Karst area heterogeneous rock group numerical model production method, storage medium and equipment

Abstract

The application discloses a karst area non-homogeneous rock group numerical model manufacturing method, a storage medium and equipment, relates to the field of geotechnical engineering, and mainly comprises the following steps: according to engineering geological characteristics and dissolution information, a non-homogeneous rock group model is constructed by using a particle flow analysis tool, and a numerical simulation tool is used to obtain a structural surface network; the non-homogeneous rock group model is divided according to the structural surface network to obtain a grid, dissolution characteristics are quantified to obtain dissolution characteristic parameters, and dissolution simulation is carried out by using the dissolution characteristic parameters according to the grid to obtain a karst area non-homogeneous rock group numerical model. The karst area non-homogeneous rock group numerical model manufacturing method, the storage medium and the equipment can effectively numerically characterize the dissolution characteristics of the non-homogeneous rock group.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of geotechnical engineering, and more particularly, to a karst area heterogeneous rock group numerical model production method, a storage medium and equipment. BACKGROUND

[0002] The karst area heterogeneous rock group refers to a rock group divided considering the differences in dissolution features such as dissolution morphology, dissolution degree and size caused by dissolution, and when the heterogeneous rock group is distributed in a reservoir area or dam area of a hydropower project established in a karst area, it often plays a decisive or controlling role in reservoir seepage and dam foundation stability. In order to meet the requirements of engineering suitability evaluation, the dissolution features of the heterogeneous rock group need to be accurately expressed on the basis of investigation and statistics, but from the engineering and technical point of view, there is a lack of numerical representation ideas and corresponding numerical model production methods that can reflect the dissolution features of different types and stages of the karst area heterogeneous rock group in the current numerical model production. SUMMARY

[0003] The purpose of the present application is to provide a karst area heterogeneous rock group numerical model production method, a storage medium and equipment, which can effectively numerically represent the dissolution features of the heterogeneous rock group.

[0004] The present application provides a karst area heterogeneous rock group numerical model production method, comprising the following steps: S1: obtaining the engineering geological features and dissolution information of the karst area heterogeneous rock group, and obtaining the heterogeneous rock group types and dissolution stages according to the engineering geological features and dissolution information of the karst area heterogeneous rock group; S2: obtaining the dissolution features of each dissolution stage of each heterogeneous rock group type of the karst area according to the heterogeneous rock group types and dissolution stages; the dissolution features include dissolution degree, dissolution uniformity and size variability; S3: constructing a heterogeneous rock group model using a particle flow analysis tool according to the engineering geological features and dissolution information; obtaining a structure surface network using a numerical simulation tool according to the heterogeneous rock group model, the heterogeneous rock group types and the dissolution stages; S4: dividing the heterogeneous rock group model by equal size to obtain a grid; obtaining a grid element dissolution probability according to the structure surface network and the grid; wherein the grid includes model particles, grid elements, grid element sizes and grid element dissolution probabilities; S5: quantifying the dissolution features to obtain dissolution feature parameters, the dissolution feature parameters including dissolution rate, uniformity coefficient and probability change coefficient; S6: performing dissolution simulation using the dissolution feature parameters according to the grid to obtain a karst area heterogeneous rock group numerical model.

[0005] Further, the step S1 of the method for making a numerical model of a non-homogeneous rock group in a karst area comprises the following steps: S11: obtaining the engineering geological characteristics and dissolution information of the non-homogeneous rock group in the karst area, the engineering geological characteristics including structural characteristics, lithology and geometric size; the dissolution information including dissolution direction, dissolution form, dissolution degree and dissolution size; obtaining the non-homogeneous rock group type according to the structural characteristics, lithology, dissolution direction and dissolution form; the non-homogeneous rock group type including a dissolution gap as the main type and a dissolution pore as the main type; the dissolution size including a dissolution gap width and a dissolution pore radius; S12: obtaining the dissolution stage of each non-homogeneous rock group type according to the dissolution gap width and the dissolution pore radius, the dissolution stage including a pre-dissolution stage, a middle-dissolution stage and a post-dissolution stage.

[0006] Further, the dissolution degree of the method for making a numerical model of a non-homogeneous rock group in a karst area includes low, medium and high; the dissolution uniformity includes low, medium and high; the size variability includes low, medium and high; the dissolution uniformity of each dissolution stage of the dissolution gap as the main type is low and the size variability is high; the dissolution degree of the pre-dissolution stage of the dissolution gap as the main type is low; the dissolution degree of the middle-dissolution stage of the dissolution gap as the main type is medium; the dissolution degree of the post-dissolution stage of the dissolution gap as the main type is high; the dissolution degree of the pre-dissolution stage of the dissolution pore as the main type is low, the dissolution uniformity is high and the size variability is low; the dissolution degree of the middle-dissolution stage of the dissolution pore as the main type is medium, the size variability is high and the dissolution uniformity includes high, medium and low; the dissolution degree of the post-dissolution stage of the dissolution pore as the main type is high, the dissolution uniformity is high and the size variability is low.

[0007] Further, the step S3 of the method for making a numerical model of a non-homogeneous rock group in a karst area specifically comprises: constructing a non-homogeneous rock group model by using a particle flow analysis tool according to the engineering geological characteristics and the dissolution information, the non-homogeneous rock group model including model particles, model particle IDs and center point coordinates; obtaining a structural surface network by using a numerical simulation tool according to the model particle IDs, the center point coordinates, the non-homogeneous rock group type and the dissolution stage, the structural surface network including the dissolution stage and a soluble range.

[0008] Further, the particle flow analysis tool of the method for making a numerical model of a non-homogeneous rock group in a karst area is PFC software, and the numerical simulation tool is MATLAB software.

[0009] Further, the grid cell size of the method for making a numerical model of a non-homogeneous rock group in a karst area is not less than the size of the particles in the non-homogeneous rock group model.

[0010] Further, the step S5 of the method for making a numerical model of a non-homogeneous rock group in a karst area specifically comprises: quantifying the dissolution characteristics to obtain dissolution characteristic parameters, the dissolution characteristic parameters including a dissolution rate, a uniformity coefficient and a probability change coefficient, such as the formula:

[0011]

[0012] Wherein, k is the dissolution rate, S k is the total area of the dissolution particles, S is the total area of the rock group, u is the uniformity coefficient, p is the dissolution probability of the dissolution range, p max is the maximum dissolution probability of the grid, p min is the dissolution probability of the grid affected by the non-structural plane, g is the probability change coefficient, p0 is the initial dissolution probability value of the grid, and p1 is the dissolution probability adjustment value of the grid.

[0013] Further, the step S6 of the above method for manufacturing the numerical model of the non-homogeneous rock group in the karst area specifically comprises: S61, obtaining an expected total dissolution area according to the dissolution characteristic parameters; S62, generating random variable values of the grid units according to the grid; S63, when the dissolution probability of the grid unit is greater than the random variable value of the grid unit, marking any model particle in the grid unit as dissolved, to obtain a dissolution particle; S64, obtaining a total area of the dissolution particles according to the dissolution particles; S65, when the total area of the dissolution particles is equal to the expected total dissolution area, the simulation of dissolution ends, the marked model particles in each grid unit are the dissolution particles at the current stage, and the numerical model of the non-homogeneous rock group in the karst area is obtained; when the total area of the dissolution particles is less than the expected total dissolution area, returning to step S62 to regenerate the random variable values of the grid units; when the total area of the dissolution particles is greater than the expected total dissolution area, sorting the marked model particles in the step S63 of the last iteration according to the difference between the dissolution probability and the random variable value of the grid unit where the model particle is located, and selecting the sufficient particles with a larger difference as the dissolution particles at the current stage, to obtain the numerical model of the non-homogeneous rock group in the karst area.

[0014] The application further provides a computer readable storage medium, which stores a computer program, and the computer program is executed by a processor to realize the steps of the above method for manufacturing the numerical model of the non-homogeneous rock group in the karst area.

[0015] The application further provides a computer device, which comprises a memory, a processor, and a computer program stored on the memory and executable on the processor, and the processor realizes the steps of the above method for manufacturing the numerical model of the non-homogeneous rock group in the karst area when executing the program.

[0016] The numerical model of the non-homogeneous rock group in the karst area provided by the application has the following beneficial effects:

[0017] The present application defines a part of uniformity by using the density of structural plane network and its influence range, and represents the uniformity of dissolution by controlling the initial distribution of dissolution probability of structural plane network in the influence range, in order to realize the uneven development of dissolution and form the condition that the dissolution fissure develops along the structural plane, the structural plane network is given the distribution of dissolution probability after the structural plane network is divided, the dissolution probability of structural plane network decreases with the distance, and there is a large gradient change, which leads to the tendency of dissolution along the structural plane, and finally forms a small number of dissolution fissures with large size, the uniformity of dissolution is represented by the uniformity coefficient, and the purpose of representing the uniformity of dissolution development in the dissolution process is realized;

[0018] When the dissolution develops, the dissolution probability of the grid is adjusted, so that the next dissolution is affected by the dissolution probability adjustment.When the dissolution probability of the grid near the structural plane increases more than that far from the structural plane, the dissolution is more concentrated near the structural plane, at this time, the dissolution pore has the tendency that the size gradually decreases with the increase of the distance from the structural plane, and the corresponding size variability is large; with the gradual reduction of the probability growth value difference of different grids far from the structural plane, the concentration of dissolution near the structural plane is weakened, at this time, the tendency that the size of the dissolution pore gradually decreases with the increase of the distance from the structural plane is weakened, and the corresponding size variability is small; it reflects that the dissolution pore developed near the structural plane is more than that developed far from the structural plane, and there is a tendency that the size gradually decreases from near to far, the change of the size of the dissolution pore is realized by the feedback and update of the dissolution probability of each grid in the dissolution process, and the size variability of the dissolution pore is represented by the probability change coefficient; the numerical model provided by the present application has higher detail level of dissolution simulation under the premise that the grid unit size is not less than the model particle size; ij

[0019] The present application provides a numerical representation idea of non-homogeneous rock group in karst area, and clearly defines the dissolution characteristics of different types and different stages of non-homogeneous rock group, such as dissolution degree, dissolution uniformity and size variability, only after the dissolution characteristics of the rock group are found out through field investigation and test, the numerical model for representing the dissolution characteristics of the non-homogeneous rock group is formed by using PFC and MATLAB platform after the parameters such as dissolution rate, uniformity coefficient and probability change coefficient are quantitatively expressed, the numerical representation problem of the dissolution characteristics of the non-homogeneous rock group in karst area is solved, the basis and support are provided for the engineering suitability evaluation of a large number of non-homogeneous rock groups with dissolution characteristics in karst area, and strong basis is also provided for the design scheme of engineering treatment of the complex non-homogeneous rock group. BRIEF DESCRIPTION OF DRAWINGS

[0020] The present application will be further described below in combination with the drawings and examples, and the drawings show:

[0021] Figure 1 is a flow chart of the method for making a numerical model of a heterogeneous rock group in a karst area provided by the present application;

[0022] Figure 2 is a flow chart of the numerical model establishment provided by the present application;

[0023] Figure 3 is a schematic diagram of each dissolution stage of a heterogeneous rock group dominated by solution fissures provided by the present application;

[0024] Figure 4 is a schematic diagram of each dissolution stage of a heterogeneous rock group dominated by solution pores provided by the present application;

[0025] Figure 5 is a structural block diagram of the computer device provided by the present application. DETAILED DESCRIPTION

[0026] In order to have a clearer understanding of the technical features, objectives and effects of the present application, the specific embodiments of the present application will be described in detail with reference to the drawings.

[0027] Figure 1 A schematic diagram of the method for making a numerical model of a heterogeneous rock group in a karst area of the present embodiment is shown. In the present embodiment, the method for making a numerical model of a heterogeneous rock group in a karst area includes the following steps:

[0028] S1: Obtain the engineering geological characteristics and dissolution information of the heterogeneous rock group in the karst area, and obtain the heterogeneous rock group type and the dissolution stage according to the engineering geological characteristics and dissolution information of the heterogeneous rock group in the karst area;

[0029] Specifically, the step S1 of the above method for making a numerical model of a heterogeneous rock group in a karst area includes the following steps:

[0030] S11: Obtain the engineering geological characteristics and dissolution information of the heterogeneous rock group in the karst area, the engineering geological characteristics including the structural characteristics, lithology and geometric size; the dissolution information including the dissolution direction, dissolution form, dissolution degree and dissolution size; obtain the heterogeneous rock group type according to the structural characteristics, lithology, dissolution direction and dissolution form; the heterogeneous rock group type including being dominated by solution fissures and being dominated by solution pores; the dissolution size including the solution fissure width and the solution pore radius; S12: Obtain the dissolution stage of each heterogeneous rock group type according to the solution fissure width and the solution pore radius, the dissolution stage including the early, middle and late stages;

[0031] S2: Obtain the dissolution characteristics of each dissolution stage of each heterogeneous rock group type in the karst area according to the heterogeneous rock group type and the dissolution stage; the dissolution characteristics including the dissolution degree, dissolution uniformity and size variability;

[0032] Specifically, the dissolution degree of the above-mentioned numerical model making method of the heterogeneous rock group in the karst area includes low, medium and high; the dissolution uniformity includes low, medium and high; the size variability includes low, medium and high; the dissolution type is mainly dissolution gap, the dissolution uniformity of each dissolution stage is low, and the size variability is high; the dissolution degree of the pre-dissolution stage of the dissolution type mainly dominated by dissolution gap is low; the dissolution degree of the middle dissolution stage of the dissolution type mainly dominated by dissolution gap is medium; the dissolution degree of the post-dissolution stage of the dissolution type mainly dominated by dissolution gap is high; the dissolution degree of the pre-dissolution stage of the dissolution type mainly dominated by dissolution pore is low, the dissolution uniformity is high, and the size variability is low; the dissolution degree of the middle dissolution stage of the dissolution type mainly dominated by dissolution pore is medium, the size variability is high, and the dissolution uniformity includes high, medium and low; the dissolution degree of the post-dissolution stage of the dissolution type mainly dominated by dissolution pore is high, the dissolution uniformity is high, and the size variability is low;

[0033] S3: According to the engineering geological characteristics and dissolution information, a heterogeneous rock group model is constructed by using a particle flow analysis tool; and according to the heterogeneous rock group model, the heterogeneous rock group type and the dissolution stage, a structure surface network is obtained by using a numerical simulation tool;

[0034] Specifically, the step S3 of the above-mentioned numerical model making method of the heterogeneous rock group in the karst area specifically includes: according to the engineering geological characteristics and dissolution information, a heterogeneous rock group model is constructed by using a particle flow analysis tool, the heterogeneous rock group model includes model particles, model particle IDs and center point coordinates; and according to the model particle IDs, the center point coordinates, the heterogeneous rock group type and the dissolution stage, a structure surface network is obtained by using a numerical simulation tool, the structure surface network includes the dissolution stage and the soluble range;

[0035] Specifically, the particle flow analysis tool of the above-mentioned numerical model making method of the heterogeneous rock group in the karst area is PFC software, and the numerical simulation tool is MATLAB software;

[0036] Specifically, on the PFC platform, a heterogeneous rock group model is established according to the lithology and geometric size, and is given mesoscopic parameters, and model particle IDs and center point coordinates are output; on the MATLAB platform, rock mass particle IDs and center point coordinates are read according to the structure characteristics, a structure surface network conforming to the rock group structure characteristics is simulated and generated, and then the generated structure surface network is taken as the basis and center, the structure surface influence range is set according to the dissolution stage, the current stage soluble range of the rock group is circled by the structure surface influence range, and the soluble particle IDs are identified;

[0037] S4: The heterogeneous rock group model is divided into grids of the same size, and a grid is obtained; the grid unit dissolution probability is obtained according to the structure surface network and the grid; wherein the grid includes model particles, grid units, grid unit sizes and grid unit dissolution probabilities;

[0038] Specifically, the grid unit size of the karst area non-homogeneous rock group numerical model manufacturing method is not less than the particle size in the non-homogeneous rock group model.

[0039] Specifically, the numerical model is divided according to the equal size grid, and the size of the grid unit depends on the detail of the dissolution simulation, that is, the smaller the size, the more detailed, but the size is not less than the particle size; after completing the grid division, a dissolution probability ρ ij ij is given to each grid unit, where i and j are the row number and column number of the grid unit respectively;

[0040] Optionally, when simulating the non-homogeneous rock group type dominated by dissolution fissure development, the structural surface grid is given a distributed dissolution probability, that is, the dissolution probability of the structural surface grid decreases with the distance and has a large gradient change, so that the dissolution has a tendency to develop along the structural surface, and finally a small number of dissolution fissures with increasing size are formed; when simulating the non-homogeneous rock group type dominated by dissolution pore development, the dissolution pores near the structural surface in stage 2 have more number and size gradually decreases from near to far than the dissolution pores far from the structural surface; referring to the dissolution fissure type, the structural surface grid is given a distributed dissolution probability, and the spatial gradient change of the dissolution probability can be adjusted according to the situation; in order to represent the strength of the dissolution pore size variability, the feedback adjustment and update of the dissolution probability ρ ij of each grid in the dissolution process are used to achieve it.

[0041] S5: Quantifying the dissolution characteristics to obtain dissolution characteristic parameters, the dissolution characteristic parameters including dissolution rate, uniformity coefficient and probability change coefficient;

[0042] Specifically, the step S5 of the karst area non-homogeneous rock group numerical model manufacturing method specifically includes: quantifying the dissolution characteristics to obtain dissolution characteristic parameters, the dissolution characteristic parameters including dissolution rate, uniformity coefficient and probability change coefficient, such as the formula:

[0043]

[0044] Wherein, k is the dissolution rate, S k is the total area of the dissolved particles, S is the total area of the rock group, u is the uniformity coefficient, ρ is the dissolution probability of the soluble range, ρ max is the maximum dissolution probability of the grid, ρ min is the dissolution probability of the non-structural surface affected grid, g is the probability change coefficient, ρ0 is the initial dissolution probability value of the grid, and ρ1 is the dissolution probability adjustment value of the grid.

[0045] S6: According to the grid, using the dissolution characteristic parameters to simulate the dissolution to obtain the karst area non-homogeneous rock group numerical model;

[0046] ​Specifically, the step S6 of the method for making the numerical model of the karst area heterogeneous rock group comprises the following steps: S61, obtaining an expected total dissolution area according to a dissolution characteristic parameter; S62, generating a random variable value of a grid cell according to the grid; S63, when a dissolution probability of the grid cell is greater than the random variable value of the grid cell, marking any model particle in the grid cell with a dissolution mark to obtain a dissolution particle; S64, obtaining a total dissolution particle area according to the dissolution particle; S65, when the total dissolution particle area is equal to the expected total dissolution area, ending the simulation of dissolution, and the marked model particles in each grid cell are the dissolution particles of the current stage to obtain the numerical model of the karst area heterogeneous rock group; when the total dissolution particle area is less than the expected total dissolution area, returning to step S62 to generate the random variable value of each grid cell again; and when the total dissolution particle area is greater than the expected total dissolution area, sorting the marked model particles in the last iteration according to the difference between the dissolution probability and the random variable value of the grid cell, and selecting the particles with a larger difference as the dissolution particles of the current stage to obtain the numerical model of the karst area heterogeneous rock group.

[0047] Optionally, the step S6 of the method for making the numerical model of the karst area heterogeneous rock group comprises the following steps: determining a dissolution upper limit of the stage according to a dissolution rate of each stage, and then defining a random variable value s for each grid, where s is a random number between 0 and 1; in the simulation of the dissolution process, the dissolution probability p of each grid is compared with the random variable value s to determine whether dissolution occurs in the grid, and any sphere in the grid is marked with a dissolution mark when p is greater than s; the total area of the marked dissolution particles is counted to obtain a total dissolution particle area; when the total dissolution particle area is equal to the expected total dissolution area, the simulation of dissolution is ended, and the marked particles in each grid are the dissolution particles of the current stage; when the total dissolution particle area is less than the expected total dissolution area, the above random number generation operation is repeated; and when the total dissolution particle area exceeds the expected total dissolution area, the last marked particles are sorted according to the difference between the grid p and s, and the particles with a larger difference are selected as the dissolution particles of the current stage. ij ij Optionally, the step S6 of the method for making the numerical model of the karst area heterogeneous rock group comprises the following steps: determining a dissolution upper limit of the stage according to a dissolution rate of each stage, and then defining a random variable value s for each grid, where s is a random number between 0 and 1; in the simulation of the dissolution process, the dissolution probability p of each grid is compared with the random variable value s to determine whether dissolution occurs in the grid, and any sphere in the grid is marked with a dissolution mark when p is greater than s; the total area of the marked dissolution particles is counted to obtain a total dissolution particle area; when the total dissolution particle area is equal to the expected total dissolution area, the simulation of dissolution is ended, and the marked particles in each grid are the dissolution particles of the current stage; when the total dissolution particle area is less than the expected total dissolution area, the above random number generation operation is repeated; and when the total dissolution particle area exceeds the expected total dissolution area, the last marked particles are sorted according to the difference between the grid p and s, and the particles with a larger difference are selected as the dissolution particles of the current stage. ij

[0048] In some embodiments, the method for making the numerical model of the karst area heterogeneous rock group can also be implemented in the following manner.

[0049] The method for making the numerical model of the karst area heterogeneous rock group divides the dissolution types of the karst area heterogeneous rock group into the dissolution interstice type and the dissolution pore type.​​

[0050] As shown in Figure 2 , for the dissolution gap dominated type, mainly sparse structural plane dolomite rock group, affected by lithology and sparse structural plane, in the early stage of dissolution, the influence range of structural plane is very small, and the dissolution develops most strongly near the structural plane, at this time, the dissolution gap with small width and less number along the structural plane is formed; with the continuous development of dissolution process, in the middle stage of dissolution, the influence range of structural plane expands, the dissolution gap with large width and less number is developed, in the late stage of dissolution, the influence range of structural plane continues to expand, the dissolution gap with large size and less number is developed along the structural plane, the overall distribution of the dissolution gap developed in the three stages is controlled by the structural plane, and the non-uniformity is strong, and the size variation is small; for the dissolution pore dominated type, mainly dense structural plane dolomite or limestone rock group, affected by lithology or dense structural plane, the layer surface and joint fissure surface are easy to form water enrichment, the rock mass is continuously eroded and dissolved by pore water and fissure water, causing the continuous dissolution of soluble substances in the rock; as shown in Figure 4 (a), in the early stage of dissolution, the influence range of a single structural plane is small, but the overall influence range of the stage surface is large, a large number of dissolution pores with small size are formed, and the uniformity and size variation of the dissolution pores are small; as shown in Figure 4 (b), in the middle stage of dissolution, the influence range of the structural plane expands, at this time, the size and distribution of the dissolution pores developed are complex, for example, the size of the dissolution pores changes in the space, the closer to the structural plane, the larger the size, and the farther to the structural plane, the smaller the size; in addition, with the increasing difference between the dissolution development degree of the position close to the structural plane and the position far away from the structural plane, the spatial distribution uniformity of the dissolution pores formed in the range of the structural plane changes, when the dissolution development difference is strong, the size variation of the dissolution pores is large and the spatial distribution is uneven; when the dissolution development difference is weak, the size variation of the dissolution pores is large but the spatial distribution is uniform; as shown in Figure 4 (c), in the late stage of dissolution, the influence range of the structural plane is wide, and the dissolution develops strongly everywhere in the influence range, a large number of dissolution pores with large size are formed, at this time, the size variation of the dissolution pores is small;

[0051] As shown in Figure 1 , the flowchart of the numerical model of the heterogeneous rock group in the karst area, the numerical model manufacturing method for the heterogeneous rock group in the karst area provided in the embodiment comprises the following steps:

[0052] Step 1), field geological investigation and test in the karst area, to obtain the engineering geological characteristics and dissolution characteristics of the heterogeneous rock group in the karst area, and comprehensively consider the structural characteristics, lithology, dissolution direction and dissolution form to divide the heterogeneous rock group type, and divide the dissolution stage of each heterogeneous rock group type according to the dissolution gap width or dissolution pore radius;

[0053] Step 2), determine the dissolution degree, uniformity and size variability of each type and each dissolution stage of the heterogeneous rock group in the karst area, as shown in Table 1;

[0054] Table 1: Dissolution characteristics of each type and each stage of the heterogeneous rock group

[0055]

[0056]

[0057] Step 3), on the Particle Flow Code (PFC) platform, a heterogeneous rock group model is established, and the mesoscopic parameters are assigned to it, and the model particle ID and center point coordinates are output; on the MATLAB platform, the rock mass particle ID and center point coordinates are read; a structure surface network conforming to the structure characteristics of the rock group is simulated, and based on the generated structure surface network and center, the influence range of the structure surface is set to define the current stage of the rock group that can be dissolved, and the particle ID that can be dissolved is identified;

[0058] Step 4), the numerical model is divided according to the equal size grid, and the grid size depends on the detail of the dissolution simulation, that is, the smaller the size, the more detailed, but the size is not less than the particle size; after completing the grid division, each grid is assigned a dissolution probability ρ ij , ρ ij is a value related to the grid position (i and j are the row number and column number of the grid, respectively); when simulating the heterogeneous rock group type dominated by dissolution fissure development, the structure surface grid is assigned a distributed dissolution probability, that is, the structure surface grid dissolution probability decreases with distance, there is a large gradient change, which leads to the development of dissolution along the structure surface, and finally forms a small number of dissolution fissures with size increasing with the dissolution stage; when simulating the heterogeneous rock group type dominated by dissolution pore development, for the dissolution pores that exist near the structure surface in stage 2, the number of dissolution pores near the structure surface is more than that far from the structure surface, and there is a trend of gradually decreasing from near to far in size, and the structure surface grid is assigned a distributed dissolution probability according to the dissolution fissure type, and the spatial gradient change of the dissolution probability can be adjusted according to the situation; in order to represent the strength of the dissolution pore size variability, the feedback adjustment and update of the dissolution probability ρ ij of each grid in the dissolution process are used to achieve it;

[0059] Step 5), before simulating dissolution, the dissolution characteristics of the heterogeneous rock group are expressed in the form of parameters by setting the quantitative dissolution rate k, uniformity coefficient u and size variability coefficient g, etc. Dissolution rate k, uniformity coefficient u and size variability coefficient g are calculated and determined according to the following formulas, respectively.

[0060]

[0061] Where: S k is the total area of ​​dissolved particles; S is the total area of ​​rock group;

[0062]

[0063] Where: ρ is [0.02, 0.4]; ρ max is the maximum dissolution probability of the grid, with a value of 0.4; ρ min The probability of network dissolution affected by non-structural surface is 0.02;

[0064]

[0065] Where: ρ0 is the initial dissolution probability value of the grid; ρ1 is the adjusted value of the dissolution probability of the grid;

[0066] The upper limit of the dissolution of each stage is determined according to the dissolution rate of each stage, and then a random variable value s is defined for each grid, s is a random number between 0 and 1; when simulating the dissolution process, the dissolution probability ρ of each grid is compared. ij and the size of the random variable value s, when ρ ij When it is greater than s, dissolution occurs in the grid, and any sphere in the grid is marked with a dissolution mark;

[0067] Step 6): After completing step 5 once, the total area of ​​the marked dissolved particles is counted. When the total area of ​​the particles is equal to the total dissolved amount of the current stage, the simulated dissolved particles are finished, and the marked particles in each grid are the dissolved particles of the current stage. When the total area of ​​the particles is less than the total dissolved amount of the current stage, repeat step 5. When the total area of ​​the particles exceeds the total dissolved amount of the current stage, the particles marked in the last step 5 are counted according to the grid where they are located. ij Sort by the difference with s, select the full-amount particles with the larger difference as the dissolved particles in the current stage, output the result file of the heterogeneous dissolved particles of each type and stage according to the ID number, and write the fish program in PFC to read the ID of each particle and delete it to make a numerical model that expresses the type of heterogeneous rock components and the stages.

[0068] This embodiment provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the method for creating a numerical model of a heterogeneous rock formation in a karst region. The storage medium may be a magnetic disk, an optical disk, a read-only memory (ROM), a random access memory (RAM), a flash memory, a hard disk drive (HDD), or a solid-state drive (SSD); the storage medium may also include a combination of the aforementioned types of memory.

[0069] This embodiment provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, the steps of the method for producing a numerical model of a heterogeneous rock group in a karst area are implemented.

[0070] like Figure 5 As shown, the computer device may include: at least one processor 121, such as a CPU (Central Processing Unit), at least one communication interface 123, a memory 124, and at least one communication bus 122. The communication bus 122 is used to realize the connection and communication between these components. The communication interface 123 may include a display screen and a keyboard. The optional communication interface 123 may also include a standard wired interface and a wireless interface. The memory 124 may be a high-speed RAM memory (Random Access Memory) or a non-volatile memory, such as at least one disk storage. The memory 124 may optionally be at least one storage device located away from the aforementioned processor 121. The memory 124 stores application programs, and the processor 121 calls the program code stored in the memory 124 to execute any of the above-mentioned method steps. The communication bus 122 may be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus, etc. The communication bus 122 can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 5The bus 123 is used to connect the above-mentioned elements in the system 120, and only one line is used to represent the bus 123, but it does not mean that there is only one bus or only one type of bus. Among them, the memory 124 can include volatile memory such as random access memory (RAM); the memory can also include non-volatile memory such as flash memory, hard disk drive (HDD) or solid-state drive (SSD); the memory 124 can also include a combination of the above-mentioned types of memory. Among them, the processor 121 can be a central processing unit (CPU), a network processor (NP) or a combination of CPU and NP. The processor 121 can further include a hardware chip. The above-mentioned hardware chip can be an application-specific integrated circuit (ASIC), a programmable logic device (PLD) or a combination thereof. The above-mentioned PLD can be a complex programmable logic device (CPLD), a field-programmable gate array (FPGA), a generic array logic (GAL) or any combination thereof. Alternatively, the memory 124 is also used to store program instructions. The processor 121 can call the program instructions to realize the karst area heterogeneous rock group numerical model manufacturing method as in the embodiment.

[0071] The embodiments of the present application are described above in combination with the drawings, but the present application is not limited to the above-mentioned specific embodiments, and the above-mentioned specific embodiments are only illustrative and not restrictive. Those skilled in the art can make many forms under the inspiration of the present application without departing from the purpose of the present application and the scope protected by the claims, and these all belong to the protection of the present application.

Claims

1. A method for making a numerical model of a karst region heterogeneous rock group, characterized in that, The following steps are involved: S1: obtaining engineering geological characteristics and dissolution information of heterogeneous rock formations in the karst area, and obtaining the type and dissolution stage of the heterogeneous rock formations based on the engineering geological characteristics and dissolution information of the heterogeneous rock formations in the karst area; S2: obtaining the dissolution characteristics of each dissolution stage of each heterogeneous rock group type in the karst area according to the heterogeneous rock group type and the dissolution stage; the dissolution characteristics include dissolution degree, dissolution uniformity and size variability; S3: Based on the engineering geological characteristics and dissolution information, a particle flow analysis tool is used to construct a heterogeneous rock group model; based on the heterogeneous rock group model, heterogeneous rock group type and dissolution stage, a structural surface network is obtained using a numerical simulation tool; S4: dividing the heterogeneous rock group model into equal sizes to obtain a grid; obtaining a grid unit dissolution probability based on the structural surface network and the grid; the grid includes model particles, grid units, grid unit sizes, and grid unit dissolution probabilities; S5: quantifying the dissolution characteristics to obtain dissolution characteristic parameters, wherein the dissolution characteristic parameters include a dissolution rate, a uniformity coefficient, and a probability variation coefficient; S6: performing a dissolution simulation based on the grid and utilizing the dissolution characteristic parameters to obtain a numerical model of the heterogeneous rock formation in the karst area.

2. The method according to claim 1, wherein, Step S1 includes the following steps: S11: Obtaining engineering geological characteristics and dissolution information of heterogeneous rock formations in the karst area, wherein the engineering geological characteristics include structural characteristics, lithology, and geometric dimensions; the dissolution information includes dissolution direction, dissolution morphology, dissolution degree, and dissolution dimension; obtaining the type of heterogeneous rock formation based on the structural characteristics, lithology, dissolution direction, and dissolution morphology; the heterogeneous rock formation types include mainly dissolution fissures and mainly dissolution pores; the dissolution dimension includes dissolution fissure width and dissolution pore radius; S12: Obtaining the dissolution stage of each heterogeneous rock group type according to the dissolution crevice width and dissolution pore radius, wherein the dissolution stage includes early, middle and late stages.

3. The method of claim 1, wherein the method further comprises: The dissolution degree includes low, medium and high; the dissolution uniformity includes low, medium and high; the size variability includes low, medium and high; the dissolution uniformity of each dissolution stage where the dissolution type is mainly dissolution fissures is low and the size variability is high, the dissolution degree of the front dissolution stage where the dissolution type is mainly dissolution fissures is low, the dissolution degree of the middle dissolution stage where the dissolution type is mainly dissolution fissures is medium, and the dissolution degree of the rear dissolution stage where the dissolution type is mainly dissolution fissures is high; the dissolution degree of the front dissolution stage where the dissolution type is mainly dissolution pores is low, the dissolution uniformity is high, and the size variability is low, the dissolution degree of the middle dissolution stage where the dissolution type is mainly dissolution pores is medium, the size variability is high, and the dissolution uniformity includes high, medium and low, and the dissolution degree of the rear dissolution stage where the dissolution type is mainly dissolution pores is high, the dissolution uniformity is high, and the size variability is low.

4. The method of claim 1, wherein the method further comprises: The step S3 specifically comprises: constructing a heterogeneous rock group model including model particles, model particle IDs and center point coordinates by using a particle flow analysis tool according to engineering geological characteristics and dissolution information; and obtaining a structural surface network including a dissolution stage and a soluble range by using a numerical simulation tool according to the model particle IDs, the center point coordinates, a heterogeneous rock group type and the dissolution stage.

5. The method of claim 1, wherein the method further comprises: The particle flow analysis tool is PFC software, and the numerical simulation tool is MATLAB software.

6. The method of claim 1, wherein the method further comprises: The grid cell size is not less than the size of the particles in the heterogeneous rock group model.

7. The method of claim 1, wherein the method further comprises: The step S5 specifically comprises: quantifying the dissolution characteristics to obtain dissolution characteristic parameters including a dissolution rate, a uniformity coefficient and a probability change coefficient, as shown in the following formula: where k is the dissolution rate, S k is the total area of the dissolution particles, S is the total area of the rock group, u is the uniformity coefficient, p is the dissolution probability of the dissolution range, p max is the maximum dissolution probability of the grid, p min is the dissolution probability of the grid affected by the non-structural plane, g is the probability change coefficient, p0 is the initial dissolution probability value of the grid, and p1 is the dissolution probability adjustment value of the grid.

8. The method according to claim 1, wherein, The step S6 specifically comprises: S61: obtaining an expected total dissolution area according to the dissolution characteristic parameters; S62: generating random variable values of the grid cells according to the grid; S63: marking any model particle in the grid cell with a dissolution mark when a grid cell dissolution probability is greater than the random variable value of the grid cell, to obtain a dissolution particle; S64: obtaining a total dissolution particle area according to the dissolution particles; S65: when the total dissolution particle area is equal to the expected total dissolution area, the simulation of dissolution ends, the marked model particles in each grid cell are the dissolution particles in the current stage, and a karst area heterogeneous rock group numerical model is obtained; when the total dissolution particle area is less than the expected total dissolution area, the random variable values of each grid cell are regenerated in step S62; when the total dissolution particle area is greater than the expected total dissolution area, the marked model particles in the last iteration in step S63 are sorted according to the difference between the dissolution probability and the random variable value of the grid cell, and the particles with a larger difference are selected as the dissolution particles in the current stage to obtain the karst area heterogeneous rock group numerical model.

9. A computer readable storage medium having stored thereon a computer program, characterized in that, The computer program is executed by the processor to implement the steps of the karst area heterogeneous rock group numerical model manufacturing method in any one of claims 1-8.

10. A computer device comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, The processor executes the program to implement the steps of the karst area heterogeneous rock group numerical model manufacturing method in any one of claims 1-8.

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