability in the existing laboratory measurement of core permeability.

[0004] To solve the problems of large data errors and instability in the laboratory measurement of core permeability, the present invention provides a method for predicting core permeability, including: Establishing a simulation observation system for a digital core, the simulation observation system including: a skeleton solid layer and a liquid layer; Setting the attribute parameter information of the liquid layer and the skeleton solid layer; Constructing a velocity field according to the skeleton solid layer and the liquid layer after setting the attribute parameter information; Adopting an elastic wave model in combination with the velocity field to obtain a wave equation of the liquid layer; Solving the wave equation by using the rotated staggered finite difference method to predict the core permeability.

[0005] In a possible implementation manner, the attribute parameter information of the liquid layer includes: Boundary condition parameter information; the boundary condition is that the pressure on the outer surface at the right end of the liquid layer is greater than zero, and the pressure on the outer surface at the left end of the liquid layer is equal to zero.

[0006] In a possible implementation manner, the pressure on the outer surface at the right end is a stable pressure value or a changing pressure value.

[0007] In a possible implementation manner, the attribute parameter information of the skeleton solid layer specifically includes: The grid parameters of the skeleton solid layer, the stress parameters of the skeleton solid layer, the displacement parameters of the skeleton solid layer and the velocity parameters of the skeleton solid layer.

[0008] In a possible implementation manner, constructing a velocity field based on the skeletal solid layer and the liquid layer after setting the attribute parameter information specifically includes: According to the set boundary conditions of the liquid layer; Under the action of the external surface pressure difference of the liquid layer, the liquid displacement and velocity of the liquid layer gradually increase, and then a velocity field is constructed by combining with the stationary skeletal solid layer.

[0009] In a possible implementation manner, solving the wave equation by the rotated staggered finite difference method to predict the core permeability specifically includes: Monitoring the relationship curve of the average flow velocity of the liquid in the liquid layer and time. When the flow velocity of the liquid is stable, the wave equation is solved by the rotated staggered finite difference method to predict the core permeability.

[0010] The present invention also provides a prediction system for core permeability, including: a simulation observation construction module, a parameter setting module, a velocity field construction module, a wave equation establishment module, and a prediction module; The simulation observation construction module is used to establish a simulation observation system of a digital core, and the simulation observation system includes: a skeletal solid layer and a liquid layer; The parameter setting module is used to set the parameter information of the liquid layer and the skeletal solid layer; The velocity field construction module is used to construct a velocity field based on the skeletal solid layer and the liquid layer after setting the attribute parameter information; The wave equation establishment module is used to obtain the wave equation of the liquid layer by using an elastic wave model in combination with the velocity field; The prediction module is used to solve the wave equation by the rotated staggered finite difference method to predict the core permeability.

[0011] The present invention also provides an electronic device, including a memory and a processor, wherein, The memory is used to store a program; The processor is coupled to the memory and is used to execute the program stored in the memory to implement the steps in a prediction method for core permeability according to any of the above solutions.

[0012] The present invention also provides a computer-readable storage medium for storing computer-readable programs or instructions, and when the programs or instructions are executed by a processor, the steps in a prediction method for core permeability according to any of the above solutions can be implemented.

[0013] The beneficial effects of the present invention are as follows: Through the solution of the present invention, the prediction of digital cores with complex material compositions can be processed. The wave equation in this solution takes into account the inertial force of the fluid and also considers the certain compressibility of the real fluid. By solving the permeability based on the wave equation and using it as the permeability parameter in the wave equation of the poroelastic theory, the calculation results are more accurate. Compared with the traditional experimental measurement method, this solution improves the accuracy and robustness of the calculated results of core permeability. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1 It is a schematic flowchart of an embodiment of a method for predicting core permeability provided by the present invention; Figure 2 It is a schematic flowchart of an embodiment of an observation system for simulating digital core permeability provided by the present invention; Figure 3 It is a schematic flowchart of an embodiment of calculating the average flow velocity of a liquid passing through a digital core provided by the present invention; Figure 4 For Figure 1 It is a schematic flowchart of an embodiment of step S102 in Figure 5 For Figure 1 It is a schematic flowchart of an embodiment of step S103 in Figure 6 It is a schematic flowchart of an embodiment of a digital core provided by the present invention; Figure 7 It is a schematic flowchart of an embodiment of the relationship between the flow velocity and time of a digital core provided by the present invention; Figure 8 It is a structural framework diagram of an embodiment of a device for predicting core permeability provided by the present invention; Figure 9 It is a schematic structural diagram of an embodiment of an electronic device provided by the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0015] The principles and features of the present invention will be described below with reference to the accompanying drawings. The embodiments given are only for explaining the present invention and are not intended to limit the scope of the present invention.

[0016] As Figure 1 shown, a specific embodiment of the present invention discloses a method for predicting core permeability. As Figure 1 shown, it includes: It should be noted that core permeability refers to the ability of a rock to allow a fluid to pass through under a certain pressure difference. It is one of the important parameters for evaluating the properties of rock reservoirs and directly affects the reservoir quality and fluid migration ability of the rock. The measurement of permeability is of great significance for evaluating the development potential of oil and gas fields.

[0017] S101. Establish a simulation observation system for digital core. The simulation observation system includes: a skeleton solid layer and a liquid layer; Digital core technology is an effective method for core analysis that has emerged in recent years and is widely used in core analysis fields such as conventional sandstone and carbonate. Its basic principle is based on CT scan images of the core, using computer image processing technology, and completing digital core reconstruction through a certain algorithm to analyze properties such as reservoir rock reservoir attributes based on the constructed digital core.

[0018] S102. Set the attribute parameter information of the liquid layer and the skeleton solid layer; S103. Construct a velocity field based on the skeleton solid layer and the liquid layer after setting the attribute parameter information. It should be noted that in a certain embodiment, the process of constructing the observation system and the velocity field may include: Regardless of how complex the material composition of the digital core is, it is divided into two parts in the simulation, one is the skeleton solid and the other is the pore liquid. When simulating permeability, it is necessary to establish a numerical simulation observation system, such as Figure 2 the observation system for digital core permeability simulation shown. Assume that the x-axis direction is the permeability calculation direction. Add two layers of pure liquid layers outside the left and right end faces of the digital core. In a certain embodiment, the thickness can be 50 grids. Apply a pressure boundary condition on the outer surface of the liquid layer. The pressure on the right end surface is greater than zero, and the pressure on the left end surface is equal to zero. The pressure on the right end boundary can be a stable value, such as 10000 Pa, or it can increase from zero to a stable value over a period of time, such as increasing from zero to 10000 Pa after 10 μs. In the digital core, the skeleton grid is a rigid grid, and the stress, displacement, and velocity are always zero in the simulation. The displacement and velocity of the liquid start to increase from 0 under the action of the pressure difference between the left and right end faces and tend to establish a stable velocity field.

[0019] It should be noted that the velocity field is a physical field composed of velocity vectors at each moment and each point. Taking a fluid as an example, the velocity field refers to the vector velocity distribution at the fluid flow front. The state of the fluid velocity vector distribution at all points in space at the same moment.

[0020] The velocity field describes the motion velocity of the fluid at different positions. In the velocity field, we can observe that the fluid at different positions has different velocity magnitudes and directions. The velocity field can be represented by a vector function, where the magnitude of the velocity vector represents the magnitude of the velocity, and the direction of the velocity vector represents the direction of the velocity.

[0021] In fluid motion, the velocity field is usually determined by the macroscopic motion of the fluid and its interactions with the surrounding fluid and solids. The properties of the velocity field can reflect the flow state of the fluid, such as whether the fluid is stable and whether there are vortices. By analyzing the velocity field, we can understand the motion laws of the fluid and then carry out fluid control and optimization design.

[0022] S104. Using the elastic wave model in combination with the velocity field to obtain the wave equation of the liquid layer; it should be noted that in a certain embodiment, S104 may specifically include: under the action of an external pressure difference, the displacement and velocity of the liquid in the liquid layer increase from 0 and tend to establish a stable velocity field. This motion is a real physical process, which is realized by solving the elastic wave equation. Since the skeletal solid always remains stationary, there is no need to solve the wave equation of the solid. The constitutive relation of the fluid is: , (1) where represents the stress of the fluid, represents the pressure of the fluid; and represent the strain; represents the viscosity coefficient of the liquid; represents the Kronecker function, . The corresponding relationship between the dummy index and the coordinate axis letter is: .

[0023] The motion equation is: (2) where represents the density of the medium represented by the grid, that is, the density of the liquid; represents the second-order time derivative of the displacement in the i direction; represents the stress the spatial derivative along the j direction.

[0024] The wave equations (1) and (2) are solved using the rotated staggered finite difference method. Solving equations (1) and (2) is a time iteration process. At each time step in the iteration process, calculate the average velocity along the x-axis direction of the liquid layer at the left end of the numerical model and the average pressure , where the schematic diagram of calculating the average flow velocity of the liquid passing through the digital core is as shown in Figure 3 , at the position shown by the dashed box in the figure. In a certain embodiment, the liquid pressure can be a value given externally, and it can be directly used without calculation, or obtained through calculation.

[0025] Solving for permeability based on the wave equation, which is used for the permeability parameter in the wave equation in poroelastic theory, is more accurate. It can also be used for modeling the poroelastic model of porous media, and this modeling process requires permeability. The permeability calculated by the method of this solution is more accurate and has higher precision.

[0026] S105. Solve the wave equation by the rotated staggered finite difference method to predict the core permeability. In one embodiment, predicting the core permeability may include: During the numerical simulation process, monitor the relationship curve of the average flow velocity versus time. When the flow velocity value is stable, end the numerical simulation calculation. Calculate the permeability with the stable flow velocity value: .(3) where is the permeability; represents the length of the digital core along the x-axis direction; represents the stable flow velocity value, which is the last data point of the - time relationship curve.

[0027] It should be noted that in the lattice Boltzmann simulation, the selection of model parameters plays a crucial role in the accuracy of the simulation results. The setting of these parameters needs to be based on rich experience or reliable experimental data. Once the selection is improper, it may lead to deviations or inaccuracies in the simulation results. In addition, the calculation accuracy and stability of the lattice Boltzmann simulation are also deeply affected by various factors. In order to ensure the accuracy and stability of the simulation results, these factors need to be carefully calibrated and adjusted during the simulation process. Compared with solving the naiver - stokes equation, the wave equation of this solution takes into account the inertial force of the fluid and also takes into account the certain compressibility of the real fluid.

[0028] Solving for permeability based on the wave equation, which is used for the permeability parameter in the wave equation in poroelastic theory, the calculation result is more accurate.

[0029] Preferably, in one of the above embodiments, the attribute parameter information of the liquid layer specifically includes: Boundary condition parameter information; the boundary condition is that the pressure on the outer surface at the right end of the liquid layer is greater than zero, and the pressure on the outer surface at the left end of the liquid layer is equal to zero. It should be noted that the boundary condition can be a pressure boundary condition. In one embodiment, a pressure boundary condition is loaded on the outer surface of the liquid layer. The pressure on the right end surface is greater than zero, and the pressure on the left end surface is equal to zero.

[0030] Preferably, in one of the above embodiments, the attribute parameter information of the skeletal solid layer includes: The grid parameters, stress parameters, displacement parameters, and velocity parameters of the skeletal solid layer. It should be noted that in a certain implementation, for the skeletal solid layer, in a digital core, the skeletal grid can be a rigid grid, and in the simulation, the stress, displacement, and velocity of the skeletal solid layer are always zero.

[0031] Preferably, in a certain above-mentioned embodiment, as Figure 4 shown, set the attribute parameter information of the liquid layer and the skeletal solid layer, specifically including: S401. Set the boundary conditions of the liquid layer; it should be noted that in a certain embodiment, the boundary conditions are that the pressure on the outer surface of the right end of the liquid layer is greater than zero, and the pressure on the outer surface of the left end of the liquid layer is equal to zero. The pressure on the outer surface of the right end is a stable pressure value or a changing pressure value.

[0032] S402. Setting the grid parameters, stress parameters, displacement parameters, and velocity parameters of the skeletal solid layer specifically includes: setting the skeletal solid layer as a rigid grid, and the stress, displacement, and velocity of the skeletal solid layer are respectively zero.

[0033] Preferably, in a certain above-mentioned embodiment, as Figure 5 shown, construct a velocity field based on the skeletal solid layer and the liquid layer after setting the attribute parameter information, specifically including: It should be noted that the velocity field is a physical field composed of velocity vectors at each moment and each point. Taking a fluid as an example, the velocity field refers to the vector velocity distribution at the fluid flow front. The state of the fluid velocity vector distribution at all points in space at the same moment.

[0034] S501. According to the set boundary conditions of the liquid layer; S502. Under the action of the pressure difference on the outer surface of the liquid layer, the liquid displacement and velocity of the liquid layer gradually increase, and then combine with the stationary skeletal solid layer to construct a velocity field. The velocity field describes the motion velocity of the fluid at different positions. In the velocity field, we can observe that the fluid at different positions has different velocity magnitudes and directions. The velocity field can be represented by a vector function, where the magnitude of the velocity vector represents the magnitude of the velocity, and the direction of the velocity vector represents the direction of the velocity.

[0035] In fluid motion, the velocity field is usually determined by the macroscopic motion of the fluid and the interaction with the surrounding fluid and solids. The properties of the velocity field can reflect the flow state of the fluid, such as whether the fluid is stable, whether there are vortices, etc.

[0036] Preferably, in a certain above-mentioned embodiment, solving the wave equation by the rotated staggered finite difference method to predict the core permeability specifically includes: Monitor the relationship curve of the average flow velocity of the liquid in the liquid layer with time. When the flow velocity of the liquid is stable, solve the wave equation by the rotated staggered finite difference method to predict the core permeability.

[0037] In one embodiment, the example digital core is shown in Figure 6 . The length of the digital core in the x-axis direction is 300 grids, and the lengths in the other two directions are 100 grids. The grid length is 5 microns.

[0038] It should be noted that, in another embodiment, as Figure 7 shown in the relationship diagram of the flow velocity of the digital core with time, it is the relationship between the average flow velocity of the liquid in the x-axis direction obtained by numerical simulation and time. Using the last value of this curve, the finally calculated permeability is about 0.16 D.

[0039] In one embodiment, as Figure 8 shown, a prediction device 800 for core permeability includes: a simulation observation construction module 801, a parameter setting module 802, a velocity field construction module 803, a wave equation establishment module 804, and a prediction module 805; The simulation observation construction module 801 is used to establish a simulation observation system for the digital core, and the simulation observation system includes: a skeleton solid layer and a liquid layer; The parameter setting module 802 is used to set the parameter information of the liquid layer and the skeleton solid layer; The velocity field construction module 803 is used to construct a velocity field according to the skeleton solid layer and the liquid layer after setting the attribute parameter information; The wave equation establishment module 804 is used to obtain the wave equation of the liquid layer by using an elastic wave model in combination with the velocity field; The prediction module 805 is used to solve the wave equation by the rotated staggered finite difference method to predict the core permeability.

[0040] The prediction device 800 for core permeability provided in the above embodiment can implement the technical solutions described in the above embodiment of the prediction method for core permeability. For the specific implementation principles of the above modules or units, reference can be made to the corresponding content in the above embodiment of the prediction method for core permeability, which will not be elaborated here.

[0041] As Figure 9 shown, the present invention also correspondingly provides an electronic device 900. The electronic device 900 includes a processor 901, a memory 902, and a display 903. Figure 9 Only some components of the electronic device 900 are shown, but it should be understood that it is not required to implement all the shown components, and more or fewer components can be alternatively implemented.

[0042] The memory 902 may be an internal storage unit of the electronic device 900 in some embodiments, such as a hard disk or memory of the electronic device 900. The memory 902 may also be an external storage device of the electronic device 900 in other embodiments, such as a plug-in hard disk equipped on the electronic device 900, a Smart Media Card (SMC), a Secure Digital (SD) card, a Flash Card, etc.

[0043] Furthermore, the memory 902 may include both an internal storage unit and an external storage device of the electronic device 900. The memory 902 is used to store application software installed on the electronic device 900 and various types of data.

[0044] The processor 901 may be a central processing unit (CPU), a microprocessor, or other data processing chips in some embodiments, and is used to run program codes stored in the memory 902 or process data, such as a method for predicting core permeability in the present invention.

[0045] The display 903 may be an LED display, a liquid crystal display, a touch liquid crystal display, and an OLED (Organic Light-Emitting Diode) toucher, etc. in some embodiments. The display 903 is used to display information on the electronic device 900 and to display a visual user interface. The components 901-903 of the electronic device 900 communicate with each other through a system bus.

[0046] In some embodiments of the present invention, when the processor 901 executes the core permeability prediction program in the memory 902, the following steps may be implemented: Establish a simulation observation system for a digital core, and the simulation observation system includes: a skeleton solid layer and a liquid layer; Set parameter information of the liquid layer and the skeleton solid layer; Construct a velocity field based on the skeleton solid layer and the liquid layer after setting the attribute parameter information; Adopt an elastic wave model in combination with the velocity field to obtain a wave equation of the liquid layer; Solve the wave equation by the rotated staggered finite difference method to predict the core permeability.

[0047] It should be understood that when the processor 901 executes the core permeability prediction program in the memory 902, in addition to the above functions, other functions may also be implemented. For specific details, reference may be made to the description of the corresponding method embodiments above.

[0048] Furthermore, the embodiments of the present invention do not specifically limit the type of the mentioned electronic device 900. The electronic device 900 may be a mobile phone, a tablet computer, a personal digital assistant (PDA), a wearable device, a laptop, or other portable electronic devices. Exemplary embodiments of the portable electronic device include, but are not limited to, portable electronic devices equipped with IOS, Android, Microsoft, or other operating systems. The above portable electronic devices may also be other portable electronic devices, such as a laptop with a touch-sensitive surface (e.g., a touch panel). It should also be understood that in some other embodiments of the present invention, the electronic device 900 may not be a portable electronic device, but a desktop computer with a touch-sensitive surface (e.g., a touch panel).

[0049] On the other hand, the present invention also provides a non-transitory computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, it is configured to execute a method for predicting the core permeability provided by the above various methods. The method includes: establishing a simulation observation system for a digital core, where the simulation observation system includes: a skeleton solid layer and a liquid layer; setting parameter information of the liquid layer and the skeleton solid layer; constructing a velocity field based on the skeleton solid layer and the liquid layer after setting the attribute parameter information; using an elastic wave model in combination with the velocity field to obtain a wave equation of the liquid layer; and solving the wave equation by the rotated staggered finite difference method to predict the core permeability.

[0050] Those skilled in the art can understand that all or part of the processes for implementing the methods of the above embodiments can be completed by instructing relevant hardware through a computer program, and the program can be stored in a computer-readable storage medium. Among them, the computer-readable storage medium is a disk, an optical disc, a read-only memory, or a random access memory, etc.

[0051] The above has introduced in detail a method, a device, an electronic device, and a medium for predicting the core permeability provided by the present invention. Specific examples are used in this article to elaborate on the principle and implementation manner of the present invention. The description of the above embodiments is only used to help understand the method and its core idea of the present invention; at the same time, for those skilled in the art, based on the idea of the present invention, there will be changes in the specific implementation manner and application scope. In summary, the content of this specification should not be construed as a limitation to the present invention.

Claims

1. A method for predicting core permeability, characterized in that: include: Establishing a simulation observation system of a digital core, the simulation observation system comprising: a skeleton solid layer and a liquid layer; Setting property parameter information of the liquid layer and the skeleton solid layer; Constructing the velocity field according to the skeleton solid layer and liquid layer after setting the attribute parameter information; Using an elastic wave model in combination with the velocity field, a wave equation of the liquid layer is obtained; The wave equation is solved by rotating staggered finite difference method to predict the core permeability.

2. A method for predicting core permeability according to claim 1, characterized in that: The property parameter information of the liquid layer specifically includes: Boundary condition parameter information; the boundary condition is that the pressure on the right end outer surface of the liquid layer is greater than zero, and the pressure on the left end outer surface of the liquid layer is equal to zero.

3. A method for predicting core permeability according to claim 2, characterized in that: The pressure on the outer surface of the right end is a stable pressure value or a changing pressure value.

4. A method for predicting core permeability according to claim 2 or 3, characterized in that: The attribute parameter information of the skeleton solid layer includes: The mesh parameters of the skeleton solid layer, the stress parameters of the skeleton solid layer, the displacement parameters of the skeleton solid layer and the velocity parameters of the skeleton solid layer.

5. A method for predicting core permeability according to claim 4, characterized in that: The constructing of the velocity field according to the skeleton solid layer and the liquid layer after setting the attribute parameter information specifically includes: According to the boundary conditions of the liquid layer set; Under the effect of the pressure difference on the outer surface, the liquid displacement and velocity of the liquid layer gradually increase, and then the velocity field is constructed in combination with the stationary skeleton solid layer.

6. A method for predicting core permeability according to claim 1, characterized in that: The method of solving the wave equation by the rotating staggered finite difference method to predict the core permeability specifically includes: The relationship curve between the average flow rate of the liquid in the liquid layer and time is monitored. When the flow rate of the liquid is stable, the wave equation is solved by the rotating staggered finite difference method to predict the core permeability.

7. A device for predicting core permeability, characterized in that: include: Simulation observation building module, parameter setting module, velocity field building module, wave equation building module and prediction module; The simulation observation construction module is used to establish a simulation observation system of a digital core, and the simulation observation system includes: a skeleton solid layer and a liquid layer; The parameter setting module is used to set parameter information of the liquid layer and the skeleton solid layer; The velocity field construction module is used to construct a velocity field according to the skeleton solid layer and the liquid layer after setting the attribute parameter information; The wave equation building module is used to obtain the wave equation of the liquid layer by combining the elastic wave model with the velocity field; The prediction module is used to solve the wave equation by rotating staggered finite difference method to predict the core permeability.

8. A core permeability prediction device according to claim 7, characterized in that: The parameter setting module is specifically used to set the boundary conditions of the liquid layer; the boundary conditions are that the pressure on the right end outer surface of the liquid layer is greater than zero, and the pressure on the left end outer surface of the liquid layer is equal to zero.

9. An electronic device, characterized in that: comprising a memory and a processor, wherein: The memory is used to store programs; The processor is coupled to the memory and is used to execute the program stored in the memory to implement the steps in the method for predicting core permeability as described in any one of claims 1 to 6 above.

10. A computer-readable storage medium, characterized in that: Used to store computer-readable programs or instructions, which, when executed by a processor, can implement the steps of a method for predicting core permeability as described in any one of claims 1 to 6.

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