CN115577597A - Simulation method, device, medium and equipment for solute hyperdiffusion in fracture channel - Google Patents

Abstract

The invention provides a simulation method, device, medium, and equipment for solute superdiffusion in a crack channel. The method includes: obtaining convection parameters and superdiffusion coefficients of the target area based on a tracer experiment in the target area; according to the convection parameters, Super-diffusion coefficient, construct the convection diffusion model of the target area; according to the tracer experiment, determine the spatial scale of the convection diffusion model; based on the spatial scale, the number of spatial distribution points in the target area; based on the spatial distribution number and the convection diffusion model, analyze and predict the target area Medium solute concentration. Based on the tracer experiment in the target area, the method constructs the convection diffusion model of the target area, and uses the characteristics of the model itself to determine the spatial scale and complete the division of the spatial grid, so as to analyze and predict the target area through the spatial distribution number and the convection diffusion model Medium solute concentration, to realize the simulation of solute superdiffusion process.

Description

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

technical field

The invention relates to the technical field of engineering simulation and numerical simulation, in particular to a simulation method, device, medium and equipment for solute superdiffusion in a crack channel.

Background technique

Due to the non-uniform and anisotropic characteristics of the medium structure in nature, there are often crack channels in it. The migration of solutes in fracture channels often manifests as superdiffusion, and the classical solute migration model is difficult to describe the non-locality of solute migration in media with fracture structures. Fractional derivatives are a kind of convolutional differential operators, which are often used to establish diffusion models and describe the phenomenon of early arrival of solute particles.

In the related technology, the convolution calculation describing the global correlation characteristics leads to a large amount of calculation after the space is discretized, which increases the difficulty of the application of the model, and reduces the accuracy of the calculation result due to the increase of the calculation amount.

Contents of the invention

Therefore, the technical problem to be solved by the present invention is to overcome the defect in the prior art that the accuracy of simulation results of solute superdiffusion cannot be guaranteed, so as to provide a simulation method, device, medium and equipment for solute superdiffusion in crack channels.

In the first aspect, an embodiment of the present invention provides a method for simulating solute superdiffusion in a crack channel, including: obtaining convection parameters and superdiffusion coefficients in the target region based on tracer experiments in the target region; Coefficient, construct the convection-diffusion model of the target area; according to the tracer experiment, determine the spatial scale of the convection-diffusion model;

Based on the spatial scale, determine the number of spatial distribution points in the target area; based on the number of spatial distribution points and the convection-diffusion model, analyze and predict the solute concentration in the target area.

In combination with the first aspect, in a possible implementation of the first aspect, determining the spatial scale of the convection-diffusion model according to the tracer experiment includes: determining the spatial scale-related value of the convection-diffusion model according to the tracer experiment Parameters; according to the parameters related to the spatial scale, the spatial scale of the convection-diffusion model is determined.

In combination with the first aspect, in another possible implementation of the first aspect, according to the tracer experiment, determining the parameters related to the spatial scale of the convection-diffusion model includes: according to the tracer experiment, determining the The development of cracks; according to the development of cracks, determine the parameters related to the spatial scale of the convection-diffusion model.

In combination with the first aspect, in another possible implementation of the first aspect, determining the number of spatial distribution points in the target area based on the spatial scale includes: calculating the first number of spatial distribution points based on the preset first spatial distribution number and the convection diffusion model Solute concentration; based on the preset spatial distribution coefficient and the first spatial distribution number, determine the second spatial distribution number; based on the second spatial distribution number and the convection diffusion model, calculate the second solute concentration; according to the first solute concentration and the second solute concentration Concentration, determine the first deviation value between calculation results; when the first deviation value satisfies the preset deviation threshold, use the second spatial distribution number as the spatial distribution number of the target area.

With reference to the first aspect, in another possible implementation of the first aspect, the method for simulating solute superdiffusion in a crack channel further includes: when the first deviation value does not meet the preset deviation threshold, based on the preset space Determine the number of points in the third space based on the point distribution coefficient and the number of points in the second space; calculate the third solute concentration based on the number of points in the third space and the convection-diffusion model; Two deviation values; when the second deviation value satisfies the preset deviation threshold, the third spatial distribution number is used as the spatial distribution number of the target area.

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

为空间分数阶导数符号。Among them, c represents the solute concentration, t represents time, x represents the spatial position, l represents the left end point of the spatial position, A represents the convection parameter, d represents the superdiffusion coefficient, α represents the spatial fractional order,

is the space fractional derivative symbol.

In combination with the first aspect, in another possible implementation of the first aspect, 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.

In the second aspect, an embodiment of the present invention provides a simulation device for solute superdiffusion in a crack channel, including: an acquisition unit, used for a tracer experiment based on a target area, to acquire convection parameters and superdiffusion coefficients of the target area; convection The diffusion model construction unit is used to construct the convection diffusion model of the target area according to the convection parameters and the super-diffusion coefficient; the spatial scale determination unit is used to determine the spatial scale of the convection diffusion model according to the tracer experiment; the spatial distribution number determination unit, It is used to determine the number of spatial distribution points in the target area based on the spatial scale; the analysis and prediction unit is used to analyze and predict the solute concentration in the target area based on the number of spatial distribution points and the convection-diffusion model.

In a third aspect, an embodiment of the present invention provides a computer-readable storage medium, where computer instructions are stored in the computer-readable storage medium. When the computer instructions are executed by a processor, the solute in the crack channel according to any implementation manner of the first aspect is realized. Simulation methods for superdiffusion.

In a fourth aspect, an embodiment of the present invention provides a computer device, including at least one processor; and a memory connected in communication with the at least one processor; computer program instructions are stored in the memory, and when the instructions are executed by the at least one processor, A method for simulating solute superdiffusion in a crack channel according to any embodiment of the first aspect.

The technical solution of the present invention has the following advantages:

The present invention provides a simulation method, device, medium, and equipment for solute superdiffusion in a crack channel. The method is based on the tracer experiment in the target area, constructs the convection diffusion model of the target area, and uses the characteristics of the model itself to determine the spatial scale , to complete the division of the spatial grid, so as to analyze and predict the solute concentration in the target area through the number of spatial distribution points and the convection-diffusion model, and realize the simulation of the solute super-diffusion process.

Description of drawings

In order to more clearly illustrate the specific implementation of the present invention or the technical solutions in the prior art, the following will briefly introduce the accompanying drawings that need to be used in the specific implementation or description of the prior art. Obviously, the accompanying drawings in the following description The drawings show some implementations of the present invention, and those skilled in the art can obtain other drawings based on these drawings without any creative work.

FIG. 1 is a flow chart of a specific example of a simulation method for solute superdiffusion in a crack channel provided by an embodiment of the present invention;

Fig. 2 is an example diagram of spatial scale transformation of a simulation method of solute superdiffusion in a crack channel provided by an embodiment of the present invention;

Fig. 3 is an example diagram of analysis and prediction results of a simulation method for solute superdiffusion in a crack channel provided by an embodiment of the present invention;

Fig. 4 is a functional block diagram of a specific example of a simulation device for solute superdiffusion in a crack channel provided by an embodiment of the present invention;

Fig. 5 is a structural example diagram of a computer device provided by an embodiment of the present invention.

detailed description

The technical solutions of the present invention will be clearly and completely described below in conjunction with the accompanying drawings. Apparently, the described embodiments are some of the embodiments of the present invention, but not all of them. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

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

In addition, the technical features involved in the different embodiments of the present invention described below may be combined with each other as long as there is no conflict with each other.

This embodiment provides a simulation method for solute superdiffusion in a crack channel, as shown in Figure 1, including:

S101. Acquiring convection parameters and superdiffusion coefficients of the target area based on a tracer experiment in the target area.

Specifically, the convection parameters in 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 speed of the solute. Among them, the convection parameters can be obtained through monitoring, and the superdiffusion coefficient can be obtained through parameter inversion. It should be understood that It is worth noting that it is a relatively mature technology to obtain the super-diffusion coefficient data of the target area through parameter inversion, which will not be repeated in the present invention.

In practical applications, the tracer experiment in the target area can be a double well pumping experiment or other tracer experiments 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 This is not specifically limited. The development of fracture channels in the target area means that the solute enters the underground aquifer with water, and the solute is retained due to the existence of cracks in the channel. In practical application, the more developed the cracks in the target area, the more obvious the stagnation phenomenon will be. The stagnation phenomenon refers to the phenomenon that the solute lags behind due to various physical, chemical and biological effects during the process of the aquifer power plant, which makes the difference between the solute migration and the groundwater around the solute.

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

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

为空间分数阶导数符号。Among them, c represents the solute concentration, t represents time, x represents the spatial position, l represents the left end point of the spatial position, A represents the convection parameter, d represents the superdiffusion coefficient, α represents the spatial fractional order,

is the space fractional derivative symbol.

In an optional implementation, 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.

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

S103. Determine the spatial scale of the convection-diffusion model according to the tracer experiment.

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, wherein the parameters related to the spatial scale are the parameters in the convection-diffusion model of the target area The spatial fractional order of . 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 according to the corresponding relationship between the crack development in the target area and the spatial fractional order, that is, the spatial scale Relevant parameters, and then determine the spatial scale of the convection-diffusion model through the spatial fractional order. Therefore, using the parameters of the model itself to reflect the physical characteristics, the spatial scale that is suitable for the convection and diffusion model of the target area is determined without increasing the parameters, that is, the division of the spatial grid is completed.

S104. Based on the spatial scale, determine the number of spatial distribution points in the target area.

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

S105. Analyze and predict the solute concentration in the target area based on the number of spatial distribution points and the convection-diffusion model.

Specifically, based on the number of spatial distribution points and the convection-diffusion model, the analysis and prediction of the solute concentration in the target area refers to discretizing the convection-diffusion model of the target area according to the determined number of spatial distribution points, and solving the discretized A convective-diffusion model to determine the solute concentration in the target region.

Through the implementation of this embodiment, based on the tracer experiment in the target area, the convection diffusion model of the target area is constructed, and the spatial scale is determined by the characteristics of the model itself, and the division of the spatial grid is completed, so that through the number of spatial distribution points and the convection diffusion model, Analyze and predict the solute concentration in the target area, and realize the simulation of the solute super-diffusion process.

In an optional implementation manner, the process of the above step S103 specifically includes:

(1) According to the tracer experiment, determine the parameters related to the spatial scale of the convection-diffusion model.

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

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

Based on tracer experiments, the development of fractures in underground aquifers was determined.

According to the development of cracks, the parameters related to the spatial scale of the convection-diffusion model are determined.

Specifically, according to the tracer experiment, determining the fracture development of the underground aquifer refers to determining whether the retention phenomenon of solutes entering the underground aquifer is obvious through the measurement data or historical data of the tracer experiment, and the retention phenomenon is more obvious, that is, The more obvious the occurrence of solute lag, the more developed the fractures of the underground aquifer in the target area.

Specifically, according to the development of cracks, determining the parameters related to the spatial scale of the convection-diffusion model refers to the corresponding relationship between the development of cracks and the parameters related to the spatial scale, that is, the corresponding relationship between the development of cracks and the fractional order. The value of the fractional order for the convection-diffusion model. Among them, the more developed the crack, the smaller the fractional order.

(2) Determine the spatial scale of the convection-diffusion model according to the parameters related to the spatial scale.

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; The spatial layout of the dimension is mapped to the dimension of the Euclidean space, that is, mapped to the dimension of the flat space.

Specifically, the scaling parameters are expressed by the following formula:

β=α-1

Among them, β represents the scaling parameter.

上，即完成

的变换，此时空间度量的关系通过如下公式表示：Specifically, according to the scale transformation parameters, uniform distribution of points on the Hausdroff dimension refers to uniform distribution of points on the Hausdroff dimension with a spatial scale of β. At this time, the space is evenly divided under the intrinsic scale, and the step size is Δx. Map the spatial distribution points of Hausdroff dimension to the dimension of Euclidean space, that is, project the points of Euclidean space dimension to Hausdroff dimension to complete the transformation of spatial scale. This process is equivalent to determining the spatial scale of the convection-diffusion model. In practical applications, the schematic diagram of spatial grid mapping is shown in Figure 2, which is equivalent to projecting x from Euclidean space to Hausdroff dimension

up, it's done

The transformation of , at this time, the relationship of spatial metrics is expressed by the following formula:

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:

Among them, m represents the mth point in space. If there are M points in space, 0<m<M, j represents the jth point in space, 0<j≤m, and x _j represents the value of the jth point in space. position, τ represents the spatial step size, τ _j =x _j -x _j-1 , ξ represents the spatial variable within the integral, δ _j =x _m -x _j .

In practical applications, projecting x _j to the position of the jth point in the external space satisfies:

x _j = (jΔx) ^1/β

Through the implementation of this embodiment, according to the tracer experiment, the fracture development of the underground aquifer is determined, and the spatial scale of the convection diffusion model is determined according to the fracture development. This process is to determine the target area through the measurement data of the tracer experiment According to the corresponding relationship between the development of cracks in the target area and the spatial fractional order, determine the spatial fractional order, that is, the parameters related to the spatial scale, and then determine the convection and diffusion model through the spatial fractional order the spatial scale. In order to use the parameters of the model itself to reflect the physical characteristics, determine the spatial scale suitable for the convection-diffusion model of the target area without increasing the parameters, that is, to complete the division of the spatial grid, to analyze and predict the solute concentration in the target area, and to realize the solute concentration in the target area. The simulation of the superdiffusion process provides the data basis.

In an optional implementation manner, the process of the above step S104 specifically includes:

(1) Calculate the first solute concentration based on the preset number of points in the first space and the convection-diffusion model.

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, which is not specifically limited in the present invention.

In practical applications, based on the preset number of points in the first space and the convection-diffusion model, the calculation of the first solute concentration refers to the discretization of the convection-diffusion model in the target area according to the preset number of points in the first space, and through the partial differential equation The finite difference method is used to solve the discretized convection-diffusion model to obtain the first solute concentration. It should be understood that solving the discretized model through the finite difference method of partial differential equations is a relatively mature technology, and this application will not repeat it here.

(2) Based on the preset spatial distribution coefficient and the first spatial distribution number, determine the second spatial distribution number.

In practical applications, the preset spatial distribution coefficient can be 2, 3 or other values, which can be selected according to actual working conditions, which is not specifically limited in the present invention.

(3) Calculate the second solute concentration based on the number of distribution points in the second space and the convection-diffusion model.

In practical applications, based on the number of distribution points in the second space and the convection-diffusion model, calculating the second solute concentration refers to discretizing the convection-diffusion model in the target area according to the number of distribution points in the second space, and solving the discrete After the convection-diffusion model, the second solute concentration is obtained.

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

Specifically, the first deviation value is expressed as:

Wherein, derror1 represents the first deviation value, result1 represents the first solute concentration, and result2 represents the second solute concentration.

(5) When the first deviation value satisfies the preset deviation threshold, the second number of spatial distribution points is used as the number of spatial distribution points of the target area.

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, which is not specifically limited in the present invention.

In practical applications, the first deviation value meeting the preset deviation threshold means that the first deviation value is smaller than the first deviation threshold.

In an optional embodiment, the method for simulating solute superdiffusion in a crack channel further includes:

(1) When the first deviation value does not meet the preset deviation threshold, determine the third number of spatial distribution points based on the preset spatial distribution coefficient and the second number of spatial distribution points.

(2) Calculate the concentration of the third solute based on the number of distribution points in the third space and the convection-diffusion model.

In practical applications, based on the number of distribution points in the third space and the convection-diffusion model, the calculation of the third solute concentration refers to discretizing the convection-diffusion model in the target area according to the number of distribution points in the third space, and solving the discretization by the finite difference method of the partial differential equation After the convection-diffusion model, a third solute concentration is obtained.

(3) Determine a second deviation value between calculation results according to the second solute concentration and the third solute concentration.

Specifically, the second deviation value is expressed as:

Wherein, derror2 represents the first deviation value, and result3 represents the third solute concentration.

(4) When the second deviation value satisfies the preset deviation threshold, the third spatial distribution number is used as the spatial distribution number of the target area.

In practical applications, if the second deviation value does not meet the preset deviation threshold, the number of distribution points in the fourth space is determined again based on the number of distribution points in the third space and the preset coefficient of distribution points in the space, and the concentration of the fourth solute is calculated and compared with that in the first space. The three deviation values can be deduced by analogy, and the present invention will not repeat them here.

In practical application, assuming that the convection parameter and superdiffusion coefficient of the solute in the river are both 1, the results of uniform distribution of 100 points on the spatial scale of Hausdroff dimension 0.4 and uniform distribution of points 100, 400 and 2000 on the normal Euclidean spatial dimension are used For comparison, the normal Euclidean space dimension of 2000 is used as an approximate exact solution, and the closer the solutions of other point layout methods are to the approximate exact solution, the higher the accuracy is. Figure 3 shows the solutions of the four point distribution methods. The results show that the uniform distribution of points on the Hausdroff dimension significantly improves the calculation accuracy, and the calculation accuracy of 100 points is higher than that of 400 points evenly distributed on the normal Euclidean space dimension.

Through the implementation of this embodiment, the number of distribution points is used as the basis for spatial discretization. Through the preset spatial distribution coefficient and the preset first spatial distribution number, the deviation value is determined to determine the distance from the target area after the introduction of a new spatial scale. The number of spatial distribution points that are compatible with the convection-diffusion model can 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.

This embodiment provides a device based on the solute transport process of the target river, as shown in FIG. Unit 25.

The acquisition unit 21 is configured to acquire convection parameters and superdiffusion coefficients of the target area based on the tracer experiment in the target area. For the specific process, reference may be made to the relevant description of step S101 in the foregoing embodiments, and details are not repeated here.

The convection-diffusion model building unit 22 is configured to construct the convection-diffusion model of the target area according to the convection parameters and the super-diffusion coefficient. For the specific process, reference may be made to the relevant description of step S102 in the foregoing embodiments, and details are not repeated here.

The spatial scale determining unit 23 is configured to determine the spatial scale of the convection-diffusion model according to the tracer experiment. For the specific process, reference may be made to the relevant description of step S103 in the foregoing embodiments, and details are not repeated here.

The spatial distribution determining unit 24 is configured to determine the number of spatial distribution points in the target area based on the spatial scale. For the specific process, reference may be made to the relevant description of step S104 in the foregoing embodiments, and details are not repeated here.

The analysis and prediction unit 25 is configured to analyze and predict the solute concentration in the target area based on the number of spatial distribution points and the convection-diffusion model. For the specific process, reference may be made to the related description of step S105 in the foregoing embodiments, and details are not repeated here.

Through the implementation of this embodiment, the acquisition unit and the convection-diffusion model construction unit are based on the tracer experiment of the target area, and the convection-diffusion model of the target area is constructed, and the single member and the number of spatial distribution are determined by the spatial scale. The unit uses the characteristics of the model itself Determine the spatial scale and complete the division of the spatial grid, so that the solute concentration in the target area can be analyzed and predicted through the analysis and prediction unit based on the number of spatial distribution points and the convection diffusion model, and the simulation of the solute super-diffusion process can be realized.

An embodiment of the present invention also provides a computer-readable storage medium, where computer-executable instructions are stored in the computer-readable storage medium, and the computer-executable instructions can execute the method based on solute superdiffusion in the crack channel in any of the above method embodiments. mock method. Wherein, the storage medium may be a magnetic disk, an optical disk, a read-only memory (Read-Only Memory, ROM), a random access memory (Random Access Memory, RAM), a flash memory (FlashMemory), a hard disk (Hard Disk Drive, HDD) or solid-state hard drive (Solid-State Drive, SSD), etc.; the storage medium may also include a combination of the above-mentioned types of memory.

An embodiment of the present invention also provides a computer device, as shown in FIG. 5 , which is a schematic structural diagram of a computer device provided in an optional embodiment of the present invention. The computer device may include at least one processor 31, at least A communication interface 32, at least one communication bus 33 and at least one memory 34, wherein the communication interface 32 can include a display screen (Display), a keyboard (Keyboard), and the optional communication interface 32 can 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 magnetic disk memory. Optionally, the memory 34 may also be at least one storage device located away from the aforementioned processor 31 . Wherein the processor 31 can be combined with the device described in FIG. 4, the application program is stored in the memory 34, and the processor 31 invokes the program code stored in the memory 34, so as to perform the solute ultrafiltration in the crack channel described in any method embodiment above. Diffusion simulation method steps.

Wherein, the communication bus 33 may be a peripheral component interconnect standard (peripheral component interconnect, PCI) bus or an extended industry standard architecture (extended industry standard architecture, EISA) bus or the like. The communication bus 33 can be divided into an address bus, a data bus, a control bus, and the like. For ease of representation, only one thick line is used in FIG. 5 , but it does not mean that there is only one bus or one type of bus.

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

Wherein, the processor 31 may be a central processing unit (central processing unit, CPU), a network processor (network processor, NP) or a combination of CPU and NP.

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

Optionally, the memory 34 is also used to store program instructions. The processor 31 can invoke program instructions to implement the method for simulating superdiffusion of solutes in crack channels in any embodiment of the present invention.

Apparently, the above-mentioned embodiments are only examples for clear description, rather than limiting the implementation. For those of ordinary skill in the art, on the basis of the above description, other changes or changes in different forms can also be made. It is not necessary and impossible to exhaustively list all the implementation manners here. And the obvious changes or changes derived therefrom are still within the scope of protection of the present invention.

Claims (10)

1. A simulation method of solute superdiffusion in a crack 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 the target area according to the convection parameters and the super-diffusion coefficient; Determine the spatial scale of the convection-diffusion model based on the tracer experiment; Based on the spatial scale, determine the number of spatial distribution points in the target area; Based on the number of points distributed in space and the convection-diffusion model, the solute concentration in the target area is analyzed and predicted. 2. The method according to claim 1, wherein, according to the tracer experiment, determining the spatial scale of the convection-diffusion model comprises: determining spatial scale-dependent parameters of the convection-diffusion model based on the tracer experiments; 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, wherein, according to the tracer experiment, determining the parameters related to the spatial scale of the convection-diffusion model includes: Determining the fracture development of the subterranean aquifer based on the tracer experiments; According to the development of the cracks, the parameters related to the spatial scale of the convection-diffusion model are determined. 4. The method according to claim 1, wherein said determining the number of spatial distribution points of said target area based on said spatial scale comprises: calculating the first solute concentration based on the preset first number of spatial distribution points and the convection-diffusion model; Based on the preset spatial distribution coefficient and the first spatial distribution number, determine the second spatial distribution number; calculating a second solute concentration based on the number of distribution points in the second space 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 satisfies a preset deviation threshold, the second spatial distribution number is used as the spatial distribution number of the target area. 5. method according to claim 4, is characterized in that, described method also comprises: When the first deviation value does not meet the preset deviation threshold, based on the preset spatial distribution coefficient and the second spatial distribution number, determine a third spatial distribution number; calculating a third solute concentration based on the number of distribution points in the third space 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 satisfies a preset deviation threshold, the third spatial distribution number is used as the spatial distribution number of the target area. 6. The method according to claim 1, wherein the convection diffusion model of the target area is expressed by the following formula:

Among them, c represents the solute concentration, t represents time, x represents the spatial position, l represents the left end point of the spatial position, A represents the convection parameter, d represents the superdiffusion coefficient, α represents the spatial fractional order,

is the space fractional derivative symbol. 7. method according to claim 6, is characterized in that, described space fractional order derivative is expressed by following formula:

Among them, Γ represents the gamma function, ξ represents the spatial variable, and _x1 represents the current position. 8. A simulation device for solute superdiffusion in a crack channel, characterized in that the device comprises: The acquisition unit is used for the tracer experiment based on the target area, and acquires the convection parameter and the superdiffusion coefficient of the target area; a convection-diffusion model building unit, configured to construct a convection-diffusion model in the target area according to the convection parameters and the super-diffusion coefficient; a spatial scale determination unit, configured to determine the spatial scale of the convection-diffusion model according to the tracer experiment; a spatial distribution number determining unit, configured to determine the spatial distribution number of the target area based on the spatial scale; An analysis and prediction unit, configured to analyze and predict the solute concentration in the target area based on the number of spatial distribution points and the convection-diffusion model. 9. A computer-readable storage medium, characterized in that the computer-readable storage medium stores computer instructions, and when the computer instructions are executed by a processor, the crack channel according to any one of claims 1-7 is realized A simulation method for solute superdiffusion. 10. A computer device, comprising: at least one processor; and a memory communicatively connected to the at least one processor; The memory stores instructions executable by the at least one processor, the instructions are executed by the at least one processor, thereby performing the solute superdiffusion in the fracture channel according to any one of claims 1-7 the simulation method.

Images