CN115577597A - Simulation method, device, medium and equipment for solute hyperdiffusion in fracture channel - Google Patents
Simulation method, device, medium and equipment for solute hyperdiffusion in fracture channel Download PDFInfo
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Abstract
The invention provides a simulation method, a device, a medium and equipment for solute hyperdiffusion in a fracture channel, wherein the method comprises the following steps: obtaining convection parameters and a super-diffusion coefficient of a target region based on a tracer experiment of the target region; constructing a convection diffusion model of the target area according to the convection parameters and the super-diffusion coefficient; determining the space scale of the convection diffusion model according to a tracer experiment; based on the spatial scale, the number of spatial points of the target area is distributed; and analyzing and predicting the solute concentration in the target region based on the number of spatial distribution points and the convection diffusion model. The method is based on a tracer experiment of a target region, a convection diffusion model of the target region is constructed, the space scale is determined by utilizing the characteristics of the model, and the division of a space grid is completed, so that the solute concentration in the target region is analyzed and predicted through the number of spatial distribution points and the convection diffusion model, and the simulation of the solute hyperdiffusion process is realized.
Description
Technical Field
The invention relates to the technical field of engineering simulation and numerical simulation, in particular to a simulation method, a simulation device, a simulation medium and simulation equipment for solute hyperdiffusion in a fracture channel.
Background
Due to the non-uniform and anisotropic nature of the medium structure in nature, fissured channels tend to exist therein. Solute transport processes in fracture channels often show a hyperdiffusion phenomenon, and a classical solute transport model has difficulty in describing the non-locality of solute transport in a medium containing a fracture structure. Fractional derivatives are a type of convolution differential operator, which is commonly used to build diffusion models for characterizing the early arrival of solute particles.
In the related technology, the convolution calculation describing the global correlation characteristics causes large calculation amount after space dispersion, increases the application difficulty of the model, and reduces the accuracy of the calculation result due to the increase of the calculation amount.
Disclosure of Invention
Therefore, the technical problem to be solved by the invention is to overcome the defect that the accuracy of the solute hyperdiffusion simulation result cannot be ensured in the prior art, so that a simulation method, a simulation device, a simulation medium and simulation equipment for solute hyperdiffusion in a fracture channel are provided.
In a first aspect, an embodiment of the present invention provides a method for simulating solute hyperdiffusion in a fracture channel, including: obtaining convection parameters and a super-diffusion coefficient of a target region based on a tracer experiment of the target region; constructing a convection diffusion model of the target region according to the convection parameters and the super-diffusion coefficient; determining the space scale of the convection diffusion model according to a tracer experiment;
determining the spatial point distribution number of the target area based on the spatial scale; and analyzing and predicting the solute concentration in the target region based on the number of spatial distribution points and the convection diffusion model.
With reference to the first aspect, in a possible implementation manner of the first aspect, determining a spatial scale of the convective diffusion model according to a tracer experiment includes: determining parameters of the convection diffusion model related to the spatial scale according to tracer experiments; and determining the space scale of the convection diffusion model according to the parameters related to the space scale.
With reference to the first aspect, in another possible implementation manner of the first aspect, determining a parameter related to a spatial scale of a convection diffusion model according to a tracer experiment includes: determining the fracture development condition of the underground aquifer according to a tracer experiment; and determining parameters related to the space scale of the convection diffusion model according to the crack development condition.
With reference to the first aspect, in another possible implementation manner of the first aspect, the determining, based on a spatial scale, a spatial point distribution number of the target region includes: calculating the concentration of a first solute based on the number of preset first space distribution points and a convection diffusion model; determining a second spatial distribution point number based on a preset spatial distribution coefficient and the first spatial distribution point number; calculating a second solute concentration based on the second spatial distribution number and the convection diffusion model; determining a first deviation value between the calculation results according to the first solute concentration and the second solute concentration; and when the first deviation value meets a preset deviation threshold value, taking the second space distribution number as the space distribution number of the target area.
With reference to the first aspect, in another possible implementation manner of the first aspect, the method for simulating solute hyperdiffusion in a fracture channel further includes: when the first deviation value does not meet a preset deviation threshold value, determining a third spatial distribution point number based on a preset spatial distribution coefficient and a second spatial distribution point number; calculating a third solute concentration based on a third spatial distribution number and a convective diffusion model; determining a second deviation value between the calculation results according to the second solute concentration and the third solute concentration; and when the second deviation value meets a preset deviation threshold value, taking the third spatial distribution number as the spatial distribution number of the target area.
With reference to the first aspect, in another possible implementation manner of the first aspect, the convective diffusion model of the target region is expressed by the following formula:
wherein c represents solute concentration, t represents time, x represents spatial position, l represents left end point of spatial position, A represents convection parameter, d represents super-diffusion coefficient, alpha represents spatial fractional order number,
is the sign of the spatial fractional order derivative.
With reference to the first aspect, in another possible implementation manner of the first aspect, the spatial fractional order derivative is expressed by the following formula:
where Γ represents a gamma function, ξ represents a spatial variable, x 1 Indicating the current location.
In a second aspect, embodiments of the present invention provide a simulation apparatus for solute hyperdiffusion in a fracture channel, including: the acquisition unit is used for acquiring convection parameters and a super-diffusion coefficient of the target region based on a tracer experiment of the target region; the convection diffusion model building unit is used for building a convection diffusion model of the target area according to the convection parameters and the super-diffusion coefficient; the space scale determining unit is used for determining the space scale of the convection diffusion model according to the tracer experiment; the spatial distribution point number determining unit is used for determining the spatial distribution point number of the target area based on the spatial scale; and the analysis and prediction unit is used for analyzing and predicting the solute concentration in the target region based on the number of the spatial distribution points and the convection diffusion model.
In a third aspect, the present invention provides a computer-readable storage medium storing computer instructions, which when executed by a processor, implement a method for simulating solute hyperdiffusion in a fracture channel according to any one of the embodiments of the first aspect.
In a fourth aspect, an embodiment of the present invention provides a computer device, including at least one processor; and a memory communicatively coupled to the at least one processor; the memory has stored therein computer program instructions which, when executed by the at least one processor, implement a method of simulating solute hyperdiffusion in a fracture channel as in any one of the embodiments of the first aspect.
The technical scheme of the invention has the following advantages:
the method is based on tracer experiments of target areas, a convection diffusion model of the target areas is constructed, the spatial scale is determined by using the characteristics of the model, and the division of spatial grids is completed, so that the solute concentration in the target areas is analyzed and predicted through the spatial distribution number and the convection diffusion model, and the simulation of the solute hyperdiffusion process is realized.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the embodiments or the prior art descriptions will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and other drawings can be obtained by those skilled in the art without creative efforts.
FIG. 1 is a flow chart of a specific example of a simulation method for solute hyperdiffusion in a fracture channel according to an embodiment of the present invention;
FIG. 2 is a diagram of an example of spatial scale conversion for a simulation method of solute hyperdiffusion in a fissure channel according to an embodiment of the present invention;
FIG. 3 is an exemplary graph of analytical prediction results of a simulation method for solute hyperdiffusion in a fracture channel according to an embodiment of the present invention;
FIG. 4 is a schematic block diagram of a specific example of a simulation apparatus for solute hyperdiffusion in a fracture channel according to an embodiment of the present invention;
fig. 5 is a diagram illustrating a structure of a computer device according to an embodiment of the present invention.
Detailed Description
The technical solutions of the present invention will be described clearly and completely with reference to the accompanying drawings, and it should be understood that the described embodiments are some, but not all embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within 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., indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings, and are only for convenience of description and simplicity of description, but do not indicate or imply that the device or element being referred to must have a particular orientation, be constructed and operated in a particular orientation, and thus, should not be construed as limiting the present invention. Furthermore, the terms "first," "second," and "third" are used for descriptive purposes only and are not to 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 they do not conflict with each other.
The present embodiment provides a simulation method of solute hyperdiffusion in a fissure channel, as shown in fig. 1, including:
s101, obtaining convection parameters and a super-diffusion coefficient of the target region based on a tracer experiment of the target region.
Specifically, the convection parameter of the target region is used to represent the flow velocity of the water body in the target region, and the hyperdiffusion coefficient is used to represent the hyperdiffusion velocity of the solute, wherein the convection parameter may be obtained by monitoring, and the hyperdiffusion coefficient is obtained by parameter back-stepping.
In practical applications, the tracer experiment of the target region may be a twin-well pumping experiment or other tracer experiments for the target region, as long as the development condition of the fracture channel of the target region can be determined through the tracer experiment, which is not specifically limited in the present invention. The development condition of the fractured channel of the target area means that solute enters an underground aquifer along with water, and the solute is retained due to the existence of fractures in the channel. In practical applications, the more developed the fissures in the target area, the more pronounced the retention phenomenon. The retention phenomenon refers to the phenomenon that solute lag occurs due to the difference between solute migration and underground water around the solute caused by various physical, chemical and biological effects in the process of an aquifer power plant.
And S102, constructing a convection diffusion model of the target area according to the convection parameters and the super-diffusion coefficient.
In an alternative embodiment, the convective diffusion model of the target region is expressed by the following equation:
wherein c represents solute concentration, t represents time, x represents spatial position, l represents left end point of spatial position, A represents convection parameter, d represents super-diffusion coefficient, alpha represents spatial fractional order number,
is the sign of the spatial fractional order derivative.
In an alternative embodiment, the spatial fractional order derivative is expressed as follows:
where Γ represents a gamma function, ξ represents a spatial variable, x 1 Indicating the current location.
In practical application, the spatial position represents a spatial distance corresponding to the target region, l represents a left end point of the spatial position, r represents a right end point of the spatial position, that is, the length of a simulation region of a convection diffusion model of the target region is r-l, and l < x 1 < r. The value range of alpha is more than 1 and less than or equal to 2.
S103, determining the space scale of the convection diffusion model according to a tracer experiment.
Specifically, the process of determining the spatial scale of the convection diffusion model is a process of calibrating a parameter related to the spatial scale through measurement data in a tracer experiment, wherein the parameter related to the spatial scale is a spatial fractional order in the convection diffusion model of the target region. The process comprises the steps of determining the fracture development condition of a target area through the measurement data of a tracer experiment, determining a spatial fractional order, namely a parameter related to a spatial scale, according to the corresponding relation between the fracture development condition of the target area and the spatial fractional order, and further determining the spatial scale of the convection diffusion model through the spatial fractional order. Therefore, the space scale adaptive to the convection diffusion model of the target area is determined by using the parameters of the model reflecting physical characteristics without increasing the parameters, and the division of the space grid is completed.
And S104, determining the spatial distribution number of the target area based on the spatial scale.
Specifically, the step of determining the spatial distribution number of the target region refers to a process of determining the spatial distribution number adapted to a convection diffusion model of the target region by calculating a deviation value after a new spatial scale is introduced.
And S105, analyzing and predicting the solute concentration in the target region based on the spatial distribution number and the convection diffusion model.
Specifically, analyzing and predicting the solute concentration in the target region based on the spatial distribution number and the convection diffusion model means dispersing the convection diffusion model of the target region according to the determined spatial distribution number, and solving the dispersed convection diffusion model by a finite difference method of a partial differential equation to determine the solute concentration of the target region.
By implementing the embodiment, a convection diffusion model of the target region is constructed based on a tracer experiment of the target region, the spatial scale is determined by utilizing the characteristics of the model, and the division of the spatial grid is completed, so that the solute concentration in the target region is analyzed and predicted through the spatial distribution number and the convection diffusion model, and the simulation of the solute hyperdiffusion process is realized.
In an optional implementation manner, the process of step S103 specifically includes:
(1) According to tracer experiments, parameters of the convective diffusion model related to the spatial scale are determined.
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 according to the measurement data or historical data of the tracer experiment.
In an alternative embodiment, the process of determining the spatial scale-dependent parameter of the convective diffusion model from tracer experiments specifically comprises:
and determining the fracture development condition of the underground aquifer according to a tracer experiment.
And determining parameters related to the space scale of the convection diffusion model according to the crack development condition.
Specifically, according to the tracer experiment, determining the fracture development condition of the underground aquifer means determining whether the retention phenomenon of the solute in the underground aquifer is obvious or not through the measurement data or the historical data of the tracer experiment, that is, the retention phenomenon is more obvious, that is, the condition of solute lag is more obvious, and the fracture of the underground aquifer in the target area is more developed.
Specifically, determining the parameters of the convection diffusion model related to the spatial scale according to the fracture development condition refers to determining the value of the fractional order of the convection diffusion model according to the corresponding relationship between the fracture development condition and the parameters related to the spatial scale, that is, the corresponding relationship between the fracture development condition and the fractional order. Wherein, the more developed the crack, the smaller the fractional order.
(2) And determining the space scale of the convection diffusion model according to the parameters related to the space scale.
Specifically, determining the spatial scale of the convective diffusion model according to the parameter related to the spatial scale comprises: determining scale transformation parameters according to parameters related to the spatial scale; according to the scale transformation parameters, performing space uniform point distribution on the Hausdroff dimension, and mapping the space point distribution of the Hausdroff dimension to the dimension of the Euclidean space, namely to the dimension of a flat space.
Specifically, the scale transformation parameters are expressed by the following formula:
β＝α-1
where β represents a scaling parameter.
Specifically, according to the scale transformation parameters, the spatial uniform distribution of points in the hausdorff dimension refers to the uniform distribution of points in the hausdorff dimension with the spatial scale β. At this time, the space is equally divided under the intrinsic scale, and the step size is Δ x. And mapping the spatial distribution points of the Hausdroff dimension to the dimension of the Euclidean space, namely projecting the points of the Euclidean space dimension to the Hausdroff dimension to complete the transformation of the space dimension, wherein the process is equivalent to the determination of the space dimension of the convection diffusion model. In practical applications, the spatial grid mapping scheme is shown in FIG. 2, which is equivalent to projecting x of Euclidean space to Hausdroff dimension
On the contrary, it is completed
When the relationship of the spatial metric is expressed by the following formula:
in practical applications, after determining the spatial scale of the convective diffusion model, the discrete form of the spatial fractional order derivative can be represented as:
wherein M represents the M-th point in space, if the number of spatial distribution points is M, M is more than 0 and less than M, j represents the j-th point in space, j is more than 0 and less than or equal to M, x j Denotes the position of the jth point in space, τ denotes the space step, τ j ＝x j -x j-1 Xi represents the spatial variable within the integral, delta j ＝x m -x j 。
In practical application, x is j The j point position projected to the external space satisfies:
x j ＝(jΔx) 1/β
by implementing the embodiment, the fracture development condition of the underground aquifer is determined according to the tracer experiment, the spatial scale of the convection diffusion model is determined according to the fracture development condition, the fracture development condition of the target area is determined according to the measurement data of the tracer experiment, the spatial fractional order, namely the parameter related to the spatial scale, is determined according to the corresponding relation between the fracture development condition of the target area and the spatial fractional order, and the spatial scale of the convection diffusion model is determined according to the spatial fractional order. Therefore, the space scale which is adaptive to the convection diffusion model of the target area is determined by using the parameters of the model reflecting physical characteristics on the premise of not increasing the parameters, namely, the division of a space grid is completed, and a data basis is provided for analyzing and predicting the solute concentration in the target area and realizing the simulation of the solute hyperdiffusion process.
In an optional implementation manner, the process of step S104 specifically includes:
(1) And calculating the first solute concentration based on the preset first space distribution point number and the convection diffusion model.
In practical applications, the preset first space distribution number may be 20,30,40 or other numerical values, and may be selected according to actual working conditions, which is not specifically limited in the present invention.
In practical application, the step of calculating the first solute concentration based on the preset first space distribution point number and the convection diffusion model refers to the step of dispersing the convection diffusion model of the target area according to the preset first space distribution point number, and the dispersed convection diffusion model is solved through a finite difference method of a partial differential equation, so that the first solute concentration is obtained. It should be understood that solving the post-discretization model by the finite difference method of partial differential equations is a mature technology, and is not described in detail herein.
(2) And determining a second spatial distribution point number based on the preset spatial distribution coefficient and the first spatial distribution point number.
In practical application, the preset spatial point distribution coefficient may be 2,3 or other numerical values, and may be selected according to actual working conditions, which is not specifically limited in the present invention.
(3) And calculating a second solute concentration based on the second spatial distribution number and the convective diffusion model.
In practical application, the step of calculating the second solute concentration based on the second spatial distribution point number and the convection diffusion model refers to dispersing the convection diffusion model of the target region according to the second spatial distribution point number, and solving the dispersed convection diffusion model through a finite difference method of a partial differential equation to obtain the second solute concentration.
(4) A first deviation value between the calculated results is determined based on the first solute concentration and the second solute concentration.
Specifically, the first deviation value is expressed as:
where derror1 is represented as a first deviation value, result1 represents a first solute concentration, and result2 represents a second solute concentration.
(5) And when the first deviation value meets a preset deviation threshold value, taking the second space distribution number as the space distribution number 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 conditions, but the present invention is not limited thereto.
In practical applications, the first deviation value satisfying the preset deviation threshold means that the first deviation value is smaller than the first deviation threshold.
In an alternative embodiment, a method of simulating solute hyperdiffusion in a fracture channel, further comprising:
(1) And when the first deviation value does not meet the preset deviation threshold value, determining the number of third spatial distribution points based on the preset spatial distribution coefficient and the number of second spatial distribution points.
(2) And calculating a third solute concentration based on the third spatial distribution number and the convective diffusion model.
In practical application, the third solute concentration is calculated based on the third space distribution point number and the convection diffusion model, namely the convection diffusion model of the target region is dispersed according to the third space distribution point number, and the dispersed convection diffusion model is solved through a finite difference method of a partial differential equation to obtain the third solute concentration.
(3) And determining a second deviation value between the calculation results according to the second solute concentration and the third solute concentration.
Specifically, the second deviation value is expressed as:
where derror2 is expressed as a first deviation value and result3 is expressed as a third solute concentration.
(4) And when the second deviation value meets a preset deviation threshold value, taking the third spatial distribution number as the spatial distribution number of the target area.
In practical applications, if the second deviation value does not satisfy the preset deviation threshold, the fourth spatial distribution point number is determined based on the third spatial distribution point number and the preset spatial distribution coefficient, the fourth solute concentration is calculated, the third deviation value is compared, and the like, and the description is omitted.
In practical application, assuming that the convection parameter and the super-diffusion coefficient of solute in a river are both 1, the results of uniformly distributing points 100 on a spatial scale with a Hausdroff dimension of 0.4 and uniformly distributing points 100, 400 and 2000 on a normal Euclidean spatial dimension are compared, wherein the normal Euclidean spatial dimension 2000 is used as an approximate precise solution, and the closer the solutions of other point distribution modes are to the approximate precise solution, the higher the precision is. Fig. 3 is a solution of four point distribution modes, and the result shows that the uniform point distribution in the spatial scale of hausdorff dimension significantly improves the calculation accuracy, and the calculation accuracy of 100 points is higher than that of the uniform point distribution 400 in the normal euclidean spatial dimension.
By implementing the embodiment, the distribution number is used as a basis for spatial dispersion, and the spatial distribution number matched with the convection diffusion model of the target region after a new spatial scale is introduced is determined by calculating a deviation value through a preset spatial distribution coefficient and a preset first spatial distribution number, so that a data basis is provided for analyzing and predicting the solute concentration in the target region and realizing the simulation of the solute hyperdiffusion process.
The present embodiment provides an apparatus for solute transport process based on target river, as shown in fig. 4, including: the device comprises an acquisition unit 21, a convection diffusion model construction unit 22, a spatial scale determination unit 23, a spatial distribution point determination unit 24 and an analysis prediction unit 25.
The obtaining unit 21 is configured to obtain a convection parameter and a super-diffusion coefficient of the target region based on a tracer experiment of the target region. For a specific process, reference may be made to the related description of step S101 in the foregoing embodiment, and details are not described herein.
And the convection diffusion model building unit 22 is configured to build a convection diffusion model of the target region according to the convection parameters and the super-diffusion coefficients. For a specific process, reference may be made to the related description of step S102 in the foregoing embodiment, and details are not described herein.
And the spatial scale determining unit 23 is configured to determine a spatial scale of the convection diffusion model according to a tracer experiment. For a specific process, reference may be made to the related description of step S103 in the foregoing embodiment, which is not described herein again.
And the spatial distribution point determining unit 24 is used for determining the spatial distribution point number of the target area based on the spatial scale. For a specific process, reference may be made to the related description of step S104 in the foregoing embodiment, which is not described herein again.
And the analysis and prediction unit 25 is used for analyzing and predicting the solute concentration in the target region based on the number of the spatial distribution points and the convection diffusion model. For a specific process, reference may be made to the related description of step S105 in the above embodiments, and details are not repeated here.
By implementing the embodiment, the acquisition unit and the convection diffusion model construction unit are used for constructing the convection diffusion model of the target region based on the tracer experiment of the target region, the member and space distribution number determination unit is used for determining the space scale by using the characteristics of the model through the space scale, and the division of the space grid is completed, so that the solute concentration in the target region is analyzed and predicted by the analysis prediction unit based on the space distribution number and the convection diffusion model, and the simulation of the solute hyperdiffusion process is realized.
An embodiment of the present invention further provides a computer-readable storage medium storing computer-executable instructions for performing a simulation method based on solute hyperdiffusion in a fracture channel in any of the method embodiments described above. The storage medium may be a magnetic Disk, an optical Disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a Flash Memory (Flash Memory), a Hard Disk (Hard Disk Drive, HDD), a Solid-State Drive (SSD), or the like; the storage medium may also comprise a combination of memories of the kind described above.
An embodiment of the present invention further provides a computer device, as shown in fig. 5, fig. 5 is a schematic structural diagram of a computer device according to an alternative 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, where the communication interface 32 may include a Display (Display) and a Keyboard (Keyboard), and the alternative communication interface 32 may also include a standard wired interface and a wireless interface. The Memory 34 may be a high-speed RAM (Random Access Memory) or a non-volatile Memory, such as at least one disk Memory. The memory 34 may optionally be at least one memory device located remotely from the processor 31. Wherein the processor 31 may be combined with the apparatus described in fig. 4, the memory 34 stores an application program, and the processor 31 calls the program code stored in the memory 34 for executing the steps of the simulation method for solute hyperdiffusion in a fracture channel according to any of the above-mentioned method embodiments.
The communication bus 33 may be a Peripheral Component Interconnect (PCI) bus, an Extended Industry Standard Architecture (EISA) bus, or the like. The communication bus 33 may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, only one thick line is shown in FIG. 5, but this is not intended to represent only one bus or type of bus.
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 (flash memory), a Hard Disk Drive (HDD) or a solid-state drive (SSD); the memory 34 may also comprise a combination of the above-mentioned kinds of memories.
The processor 31 may be a Central Processing Unit (CPU), a Network Processor (NP), or a combination of the CPU and the NP.
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 General Array Logic (GAL), or any combination thereof.
Optionally, the memory 34 is also used to store program instructions. The processor 31 may call program instructions to implement the method for simulating the hyper-diffusion of solutes in a fracture channel as described in any of the embodiments of the present invention.
It should be understood that the above examples are only for clarity of illustration and are not intended to limit the embodiments. Other variations and modifications will be apparent to persons skilled in the art in light of the above description. And are neither required nor exhaustive of all embodiments. And obvious variations or modifications therefrom are within the scope of the invention.
Claims (10)
1. A method of simulating solute hyperdiffusion in a fracture channel, the method comprising:
acquiring a convection parameter and a super-diffusion coefficient of a target region based on a tracer experiment of the target region;
constructing a convection diffusion model of the target area according to the convection parameters and the super-diffusion coefficient;
determining the spatial scale of the convection diffusion model according to the tracer experiment;
determining the spatial point distribution number of the target area based on the spatial scale;
and analyzing and predicting the solute concentration in the target region based on the spatial distribution number and the convection diffusion model.
2. The method of claim 1, wherein determining the spatial scale of the convective diffusion model from the tracer experiment comprises:
determining parameters of the convection diffusion model related to spatial scale according to the tracer experiment;
and determining the space scale of the convection diffusion model according to the parameters related to the space scale.
3. The method of claim 2, wherein determining the spatial scale-related parameter of the convective diffusion model from the tracer experiment comprises:
determining the fracture development condition of the underground aquifer according to the tracer experiment;
and determining parameters of the convection diffusion model related to the spatial scale according to the fracture development condition.
4. The method of claim 1, wherein the determining the spatial stationing number of the target region based on the spatial scale comprises:
calculating a first solute concentration based on a preset first space distribution point number and the convection diffusion model;
determining a second spatial distribution point number based on a preset spatial distribution coefficient and the first spatial distribution point number;
calculating a second solute concentration based on the second spatial distribution number and the convective diffusion model;
determining a first deviation value between calculation results according to the first solute concentration and the second solute concentration;
and when the first deviation value meets a preset deviation threshold value, taking the second spatial point distribution number as the spatial point distribution number of the target area.
5. The method of claim 4, further comprising:
when the first deviation value does not meet a preset deviation threshold value, determining a third spatial distribution point number based on a preset spatial distribution coefficient and the second spatial distribution point number;
calculating a third solute concentration based on the third spatial distribution number and the convective diffusion model;
determining a second deviation value between the calculation results according to the second solute concentration and the third solute concentration;
and when the second deviation value meets a preset deviation threshold value, taking the third spatial point distribution number as the spatial point distribution number of the target area.
6. The method of claim 1, wherein the convective diffusion model of the target region is expressed by the following equation:
wherein c represents solute concentration, t represents time, x represents spatial position, l represents left end point of spatial position, A represents convection parameter, d represents super-diffusion coefficient, alpha represents spatial fractional order number,
is the sign of the spatial fractional order derivative.
7. The method of claim 6, wherein the spatial fractional order derivative is expressed by the following formula:
where Γ represents a gamma function, ξ represents a spatial variable, x 1 Indicating the current location.
8. A simulation device for solute hyperdiffusion in a fracture channel, the device comprising:
the acquisition unit is used for acquiring convection parameters and a super-diffusion coefficient of the target region based on a tracer experiment of the target region;
the convection diffusion model building unit is used for building a convection diffusion model of the target area according to the convection parameters and the super-diffusion coefficient;
the space scale determining unit is used for determining the space scale of the convection diffusion model according to the tracer experiment;
the spatial distribution point number determining unit is used for determining the spatial distribution point number of the target area based on the spatial scale;
and the analysis and prediction unit is used for analyzing and predicting the solute concentration in the target region based on the space distribution number and the convection diffusion model.
9. A computer-readable storage medium storing computer instructions which, when executed by a processor, implement a method of simulating solute hyperdiffusion in a fracture channel as claimed in any one of claims 1 to 7.
10. A computer device, comprising: at least one processor; and a memory communicatively coupled to the at least one processor;
the memory stores instructions executable by the at least one processor to perform a method of simulating solute hyperdiffusion in a fissure channel according to any one of claims 1-7.
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