Grouting engineering fracture connectivity evaluation method based on fracture pipe network model

Abstract

According to the grouting engineering fracture connectivity evaluation method based on the fracture pipe network model, the fracture pipe network model is applied to fracture network connectivity evaluation of grouting engineering, the fracture pipe network model serves as the basis for calculating a connectivity function matrix, a weighting matrix is provided, the correlation among parameters such as fracture occurrence, trace length and number can be comprehensively considered, and the fracture connectivity evaluation accuracy is improved. And connectivity evaluation is carried out by utilizing the weighted connectivity function matrix, so that fracture connectivity evaluation is closer to engineering practice. Fracture trace length, occurrence, density and other factors are coupled to perform weighted analysis on a connectivity function matrix to assess connectivity, and compared with direct flow simulation, a fracture pipe network model (FPNM) is high in calculation efficiency; the method for converting the discrete fracture network model into the equivalent pipeline network model is an effective method for analyzing the connectivity and seepage characteristics of the three-dimensional disc-shaped fracture network.

Description

Technical Field

[0001] The invention relates to a method for evaluating the connectivity of fractures in a grouting project, and in particular to a method for evaluating the connectivity of fractures in a grouting project based on a fracture pipe network model. Background Art

[0002] Cracks are widely present in geology, affecting the mechanical properties and seepage properties of rock mass. The causes of cracks are complex, and the distribution of crack joints in rock mass is random and diverse in form. Dam bedrock grouting can effectively improve the mechanical properties of the dam foundation rock mass, improve the integrity of the dam foundation and reduce the permeability of the dam foundation, and is widely used in water conservancy projects. With the continuous expansion of project scale and the increasing complexity of engineering conditions, the technical requirements and difficulty of grouting projects are also increasing. Therefore, it is of great significance to accurately describe the connectivity of cracks in grouting projects.

[0003] Fracture connectivity can be generally defined as the performance of rapid flow and transportation from one location to another. Traditional analysis of fracture connectivity often uses a discrete fracture network model (DFN) for numerical simulation. However, when the number of fractures is large, the calculation time will be too long and the local mesh will be encrypted.

[0004] Some researchers define an evaluation index to assess connectivity based on specific parameters or characteristics of the fracture network, such as the fracture connectivity index is , is the crack density, Or the connectivity function matrix is ​​directly established according to the flow simulation (the matrix elements are 0 or 1), without considering the correlation between the parameters of the discrete fracture network model (referring to the correlation between the fracture trace length, occurrence, and quantity), which leads to large errors in the analysis results. Summary of the invention

[0005] In view of the deficiencies in the prior art, the technical problem to be solved by the present invention is to provide a method for evaluating the connectivity of fractures in grouting projects based on a fracture pipe network model.

[0006] The technical solution adopted by the present invention to solve the technical problem is: A method for evaluating the connectivity of fractures in a grouting project based on a fracture pipe network model, the method comprising the following steps: Step 1: Analyze and generate a three-dimensional discrete fracture network model based on the data obtained from all drilling exploration in the project, and convert the three-dimensional discrete fracture network model into a fracture pipe network model; Step 2: Generate the initial connectivity function matrix based on the fracture network model , m is the number of drilling sections, It is defined as describing the connectivity between the i-th borehole segment and the j-th borehole segment. When the value of is 0, it means that the i-th drilling section is not connected to the j-th drilling section; when When the value of is 1, it means that the two borehole sections are connected; and the connecting paths between the borehole sections of any adjacent boreholes are determined based on the fracture network model. When there are multiple connecting paths, the number of fractures corresponding to the connecting path with the least number of fractures and the average occurrence of fractures are selected to calculate the weight; Step 3: Obtain the data obtained from all borehole exploration in the project, divide the borehole into several sections, calculate the average trace length of each borehole section, and obtain the center line between the borehole sections of two adjacent boreholes, and calculate the angle between the center line and the average occurrence of the corresponding fracture. ; The weighting matrix ω is calculated according to formula (7): represents the k-th row and j-th column element in ω,

[0007] in, , is the average trace length of the kth drilling section trace and the jth drilling section trace, is the number of fractures contained in the connecting path with the least number of fractures between the two drilling sections, is the angle between the center line of the kth and jth drilling sections and the average occurrence of the fracture; Step 4: Multiply the initial connectivity function matrix GC by the weighting matrix ω to obtain the weighted connectivity matrix :

[0008] Weighted connectivity matrix is a symmetric matrix whose elements represents the weighted connectivity value between the ith borehole segment and the jth borehole segment,

[0009] It represents the overall connectivity value of the j-th drilling section, which represents the connectivity of the j-th drilling section in the project. The larger the value, the higher the connectivity of the drilling section.

[0010] Furthermore, the process of step 1 is: 1) Based on the data obtained from all the drilling exploration in the project, the fracture data are clustered and grouped, and the fracture attributes in the same group are statistically analyzed and fitted to obtain the fracture attributes of each group, their distribution model and the geometric distribution parameter values ​​of the distribution model. The fracture attributes include fracture occurrence, fracture trace length and fracture density; 2) Determine the model space range according to the exploration range of all boreholes in the project, determine the total model volume from the model space range, multiply the total model volume by the fracture density of each group to obtain the number of fractures in a single group within the model space range, use the random number generation function in MATLAB to generate the coordinates of the fracture center point of each group according to the three-dimensional Poisson distribution, and then obtain the coordinates of the fracture center points of all groups; the coordinates of each fracture center point are independent of each other and are generated by a uniform distribution function; 3) At the generated crack center point, the crack occurrence and crack trace length are randomly simulated in MATLAB based on the distribution model of each group and the corresponding geometric distribution parameter value; then, according to the relationship between the crack trace length and the crack diameter, the crack diameter under the generated crack trace length is obtained, and then the three-dimensional discrete crack network model is obtained; 4) Determine the position of the fracture within the model space and whether the positional relationship of the fracture surfaces intersects. If the fracture surfaces intersect, calculate the intersection lines of the fracture surfaces, connect the midpoints of the intersection lines of the fracture surfaces with the center of the fracture surfaces in sequence, and represent the fractures with one-dimensional pipes, thereby converting the three-dimensional discrete fracture network model into a fracture pipe network model.

[0011] Furthermore, when judging the positional relationship of the fracture surfaces, the depth-first search method is used to iteratively eliminate isolated and dead-end fractures until each fracture is connected to at least two other fractures or at least one fracture and a boundary, ensuring the connectivity of the fracture network and generating a connected discrete fracture network model.

[0012] Compared with the prior art, the present invention has the following beneficial effects: The present invention creatively applies the fracture pipe network model to the fracture network connectivity evaluation of the grouting project, takes it as the basis for calculating the connectivity function matrix, and proposes a weighted matrix, which can comprehensively consider the correlation between parameters such as fracture occurrence, trace length, and quantity. The connectivity evaluation is performed using the weighted connectivity function matrix, making the fracture connectivity evaluation closer to engineering practice.

[0013] The method of the present invention can simplify model calculations, and can still quickly implement calculations when the number of scale cracks in grouting engineering is large, thereby improving calculation efficiency.

[0014] This application couples factors such as fracture trace length, occurrence, and density to perform weighted analysis on the connectivity function matrix to evaluate connectivity. Compared with direct flow simulation, the fracture pipe network model (FPNM) has high computational efficiency. Converting the discrete fracture network model into an equivalent pipe network model is an effective method for analyzing the connectivity and seepage characteristics of a three-dimensional disk-shaped fracture network. The fracture pipe network method uses the flow in the equivalent fracture network of pipe flow, which greatly reduces the computational time and improves the computational efficiency, and can meet the connectivity evaluation requirements of large fractured rock masses. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 It is a schematic diagram of the process of the present invention; Figure 2 It is a schematic diagram of the spatial model of the fracture occurrence of the present invention; Figure 3 Generate a schematic diagram for the fractured pipe network model of the present invention; Figure 4 A schematic diagram is generated for the fracture pipe network model around the borehole of the present invention; Figure 5 A schematic diagram of connectivity analysis of multiple borehole sections according to an embodiment of the present invention. DETAILED DESCRIPTION

[0016] Specific embodiments are given below in conjunction with the accompanying drawings. The specific embodiments are only used to illustrate the technical solutions of the present invention in detail and are not used to limit the protection scope of the present application.

[0017] The present invention provides a method for evaluating the connectivity of fractures in a grouting project based on a fracture pipe network model, the method comprising the following contents: Step 1: Processing fracture data Step 1.1: Cluster the cracks; Based on the data obtained from all the drilling exploration in the project, the k-means clustering method is used to group the fractures with similar occurrences into one group: first, the cluster center is initialized, that is, k cluster centers are randomly selected, and the distance between the fracture and each cluster center is calculated, and the fracture is assigned to the cluster where the nearest cluster center is located; then, the cluster center is updated according to the average dip and inclination data of the fractures in each cluster, and the process is repeated until the cluster center no longer changes; The cost function is defined as the sum of the distances from all data points to the center of the corresponding cluster (SSE). When the cost function changes the least, it is the appropriate k value. The optimal number of clusters k is determined, and the group number label corresponding to each crack is recorded at this time.

[0018] Step 1.2: Fit the fracture attribute distribution; After the fractures are clustered and grouped, the fracture properties (including fracture occurrence, trace length, and density) in the same group are statistically analyzed and fitted using an appropriate mathematical distribution model to obtain the distribution model of each group's fracture properties (occurrence, trace length, and density) and the geometric distribution parameter values ​​of the distribution model. Based on the distribution model, the probability density function of the fracture properties (occurrence, trace length, and density) can be obtained.

[0019] By calculating the goodness of fit index R², the distribution model with the largest R² value is selected as the best description of the fracture properties to ensure that the characterization of the fracture properties is as accurate as possible. The calculation method of is as follows,

[0020] in, is the expected value, is the sample value, is the average value, and n represents the number of sample cracks.

[0021] Step 2: Generate a 3D discrete fracture network model Step 2.1: Get the crack center point based on the crack density The model space range is determined according to the exploration range of all boreholes in the project, and the total volume of the model is determined by the model space range. The total volume of the model is multiplied by the fracture density of each group to obtain the number of fractures in a single group within the model space range. The random number generation function is used in MATLAB to generate the coordinates of the fracture center point of each group according to the three-dimensional Poisson distribution, and then the coordinates of the fracture center points of all groups are obtained; the coordinates of each fracture center point are independent of each other and are generated by a uniform distribution function; Step 2.2: At the crack center point generated in step 2.1, based on the distribution model of each group obtained in step 1.2 and the corresponding geometric distribution parameter values, randomly simulate the crack occurrence and crack trace length in MATLAB; then, based on the relationship between the crack trace length and the crack diameter, obtain the crack diameter under the generated crack trace length, and then obtain the three-dimensional discrete crack network model.

[0022] A three-dimensional disk is used to describe the crack, and its specific equation is as follows:

[0023] in , , ) is the center coordinate of the crack disk, For crack tendency, is the crack inclination angle, is the crack diameter, (x, y, z) is the coordinate of the three-dimensional crack surface in the spherical coordinate system; The crack diameter According to the relationship between the crack diameter and the crack trace length shown in formula (5), the relationship is as follows:

[0024] in, is the crack diameter, The crack is long. It can be directly measured from engineering data. t represents the expected value of the crack diameter. is the probability density function of the crack diameter; is the probability density function of the crack trace length.

[0025] Step 3: Generate a fractured pipe network model.

[0026] Step 3.1: Generate a connected discrete fracture network model The position of the cracks within the model space is determined to determine whether the position relationship of the crack surfaces is intersecting or non-intersecting. The depth-first search method is used to iteratively remove isolated and dead-end cracks until each crack is connected to at least two other cracks or at least one crack and a boundary to ensure the connectivity of the crack network and generate a connected discrete crack network model; Fractures that do not contribute to fluid flow in a discrete fracture network model can be divided into three categories: isolated fractures (not intersecting other fractures), dead-end fractures (intersecting only one fracture or only one model boundary), and isolated fracture groups (consisting of a group of fractures that intersect each other and form closed flow paths but do not exchange fluid with the model boundary). By iteratively removing fractures that do not intersect other fractures or boundaries, a connected fracture network that contributes to fluid flow is eventually formed.

[0027] Step 3.2: Generate fracture network model Based on the position relationship of the fractures determined in step 3.1, calculate the fracture intersection lines: if the fracture surfaces intersect, it is necessary to calculate their fracture intersection lines; if they do not intersect, they do not need to be calculated and have been deleted. Connect the midpoints of the fracture intersection lines with the center of the fracture surface in sequence, and represent the fractures in the interconnected fracture network with equivalent one-dimensional pipes, thereby converting the three-dimensional discrete fracture network model into a fracture pipe network model.

[0028] The number of connecting paths between two adjacent borehole sections can be 0, 1, or greater than 1. When it is 0, it means that the two borehole sections are not connected. When there are multiple connecting paths, the number of fractures corresponding to the path with the least number of fractures in the connecting path and the average fracture occurrence are selected as the basis for calculating the weight. The average fracture occurrence is the average value of all fracture occurrences on the currently selected connecting path.

[0029] like Figure 3 As shown in the figure, the center of the fracture disk inside the discrete fracture network model is set as the "central node", the midpoint of the intersection line between the connected fracture disks is set as the "intersection node", the midpoint of the intersection line between the fracture disk and the boundary of the model space range is set as the "boundary node", and an equivalent pipe is specified for the flow path between the central node and the intersection node / boundary node, that is, pipe a is placed between the center of fracture disk A and the midpoint of line h, and pipe b is placed between the center of fracture disk B and the midpoint of line h, where line h is the intersection line of fracture disk A and fracture disk B. The seepage between fracture disks A and B is carried out through pipes a and b. Therefore, a conceptual equivalent pipe network is formed to describe the seepage between intersecting multiple fractures.

[0030] Step 4: Calculate fracture connectivity Step 4.1: Determine the initial connectivity function matrix Due to the large length of the borehole, each borehole is usually divided into several sections in engineering practice, usually 5 meters per section. Assuming that multiple sections on the same borehole are definitely connected, It must be equal to 1, and the weight matrix is ​​also 1. The drilling network in the area to be evaluated has a number of drilling holes, and the connectivity between the drilling sections on all adjacent drilling holes is evaluated to analyze the fracture connectivity between these drilling sections.

[0031] Will It is defined as describing the connectivity between the i-th borehole segment and the j-th borehole segment. When the value of is 0, it means that the i-th drilling section is not connected to the j-th drilling section; when When the value of is 1, it means that the two sections of the borehole are connected; the connectivity of the borehole sections within the entire model space can be described by an m×m matrix. Based on the fracture pipe network model, the initial connectivity function matrix GC within the model space is obtained.

[0032] Step 4.2: Weighted analysis of the initial connectivity function matrix Obtain the data obtained from all borehole exploration in the project, divide the borehole into several sections, calculate the average trace length of each borehole section, and obtain the center line between the borehole sections of two adjacent boreholes, and calculate the angle between the center line and the average occurrence of the corresponding fracture. ; Weighted Connectivity The calculation formula is:

[0033] in, , is the average trace length of the kth drilling section trace and the jth drilling section trace, is the number of fractures contained in the connecting path with the least number of fractures between the two drilling sections, It is the angle between the line connecting the centers of the kth and jth drilling sections and the average occurrence of the fracture.

[0034] There may be multiple traces for each drilling section. If there are multiple traces, their average value is calculated as the average trace length of the current drilling section. When calculating the average trace length between two drilling sections, the averages may be calculated separately first, or all traces may be added together to directly calculate the average.

[0035] Then, the initial connectivity function matrix GC is multiplied by the weighting matrix ω, represents the element in row k and column j in ω, and the weighted connectivity matrix is ​​obtained :

[0036] Weighted connectivity matrix is a symmetric matrix whose elements represents the weighted connectivity value between the ith borehole segment and the jth borehole segment,

[0037] Represents the weighted connectivity matrix The element in the i-th row and j-th column of ; It represents the overall connectivity value of the j-th drilling section, which represents the connectivity of the j-th drilling section in the project. The larger the value, the higher the connectivity of the drilling section.

[0038] Example 1 The present embodiment provides a method for evaluating the connectivity of fractures in a grouting project based on a fracture pipe network model, comprising the following steps: Step 1: Process the fracture data.

[0039] Step 1.1: Cluster the cracks; Due to the influence of ground stress, similar cracks are often concentrated, so it is necessary to cluster the cracks first to obtain the distribution of similar cracks. The occurrence of cracks includes crack inclination and crack dip, such as Figure 2 As shown, For crack tendency, is the fracture inclination. The k-means clustering method is used to group fractures of similar occurrence into one group. First, the cluster center is initialized, that is, k cluster centers are randomly selected, and the distance between the fracture and each cluster center is calculated, and the fracture is assigned to the cluster where the nearest cluster center is located. Then, the cluster center is updated according to the average strike and inclination of the fractures in each cluster, and the process is repeated until the cluster center no longer changes. In order to determine the optimal number of clusters k, the cost function (loss function) is defined as the sum of the distances from all data points to the corresponding cluster centers (SSE). When the cost function loss is minimized, that is, the cost function change is minimized, it is the appropriate k value, and the group number label corresponding to each fracture at this time is recorded.

[0040] Step 1.2: Fit the fracture attribute distribution; After the fractures are clustered and grouped, the fracture properties in the same group (including fracture occurrence, trace length, and density) are statistically analyzed and fitted using an appropriate mathematical distribution model to obtain the geometric distribution parameters of each group of fracture properties. Common distribution models include normal distribution, lognormal distribution, negative exponential distribution, etc. Geometric distribution parameters refer to the relevant parameters when characterizing the distribution model.

[0041] By calculating the goodness of fit index R², the distribution model with the largest R² value is selected as the best description of the fracture properties to ensure that the characterization of the fracture properties is as accurate as possible. The calculation method of is as follows,

[0042] in, is the expected value, is the sample value, is the average value.

[0043] Step 2: Generate a discrete fracture network model.

[0044] Step 2.1: Get the crack center point based on the crack density The model space range is determined according to the exploration range of all boreholes in the project, and the total volume of the model is determined by the model space range. The total volume of the model is multiplied by the fracture density of each group to obtain the number of fractures in a single group within the model space range. The fracture center point obeys Poisson distribution. A random number generation function is used in MATLAB to generate the coordinates of the fracture center point of each group according to the three-dimensional Poisson distribution, and then the coordinates of the fracture center points of all groups are obtained; the coordinates of each fracture center point are independent of each other and are generated by a uniform distribution function; Step 2.2: Generate a fully random 3D discrete fracture network model At the crack center point position generated in step 2.1, based on the distribution model of each group obtained in step 1.2 and the corresponding geometric distribution parameter value, the crack occurrence and crack trace length are randomly simulated in MATLAB; then, according to the relationship between the crack trace length and the crack diameter, the crack diameter under the generated crack trace length is obtained, and then the three-dimensional discrete crack network model is obtained. At all the generated crack center point positions, corresponding instances are generated in MATLAB to obtain the three-dimensional discrete crack network model.

[0045] Step 3: Generate a fractured pipe network model.

[0046] Step 3.1: Generate a connected discrete fracture network model Determine the location of the fractures in the model area. Fractures that do not contribute to fluid flow in the model can be divided into three categories: isolated fractures (not intersecting with other fractures), dead-end fractures (intersecting with only one fracture or only one model boundary), and isolated fracture groups (consisting of a group of fractures that intersect with each other and form a closed flow path, but do not exchange fluid with the model boundary). To identify and remove these types of fractures, a depth-first search method is used to iteratively remove isolated and dead-end fractures until each fracture is connected to at least two other fractures or at least one fracture and a boundary to ensure the connectivity of the fracture network. By iteratively removing fractures that do not intersect with other fractures or boundaries, a connected fracture network that contributes to fluid flow is eventually formed.

[0047] Step 3.2: Generate fracture network model Based on the position relationship of the fractures determined in step 3.1, calculate the fracture intersection lines: if the fracture surfaces intersect, it is necessary to calculate their fracture intersection lines; if they do not intersect, they do not need to be calculated and have been deleted. Connect the midpoints of the fracture intersection lines with the center of the fracture surface in sequence, and represent the fractures in the interconnected fracture network with equivalent one-dimensional pipes, thereby converting the three-dimensional discrete fracture network model into a fracture pipe network model.

[0048] Step 4: Calculate fracture connectivity Step 4.1: Determine the initial connectivity function matrix The connectivity of the borehole segments within the entire model space can be described by an m×m matrix, which can quantitatively analyze and represent the connectivity between the borehole segments and further be used to infer the connectivity of the entire borehole segment area.

[0049] like Figure 5 As shown, the initial connectivity function matrix It can be expressed as , where both rows and columns represent the total number of drilling segments within the entire model space. Assuming that the same drilling holes are connected, the corresponding elements are all 1. Starting from a certain drilling hole, they are numbered from top to bottom, and the rows and columns of the matrix are formed according to the total number. The matrix represents 9 drilling holes and a total of 9 drilling segments.

[0050] Step 4.2: Weighted analysis of the initial connectivity function matrix Since the connectivity function matrix GC does not consider the correlation of fracture properties between borehole sections, factors such as fracture trace length, occurrence and number are introduced on the basis of step 4.1 as weighting factors to perform weighted analysis on the connectivity function matrix. ( ) is determined by three key factors: the average trace length of the kth drilling section trace and the jth drilling section trace ( ), the number of fractures contained in the connecting path with the least number of fractures between the two drilling sections ( ), and the angle between the center line of the kth and jth drilling sections and the average occurrence of the fracture . Weight The calculation formula is:

[0051] Then, the initial connectivity function matrix GC is multiplied by the weighting matrix ω to obtain the weighted connectivity matrix:

[0052] Weighted connectivity matrix is a symmetric matrix whose elements Represents the weighted connectivity value between the i-th borehole segment and the j-th borehole segment. The weighted connectivity matrix is a symmetric matrix whose elements represents the weighted connectivity value between the ith borehole segment and the jth borehole segment,

[0053] Represents the weighted connectivity matrix The element in the i-th row and j-th column of ; It represents the overall connectivity value of the jth borehole section, which represents the connectivity of the jth borehole section in the grouting project. The larger the value, the higher the connectivity of the borehole section.

[0054] For example, Figure 5 is an example of a fractured pipe network model in the spatial range of the model to be evaluated. The average trace length between the second and fifth borehole sections is 0.3, the number of fractures contained in the minimum number of fractures in the connection path between the two borehole sections is 6, and the angle between the center line of the second and fifth borehole sections and the average fracture occurrence (the average value of the occurrence of 6 fractures) is , then the corresponding weighting factor is 1.6. Figure 5 As shown, the weighted connectivity values ​​of each segment are 4.2, 6.5, 3.0, 8.9, 7.6, 8.0, 5.5, 6.7, and 5.6, among which the connectivity of the 4th drilling segment is the highest.

[0055] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical scheme and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

[0056] Any matters not described in the present invention are applicable to the prior art.

Claims

1. A method for evaluating the connectivity of fractures in grouting engineering based on a fracture network model, characterized in that: The evaluation method comprises the following steps: Step 1: Obtain the fracture pipe network model based on the data obtained from all drilling exploration in the project; Step 2: Generate the initial connectivity function matrix based on the fracture network model , m is the number of drilling sections, It is defined as describing the connectivity between the i-th borehole segment and the j-th borehole segment. When the value of is 0, it means that the i-th drilling section is not connected to the j-th drilling section; when When the value of is 1, it means that the two borehole sections are connected; and the connecting paths between the borehole sections of any adjacent boreholes are determined based on the fracture network model. When there are multiple connecting paths, the number of fractures corresponding to the connecting path with the least number of fractures and the average occurrence of fractures are selected to calculate the weight; Step 3: Obtain the data obtained from all borehole exploration in the project, divide the borehole into several sections, calculate the average trace length of each borehole section, and obtain the center line between the borehole sections of two adjacent boreholes, and calculate the angle between the center line and the average occurrence of the corresponding fracture. ; The weighting matrix ω is calculated according to formula (7): represents the k-th row and j-th column element in ω, in, , is the average trace length of the kth drilling section trace and the jth drilling section trace, is the number of fractures contained in the connecting path with the least number of fractures between the two drilling sections, is the angle between the center line of the kth and jth drilling sections and the average occurrence of the fracture; Step 4: Multiply the initial connectivity function matrix GC by the weighting matrix ω to obtain the weighted connectivity matrix : Weighted connectivity matrix is a symmetric matrix whose elements represents the weighted connectivity value between the ith borehole segment and the jth borehole segment, It represents the overall connectivity value of the j-th drilling section, which represents the connectivity of the j-th drilling section in the project. The larger the value, the higher the connectivity of the drilling section.

2. The method according to claim 1, characterized in that The process of step 1 is: 1) Based on the data obtained from all the drilling exploration in the project, the fracture data are clustered and grouped, and the fracture attributes in the same group are statistically analyzed and fitted to obtain the fracture attributes of each group, their distribution model and the geometric distribution parameter values ​​of the distribution model. The fracture attributes include fracture occurrence, fracture trace length and fracture density; 2) Determine the model space range according to the exploration range of all boreholes in the project, determine the total model volume from the model space range, multiply the total model volume by the fracture density of each group to obtain the number of fractures in a single group within the model space range, use the random number generation function in MATLAB to generate the coordinates of the fracture center point of each group according to the three-dimensional Poisson distribution, and then obtain the coordinates of the fracture center points of all groups; the coordinates of each fracture center point are independent of each other and are generated by a uniform distribution function; 3) At the generated crack center point, the crack occurrence and crack trace length are randomly simulated in MATLAB based on the distribution model of each group and the corresponding geometric distribution parameter value; then, according to the relationship between the crack trace length and the crack diameter, the crack diameter under the generated crack trace length is obtained, and then the three-dimensional discrete crack network model is obtained; 4) Determine the position of the fracture within the model space and whether the positional relationship of the fracture surfaces intersects. If the fracture surfaces intersect, calculate the intersection lines of the fracture surfaces, connect the midpoints of the intersection lines of the fracture surfaces with the center of the fracture surfaces in sequence, and represent the fractures with one-dimensional pipes, thereby converting the three-dimensional discrete fracture network model into a fracture pipe network model.

3. The method according to claim 2, characterized in that When determining the positional relationship of the fracture surfaces, the depth-first search method is used to iteratively remove isolated and dead-end fractures until each fracture is connected to at least two other fractures or at least one fracture and a boundary, ensuring the connectivity of the fracture network and generating a connected discrete fracture network model.

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