Rock mass random fracture network generation method, system, equipment and medium

Abstract

The invention discloses a rock mass random fracture network generation method, system and device and a medium, and relates to the technical field of rock mass random fracture network generation, and the method comprises the steps: obtaining the actual measurement data of a to-be-measured region rock mass; selecting a fracture network geometric parameter probability distribution model according to measured data; determining the number of fracture groups according to the occurrence of fracture development; stipulating a mean value and a standard deviation of occurrence, trace length and gap width of each group of fractures, inputting the mean value and the standard deviation into the distribution model, obtaining standard uniformly-distributed pseudo-random numbers of each group, and generating an initial random fracture network through specific transformation of the pseudo-random numbers; calculating node information of the random fracture network by adopting a plane scanning algorithm, and judging all intersection points of the fracture network; an isolated single fracture and a fracture with only one intersection point on the isolated single fracture are searched by adopting a block unit searching method, an isolated closed loop is searched, a random fracture network without considering the isolated single fracture and the closed loop is generated, and the method can simulate multiple groups of fracture networks under different scales without limitation.

Description

Technical Field

[0001] The invention relates to the technical field of rock mass random fracture network generation, and in particular to a rock mass random fracture network generation method, system, equipment and medium. Background Art

[0002] In the natural state, fractured rock mass often has fracture networks of different scales, which are different from intact rocks. The stability of rock slopes and surrounding rocks of underground caverns is often affected by fracture networks. During the excavation of slopes or underground caverns, the independent rock blocks cut out by the main control connected fracture network are often in random positions, which brings great inconvenience to stability analysis and design. It is often necessary to find out the fracture distribution in the engineering survey and design stage and carry out displacement prediction of random rock blocks in the main control connected network. Therefore, the generation of random fracture networks of rock mass based on survey results and the search of main control connected surfaces have good practical value.

[0003] The numerical simulation of fracture network is based on field survey and probability distribution model, and can also fully consider the microcracks distributed in rock mass. It has high theoretical and practical value, so it has attracted widespread attention from researchers, and a variety of simulation algorithms have been proposed. At present, the numerical simulation of fracture network mainly includes Monte Carlo method, graph theory method and image analysis method. Monte Carlo method can reflect the distribution law of different geometric parameters of fracture, and the program is easy to implement, so it has attracted the attention of many scholars and is a more commonly used algorithm at this stage. There is little analysis on the acquisition of random fracture network parameters in the existing technology, and the nodes, length, connectivity, etc. of the fracture network have an important influence on the calculation of rock mass stress and seepage. Some studies use the method of mathematical matrix to establish the connection matrix and loop matrix respectively. The former describes the connection relationship between fracture nodes and fracture line units and the fracture direction, and the latter describes the basic loop in the fracture network. Each basic loop corresponds to a polygonal rock block. However, the direction of each characteristic needs to be set manually during the calculation process, and this method will cause repeated calculation of nodes or fracture line units, which not only increases the complexity of the numerical calculation of the model, but also increases the calculation cost.

[0004] In summary, the existing technology still lacks a simple method for searching the main control connected network for the fracture network obtained by numerical simulation. It is very difficult to calculate the node (intersection) information on each fracture, and it is difficult to obtain parameters such as the number and position of intersections on each fracture in the random fracture network. Moreover, special fractures such as isolated fractures often appear in the random fracture network. These fractures do not constitute the main control structural surface of the rock stability analysis, which increases the complexity of the numerical calculation implementation of the model. Summary of the invention

[0005] In view of the problem that it is difficult to obtain the intersection information of each fracture and special fractures cannot be screened out in the prior art, the present invention proposes a method, system, equipment and medium for generating a random fracture network of a rock mass, which solves the problems existing in the prior art by generating a random fracture network of a rock mass and a search method for a main control connection network.

[0006] A method for generating a random fracture network of a rock mass comprises the following steps:

[0007] Obtain measured data of the rock mass in the area to be measured, and determine the probability distribution model of the fracture network geometric parameters, the number of rock fracture groups and the occurrence, trace length and gap width of each group of fractures based on the measured data of the rock mass;

[0008] The mean and standard deviation of each group of fracture occurrence, trace length and gap width are input into the probability distribution model to obtain each group of standard uniformly distributed pseudo-random numbers, and the initial random fracture network is generated by performing specific transformation on the pseudo-random numbers;

[0009] Determine all the intersections of each fracture line segment in the initial random fracture network; specifically, the method includes: inputting the endpoint information of each fracture line segment of the initial random fracture network into the plane scanning algorithm and sorting them by coordinate size, establishing a node sequence and a fracture line segment sorting sequence intersecting with the scanning line; determining whether the node sequence number of each fracture line segment is empty, if it is empty, outputting the node information and the fracture line segment number, if it is not empty, taking out the smallest node, dividing it into the left endpoint, the right endpoint and the intersection of the fracture line segment according to the smallest node, adding, deleting or exchanging the position of the fracture line segment sorting sequence, sorting the endpoints of the fracture line segment again by coordinate size, updating the fracture line segment node sequence, and obtaining all the intersections of the initial random fracture network;

[0010] According to all the intersections of the initial random fracture network, isolated single fractures, fractures with only one intersection point, and isolated closed loop fractures in the initial random fracture network are removed to generate a two-dimensional random fracture network.

[0011] Furthermore, the probability distribution model of the fracture network geometric parameters includes: uniform distribution, negative exponential distribution, normal distribution or log-normal distribution model.

[0012] Furthermore, a Monte-Carlo sampling method is used to obtain each group of standard uniformly distributed pseudo-random numbers, which specifically includes the following steps:

[0013] A set of pseudo-random number sequences is obtained by linear congruential method, and the acquisition process is expressed as:

[0014] x i+1 =(ax i +c)mod(m)

[0015]

[0016] Among them, ε i is a pseudo-random number; x i is a pseudo-random variable; m is the modulus, i.e., the maximum period of the production sequence; a is the multiplier, and 0<a<m; c is the increment, and 0≤c<m, mod is the remainder function; when m is 2k, the parameters a and c are expressed as: The parameter k reflects the length of the random number generator cycle;

[0017] According to the pseudo-random number sequence, a distribution function F(ε i ), then we get the inverse function F of the distribution function -1 (ε i ), i is a random number sequence number, let:

[0018] R i =F -1 (ε i )

[0019] Get a sample R that conforms to a uniform random number in the interval [0,1];

[0020] By performing corresponding transformations on the sample R, the sample is applied to different distribution functions in any interval, and random numbers x that conform to uniform distribution, negative exponential distribution, normal distribution or lognormal distribution are obtained on the interval [s, t]; the sample transformation expression is:

[0021] x=s+(ts)R

[0022] x=-ln(1-R) / M

[0023] Among them, M is the probability parameter, which refers to the number of times an event occurs per unit time;

[0024] According to the central limit theorem, n independent and identically distributed random variables, and obey the uniform distribution [0,1], As its mean and S as its standard deviation, the asymptotically normal distribution of x is:

[0025]

[0026] According to x that asymptotically obeys normal distribution, we can obtain the random number, mean and standard deviation of lognormal distribution, which are expressed as:

[0027]

[0028] Among them, x' is a random number that obeys the log-normal distribution. and S' are its mean and standard deviation respectively.

[0029] Furthermore, the endpoint information of each fracture line segment of the initial random fracture network includes the inclination angle, trace length and coordinates of the random fracture network.

[0030] Furthermore, a block unit search method is used to find isolated single fractures and fractures with only one intersection, which specifically includes the following steps:

[0031] According to the output node information and crack line segment number, a sequence Q, a sequence P and a sequence R are respectively established; the sequence Q is used to store the order of intersections on each crack line; the sequence P is used to store each crack line segment number and the number of nodes on the crack; the sequence R is used to store the coordinates of all nodes;

[0032] Find the number of the crack line segments with the number of nodes equal to 1 in the sequence P one by one; each time this event occurs, the sequence Q will be triggered, the node information stored in the corresponding crack in the sequence will be extracted, and then the node information will be deleted; the coordinates of the corresponding node information are found in the sequence R and cleared; if the number of nodes on all cracks in P is greater than 1 or equal to 0, then the search is completed, and the crack line segment number, the corresponding node order and coordinates are output; if there is a crack line segment in P that is not greater than 1 or equal to 0, then return to the initial search position and search in a loop to find isolated single cracks and cracks with only one intersection on them.

[0033] Furthermore, the search for isolated closed loop cracks using a correlation unit search method includes the following steps:

[0034] Read boundary information and node information of the fracture network; wherein the boundary selects the fracture at the leftmost or rightmost end of the fracture network;

[0035] Mark the line segments that intersect the boundary as associated line segments and store them in the array M;

[0036] Screen the intersecting line segment clusters of the associated line segments and remove the marked line segments and duplicate line segments;

[0037] The number of intersecting line segments stored in the intersecting line segment cluster is counted. If the number of line segments is not 0, the intersecting line segment is used as the boundary and the associated line segments are re-marked. If the number of intersecting line segments is 0, the search ends and all marked line segments and node information are output to obtain isolated closed loop cracks.

[0038] The present invention also provides a rock mass random fracture network generation system, comprising:

[0039] The data acquisition module is used to obtain the measured data of the rock mass in the test area, and determine the probability distribution model of the fracture network geometric parameters, the number of rock fracture groups and the occurrence, trace length and gap width of each group of fractures according to the measured data of the rock mass;

[0040] An initial random fracture network generation module is used to input the mean and standard deviation of each group of fracture occurrence, trace length and gap width into a probability distribution model, obtain each group of standard uniformly distributed pseudo-random numbers, and generate an initial random fracture network by performing specific transformations on the pseudo-random numbers;

[0041] The judgment module is used to judge all the intersections of each fracture line segment in the initial random fracture network; specifically, it includes: inputting the endpoint information of each fracture line segment of the initial random fracture network into the plane scanning algorithm and sorting them by coordinate size, establishing the node sequence and fracture line segment sorting series intersecting with the scanning line; judging whether the node sequence number of each fracture line segment is empty, if it is empty, outputting the node information and the fracture line segment number, if it is not empty, taking out the smallest node, dividing it into the left endpoint, the right endpoint and the intersection of the fracture line segment according to the smallest node, adding, deleting or exchanging the position of the fracture line segment sorting series, sorting the fracture line segment endpoints again by coordinate size, updating the fracture line segment node sequence, and obtaining all the intersections of the initial random fracture network;

[0042] The generation module is used to remove isolated single cracks, cracks with only one intersection point, and isolated closed loop cracks in the initial random crack network according to all intersection points of the initial random crack network, so as to generate a two-dimensional random crack network.

[0043] The present invention also provides a computer device for generating a rock mass random fracture network, comprising: a memory, a processor and a computer program stored in the memory, wherein the processor implements the steps of the rock mass random fracture network generating method when executing the computer program.

[0044] The present invention also provides a readable storage medium, wherein the readable storage medium stores a computer program, wherein the computer program includes program instructions, and when the program instructions are executed by a processor, the steps of the rock mass random fracture network generation method are executed.

[0045] The present invention provides a method, system, device and medium for generating a random fracture network in a rock mass, which has the following beneficial effects:

[0046] The present invention reasonably groups the fractures according to the occurrence of fracture development, determines the number of fracture groups that need to be simulated, selects a probability distribution model to generate an initial random fracture network, and can accurately simulate the occurrence of the rock fracture network; by inputting the endpoint information of each fracture line segment of the initial random fracture network into a plane scanning algorithm, all intersections of each fracture line segment are judged, and the calculation method is simple and efficient, and the main control connection network can be obtained conveniently, and multiple groups of fracture networks at different scales can be simulated without restriction; at the same time, special fractures such as isolated fractures that often appear in the initial random fracture network are removed, which reduces the complexity of the numerical calculation implementation of the model and facilitates the solution of the physical model under different subsequent working conditions. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 It is a flow chart of a method for generating a random fracture network of a rock mass and searching a master connected network in an embodiment of the present invention;

[0048] Figure 2 Schematic diagram of two groups of fracture network models in an embodiment of the present invention;

[0049] Figure 3 Schematic diagram of three groups of fracture network models in an embodiment of the present invention;

[0050] Figure 4 Three groups of fracture network distribution rose diagrams obtained by the random algorithm in the embodiment of the present invention;

[0051] Figure 5 A schematic diagram of a plane scanning method calculation flow in an embodiment of the present invention;

[0052] Figure 6 This is a schematic diagram of an initial crack network of plane scanning in an embodiment of the present invention;

[0053] Figure 7 This is a schematic diagram of the block unit calculation process in an embodiment of the present invention;

[0054] Figure 8 A schematic diagram of deleting invalid cracks using a block unit algorithm in an embodiment of the present invention;

[0055] Fig. 9 This is a schematic diagram of the calculation process of the association unit in an embodiment of the present invention;

[0056] Fig.10 A schematic diagram of an isolated closed loop for calculating an association unit in an embodiment of the present invention;

[0057] Fig.11 Schematic diagram of displacement calculation profile change of a rock slope with a main through-fracture network in an embodiment of the present invention. DETAILED DESCRIPTION

[0058] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments.

[0059] The present invention proposes a method for generating a random fracture network of a rock mass, which specifically comprises the following steps:

[0060] S1. Use field surveys, drilling data, geophysical data and other measured data to select the probability distribution model of fracture network geometry parameters and determine the length and width of the simulation area. The probability distribution model of fracture network geometry parameters includes: uniform distribution, negative exponential distribution, normal distribution or lognormal distribution.

[0061] S2. Rationally group the fractures according to their development patterns and determine the number of fracture groups that need to be simulated.

[0062] S3. For each group of fractures, reasonably determine the mean value of their occurrence and standard deviation (S), where the inclination is calculated as the angle between each fracture surface and the longitudinal axis (i.e., the y-axis), and is substituted as the initial value into the selected distribution model. The mean and standard deviation of each group of fracture trace lengths are specified, and are substituted as the initial value into the selected distribution model. The mean and standard deviation of each group of fracture widths are specified, and are substituted as the initial value into the selected distribution model. After the initial values ​​are brought into each model, a series of random numbers can be obtained using the following calculation method, and their distribution conforms to the selected distribution model, and finally a random fracture network can be generated.

[0063] Monte-Carlo sampling method is used to obtain pseudo-random numbers with standard uniform distribution, whose density function is constant within the sampling interval, and through specific transformation of pseudo-random numbers, random values ​​of geometric parameters that meet different distribution characteristics are finally obtained to complete random sampling. Specifically, the following steps are included:

[0064] (1) The linear congruential method generates pseudo-random numbers.

[0065] The linear congruential method obtains a set of pseudo-random number sequences through the following recursive relationship:

[0066] x i+1 =(ax i +c)mod(m) (1)

[0067]

[0068] In the formula, ε i is a pseudo-random number; x i is a pseudo-random variable; m is the modulus, that is, the maximum period of the production sequence; a is the multiplier and 0<a<m; c is the increment and 0≤c<m, and mod is the remainder function. All the above parameters are positive integers, and i is the pseudo-random number sequence.

[0069] From statistics, we know that when m is 2k, the selection formula of parameters a and c is as follows:

[0070] a=2 c +1 (3)

[0071]

[0072] Among them, c is a number near k / 2, which can be approximated as The parameter k reflects the length of the random number generator cycle. For example, the value of the parameter k is 31 for a computer system with a word length of 32 bits.

[0073] (2) Direct sampling of pseudo-random numbers (Monte-Carlo sampling).

[0074] According to the pseudo-random number sequence calculated above, a distribution function F(ε i ), then we can get its inverse function F -1 (ε i ),make:

[0075] R i =F -1 (ε i ) (5)

[0076] We can get samples that conform to uniform random numbers in the interval [0,1], F(ε i ) is the distribution function.

[0077] (3) Calculate random values ​​under different distributions from pseudo-random numbers.

[0078] The uniform random number sample R obtained by Monte-Carlo sampling is only distributed in the interval [0,1]. In order to make the sample applicable to different distribution functions in any interval, corresponding transformations should be performed through equations (6) to (9), and finally the random number x that conforms to the uniform distribution, negative exponential distribution, normal distribution or lognormal distribution in the interval [s,t] is obtained. The transformation expressions of each sample are as follows:

[0079] x=s+(ts)R (6)

[0080] x=-ln(1-R) / M (7)

[0081] Where M is the probability parameter, which refers to the number of times an event occurs per unit time.

[0082] According to the central limit theorem, n independent and identically distributed random variables, and they obey the uniform distribution [0,1], asymptotically obey the normal distribution. Then, from the above analysis, we can get x that asymptotically obeys the normal distribution as follows:

[0083]

[0084] Substituting the result of formula (8) into (9) we can obtain the random number, mean and standard deviation of the log-normal distribution.

[0085]

[0086] In the formula, x' is a random number that follows a log-normal distribution, and and S' are its mean and standard deviation respectively.

[0087] S4, importing the random fracture network inclination angle, trace length, coordinates and other parameters; using the plane scanning algorithm to calculate the node information of the random fracture network, and completing the determination of all intersections of the fracture network; specifically including the following steps:

[0088] (1) Import the endpoint information of each fracture network.

[0089] (2) Sort the endpoints of the crack coordinates by coordinate size (such as x-coordinate value) to establish a node sequence E of comparable line segments intersecting the scan line and a crack line segment sorting sequence T.

[0090] (3) Determine whether the sequence number of each line segment node is empty: if yes, output the node information and line segment number and end the calculation.

[0091] (4) If the number of line segment node sequences is not empty, take out the smallest node P, divide the line segment into the left endpoint, right endpoint and intersection according to P, and add, delete or exchange the position of the line segment sequence respectively, then return to step (2) to update the line segment node sequence.

[0092] In order to achieve the orderly arrangement of the positions of the crack segments at each scanning position, it is necessary to establish a crack segment sequence T during the solution process. This sequence is used to store the order of comparable segments in the crack network. As the segments are added, deleted or exchanged, the sequence T is updated. In addition, in order to ensure that the scan line can scan the information of the endpoints and intersections on each crack segment in order, the sequence sequence E of each node should also be established. The sequence E must arrange the positions of each node in a certain way (such as the size of the x coordinate). When the scan line encounters the left endpoint, right endpoint or intersection of the segment, the sequence E will activate the sequence T to update the sequence of the segment number, and the T sequence itself will also reorder the node position. This will be done gradually until no new comparable segments are added or deleted when the scan line moves to the next position, that is, the scan ends when the sequence E is empty.

[0093] At the same time, this method can also calculate whether there are real intersection points for comparable line segments, as follows:

[0094] Assume that any two intersecting line segments V1V2 and V3V4 have an intersection point p. The coordinates of the endpoints of each line segment are expressed as follows

[0095] V i =(x i ,y i )(i=1,2,3,4) (10)

[0096] Then, the equation of the line segment V1V2 can be expressed as:

[0097] x=x1+(x2-x1)t

[0098] y=y1+(y2-y1)t (11)

[0099] Similarly, the equation of line segment V3V4 is expressed as follows:

[0100] x=x3+(x4-x3)T

[0101] y=y3+(y4-y3)T (12)

[0102] The range of parameters t and T is [0,1]. The parameters represent the point (x,y) at a certain proportional position on the line segment. When t=0 or t=1, they represent the two endpoints of the V1V2 line segment respectively; and when t is at (0,1), it represents the position of any point between the two endpoints.

[0103] If the point (x, y) is the intersection of the two line segments V1V2 and V3V4, and both are located inside the endpoints of the two line segments, then from equations (11) and (12), we can know that:

[0104]

[0105] The above system of equations is linear, with only two unknowns t and T, which can be expressed as a matrix:

[0106]

[0107] If a solution exists, and satisfies:

[0108] 0≤t≤1,0≤T≤1 (15)

[0109] Then, the point (x, y) is between the line segments V1V2 and V3V4, and the values ​​of x and y can be obtained by equation (11) or (12). If a solution exists but does not satisfy equation (15), then the point (x, y) is located on the extension line of one of the two line segments. In this case, there is no actual intersection between the two line segments, and their intersection point is the intersection point of the extension lines.

[0110] S5. Using a block unit search method to find isolated single fractures (i.e. fractures that do not intersect with other line segments) and fracture line segments with only one intersection point; specifically, the following steps are included:

[0111] (1) According to the results of the plane scanning algorithm, the sequence Q, sequence P and sequence R can be established respectively. Sequence Q is used to store the order of intersection points on each crack line, such as arranging the order of nodes from small to large by x position, sequence P is used to store each crack number and the number of nodes on the crack, and sequence R is used to save the coordinates of all nodes;

[0112] (2) Find the number of the crack line segment with the number of nodes equal to 1 in the sequence P one by one. Each time this event occurs, the sequence Q is triggered, the node number stored in the corresponding crack in the sequence is extracted, and then the node number is deleted;

[0113] (3) Find the coordinates of the corresponding node number in the sequence R and clear them, thereby completing the search for a dead-end unit;

[0114] (4) If the number of nodes on all cracks in P is greater than 1 or equal to 0, the search ends and the crack number, corresponding node order and coordinates are output;

[0115] (5) If the number of crack segments in P is not greater than 1 or equal to 0, then return to the initial search position and search in a loop.

[0116] S6. In the seepage analysis of fractured rock mass, the connected main fracture network contributes the most to the seepage volume, while isolated fractures, single intersection fractures and closed loop fractures (i.e., multiple cross fractures not connected to the main fracture network) have a small seepage volume due to the unconnected fracture network. To simplify the analysis, they can be excluded from the seepage calculation. Therefore, they need to be removed from the initial random fracture network. After completing the search for isolated fractures and single intersection fractures in S5, the associated unit search method is used to find isolated closed loop fractures, and finally these three types of fractures are deleted to simplify the calculation. The specific steps include the following:

[0117] (1) Reading boundary conditions and crack network node information, where the boundary can be selected from the leftmost or rightmost crack, or a vertical line passing through the leftmost or rightmost crack can be specified as the sweep boundary, and the network nodes are swept sequentially from the boundary;

[0118] (2) Mark the line segments that intersect the boundary as associated line segments and store them in the array M;

[0119] (3) Screen the intersecting line segment clusters of the associated line segments and remove the marked line segments and duplicate line segments;

[0120] (4) Count the number of intersecting line segments stored in the intersecting line cluster. If the number of line segments is not 0, take the intersecting line segment as the boundary and return to step (2) to repeat the calculation; if the number of intersecting line segments is 0, the search ends and all marked line segments and node information are output.

[0121] S7. Generate a two-dimensional random fracture network model that ignores the master connection between isolated single fractures and closed loops.

[0122] Embodiment 1:

[0123] In one or more embodiments, a method for generating a random fracture network of a rock mass is disclosed, which specifically includes the following process:

[0124] 1. Based on field surveys, drilling data, geophysical data and other measured data, the probability distribution model of fracture network geometric parameters is obtained to determine the length and width of the simulation area, as shown in Table 1.

[0125] Table 1 Distribution and grouping of cracks in natural rock slopes

[0126]

[0127]

[0128] In this embodiment, the model size is 20m×20m, the fracture dip angle obeys a uniform distribution, and it is assumed that the trace length obeys a log-normal distribution.

[0129] 2. Rationally group the fractures according to their development patterns and determine the number of fracture groups that need to be simulated.

[0130] In this embodiment, the natural fractures are mainly divided into three groups, and the average values ​​of the inclination angles of each group are 0 degree, 35 degrees and 55 degrees respectively.

[0131] 3. For each group of fractures, reasonably determine the mean of their occurrence and standard deviation (S), where the inclination is calculated as the angle between each fracture surface and the longitudinal axis (i.e., y-axis), and is substituted into the distribution model selected in step 1 as the initial value.

[0132] 4. Define the mean and standard deviation of each group of crack trace lengths and substitute them as initial values ​​into the distribution model selected in step 1.

[0133] 5. Define the mean and standard deviation of each group of crack widths and substitute them as initial values ​​into the distribution model selected in step 1.

[0134] In this embodiment, the values ​​of the initial geometric parameters of each group of cracks are shown in Table 2:

[0135] Table 2 Values ​​of fracture geometric parameters for each group

[0136]

[0137] 6. Output the simulation results and post-process the results through secondary development of the drawing software.

[0138] In this embodiment, Figure 3 It shows that the three groups of fracture network models simulated by the above parameters and probability distribution model are Figure 4 The distribution range of each group of cracks in the simulated model is shown.

[0139] In this embodiment, the post-processing of the results includes using drawing software (CAD, Tecplot, etc.) to draw the simulation data, and cutting the model according to the model size selected in step 1 to obtain the final fracture network diagram.

[0140] Embodiment 2

[0141] In one or more embodiments, a two-dimensional random fracture network plane scanning algorithm is disclosed, combined with Figure 5 , specifically including the following process:

[0142] 1. Import the endpoint information of each fracture network.

[0143] In this embodiment, Figure 6 The initial fracture network obtained by the two-dimensional random simulation method is shown, which is used for the fracture network intersection judgment and intersection point calculation in this embodiment. The model size is 9cm×9cm, and 2 groups of fractures with a total of 16 fracture line segments are randomly generated.

[0144] 2. Sort the endpoints of the crack coordinates by coordinate size (such as x-coordinate value), and establish the node order sequence E of comparable line segments intersecting the scan line and its crack line segment sorting sequence T.

[0145] 3. Determine whether the order sequence number of each line segment node is empty: if yes, output the node information and line segment number and end the calculation.

[0146] 4 If the number of line segment node sequences is not empty, take out the smallest node P, divide it into the left endpoint, right endpoint and intersection of the line segment according to P, and add, delete or exchange the position of the line segment sequence respectively, then return to step (2) to update the line segment node sequence.

[0147] In this embodiment, the calculation program is written in Fortran language, and the scanning is performed from the left boundary to the right boundary of the model, and a total of 23 intersections are obtained. All intersections are arranged in the order of x coordinates from small to large. Detailed information such as the coordinates of each node and its intersecting line segment number are listed in Table 3.

[0148] Table 3 Coordinates of intersection points and intersection line numbers of fracture networks

[0149]

[0150]

[0151] Embodiment 3

[0152] In one or more embodiments, a block unit calculation method is disclosed, combined with Figure 7 , specifically including the following process:

[0153] 1. According to the results of the plane scanning algorithm, the sequence Q, sequence P and sequence R can be established respectively. Sequence Q is used to store the order of intersection points on each crack line, such as arranging the order of each node from small to large by x position, sequence P is used to store each crack number and the number of nodes on the crack, and sequence R is used to save the coordinates of all nodes.

[0154] In this embodiment, Figure 8 There are two groups of initial cracks, each with 5 and 8 cracks respectively, and the number of intersections of the crack network is 17. The order of the nodes is arranged from small to large by x coordinate. A calculation program is written in Fortran language to find isolated single cracks and crack line segments with only one intersection on them.

[0155] 2. Find the crack line segment numbers with the number of nodes equal to 1 in the sequence P one by one. Each time this event occurs, the sequence Q will be triggered, the node number stored in the corresponding crack in the sequence will be extracted, and then the node number will be deleted.

[0156] In this embodiment, Figure 8 As shown, there are three cracks, l2, l3 and l5, with the intersection number of 1, and l1 is a crack with the intersection number of 0. Then use the calculation program to read the sequence Q and leave the corresponding node number blank.

[0157] 3. Find the coordinates of the corresponding node number in the sequence R and clear them, thus completing the search for a dead-end unit.

[0158] 4. If the number of nodes on all cracks in P is greater than 1 or equal to 0, the search ends and the crack number, corresponding node order and coordinates are output.

[0159] 5. If there is a crack segment in P that is not greater than 1 or equal to 0, then return to the initial search position and search in a loop.

[0160] In this embodiment, a calculation program is used to traverse the crack number sequence P, and the coordinates and nodes of all cracks that are not 1 nodes are saved to facilitate the subsequent drawing of the crack network diagram.

[0161] Embodiment 4

[0162] In one or more embodiments, a method for calculating an association unit is disclosed, combining Fig. 9 , specifically including the following process:

[0163] 1. Read boundary conditions and fracture network node information.

[0164] In this embodiment, Fig.10 As shown, the left boundary line is first assumed as the boundary condition, and the fracture network nodes are imported after being calculated by the block elements.

[0165] 2. Mark the line segments that intersect the boundary as associated line segments and store them in the array M.

[0166] 3. Screen the intersecting line segment clusters of the associated line segments and remove the marked line segments and duplicate line segments.

[0167] In this embodiment, the associated line segments in the sequence M are used as boundaries to search for line segments intersecting with them and stored in the sequence N. In order to prevent repeated counting of intersecting line segments, the intersecting line segments in the sequence N need to be screened, the marked line segments in the sequence M are removed, and the line segment numbers that appear twice or more in N are merged.

[0168] 4. Count the number of intersecting line segments stored in the intersecting line cluster. If the number of line segments is not 0, use the intersecting line segment as the boundary and return to step (2) to calculate repeatedly. If the number of intersecting line segments is 0, the search ends and all marked line segments and node information are output.

[0169] Embodiment five:

[0170] In one or more embodiments, a process for combining the generation of a random fracture network of a rock mass and the search for a master connected network is disclosed, combined with Fig.11 , specifically including the following process:

[0171] 1. Select the probability distribution model of fracture network geometric parameters based on measured data.

[0172] 2. Rationally group the fissures according to their development patterns.

[0173] In this embodiment, the model slope angle is 60°, the slope height is 6.95m, the horizontal length is 3.97m, and the slope length is 8m. There are two groups of cracks inside the rock slope. To simplify the modeling process, it should be noted that the rock slope boundary line is also analyzed as the third group of cracks in this example.

[0174] 3. Generate random crack networks using Fortran language based on the Monte-Carlo sampling method.

[0175] In this embodiment, a program is written in Fortran language to generate two groups of fracture networks inside the rock slope. The boundary line of the rock slope is a known condition and is directly read into the program. Fig.11 To show that the initial fracture network rock slope profile also needs to delete some fractures extending beyond the rock slope boundary line.

[0176] 4. Use the plane scanning algorithm to calculate the node information of the random fracture network and determine all the intersections of the fracture network.

[0177] 5. Use the block element search method to find isolated single cracks and cracks with only one intersection.

[0178] In this embodiment, Fig.11 As shown in the figure, the calculation program obtains that there are 3 special cracks such as isolated cracks and dead-end cracks ( Fig.11 After deleting these cracks, we can get the main control connected crack network as follows: Fig.11 b.

[0179] 6. Use the associative unit search method to find isolated closed loops.

[0180] 7. Generate a two-dimensional random fracture network model with master control connectivity.

[0181] Based on the same inventive concept, the present invention also proposes a rock mass random fracture network generation system, comprising:

[0182] The data acquisition module is used to obtain the measured data of the rock mass in the test area, and determine the probability distribution model of the fracture network geometric parameters, the number of rock fracture groups and the occurrence, trace length and gap width of each group of fractures based on the measured data of the rock mass.

[0183] The initial random fracture network generation module is used to input the mean and standard deviation of each group of fracture occurrence, trace length and gap width into the probability distribution model, obtain each group of standard uniformly distributed pseudo-random numbers, and generate the initial random fracture network by performing specific transformations on the pseudo-random numbers.

[0184] The judgment module is used to judge all the intersections of each fracture line segment in the initial random fracture network; specifically, it includes: inputting the endpoint information of each fracture line segment of the initial random fracture network into the plane scanning algorithm and sorting them by coordinate size, establishing the node sequence and fracture line segment sorting series intersecting with the scanning line; judging whether the node sequence number of each fracture line segment is empty, if it is empty, outputting the node information and the fracture line segment number, if it is not empty, taking out the smallest node, dividing it into the left endpoint, the right endpoint and the intersection of the fracture line segment according to the smallest node, adding, deleting or exchanging the position of the fracture line segment sorting series, and then sorting the fracture line segment endpoints again by coordinate size, updating the fracture line segment node sequence, and obtaining all the intersections of the initial random fracture network.

[0185] The generation module is used to remove isolated single cracks, cracks with only one intersection point, and isolated closed loop cracks in the initial random crack network according to all intersection points of the initial random crack network, so as to generate a two-dimensional random crack network.

[0186] The present invention also provides a computer device for generating a random fracture network of a rock mass, comprising: a memory, a processor and a computer program stored in the memory, and the processor implements the steps of the method for generating a random fracture network of a rock mass when executing the computer program.

[0187] The present invention also provides a readable storage medium, which stores a computer program. The computer program includes program instructions. When the program instructions are executed by a processor, they are used to execute the steps of the method for generating a random fracture network of a rock mass.

[0188] 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.

Claims

1. A method for generating a random fracture network of a rock mass, characterized in that: The following steps are involved: Obtain measured data of the rock mass in the area to be measured, and determine the probability distribution model of the fracture network geometric parameters, the number of rock fracture groups and the occurrence, trace length and gap width of each group of fractures based on the measured data of the rock mass; The mean and standard deviation of each group of fracture occurrence, trace length and gap width are input into the probability distribution model to obtain each group of standard uniformly distributed pseudo-random numbers, and the initial random fracture network is generated by performing specific transformation on the pseudo-random numbers; Determine all the intersection points of each fracture line segment in the initial random fracture network; Specifically, the method includes: inputting the endpoint information of each fracture line segment of the initial random fracture network into the plane scanning algorithm and sorting them by coordinate size, establishing a node sequence and fracture line segment sorting series intersecting with the scanning line; judging whether the node sequence number of each fracture line segment is empty, if it is empty, outputting the node information and fracture line segment number, if it is not empty, taking out the smallest node, dividing it into the left endpoint, right endpoint and intersection of the fracture line segment according to the smallest node, adding, deleting or exchanging the position of the fracture line segment sorting series, sorting the endpoints of the fracture line segment again by coordinate size, updating the node sequence of the fracture line segment, and obtaining all the intersections of the initial random fracture network; According to all the intersections of the initial random fracture network, isolated single fractures, fractures with only one intersection point, and isolated closed loop fractures in the initial random fracture network are removed to generate a two-dimensional random fracture network.

2. A method for generating a random fracture network of a rock mass according to claim 1, characterized in that: The fracture network geometric parameter probability distribution model includes: uniform distribution, negative exponential distribution, normal distribution or log-normal distribution model.

3. A method for generating a random fracture network of a rock mass according to claim 1, characterized in that: Monte-Carlo sampling method is used to obtain pseudo-random numbers of each group of standard uniform distribution, which specifically includes the following steps: A set of pseudo-random number sequences is obtained by linear congruential method, and the acquisition process is expressed as: x i+1 =(ax i +c)mod(m) Among them, ε i is a pseudo-random number; x i is a pseudo-random variable; m is the modulus, i.e., the maximum period of the production sequence; a is the multiplier, and 0<a<m; c is the increment, and 0≤c<m, mod is the remainder function; when m is 2k, the parameters a and c are expressed as: The parameter k reflects the length of the random number generator cycle; According to the pseudo-random number sequence, a distribution function F(ε i ), then we get the inverse function F of the distribution function -1 (ε i ), i is a random number sequence number, let: R i =F -1 (e i ) Get a sample R that conforms to a uniform random number in the interval [0,1]; By performing corresponding transformations on the sample R, the sample is applied to different distribution functions in any interval, and random numbers x that conform to uniform distribution, negative exponential distribution, normal distribution or lognormal distribution are obtained on the interval [s, t]; the sample transformation expression is: x=s+(ts)R x=-ln(1-R) / M Among them, M is the probability parameter, which refers to the number of times an event occurs per unit time; According to the central limit theorem, there are n independent and identically distributed random variables, and they obey the uniform distribution [0,1]. X is their mean and S is their standard deviation. Then the asymptotically normal distribution of x is: According to x that asymptotically obeys normal distribution, we can obtain the random number, mean and standard deviation of lognormal distribution, which are expressed as: Among them, x' is a random number that obeys the log-normal distribution. and S' are its mean and standard deviation respectively.

4. A method for generating a random fracture network of a rock mass according to claim 1, characterized in that: The endpoint information of each fracture line segment of the initial random fracture network includes the inclination angle, trace length and coordinates of the random fracture network.

5. A method for generating a random fracture network in a rock mass according to claim 1, characterized in that: The block element search method is used to find isolated single fractures and fractures with only one intersection, which specifically includes the following steps: According to the output node information and crack line segment number, a sequence Q, a sequence P and a sequence R are respectively established; the sequence Q is used to store the order of intersections on each crack line; the sequence P is used to store each crack line segment number and the number of nodes on the crack; the sequence R is used to store the coordinates of all nodes; Find the number of the crack line segments with the number of nodes equal to 1 in the sequence P one by one; each time this event occurs, the sequence Q will be triggered, the node information stored in the corresponding crack in the sequence will be extracted, and then the node information will be deleted; the coordinates of the corresponding node information are found in the sequence R and cleared; if the number of nodes on all cracks in P is greater than 1 or equal to 0, then the search is completed, and the crack line segment number, the corresponding node order and coordinates are output; if there is a crack line segment in P that is not greater than 1 or equal to 0, then return to the initial search position and search in a loop to find isolated single cracks and cracks with only one intersection on them.

6. A method for generating a random fracture network in a rock mass according to claim 1, characterized in that: The search for isolated closed loop cracks using the correlation unit search method includes the following steps: Read boundary information and node information of the fracture network; wherein the boundary selects the fracture at the leftmost or rightmost end of the fracture network; Mark the line segments that intersect the boundary as associated line segments and store them in the array M; Screen the intersecting line segment clusters of the associated line segments and remove the marked line segments and duplicate line segments; The number of intersecting line segments stored in the intersecting line segment cluster is counted. If the number of line segments is not 0, the intersecting line segment is used as the boundary and the associated line segments are re-marked. If the number of intersecting line segments is 0, the search ends and all marked line segments and node information are output to obtain isolated closed loop cracks.

7. A rock mass random fracture network generation system, characterized in that: include: The data acquisition module is used to obtain the measured data of the rock mass in the test area, and determine the probability distribution model of the fracture network geometric parameters, the number of rock fracture groups and the occurrence, trace length and gap width of each group of fractures according to the measured data of the rock mass; An initial random fracture network generation module is used to input the mean and standard deviation of each group of fracture occurrence, trace length and gap width into a probability distribution model, obtain each group of standard uniformly distributed pseudo-random numbers, and generate an initial random fracture network by performing specific transformations on the pseudo-random numbers; A judgment module, used to judge all the intersection points of each fracture line segment in the initial random fracture network; Specifically, the method includes: inputting the endpoint information of each fracture line segment of the initial random fracture network into the plane scanning algorithm and sorting them by coordinate size, establishing a node sequence and fracture line segment sorting series intersecting with the scanning line; judging whether the node sequence number of each fracture line segment is empty, if it is empty, outputting the node information and fracture line segment number, if it is not empty, taking out the smallest node, dividing it into the left endpoint, right endpoint and intersection of the fracture line segment according to the smallest node, adding, deleting or exchanging the position of the fracture line segment sorting series, sorting the endpoints of the fracture line segment again by coordinate size, updating the node sequence of the fracture line segment, and obtaining all the intersections of the initial random fracture network; The generation module is used to remove isolated single cracks, cracks with only one intersection point, and isolated closed loop cracks in the initial random crack network according to all intersection points of the initial random crack network, so as to generate a two-dimensional random crack network.

8. A computer device for generating a random fracture network of a rock mass, characterized in that: include: A memory, a processor and a computer program stored in the memory, wherein when the processor executes the computer program, the steps of the method for generating a random fracture network of a rock mass as described in any one of claims 1 to 6 are implemented.

9. A readable storage medium, characterized in that: The readable storage medium stores a computer program, which includes program instructions. When the program instructions are executed by a processor, they are used to execute the steps of the method for generating a random fracture network of a rock mass as described in any one of claims 1 to 6.

Images