Simulation method, device, medium and equipment for solute superdiffusion in fracture channel

Abstract

The present invention provides a simulation method, device, medium and equipment for solute superdiffusion in a fracture channel, the method comprising: obtaining convection parameters and superdiffusion coefficients of the target area based on a tracer experiment in the target area; constructing a convection-diffusion model of the target area according to the convection parameters and superdiffusion coefficients; determining the spatial scale of the convection-diffusion model according to the tracer experiment; determining the number of spatial points in the target area based on the spatial scale; and analyzing and predicting the solute concentration in the target area based on the number of spatial points and the convection-diffusion model. The method constructs a convection-diffusion model of the target area based on a tracer experiment in the target area, determines the spatial scale using the characteristics of the model itself, and completes the division of the spatial grid, thereby analyzing and predicting the solute concentration in the target area through the number of spatial points and the convection-diffusion model, and realizing the simulation of the solute superdiffusion process.

Description

Technical Field

[0001] The present invention relates to the technical field of engineering simulation and numerical simulation, and in particular to a simulation method, device, medium and equipment for solute superdiffusion in a fracture channel. Background Art

[0002] Due to the inhomogeneous and anisotropic characteristics of the medium structure in nature, there are often fracture channels. The solute migration process in the fracture channel often manifests as superdiffusion phenomenon. The classical solute migration model is difficult to describe the non-locality of solute migration in the medium with fracture structure. Fractional derivatives are a type of convolution differential operator, which is often used to establish diffusion models to describe the early arrival phenomenon of solute particles.

[0003] In the related technology, the convolution calculation that characterizes the global correlation characteristics leads to a large amount of calculation after spatial discretization, which increases the difficulty of applying the model, and reduces the accuracy of the calculation results due to the increase in the amount of calculation. Summary of the invention

[0004] Therefore, the technical problem to be solved by the present invention is to overcome the defect in the prior art that the accuracy of the solute superdiffusion simulation results cannot be guaranteed, thereby providing a simulation method, device, medium and equipment for solute superdiffusion in a fracture channel.

[0005] In a first aspect, an embodiment of the present invention provides a method for simulating solute superdiffusion in a fracture channel, comprising: obtaining convection parameters and superdiffusion coefficients of the target area based on a tracer experiment in the target area; constructing a convection-diffusion model of the target area according to the convection parameters and superdiffusion coefficients; determining the spatial scale of the convection-diffusion model according to the tracer experiment;

[0006] Based on the spatial scale, the number of spatial distribution points in the target area is determined; based on the number of spatial distribution points and the convection-diffusion model, the solute concentration in the target area is analyzed and predicted.

[0007] In combination with the first aspect, in a possible implementation of the first aspect, the spatial scale of the convection-diffusion model is determined based on tracer experiments, including: determining parameters of the convection-diffusion model related to the spatial scale based on the tracer experiments; determining the spatial scale of the convection-diffusion model based on the parameters related to the spatial scale.

[0008] In combination with the first aspect, in another possible implementation of the first aspect, parameters of the convection-diffusion model related to the spatial scale are determined based on tracer experiments, including: determining the fracture development of the underground aquifer based on the tracer experiments; determining the parameters of the convection-diffusion model related to the spatial scale based on the fracture development.

[0009] In combination with the first aspect, in another possible implementation of the first aspect, the spatial point number of the target area is determined based on the spatial scale, including: calculating the first solute concentration based on a preset first spatial point number and a convection-diffusion model; determining the second spatial point number based on a preset spatial point coefficient and the first spatial point number; calculating the second solute concentration based on the second spatial point number and the convection-diffusion model; determining a first deviation value between the calculation results based on the first solute concentration and the second solute concentration; when the first deviation value meets a preset deviation threshold, using the second spatial point number as the spatial point number of the target area.

[0010] In combination with the first aspect, in another possible implementation of the first aspect, the simulation method of solute superdiffusion in a fracture channel also includes: when the first deviation value does not meet the preset deviation threshold, determining a third spatial distribution point number based on a preset spatial distribution point coefficient and the second spatial distribution point number; calculating a third solute concentration based on the third spatial distribution point number and a convection-diffusion model; determining a second deviation value between the calculation results based on the second solute concentration and the third solute concentration; and when the second deviation value meets the preset deviation threshold, using the third spatial distribution point number as the spatial distribution point number of the target area.

[0011] In combination with the first aspect, in another possible implementation manner of the first aspect, the convection-diffusion model of the target area is expressed by the following formula:

[0012]

[0013] Where c represents the solute concentration, t represents the time, x represents the spatial position, l represents the left endpoint of the spatial position, A represents the convection parameter, d represents the superdiffusion coefficient, and α represents the spatial fractional order. is the symbol of the spatial fractional derivative.

[0014] In combination with the first aspect, in another possible implementation manner of the first aspect, the spatial fractional derivative is expressed by the following formula:

[0015]

[0016] Among them, Γ represents the gamma function, ξ represents the spatial variable, and x1 represents the current position.

[0017] In the second aspect, an embodiment of the present invention provides a simulation device for solute superdiffusion in a fracture channel, comprising: an acquisition unit, used to acquire convection parameters and superdiffusion coefficients of a target area based on a tracer experiment in the target area; a convection-diffusion model construction unit, used to construct a convection-diffusion model of the target area according to the convection parameters and superdiffusion coefficients; a spatial scale determination unit, used to determine the spatial scale of the convection-diffusion model according to the tracer experiment; a spatial point number determination unit, used to determine the number of spatial points in the target area based on the spatial scale; and an analysis and prediction unit, used to analyze and predict the solute concentration in the target area based on the number of spatial points and the convection-diffusion model.

[0018] In a third aspect, an embodiment of the present invention provides a computer-readable storage medium, which stores computer instructions. When the computer instructions are executed by a processor, a simulation method for solute superdiffusion in a fracture channel as in any embodiment of the first aspect is implemented.

[0019] In a fourth aspect, an embodiment of the present invention provides a computer device, comprising at least one processor; and a memory communicatively connected to the at least one processor; the memory stores computer program instructions, and when the instructions are executed by the at least one processor, a method for simulating solute superdiffusion in a fracture channel as in any embodiment of the first aspect is implemented.

[0020] The technical solution of the present invention has the following advantages:

[0021] The present invention provides a method, device, medium and equipment for simulating solute superdiffusion in a fracture channel. The method constructs a convection-diffusion model of the target area based on a tracer experiment in the target area, and uses the characteristics of the model itself to determine the spatial scale and complete the division of the spatial grid. Therefore, the solute concentration in the target area is analyzed and predicted through the number of spatial points and the convection-diffusion model, thereby realizing the simulation of the solute superdiffusion process. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] In order to more clearly illustrate the specific implementation methods of the present invention or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some implementation methods of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0023] Figure 1 A flowchart of a specific example of a method for simulating solute superdiffusion in a fracture channel provided by an embodiment of the present invention;

[0024] Figure 2An example diagram of spatial scale conversion for a simulation method of solute superdiffusion in a fracture channel provided by an embodiment of the present invention;

[0025] Figure 3 An example diagram of analysis and prediction results of a simulation method for solute superdiffusion in a fracture channel provided by an embodiment of the present invention;

[0026] Figure 4 A principle block diagram of a specific example of a simulation device for solute superdiffusion in a fracture channel provided by an embodiment of the present invention;

[0027] Figure 5 A diagram showing an example structure of a computer device provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0028] The technical solution of the present invention will be described clearly and completely below in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0029] In the description of the present invention, it should be noted that the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", etc., indicating the orientation or positional relationship, are based on the orientation or positional relationship shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, the terms "first", "second", and "third" are used for descriptive purposes only, and cannot be understood as indicating or implying relative importance.

[0030] In addition, the technical features involved in the different embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0031] This embodiment provides a simulation method for solute superdiffusion in a fracture channel. Figure 1 As shown, including:

[0032] S101. Based on the tracer experiment in the target area, obtain the convection parameters and superdiffusion coefficient of the target area.

[0033] Specifically, the convection parameters of the target area are used to characterize the flow velocity of the water body in the target area, and the superdiffusion coefficient is used to characterize the superdiffusion velocity of the solute, wherein the convection parameters can be obtained through monitoring, and the superdiffusion coefficient is obtained by parameter inversion. It should be understood that obtaining the superdiffusion coefficient data of the target area by parameter inversion is a relatively mature technology, and the present invention will not go into details therein.

[0034] In practical applications, the tracer experiment in the target area can be a double-well injection experiment or other tracer experiment for the target area. As long as the development of the fracture channel in the target area can be determined through the tracer experiment, the present invention does not make specific limitations on this. The development of the fracture channel in the target area refers to the phenomenon that the solute enters the underground aquifer with water, and the solute is retained due to the presence of fractures in the channel. In practical applications, the more developed the fractures in the target area, the more obvious the retention phenomenon. The retention phenomenon refers to the phenomenon that in the process of the aquifer power plant, due to various physical, chemical and biological effects, the solute migration is different from the groundwater around the solute, resulting in solute lag.

[0035] S102. Construct a convection-diffusion model of the target area according to the convection parameters and the superdiffusion coefficient.

[0036] In an optional implementation, the convection-diffusion model of the target area is expressed by the following formula:

[0037]

[0038] Where c represents the solute concentration, t represents the time, x represents the spatial position, l represents the left endpoint of the spatial position, A represents the convection parameter, d represents the superdiffusion coefficient, and α represents the spatial fractional order. is the symbol of the spatial fractional derivative.

[0039] In an optional implementation, the spatial fractional derivative is expressed by the following formula:

[0040]

[0041] Among them, Γ represents the gamma function, ξ represents the spatial variable, and x1 represents the current position.

[0042] In practical applications, the spatial position represents the spatial distance corresponding to the target area, l represents the left endpoint of the spatial position, and r represents the right endpoint of the spatial position, that is, the simulation area length of the convection-diffusion model of the target area is rl, and l<x1<r. The value range of α is 1<α≤2.

[0043] S103. Determine the spatial scale of the convection-diffusion model based on tracer experiments.

[0044] Specifically, the process of determining the spatial scale of the convection-diffusion model is the process of calibrating the parameters related to the spatial scale through the measurement data in the tracer experiment, where the parameter related to the spatial scale is the spatial fractional order in the convection-diffusion model of the target area. This process is to determine the crack development in the target area through the measurement data of the tracer experiment, and determine the spatial fractional order, that is, the parameter related to the spatial scale, based on the correspondence between the crack development in the target area and the spatial fractional order, and then determine the spatial scale of the convection-diffusion model through the spatial fractional order. In this way, the parameters that reflect the physical characteristics of the model itself are used to determine the spatial scale that is suitable for the convection-diffusion model of the target area without increasing the parameters, that is, to complete the division of the spatial grid.

[0045] S104. Determine the number of spatial distribution points in the target area based on the spatial scale.

[0046] Specifically, determining the number of spatial points in the target area refers to the process of determining the number of spatial points that is compatible with the convection-diffusion model of the target area by calculating the deviation value after introducing a new spatial scale.

[0047] S105. Analyze and predict the solute concentration in the target area based on the spatial distribution point number and the convection-diffusion model.

[0048] Specifically, based on the number of spatial points and the convection-diffusion model, analyzing and predicting the solute concentration in the target area means discretizing the convection-diffusion model of the target area according to the determined number of spatial points, and solving the discretized convection-diffusion model through the finite difference method of partial differential equations to determine the solute concentration in the target area.

[0049] By implementing this embodiment, based on the tracer experiment in the target area, a convection-diffusion model of the target area is constructed, and the spatial scale is determined by using the characteristics of the model itself to complete the division of the spatial grid. Therefore, the solute concentration in the target area is analyzed and predicted through the spatial point number and the convection-diffusion model, thereby realizing the simulation of the solute superdiffusion process.

[0050] In an optional implementation manner, the process of step S103 specifically includes:

[0051] (1) Based on tracer experiments, determine the parameters of the convection-diffusion model that are related to the spatial scale.

[0052] Specifically, the process of determining the parameters of the convection-diffusion model related to the spatial scale is the process of determining the fractional order of the convection-diffusion model based on the measurement data or historical data of the tracer experiment.

[0053] In an optional embodiment, the process of determining the parameters related to the spatial scale of the convection-diffusion model according to the tracer experiment specifically includes:

[0054] Based on the tracer experiment, the fracture development of the underground aquifer was determined.

[0055] According to the development of fractures, the parameters related to the spatial scale of the convection-diffusion model are determined.

[0056] Specifically, determining the development of fractures in underground aquifers based on tracer experiments means determining whether the retention of solutes after entering underground aquifers is obvious through the measurement data or historical data of tracer experiments. The more obvious the retention is, that is, the more obvious the solute lag is, the more developed the fractures in the underground aquifers in the target area are.

[0057] Specifically, according to the development of cracks, determining the parameters related to the spatial scale of the convection-diffusion model means determining the value of the fractional order of the convection-diffusion model according to the correspondence between the development of cracks and the parameters related to the spatial scale, that is, the correspondence between the development of cracks and the fractional order. The more developed the cracks, the smaller the fractional order.

[0058] (2) Determine the spatial scale of the convection-diffusion model based on parameters related to the spatial scale.

[0059] Specifically, determining the spatial scale of the convection-diffusion model according to the parameters related to the spatial scale includes: determining the scale transformation parameters according to the parameters related to the spatial scale; according to the scale transformation parameters, spatially distributing points uniformly in the Hausdroff dimension, and mapping the spatial distribution points in the Hausdroff dimension to the dimension of the Euclidean space, that is, mapping to the dimension of the flat space.

[0060] Specifically, the scale transformation parameters are expressed by the following formula:

[0061] β=α-1

[0062] Among them, β represents the scale transformation parameter.

[0063] Specifically, according to the scale transformation parameter, spatially uniformly distributing points in the Hausdroff dimension means uniformly distributing points in the Hausdroff dimension with a spatial scale of β. At this time, the space is evenly divided under the inherent scale, and the step size is Δx. The spatial distribution of the Hausdroff dimension is mapped to the dimension of the Euclidean space, that is, the points of the Euclidean space dimension are projected to the Hausdroff dimension to complete the transformation of the spatial scale. This process is equivalent to determining the spatial scale of the convection-diffusion model. In practical applications, the schematic diagram of the spatial grid mapping is shown in Figure 2 As shown, this is equivalent to projecting x in Euclidean space into Hausdroff dimension. On, it is completed The relationship between spatial metrics is expressed by the following formula:

[0064]

[0065] In practical applications, after determining the spatial scale of the convection-diffusion model, the discrete form of the spatial fractional derivative can be expressed as:

[0066]

[0067]

[0068] Where m represents the mth point in space. If the number of points in space is M, 0<m<M, j represents the jth point in space, 0<j≤m, and x j represents the position of the jth point in space, τ represents the spatial step length, τ j =x j -x j-1 , ξ represents the spatial variable in the integral, δ j =x m -x j .

[0069] In practical applications, x j The position of the jth point projected to the external space satisfies:

[0070] x j =(jΔx) 1 / β

[0071] By implementing this embodiment, the fracture development of the underground aquifer is determined according to the tracer experiment, and the spatial scale of the convection-diffusion model is determined according to the fracture development. This process is to determine the fracture development of the target area through the measurement data of the tracer experiment, and determine the spatial fractional order according to the corresponding relationship between the fracture development of the target area and the spatial fractional order, that is, the parameter related to the spatial scale, and then determine the spatial scale of the convection-diffusion model through the spatial fractional order. Thus, the parameters of the model itself that reflect the physical characteristics are used to determine the spatial scale that is suitable for the convection-diffusion model of the target area without increasing the parameters, that is, to complete the division of the spatial grid, and provide a data basis for analyzing and predicting the solute concentration in the target area and realizing the simulation of the solute super diffusion process.

[0072] In an optional implementation manner, the process of step S104 specifically includes:

[0073] (1) Based on a preset first spatial point number and a convection-diffusion model, a first solute concentration is calculated.

[0074] In practical applications, the preset number of first spatial distribution points may be 20, 30, 40 or other values, which may be selected according to actual working conditions, and the present invention does not make any specific limitation on this.

[0075] In practical applications, based on the preset first spatial point number and the convection-diffusion model, calculating the first solute concentration means discretizing the convection-diffusion model of the target area according to the preset first spatial point number, and solving the discretized convection-diffusion model by the finite difference method of partial differential equations to obtain the first solute concentration. It should be understood that solving the discretized model by the finite difference method of partial differential equations is a relatively mature technology, and this application will not go into details.

[0076] (2) Determine the second spatial distribution point number based on the preset spatial distribution point coefficient and the first spatial distribution point number.

[0077] In practical applications, the preset spatial distribution coefficient may be 2, 3 or other values, which may be selected according to actual working conditions, and the present invention does not make any specific limitation on this.

[0078] (3) Based on the number of points in the second space and the convection-diffusion model, calculate the second solute concentration.

[0079] In practical applications, based on the second spatial point number and the convection-diffusion model, calculating the second solute concentration means discretizing the convection-diffusion model of the target area according to the second spatial point number, and solving the discretized convection-diffusion model by the finite difference method of partial differential equations to obtain the second solute concentration.

[0080] (4) Determine a first deviation value between the calculation results according to the first solute concentration and the second solute concentration.

[0081] Specifically, the first deviation value is expressed as:

[0082]

[0083] Among them, derror1 represents the first deviation value, result1 represents the first solute concentration, and result2 represents the second solute concentration.

[0084] (5) When the first deviation value meets the preset deviation threshold, the second spatial point number is used as the spatial point number of the target area.

[0085] In practical applications, the preset deviation threshold may be 0.1, 0.2 or other values, which may be selected according to actual working conditions, and the present invention does not make any specific limitation on this.

[0086] In practical applications, the first deviation value satisfying the preset deviation threshold means that the first deviation value is less than the first deviation threshold.

[0087] In an optional embodiment, the method for simulating solute superdiffusion in a fracture channel further includes:

[0088] (1) When the first deviation value does not meet the preset deviation threshold, a third spatial point distribution number is determined based on a preset spatial point distribution coefficient and the second spatial point distribution number.

[0089] (2) Based on the number of points in the third space and the convection-diffusion model, calculate the concentration of the third solute.

[0090] In practical applications, based on the third space point number and the convection-diffusion model, calculating the third solute concentration means discretizing the convection-diffusion model of the target area according to the third space point number, and solving the discretized convection-diffusion model through the finite difference method of partial differential equations to obtain the third solute concentration.

[0091] (3) Determine a second deviation value between the calculation results based on the second solute concentration and the third solute concentration.

[0092] Specifically, the second deviation value is expressed as:

[0093]

[0094] Among them, derror2 represents the first deviation value, and result3 represents the third solute concentration.

[0095] (4) When the second deviation value meets the preset deviation threshold, the third spatial point number is used as the spatial point number of the target area.

[0096] In actual applications, if the second deviation value still does not meet the preset deviation threshold, the fourth spatial distribution point number is determined again based on the third spatial distribution point number and the preset spatial distribution point coefficient, and the fourth solute concentration is calculated and compared with the third deviation value, and so on. The present invention will not be elaborated again.

[0097] In practical applications, assuming that the convection parameter and superdiffusion coefficient of solutes in the river are both 1, the results of 100 uniformly distributed points on a spatial scale with a Hausdroff dimension of 0.4 and 100, 400 and 2000 uniformly distributed points on a normal Euclidean space dimension are compared. The normal Euclidean space dimension of 2000 is used as an approximate exact solution. The closer the solutions of other distribution methods are to the approximate exact solution, the higher the accuracy. Figure 3 The results show that the uniform distribution of points on the spatial scale of Hausdroff dimension significantly improves the calculation accuracy. The calculation accuracy of 100 points is higher than that of 400 points on the normal Euclidean space dimension.

[0098] By implementing this embodiment, the number of points is used as the basis for spatial discretization. Through the preset spatial point coefficient and the preset first spatial point number, the deviation value is calculated to determine the number of spatial points that is compatible with the convection-diffusion model of the target area after the introduction of the new spatial scale, thereby providing a data basis for analyzing and predicting the solute concentration in the target area and realizing the simulation of the solute superdiffusion process.

[0099] This embodiment provides a device based on the solute transport process of the target river, such as Figure 4 As shown, it includes: an acquisition unit 21, a convection-diffusion model construction unit 22, a spatial scale determination unit 23, a spatial point determination unit 24, and an analysis and prediction unit 25.

[0100] The acquisition unit 21 is used to acquire the convection parameters and superdiffusion coefficient of the target area based on the tracer experiment of the target area. The specific process can be referred to the relevant description of step S101 in the above embodiment, which will not be repeated here.

[0101] The convection diffusion model building unit 22 is used to build a convection diffusion model of the target area according to the convection parameters and the super diffusion coefficient. The specific process can be found in the description of step S102 in the above embodiment, which will not be repeated here.

[0102] The spatial scale determination unit 23 is used to determine the spatial scale of the convection-diffusion model according to the tracer experiment. The specific process can be referred to the relevant description of step S103 in the above embodiment, which will not be repeated here.

[0103] The spatial point determination unit 24 is used to determine the number of spatial points in the target area based on the spatial scale. The specific process can be found in the description of step S104 in the above embodiment, which will not be repeated here.

[0104] The analysis and prediction unit 25 is used to analyze and predict the solute concentration in the target area based on the number of spatial points and the convection-diffusion model. The specific process can be found in the description of step S105 in the above embodiment, which will not be repeated here.

[0105] By implementing this embodiment, the convection-diffusion model of the target area is constructed by acquiring the tracer experiment of the target area by the acquisition unit and the convection-diffusion model construction unit, and the spatial scale is determined by the spatial scale determination unit and the spatial point number determination unit using the characteristics of the model itself to complete the division of the spatial grid, so that the solute concentration in the target area is analyzed and predicted based on the spatial point number and the convection-diffusion model by the analysis and prediction unit, thereby realizing the simulation of the solute superdiffusion process.

[0106] One embodiment of the present invention further provides a computer-readable storage medium, which stores computer-executable instructions, and the computer-executable instructions can execute the simulation method based on solute superdiffusion in the fracture channel in any of the above method embodiments. Wherein, the storage medium can be a magnetic disk, an optical disk, a read-only memory (ROM), a random access memory (RAM), a flash memory, a hard disk (HDD) or a solid-state drive (SSD), etc.; the storage medium can also include a combination of the above types of memory.

[0107] An embodiment of the present invention further provides a computer device, such as Figure 5 As shown, Figure 5 It is a structural diagram of a computer device provided by an optional embodiment of the present invention, and the computer device may include at least one processor 31, at least one communication interface 32, at least one communication bus 33 and at least one memory 34, wherein the communication interface 32 may include a display screen (Display), a keyboard (Keyboard), and the optional communication interface 32 may also include a standard wired interface and a wireless interface. The memory 34 may be a high-speed RAM memory (Random Access Memory, volatile random access memory) or a non-volatile memory (non-volatile memory), such as at least one disk storage. The memory 34 may also be at least one storage device located away from the aforementioned processor 31. The processor 31 may be combined with Figure 4 In the described device, the memory 34 stores an application program, and the processor 31 calls the program code stored in the memory 34 to execute the steps of the method for simulating solute superdiffusion in a fracture channel described in any of the above method embodiments.

[0108] The communication bus 33 may be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus. The communication bus 33 may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 5 Only one thick line is used in the diagram, but this does not mean that there is only one bus or only one type of bus.

[0109] Among them, the memory 34 may include a volatile memory (volatile memory), such as a random-access memory (RAM); the memory may also include a non-volatile memory (non-volatile memory), such as a flash memory, a hard disk drive (HDD) or a solid-state drive (SSD); the memory 34 may also include a combination of the above types of memory.

[0110] The processor 31 may be a central processing unit (CPU), a network processor (NP) or a combination of a CPU and a NP.

[0111] The processor 31 may further include a hardware chip. The hardware chip may be an application-specific integrated circuit (ASIC), a programmable logic device (PLD) or a combination thereof. The PLD may be a complex programmable logic device (CPLD), a field-programmable gate array (FPGA), a generic array logic (GAL) or any combination thereof.

[0112] Optionally, the memory 34 is also used to store program instructions. The processor 31 can call the program instructions to implement the simulation method of solute superdiffusion in a fracture channel described in any embodiment of the present invention.

[0113] Obviously, the above embodiments are merely examples for the purpose of clear explanation, and are not intended to limit the implementation methods. For those skilled in the art, other different forms of changes or modifications can be made based on the above description. It is not necessary and impossible to list all the implementation methods here. The obvious changes or modifications derived therefrom are still within the scope of protection of the invention.

Claims

1. A method for simulating solute superdiffusion in a fracture channel, characterized in that: The method comprises: Based on the tracer experiment in the target area, the convection parameters and superdiffusion coefficient of the target area are obtained; Constructing a convection-diffusion model of a target area according to the convection parameter and the superdiffusion coefficient; Determining the spatial scale of the convection-diffusion model based on the tracer experiment; Based on the spatial scale, determining the number of spatial distribution points of the target area; Analyze and predict the solute concentration in the target area based on the number of spatial distribution points and the convection-diffusion model; The convection-diffusion model of the target area is expressed by the following formula: Where C represents the solute concentration, t represents the time, x represents the spatial position, l represents the left endpoint of the spatial position, A represents the convection parameter, d represents the superdiffusion coefficient, and α represents the spatial fractional order. is the symbol of spatial fractional derivative; The spatial fractional derivative is expressed by the following formula: Among them, Γ represents the gamma function, ξ represents the spatial variable, and x1 represents the current position.

2. The method according to claim 1, characterized in that Determining the spatial scale of the convection-diffusion model according to the tracer experiment includes: Determining parameters of the convection-diffusion model related to spatial scales based on the tracer experiment; The spatial scale of the convection-diffusion model is determined according to the parameters related to the spatial scale.

3. The method according to claim 2, characterized in that Determining parameters of the convection-diffusion model related to the spatial scale according to the tracer experiment includes: Determining the fracture development of the underground aquifer based on the tracer experiment; According to the development of the fractures, the parameters of the convection-diffusion model related to the spatial scale are determined.

4. The method according to claim 1, characterized in that: The determining, based on the spatial scale, the number of spatial distribution points of the target area includes: Calculating a first solute concentration based on a preset first spatial point number and the convection-diffusion model; Determining a second spatial distribution point number based on a preset spatial distribution point coefficient and the first spatial distribution point number; Calculating a second solute concentration based on the second spatial point number and the convection-diffusion model; Determining a first deviation value between calculation results according to the first solute concentration and the second solute concentration; When the first deviation value meets a preset deviation threshold, the second spatial point number is used as the spatial point number of the target area.

5. The method according to claim 4, characterized in that The method further comprises: When the first deviation value does not meet the preset deviation threshold, determining a third spatial point distribution number based on a preset spatial point distribution coefficient and the second spatial point distribution number; Calculating a third solute concentration based on the third spatial point number and the convection-diffusion model; Determining a second deviation value between calculation results according to the second solute concentration and the third solute concentration; When the second deviation value meets a preset deviation threshold, the third spatial point number is used as the spatial point number of the target area.

6. A simulation device for solute superdiffusion in a fracture channel, characterized in that: The device comprises: An acquisition unit, used for acquiring convection parameters and superdiffusion coefficients of a target area based on a tracer experiment in the target area; A convection-diffusion model building unit, used to build a convection-diffusion model of a target area according to the convection parameter and the superdiffusion coefficient; A spatial scale determination unit, used to determine the spatial scale of the convection-diffusion model according to the tracer experiment; A spatial point number determination unit, used to determine the number of spatial points in the target area based on the spatial scale; An analysis and prediction unit, used for analyzing and predicting the solute concentration in the target area based on the number of spatial distribution points and the convection-diffusion model; The convection-diffusion model of the target area is expressed by the following formula: Where C represents the solute concentration, t represents the time, x represents the spatial position, l represents the left endpoint of the spatial position, A represents the convection parameter, d represents the superdiffusion coefficient, and α represents the spatial fractional order. is the symbol of spatial fractional derivative; The spatial fractional derivative is expressed by the following formula: Among them, Γ represents the gamma function, ξ represents the spatial variable, and x1 represents the current position.

7. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, which, when executed by a processor, implement the method for simulating solute superdiffusion in a fracture channel according to any one of claims 1 to 5.

8. A computer device, characterized in that: include: at least one processor; and a memory communicatively coupled to the at least one processor; The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to perform the method for simulating solute superdiffusion in a fracture channel according to any one of claims 1 to 5.

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