CN114088015A - Rapid intelligent generation and sectioning method for rock three-dimensional fracture network model - Google Patents

Rapid intelligent generation and sectioning method for rock three-dimensional fracture network model Download PDF

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CN114088015A
CN114088015A CN202010822751.7A CN202010822751A CN114088015A CN 114088015 A CN114088015 A CN 114088015A CN 202010822751 A CN202010822751 A CN 202010822751A CN 114088015 A CN114088015 A CN 114088015A
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胡高建
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Abstract

A method for rapidly and intelligently generating and sectioning a rock three-dimensional fracture network model belongs to the technical field of rock characterization, and comprises the following steps: (1) rapidly acquiring the rock mass structural plane by digital photogrammetry; (2) research and development of an intelligent drawing system for a rock mass structural plane polar diagram and a production rose diagram; (3) intelligent generation and sectioning system research and development of a rock three-dimensional fracture network model. The method adopts a digital photogrammetry method to quickly obtain the geometric parameters of the structural surface, programs and researches a polar point diagram and an intelligent production rose diagram drawing system of the rock structural surface based on a fuzzy equivalent clustering analysis method, programs and researches an intelligent generation and sectioning system of a three-dimensional fracture network model of the rock based on a Monte Carlo method, and realizes the quick and intelligent drawing of the polar point diagram, the production rose diagram, the three-dimensional fracture network model and the two-dimensional fracture network model of the structural surface. The method of the invention has the advantages of rapid and intelligent means and convenient engineering application.

Description

Rapid intelligent generation and sectioning method for rock three-dimensional fracture network model
Technical Field
The invention relates to a method for quickly and intelligently generating and sectioning a rock three-dimensional fracture network model, in particular to a method for quickly and intelligently generating and sectioning a rock three-dimensional fracture network model, which adopts a digital photogrammetry method to quickly obtain parameter information of a rock structural plane, is used for programming and researching a polar diagram and an intelligent drawing system of a rosette diagram of the rock structural plane based on a fuzzy equivalent clustering analysis method, is used for programming and researching the intelligent generating and sectioning system of the rock three-dimensional fracture network model based on a Monte Carlo method, combines the digital photogrammetry, the intelligent drawing of the polar diagram and the rosette diagram of the structural plane, the intelligent generating and software programming and researching of the rock three-dimensional fracture network, and belongs to the technical field of rock measurement and characterization.
Background
The structural plane is widely developed in the rock mass, the continuity and the integrity of the rock mass are damaged, and the stability of the rock mass is influenced and controlled to a great extent. In the long geological history evolution process, the rock mass is subjected to the action of multi-phase tectonic stress fields with different sizes and different directions, and the randomness, the form diversity, the distribution nonuniformity and the space combination complexity of the rock mass joint distribution are caused by the heterogeneity of the rock mass. The research on rock mass structure and description of properties thereof are always hot spots and difficulties in the fields of engineering geology and rock mass mechanics.
Structural planes play a crucial role in rock mass stability. For example, in the analysis of the stability of the rock slope, the occurrence of the structural plane has a great influence on the stability, for example, the slope instability can be caused by the joints that the rock mass develops in the same direction as the slope and the inclination angle is smaller than the slope angle, and if the development degree of the joints is dense, the stability of the slope is greatly weakened. Therefore, how to rapidly and effectively analyze and describe the occurrence of the structural surface and intelligently obtain the occurrence, distribution characteristics and the like of the structural surface in the region is always the most concerned and urgent key technical problem to be solved in the rock engineering field.
At present, the commonly used structural surface attitude acquisition methods at home and abroad mainly comprise a line measurement method, a fine line measurement method, a sampling window method and a drilling core joint acquisition method. When the measuring methods are applied, the measuring methods have the defects of large field workload, large error and poor effect, and cannot meet the requirements of modern construction. The digital photogrammetry technology is a brand-new method for quickly, efficiently, accurately and comprehensively acquiring the information of the random rock mass structural plane, and is particularly advanced in the aspect of solving the azimuth and scale information of the structural plane. The method has the advantages that according to a non-contact measurement means, a digital product based on three-dimensional space coordinate data and a solid model is provided, a real-time geological information exchange and feedback environment is created, structural plane information data of the rock body is directly obtained through software processing and operation, the three-dimensional solid model of the surface of the rock body in a measured range is established, and the development condition of the structural plane of the surface of the rock body and block information are visually reflected. Therefore, through the digital photogrammetry technology, the rapid acquisition of structural plane data can be realized.
Common statistical methods for structural plane attitude include structural plane rose diagrams and polar point diagrams. The structural surface rose diagram is a simple, clear and visual basic geological diagram and is widely applied to the aspects of representing the development degree and the dominant direction of the structural fracture surface. The method is simple and striking, can clearly reflect the direction of main joints, and is beneficial to analyzing the regional structure. In geological analysis, joint rosettes are usually plotted on a geological map according to the positions of measuring points so as to clearly reflect the relationship of joints, folds or faults of different structural parts, comprehensively analyze the condition of local stress of the joints, and roughly determine the property and the direction of a main stress axis. The trend rose diagram is mainly applied to the condition that the joint occurrence is relatively steep, and the trend and inclination angle rose diagram is mainly applied to the condition that the joint occurrence changes relatively large. The disadvantage of the rosette is that the rosette is grouped only according to the distribution of the occurrence, and when the same occurrence has multiple groups of structural surfaces, the rosette cannot be completely represented.
The polar diagram is a method for projecting the poles of the measured structural plane onto a planimetric projection diagram, and is a graphical method for analyzing lines and planes in a three-dimensional space by using points and lines on a plane. The joint and stratum attitude before structural failure can be recovered through rotation transformation, and the attitude of the dominant structural plane can be obtained through a joint isopycnic map. The polar diagram can simultaneously show the inclination of the structural plane and the distribution of the inclination angle, and is more scientific and accurate compared with a rose diagram method. The illustration of the pole figure is rather cumbersome. A pole point diagram such as an equal-density diagram is manually completed, and the procedures of casting points, density statistics, percentage conversion, drawing straight lines and the like are required, so that time is consumed, and errors are easy to occur. Meanwhile, the polar diagram also has the defects that the grouping result mainly depends on experience, and the grouping result is lack of objectivity under the condition that the boundary of each group is not obvious. Therefore, statistical analysis methods and computer processing programs are becoming important means for pole point mapping. Cluster analysis is a method of statistically studying the classification problem and its task is to assign all sample data to a number of clusters so that the sample data of the same cluster is clustered around the center of the cluster at relatively close distances and the sample data of different clusters at relatively far distances. The clustering analysis method comprises a systematic clustering method, an ordered sample clustering method, a dynamic clustering method, a fuzzy clustering method and the like. The fuzzy equivalent clustering method has better advantages on the aspect of processing the structure.
Since the structural surface rose diagram and the polar diagram can reflect different aspects of the occurrence of the structural surface, a single diagram always has more or less problems in the application and drawing processes. If the data volume of the structural surface measured on site is too large, the problems of complex processing and time consumption exist. Therefore, if the two drawing methods can be integrated into one drawing system, the self-intelligent drawing of the structural surface rose flower diagram and the intelligent drawing of the structural surface polar point diagram can be realized, and great benefits can be brought to the occurrence analysis of the structural surface. At present, although scholars at home and abroad realize the identification of structural aspect by writing programs, few scholars form a system intelligent software system.
The fractured rock mass is a very complex heterogeneous anisotropic medium, the structural property is the most basic characteristic of the fractured rock mass, and the fractured rock mass is influenced and controlled by the distribution condition of a structural plane like macroscopic mechanical characteristics. A large number of primary and secondary structural surfaces in the rock mass jointly form a fracture network state in the rock mass. The rock mass fracture network redistributes rock mass three-dimensional stress under the action of engineering disturbance, so that the fracture network is continuously expanded and communicated, the structural plane is further developed, and the strength and the stability of the rock mass are further reduced.
In fracture network simulation, structural surfaces are endowed with random characteristics, and structural surface network simulation technology can be used as a tool for quantitatively describing and processing a numerous structural surface system. By researching the characteristics and the distribution rule of the jointed cracks of the rock mass, a jointed network model with statistical similarity to the distribution characteristics of the actual jointed cracks of the on-site rock mass is constructed, and the method is the basis for calculating and analyzing the engineering mechanical behavior of the jointed cracked rock mass.
The rock mass structural plane grid simulation technology is an important means for researching the structural characteristics and the discontinuous mechanical characteristics of rock masses by simulating a structural plane grid by a Monte Carlo method by utilizing the principle of probability statistics. The fracture network simulation technology is a multidisciplinary crossing problem related to statistics, civil engineering, mining engineering, petroleum engineering, geological engineering and computers. The rock mass fracture network technology establishes a structural plane probability model through the probability distribution form of the structural plane, and then generates a rock mass fracture network model based on the Monte Carlo method.
The shortages of the rock three-dimensional fracture network model in the aspects of rapid and intelligent generation and sectioning are summarized as how to rapidly and intelligently realize data identification processing, occurrence grouping, pole point diagram drawing, data statistical analysis, data derivation and rose diagram drawing on a large amount of structural surface data measured in the field, and how to rapidly and intelligently realize solving of random numbers, generation of the three-dimensional fracture network model, intelligent sectioning of the two-dimensional fracture network model and data derivation. Namely how to form a set of rapid, intelligent and visual intelligent generation and sectioning system of a rock three-dimensional fracture network model. These deficiencies are particularly manifested in three broad areas:
(I) fast acquisition of structural surface data
The acquisition of the structural plane data is the basis for developing the rock three-dimensional fracture network simulation and is also an important link. However, people often adopt a manual method to obtain the structural plane, face the problems of large field workload, large error, poor effect and the like, and can not meet the requirements of modern construction. The digital photogrammetry technology is a brand-new method for quickly, efficiently, accurately and comprehensively acquiring the random rock mass structural plane information, can provide a digital product based on three-dimensional space coordinate data and a solid model according to a non-contact measurement means, creates a real-time geological information exchange and feedback environment, establishes a three-dimensional solid model of the rock mass surface in a measured range, and intuitively reflects the development condition and the block information of the rock mass surface structural plane. Through the digital photogrammetry technology, the data of the structural plane can be rapidly acquired.
The method comprises (II) intelligently drawing a polar point diagram and a rosette diagram of the rock mass structural plane, and specifically comprises the following 7 aspects:
(1) and intelligently identifying and importing structural surface data. A large amount of structural surface data are obtained through conventional field measurement, the structural surface data are numerous and complicated and irregular, manual processing is very complicated and difficult, a large amount of repeated operations exist, and the processing efficiency is low. How to intelligently identify and import the structural plane data with different occurrence into an analysis system is a first and important step for structural plane analysis.
(2) Intelligent grouping of structural plane occurrence. After the structure surface data is imported, how to intelligently realize the grouping of the structure surfaces according to a certain algorithm flow is the most important step in the analysis and the processing of the structure surfaces. Compared with the traditional statistical method, the intelligent grouping method has the advantages of rapidness, convenience, accuracy, great processing time saving and the like.
(3) And intelligently drawing a pole point diagram of the structural plane. The conventional structural plane attitude analysis usually adopts methods such as a scatter diagram and an isopycnic map, although the methods are intuitive and clear, only qualitative division can be given, quantitative structural plane attitude cannot be given, and the grouping result depends on human experience and is lack of objectivity. By the equivalent fuzzy clustering method, intelligent clustering analysis on the structure surface occurrence can be realized, actual data distribution can be accurately reflected, accurate occurrence distribution and occurrence data of the structure surface can be obtained, and the non-objectivity of artificial experience grouping can be overcome.
(4) And (4) intelligent statistical analysis of structural plane data. The geometric parameters of the structural surface mainly comprise inclination, inclination angle, trace length, spacing, fault distance and the like, and the statistics of the mean value, variance and probability distribution form has the problems of large workload, time and labor waste, high repeatability and the like during manual solving and processing, so that the intelligent statistical analysis of the structural surface data is realized, the solving workload and the solving time are effectively shortened, and the working efficiency is improved.
(5) And intelligently outputting structural plane data. The conventional structural surface processing method is complex, and data output cannot be effectively intelligent. Therefore, the intelligent output of the structural surface data is realized, and the data processing time is effectively shortened.
(6) And intelligently drawing the occurrence rose flower map. The conventional rose diagram drawing method is complicated, the intelligent drawing of large-batch structural surface data is difficult to realize, and when a certain birth form has multiple groups of structural surfaces, the drawing needs to be repeated for many times. Therefore, the intelligent drawing of the attitude rose flower map is realized, the structural plane attitude rose flower map can be rapidly and intelligently obtained, the workload is reduced, and the working efficiency is improved.
(7) The intelligence and systematicness of the drawing of the structural plane polar diagram and the occurrence rose diagram. The conventional structural plane polar diagram and the rose diagram are often drawn independently, manually analyzed or operated step by step, and no digital and intelligent process operation system such as systematic structural plane data intelligent import, intelligent classification, intelligent drawing, intelligent statistical analysis and intelligent output is formed.
The intelligent generation and sectioning of the rock three-dimensional fracture network model specifically comprises the following 5 aspects:
(1) and intelligently importing data. The processed data of the structural plane are often very large in quantity, and if the data are manually input into a software system, the processing efficiency is very low. Therefore, how to intelligently identify and import the mass structural plane data into an analysis system is a first and important step for intelligently generating and sectioning a rock three-dimensional fracture network model.
(2) And (6) solving the random number. The random number is solved by generating uniformly distributed random variables ri in the (0, 1) interval according to the distribution form of the structural surface, and generating random numbers subject to other distributions by using these uniformly distributed random variables. The density function of a plurality of joint geometric parameters needs to be solved, the method has the characteristics of large calculation amount, time consumption, repeatability and the like, and if the density function is manually solved, the method is quite complicated and troublesome. How to realize the solution of the random number by adopting a system intelligent method is an important work.
(3) And intelligently generating a three-dimensional fracture network model of the rock mass. The three-dimensional fracture network model of the rock mass utilizes the obtained random number and the data information of each structural plane, the structural plane network model obeying the model is intelligently reproduced, in-process disc central point coordinates (x, y, z) of each structural plane are involved, disc radius D, inclination DA, inclination DD, trend SD, thickness thin, normal direction NX, NY, NZ and joint groups are involved, the data volume is very large, the solving process is complicated, and the method can be realized by means of a computer program language. Therefore, how to utilize programming software and intelligently generate a three-dimensional fracture network model through the basic information and random numbers of each structural plane is a key point and a difficult point of research.
(4) And intelligently cutting the two-dimensional fracture network model. A conventional two-dimensional fracture network model is usually generated and realized through a two-dimensional data form, but the range covered by the two-dimensional data has certain limitation, meanwhile, the two-dimensional data has certain limitation, and after a two-dimensional section is generated through the two-dimensional data, the reliability degree of a real rock body which can be represented is greatly reduced. Therefore, the real section state of the rock can be better reflected by cutting at any angle and any position on the three-dimensional fracture network model.
(5) And intelligently outputting data. Whether the three-dimensional fracture network model or the two-dimensional fracture network model is adopted, a large amount of structural plane basic information is contained in the three-dimensional fracture network model or the two-dimensional fracture network model, the structural plane basic information mainly comprises tendency, inclination angle, trace length, spacing and fault distance, mean value, variance and probability distribution form, central point coordinates (x, y, z), disc radius D, thickness thin, normal direction NX, NY, NZ, joint grouping and the like, the data information is output intelligently and standardly, the solving workload and the solving time can be effectively shortened, and the working efficiency is improved.
In view of the above, the invention provides a method for rapidly and intelligently generating and sectioning a rock three-dimensional fracture network model.
Disclosure of Invention
The invention provides a method for quickly and intelligently generating and sectioning a three-dimensional fracture network model of a rock body, aiming at realizing quick and intelligent representation reconstruction and quick and arbitrary section sectioning of the three-dimensional fracture network model of the rock body. The method is characterized in that a digital photogrammetry method is adopted to quickly obtain geometrical parameter information of a rock mass structural plane, a rock mass structural plane polar diagram and occurrence rose diagram intelligent drawing system is programmed and researched based on a fuzzy equivalent clustering analysis method, a rock mass three-dimensional fracture network model intelligent generation and sectioning system is programmed and researched based on a Monte Carlo method, digital photogrammetry, structural plane polar diagram and occurrence rose diagram intelligent drawing, rock mass three-dimensional fracture network intelligent generation and software programming research and development are combined, and the method for quickly and intelligently generating and sectioning the rock mass three-dimensional fracture network model is provided.
In order to solve the technical problems, the invention provides the following technical scheme: a method for rapidly and intelligently generating and sectioning a rock three-dimensional fracture network model comprises the following steps:
1) the method comprises the following steps of (1) quickly obtaining the digital photogrammetry of the structural surface:
1.1: selecting a rock mass with good surface joint development and no obstacles as a photogrammetric region according to the rock mass range and the spatial position of the observation region, and vertically erecting a marker post on one side of the measurement region for calibrating the distance between any two points on the finally generated three-dimensional image;
1.2: selecting a structural surface which is exposed, has a large area and is smooth on the surface of the rock mass as a calibration point, measuring the inclination and the dip angle by using a compass, and marking the structural surface for orientation reality of an image during post-processing;
1.3: sequentially photographing a rock mass at the left and right positions right in front of the selected region by using a high-resolution camera, wherein the distance D between a lens and the measured rock mass and the distance B between two imaging positions satisfy the relation B of D/8-D/5 when the two times of photographing are carried out;
1.4: after the measurement point data are collected, the marker post is taken back, and the marker post returns to the room for further post-processing operation;
1.5: importing the left and right views obtained by field photogrammetry into a software analysis system, matching the pixels in the left and right views by adopting reference calibration, pixel matching and image deformation correction to synthesize a three-dimensional solid model of the rock surface;
1.6: according to the size of the marker post and the appearance of the calibration point measured by the compass, the orientation, the size and the distance of the three-dimensional solid model are realized;
1.7: identifying and positioning each structural surface based on a realistic entity model, and deriving structural surface data information;
2) the intelligent drawing system for the polar point diagram and the occurrence rose flower diagram of the rock mass structural plane is developed and developed, and the process is as follows:
the intelligent drawing system for the polar point diagram and the occurrence rose flower diagram of the rock mass structural plane comprises 8 modules which are respectively: the system comprises a data intelligent import module, a fuzzy equivalent clustering algorithm intelligent calculation module, a polar diagram intelligent drawing module, a structural surface intelligent statistical analysis module, a data intelligent output module, a trend rose diagram intelligent drawing module and an inclination rose diagram intelligent drawing module;
2.1: intelligent data import module
The system is used for intelligently importing structural surface data obtained by digital photogrammetry into a software system;
2.2: intelligent computing module for fuzzy equivalent clustering algorithm
Based on a fuzzy equivalent clustering algorithm, the fuzzy equivalent clustering of the structural plane occurrence is intelligently realized, and the process is as follows:
2.2.1: let the number of actual measurement samples of the structural surface be N, and the ith sample be (x)i1，xi2)，xi1For structural orientation, xi2The structural plane inclination angle is shown as the fuzzy relation matrix R:
Figure BSA0000216906350000071
element r in the matrixijRepresenting the similarity degree between the ith sample and the jth sample for the similarity coefficient between the ith sample and the jth sample; r isijLarger indicates that sample i is more similar to sample j;
2.2.2: calculating a similarity coefficient rij：
Figure BSA0000216906350000072
Wherein i is 1, 2.. N; n ═ 1, 2.. N; c is a calculation parameter (c is more than or equal to 0 and less than or equal to 1), and the value of c is properly selected to ensure that r isijIn [0, 1 ]]Disperse from the middle;
2.2.3: solving the closure t (R):
R2＝RR
R4＝R2R2
... (3)
2.2.4: and (3) carrying out structural surface grouping judgment: the fuzzy matrix multiplication steps are similar to the common matrix multiplication, and the difference is that the multiplication of two terms is not carried out first and then the addition is carried out, but the multiplication is carried out first and then the multiplication is carried out; if C ═ AB, then the elements in C
Figure BSA0000216906350000073
The n-level fuzzy relation matrix R is n continuous multiplications of R: namely, it is
Figure BSA0000216906350000074
When R isn＝Rn+1＝Rn+2When (5)
There, the fuzzy equivalence matrix t (R) ═ Rn (6)
Taking the definite intercept set level lambda belongs to [0, 1 ]]If r in t (R)ijIf the structural plane i and the structural plane j belong to the same class, the structural plane i and the structural plane j belong to the same class; namely, it is
rij≥λ (7)
2.3: intelligent pole point drawing module
Intelligently drawing a structural plane occurrence polar point diagram according to the clustering result and the structural plane grouping result, wherein the process is as follows;
2.3.1: drawing a polar point diagram by adopting a lower hemisphere equal-angle projection method;
2.3.2: will tend to be alphadAnd angle of inclination betadThe represented joint attitude data is converted into structural plane attitude data expressed by normal vector of joint unit, and alpha is setnAnd betanThe inclination direction and the inclination angle are respectively the unit normal vector of the structural plane, and the unit normal vector of any structural plane is expressed as X ═ X (X1，x2，x3) At this time, each point on the hemispherical surface corresponds to a joint occurrence form, and the formula is as follows:
X＝(x1，x2，x3) (8)
Figure BSA0000216906350000081
Figure BSA0000216906350000082
αd∈(0，360)，βd∈(0，90) (11)
2.3.3: obtaining structural surface attitude data expressed by unit normal vectors;
2.3.4: based on normal attitude data of the structural plane and based on the longitudinal section principle diagram of the spatial planogrammatic projection diagram of the structural plane, the point A 'is the planogrammatic projection of the plane normal, and the coordinate x of the point A' on the planogrammatic projection diagram is calculated by combining the planogrammatic projection principle diagramnAnd ynThe formula is as follows:
Figure BSA0000216906350000083
Figure BSA0000216906350000084
2.3.5: solving the coordinate point (x) of the declination projection of all the structural surface normalsn，yn)；
2.3.6: drawing a base circle with the diameter as the unit length, drawing two diameters of vertical and horizontal, and marking E, S, W, N;
2.3.7: the coordinate (x) of the declination plane of all the structural surfaces is measuredn，yn) Plotted on a base circle graph;
2.3.8: intelligently drawing a pole point diagram of the structural plane;
2.4: structural surface intelligent statistical analysis module
The method is used for carrying out intelligent statistical analysis on the clustered structural surfaces, and obtaining the mean value and variance of the tendency, the inclination angle, the trace length, the spacing and the fault distance of each group of structural surfaces, and the process is as follows:
2.4.1: determining a sample partition interval m;
2.4.2: solving sample range
Figure BSA0000216906350000091
Figure BSA0000216906350000092
2.4.3: calculate each partition interval Mm：
Figure BSA0000216906350000093
2.4.4: determining the probability of the sample falling in each partition interval, and counting the number N of the samples falling in each interval by using a computer circulation languagemCalculating the probability P of the number of samples by combining the total number N of samplesm：
Figure BSA0000216906350000094
2.4.5: solving sample mean
Figure BSA0000216906350000095
Figure BSA0000216906350000096
2.4.6: solving for sample variance S2Wherein S is the standard deviation:
Figure BSA0000216906350000097
2.4.7: according to the probability PmAutomatically drawing the probability distribution form of the inclination, dip angle, trace length, space and fault distance of each group of structural surfaces；
2.5: intelligent data output module
Intelligently outputting classification information of the occurrence of the structural surfaces, including the mean value and the variance of the inclination, the inclination angle, the trace length, the spacing and the fault distance of each group of structural surfaces;
2.6: intelligent drawing module for trend rose diagram
According to the trend rose diagram drawing method, intelligently drawing the structural surface trend rose diagram, and the process is as follows;
2.6.1: converting the joint trend data into northeast and northwest directions, sequencing the data in sequence according to the size of the joint trend azimuth angles, grouping the data at intervals of alpha-10 degrees, and naming T in each groupi；
Ti＝{α，α+9°} (19)
α＝10(i-1) (20)
i∈(1，10)∪(27，36) (21)
2.6.2: counting the number of joints in each group
Figure BSA0000216906350000101
And average orientation of each set of joints
Figure BSA0000216906350000102
Figure BSA0000216906350000103
i∈(1，10)∪(27，36) (23)
2.6.3: according to the size of the drawing and the number of each group of joints, selecting a line segment with a certain length to represent a group of joints, and determining the scale L of the line segmentT；
2.6.4: to equal to the scale LTRepresented, most numerous set of joints
Figure BSA0000216906350000104
Length of line segment
Figure BSA0000216906350000105
Making a semicircle by taking the radius, making a north-south line and an east-west line by crossing the circle center, and marking an azimuth angle on the circumference;
Figure BSA0000216906350000106
NTis constant (24)
2.6.5: for each group of joints TiAccording to the average trend
Figure BSA0000216906350000107
Making marks on the semi-circle for the azimuth angle, from the center of the circle to the radius of the mark point on the circumference, according to the number in the group
Figure BSA0000216906350000108
And scale LTSet out a point
Figure BSA0000216906350000109
The point represents the average trend and the number of joints of the group of joints;
Figure BSA00002169063500001010
2.6.6: are connected in sequence
Figure BSA00002169063500001011
And
Figure BSA00002169063500001012
if the certain group of the rational numbers is zero, the connection line returns to the circle center, and then the connection line is led out from the circle center to be connected with the next group;
2.6.7: drawing a joint trend rose diagram;
2.7: intelligent drawing module for trend rose chart
The module has the function of intelligently drawing the structural surface tendency rose diagram according to the tendency rose diagram drawing method;
2.7.1: the joint tendency data are sequentially sorted according to the size of the joint tendency azimuth angle, and are grouped at an angle of 10 degrees every thetaGroup name Dj；
Dj＝{θ，θ+9°} (26)
θ＝10(j-1) (27)
j∈(1，36) (28)
2.7.2: counting the number of joints in each group
Figure BSA00002169063500001013
And average propensity of each group of joints
Figure BSA00002169063500001014
Figure BSA00002169063500001015
j∈(1，36) (30)
2.7.3: according to the size of the drawing and the number of each group of joints, selecting a line segment with a certain length to represent a group of joints, and determining the scale L of the line segmentD；
2.7.4: to equal to the scale LDRepresented, most numerous set of joints
Figure BSA0000216906350000111
Length of line segment
Figure BSA0000216906350000112
Making a circle for the radius, making a north-south line and an east-west line through the circle center, and marking an azimuth angle on the circumference;
Figure BSA0000216906350000113
NDis constant (31)
2.7.5: for each group of joints DjIn average tendency
Figure BSA0000216906350000114
Making marks on the semi-circle for the azimuth angle, from the center of the circle to the radius of the mark point on the circumference, according to the number in the group
Figure BSA0000216906350000115
And scale LDSet out a point
Figure BSA0000216906350000116
The point represents the set of joint mean tendency and the number of joints;
Figure BSA0000216906350000117
2.7.6: are connected in sequence
Figure BSA0000216906350000118
And
Figure BSA0000216906350000119
if the certain group of the rational numbers is zero, the connection line returns to the circle center, and then the connection line is led out from the circle center to be connected with the next group;
2.7.7: drawing a structural surface trend rose diagram;
2.8: intelligent drawing module for rose diagram at inclination angle
According to the inclination angle rose diagram drawing method, intelligently drawing the inclination angle rose diagram of the structural plane, and the process is as follows;
2.8.1: sequentially ordering the joint data according to the size of the joint inclination azimuth angle, grouping every theta as 10 degrees, and naming each group as Qj；
Qj＝{θ，θ+9°} (33)
θ＝10(j-1) (34)
j∈(1，36) (35)
2.8.2: counting the number of joints in each group
Figure BSA00002169063500001110
Average propensity of each group of joints
Figure BSA00002169063500001111
And average tilt angle
Figure BSA00002169063500001112
Figure BSA00002169063500001113
j∈(1，36) (37)
Figure BSA00002169063500001114
2.8.3: selecting a certain inclination angle to represent a group of joints according to the size of the drawing and the number of the joints, and determining a scale L of the line segmentQ；
2.8.4: to equal to the scale LQRepresented, most numerous set of joints
Figure BSA0000216906350000121
Line segment inclination angle
Figure BSA0000216906350000122
Making a circle for the radius, making a north-south line and an east-west line through the circle center, and marking an azimuth angle on the circumference;
Figure BSA0000216906350000123
NQis constant (39)
2.8.5: for each group of joints DjIn average tendency
Figure BSA0000216906350000124
Making marks on the semi-circle for the azimuth angle, from the center of the circle to the radius of the mark point on the circumference, according to the number in the group
Figure BSA0000216906350000125
And scale LQSet out a point
Figure BSA0000216906350000126
The point represents the set of joint mean inclination angles and the number of joints;
Figure BSA0000216906350000127
2.8.6: are connected in sequence
Figure BSA0000216906350000128
And
Figure BSA0000216906350000129
if the certain group of the rational numbers is zero, the connection line returns to the circle center, and then the connection line is led out from the circle center to be connected with the next group;
2.8.7: drawing a rose picture of the joint inclination angle;
3) the intelligent generation and sectioning system of the rock three-dimensional fracture network model is developed and developed, and the process is as follows;
the intelligent generation of three-dimensional fracture network model of rock mass and the system research and development of dissecting mainly include 5 modules, do respectively: the system comprises a data intelligent importing module, a random number intelligent solving module, a three-dimensional fracture network model intelligent generating module and a two-dimensional fracture network model intelligent cutting module;
3.1: intelligent data import module
The system is used for intelligently importing the processed structural surface data into a software system;
3.2: intelligent random number solving module
Based on the Monte Carlo method and the joint distribution form, the random number is solved intelligently, and the process is as follows:
3.2.1: the generation of pseudo random numbers, the mathematical method for generating random numbers should satisfy the following conditions: the generated random number sequence is uniformly distributed in the (0, 1) interval; there should be no correlation between sequences; the random sequence has a long enough repetition period, the generation speed on a computer is high, the occupied memory space is small, and the repeatability is complete;
3.2.2: the Monte Carlo method is to reproduce a structural plane network model obeying the model according to a determined structural plane geometric probability model, the core of the method is the randomness of sampling numbers, high-quality random numbers can obtain good simulation results, namely, uniformly distributed random variables ri are generated in a (0, 1) interval, and random numbers obeying other distributions are generated by utilizing the uniform random variables;
3.2.3: the density function of the joint geometric parameters generally comprises normal distribution, log-normal distribution, negative exponential distribution and uniform distribution;
3.2.4: determining basic geometric parameters for generating joints according to the obtained random numbers;
3.3: intelligent generation module for three-dimensional fracture network model
According to the established structural surface geometric probability model, determining basic geometric parameters for generating joints by using the obtained random numbers, and intelligently reproducing a structural surface network model complying with the model, wherein the process is as follows;
3.3.1: storing the data of each group of structural surfaces into a text file according to the structural surface data intelligent statistical result and the obtained random number, and expressing the data by st.dat;
3.3.2: and the content format of dat data is as follows: the coordinates (x, y and z) of the center point of the disc of each structural plane, the radius D of the disc, the inclination angle DA, the inclination DD, the trend SD, the thickness thin, the normal directions NX, NY and NZ and joints are grouped;
3.3.3: in order to distinguish the structural surfaces of different groups, the structural surface discs of the same group are endowed with the same color and are represented by a number array GID;
3.3.4: writing a program by using Matlab software, reading a structural plane data file st.dat, and intelligently generating a rock three-dimensional fracture network model after running;
3.3.5: obtaining a rock three-dimensional fracture network model;
3.4: two-dimensional fracture network model intelligent cutting module
On the basis of the three-dimensional fracture network model, intelligently cutting the two-dimensional fracture network model at any angle and any direction in an intelligent manner, wherein the process is as follows;
3.4.1: combining a Matlab software programming tool on the three-dimensional fracture network model, and taking the central point of the three-dimensional fracture network model as a center to realize the section cutting function at any angle;
3.4.2: obtaining a two-dimensional fracture network model of any angle passing through a central point;
3.4.3: combining a Matlab software programming tool on the three-dimensional fracture network model, and realizing the section cutting function of any angle and any direction on any position of the three-dimensional fracture network model;
3.4.4: obtaining a two-dimensional fracture network model at any angle and any direction;
3.4.5: and storing the data on the cut section into an st1.dat file, wherein the section is in a three-dimensional coordinate system, and the data formats in the file are as follows from left to right: joint center point coordinates (x, y, z), joint length D, inclination DA, inclination DD, strike SD, thickness thin, normal directions NX, NY, NZ;
3.4.6: converting the three-dimensional coordinate system into a two-dimensional coordinate system, and storing the two-dimensional profile data into a st2.dat file, wherein the data formats in the file are as follows from left to right: joint center point coordinates (x, y), joint length D, inclination DA, inclination DD, thickness thin, normal directions NX, NY, NZ;
3.5: intelligent data output module
The data output of the three-dimensional fracture network model and the data output of any two-dimensional fracture network model are intelligently realized, and the process is as follows;
3.5.1: intelligently outputting st.dat file data information;
3.5.2: intelligently outputting data information of the st1.dat file;
3.5.3: and intelligently outputting the data information of the st2.dat file.
The invention has the following beneficial effects:
1. adopting a digital photogrammetry technology to quickly obtain geometric parameter data of the structural surface, wherein the geometric parameter data comprises inclination, dip angle, spacing, breaking distance and track length;
2. the intelligent drawing system of the polar point diagram and the occurrence rose flower diagram of the rock mass structural plane is researched and developed, and intelligent import of parameters of the rock mass structural plane, intelligent fuzzy equivalent clustering grouping of occurrence, intelligent drawing of the polar point diagram, intelligent statistical analysis of the structural plane, intelligent output of data, intelligent drawing of a trend rose flower diagram and intelligent drawing of an inclination rose flower diagram are realized;
3. the intelligent generation and sectioning system of the rock three-dimensional fracture network model is developed, and intelligent import of structural surface data, intelligent solution of random numbers, intelligent generation of the three-dimensional fracture network model, intelligent cutting of the two-dimensional fracture network model and intelligent output of data are realized;
4. the rapid intelligent generation of a rock three-dimensional fracture network model and the rapid arbitrary cutting of a two-dimensional profile are realized;
5. the method has intelligent means and convenient and fast engineering application.
Description of the drawings:
FIG. 1 is a method flow diagram.
Fig. 2 is a structural plane attitude polar diagram.
FIG. 3 is a structural plane oriented rose diagram.
FIG. 4 is a structural plane trend rosette.
FIG. 5 is a two-dimensional fracture network model diagram.
Detailed Description
The invention will be further explained with reference to the drawings.
Referring to fig. 1 to 5, a method for rapidly and intelligently generating and sectioning a three-dimensional fracture network model of a rock mass, the method flow is shown in fig. 1, and the method comprises the following steps:
1) the method comprises the following steps of (1) quickly obtaining the digital photogrammetry of the structural surface:
1.1: selecting a rock mass with good surface joint development and no obstacles as a photogrammetric region according to the rock mass range and the spatial position of the observation region, and vertically erecting a marker post on one side of the measurement region for calibrating the distance between any two points on the finally generated three-dimensional image;
1.2: selecting a structural surface which is exposed, has a large area and is smooth on the surface of the rock mass as a calibration point, measuring the inclination and the dip angle by using a compass, and marking the structural surface for orientation reality of an image during post-processing;
1.3: sequentially photographing a rock mass at the left and right positions right in front of the selected region by using a high-resolution camera, wherein the distance D between a lens and the measured rock mass and the distance B between two imaging positions satisfy the relation B of D/8-D/5 when the two times of photographing are carried out;
1.4: after the measurement point data are collected, the marker post is taken back, and the marker post returns to the room for further post-processing operation;
1.5: importing the left and right views obtained by field photogrammetry into a software analysis system, matching the pixels in the left and right views by adopting reference calibration, pixel matching and image deformation correction to synthesize a three-dimensional solid model of the rock surface;
1.6: according to the size of the marker post and the appearance of the calibration point measured by the compass, the orientation, the size and the distance of the three-dimensional solid model are realized;
1.7: identifying and positioning each structural surface based on a realistic entity model, and deriving structural surface data information;
2) the intelligent drawing system for the polar point diagram and the occurrence rose flower diagram of the rock mass structural plane is developed and developed, and the process is as follows:
the intelligent drawing system for the polar point diagram and the occurrence rose flower diagram of the rock mass structural plane comprises 8 modules which are respectively: the system comprises a data intelligent import module, a fuzzy equivalent clustering algorithm intelligent calculation module, a polar diagram intelligent drawing module, a structural surface intelligent statistical analysis module, a data intelligent output module, a trend rose diagram intelligent drawing module and an inclination rose diagram intelligent drawing module;
2.1: intelligent data import module
The system is used for intelligently importing structural surface data obtained by digital photogrammetry into a software system;
2.2: intelligent computing module for fuzzy equivalent clustering algorithm
Based on a fuzzy equivalent clustering algorithm, the fuzzy equivalent clustering of the structural plane occurrence is intelligently realized, and the process is as follows:
2.2.1: let the number of actual measurement samples of the structural surface be N, and the ith sample be (x)i1，xi2)，xi1For structural orientation, xi2The structural plane inclination angle is shown as the fuzzy relation matrix R:
Figure BSA0000216906350000151
element r in the matrixijRepresenting the similarity degree between the ith sample and the jth sample for the similarity coefficient between the ith sample and the jth sample; r isijLarger indicates that sample i is more similar to sample j;
2.2.2: calculating a similarity coefficient rij：
Figure BSA0000216906350000161
Wherein i is 1, 2.. N; n ═ 1, 2.. N; c is a calculation parameter (c is more than or equal to 0 and less than or equal to 1), and the value of c is properly selected to ensure that r isijIn [0, 1 ]]Disperse from the middle;
2.2.3: solving the closure t (R):
R2＝RR
R4＝R2R2
... (3)
2.2.4: and (3) carrying out structural surface grouping judgment: the fuzzy matrix multiplication steps are similar to the common matrix multiplication, and the difference is that the multiplication of two terms is not carried out first and then the addition is carried out, but the multiplication is carried out first and then the multiplication is carried out; if C ═ AB, then the elements in C
Figure BSA0000216906350000162
n-level fuzzy relation matrix R is n R continuous multiplication; namely, it is
Figure BSA0000216906350000163
When R isn＝Rn+1＝Rn+2When (5)
There, the fuzzy equivalence matrix t (R) ═ Rn (6)
Taking the definite intercept set level lambda belongs to [0, 1 ]]If r in t (R)ijIf the structural plane i and the structural plane j belong to the same class, the structural plane i and the structural plane j belong to the same class; namely, it is
rij≥λ (7)
2.3: intelligent pole point drawing module
Intelligently drawing a structural plane occurrence polar point diagram according to the clustering result and the structural plane grouping result, wherein the process is as follows;
2.3.1: drawing a polar point diagram by adopting a lower hemisphere equal-angle projection method;
2.3.2: will tend to be alphadAnd angle of inclination betadThe represented joint attitude data is converted into structural plane attitude data expressed by normal vector of joint unit, and alpha is setnAnd betanThe inclination direction and the inclination angle are respectively the unit normal vector of the structural plane, and the unit normal vector of any structural plane is expressed as X ═ X (X1，x2，x3) At this time, each point on the hemispherical surface corresponds to a joint occurrence form, and the formula is as follows:
X＝(x1，x2，x3) (8)
Figure BSA0000216906350000171
Figure BSA0000216906350000172
αd∈(0，360)，βd∈(0，90) (11)
2.3.3: obtaining structural surface attitude data expressed by unit normal vectors;
2.3.4: based on normal attitude data of the structural plane and based on the longitudinal section principle diagram of the spatial planogrammatic projection diagram of the structural plane, the point A 'is the planogrammatic projection of the plane normal, and the coordinate x of the point A' on the planogrammatic projection diagram is calculated by combining the planogrammatic projection principle diagramnAnd ynThe formula is as follows:
Figure BSA0000216906350000173
Figure BSA0000216906350000174
2.3.5: solving the coordinate point (x) of the declination projection of all the structural surface normalsn，yn)；
2.3.6: drawing a base circle with the diameter as the unit length, drawing two diameters of vertical and horizontal, and marking E, S, W, N;
2.3.7: the coordinate (x) of the declination plane of all the structural surfaces is measuredn，yn) Plotted on a base circle graph;
2.3.8: intelligently realizing the drawing of a pole point diagram of the structural plane, as shown in figure 2;
2.4: structural surface intelligent statistical analysis module
The method is used for carrying out intelligent statistical analysis on the clustered structural surfaces, and obtaining the mean value and variance of the tendency, the inclination angle, the trace length, the spacing and the fault distance of each group of structural surfaces, and the process is as follows:
2.4.1: determining a sample partition interval m;
2.4.2: solving sample range
Figure BSA0000216906350000175
Figure BSA0000216906350000176
2.4.3: calculate each partition interval Mm：
Figure BSA0000216906350000181
2.4.4: determining the probability of the sample falling in each partition interval, and counting the number N of the samples falling in each interval by using a computer circulation languagemCalculating the probability P of the number of samples by combining the total number N of samplesm：
Figure BSA0000216906350000182
2.4.5: solving sample mean
Figure BSA0000216906350000183
Figure BSA0000216906350000184
2.4.6: solving for sample variance S2Wherein S is the standard deviation:
Figure BSA0000216906350000185
2.4.7: according to the probability PmAutomatically drawing the probability distribution forms of the inclination, the dip angle, the trace length, the spacing and the fault distance of each group of structural surfaces;
2.5: intelligent data output module
Intelligently outputting classification information of the occurrence of the structural surfaces, including the mean value and the variance of the inclination, the inclination angle, the trace length, the spacing and the fault distance of each group of structural surfaces;
2.6: intelligent drawing module for trend rose diagram
According to the trend rose diagram drawing method, intelligently drawing the structural surface trend rose diagram, and the process is as follows;
2.6.1: converting the joint trend data into northeast and northwest directions, sequencing the data in sequence according to the size of the joint trend azimuth angles, grouping the data at intervals of alpha-10 degrees, and naming T in each groupi；
Ti＝{α，α+9°} (19)
α＝10(i-1) (20)
i∈(1，10)∪(27，36) (21)
2.6.2: counting the number of joints in each group
Figure BSA0000216906350000186
And average orientation of each set of joints
Figure BSA0000216906350000187
Figure BSA0000216906350000188
i∈(1，10)∪(27，36) (23)
2.6.3: according to the size of the drawing and the number of each group of joints, selecting a line segment with a certain length to represent a group of joints, and determining the scale L of the line segmentT；
2.6.4: to equal to the scale LTRepresented, most numerous set of joints
Figure BSA0000216906350000191
Length of line segment
Figure BSA0000216906350000192
Making a semicircle by taking the radius, making a north-south line and an east-west line by crossing the circle center, and marking an azimuth angle on the circumference;
Figure BSA0000216906350000193
NTis constant (24)
2.6.5: for each group of joints TiAccording to the average trend
Figure BSA0000216906350000194
Making marks on the semi-circle for the azimuth angle, from the center of the circle to the radius of the mark point on the circumference, according to the number in the group
Figure BSA0000216906350000195
And scale LTSet out a point
Figure BSA0000216906350000196
The point represents the average trend and the number of joints of the group of joints;
Figure BSA0000216906350000197
2.6.6: are connected in sequence
Figure BSA0000216906350000198
And
Figure BSA0000216906350000199
if the certain group of the rational numbers is zero, the connection line returns to the circle center, and then the connection line is led out from the circle center to be connected with the next group;
2.6.7: drawing a joint trend rose diagram, as shown in FIG. 3; (ii) a
2.7: intelligent drawing module for trend rose chart
The module has the function of intelligently drawing the structural surface tendency rose diagram according to the tendency rose diagram drawing method;
2.7.1: sequencing the joint tendency data in sequence according to the size of the joint tendency azimuth angle, grouping every theta as 10 degrees, and naming D in each groupj；
Dj＝{θ，θ+9°} (26)
θ＝10(j-1) (27)
j∈(1，36) (28)
2.7.2: counting the number of joints in each group
Figure BSA00002169063500001910
And average propensity of each group of joints
Figure BSA00002169063500001911
Figure BSA00002169063500001912
j∈(1，36) (30)
2.7.3: according to the size of the drawing and the number of each group of joints, selecting a line segment with a certain length to represent a group of joints, and determining the scale L of the line segmentD；
2.7.4: to equal to the scale LDRepresented, most numerous set of joints
Figure BSA00002169063500001913
Length of line segment
Figure BSA00002169063500001914
Making a circle for the radius, making a north-south line and an east-west line through the circle center, and marking an azimuth angle on the circumference;
Figure BSA00002169063500001915
NDis constant (31)
2.7.5: for each group of joints DjIn average tendency
Figure BSA00002169063500001916
Making marks on the semi-circle for the azimuth angle, from the center of the circle to the radius of the mark point on the circumference, according to the number in the group
Figure BSA00002169063500001917
And scale LDSet out a point
Figure BSA00002169063500001918
The point represents the set of joint mean tendency and the number of joints;
Figure BSA0000216906350000201
2.7.6: are connected in sequence
Figure BSA0000216906350000202
And
Figure BSA0000216906350000203
if the certain group of the rational numbers is zero, the connection line returns to the circle center, and then the connection line is led out from the circle center to be connected with the next group;
2.7.7: plotting the structural aspect trend rose plot, as shown in fig. 4;
2.8: intelligent drawing module for rose diagram at inclination angle
According to the inclination angle rose diagram drawing method, intelligently drawing the inclination angle rose diagram of the structural plane, and the process is as follows;
2.8.1: sequentially ordering the joint data according to the size of the joint inclination azimuth angle, grouping every theta as 10 degrees, and naming each group as Qj；
Qj＝{θ，θ+9°} (33)
θ＝10(j-1) (34)
j∈(1，36) (35)
2.8.2: counting the number of joints in each group
Figure BSA0000216906350000204
Average propensity of each group of joints
Figure BSA0000216906350000205
And average tilt angle
Figure BSA0000216906350000206
Figure BSA0000216906350000207
j∈(1，36) (37)
Figure BSA0000216906350000208
2.8.3: selecting a certain inclination angle to represent a group of joints according to the size of the drawing and the number of the joints, and determining a scale L of the line segmentQ；
2.8.4: to equal to the scale LQRepresented, most numerous set of joints
Figure BSA0000216906350000209
Line segment inclination angle
Figure BSA00002169063500002010
Making a circle with radius, making north-south line and east-west line through the center of the circleAzimuth is indicated on the week;
Figure BSA00002169063500002011
NQis constant (39)
2.8.5: for each group of joints DjIn average tendency
Figure BSA00002169063500002012
Making marks on the semi-circle for the azimuth angle, from the center of the circle to the radius of the mark point on the circumference, according to the number in the group
Figure BSA00002169063500002013
And scale LQSet out a point
Figure BSA00002169063500002014
The point represents the set of joint mean inclination angles and the number of joints;
Figure BSA00002169063500002015
2.8.6: are connected in sequence
Figure BSA00002169063500002016
And
Figure BSA00002169063500002017
if the certain group of the rational numbers is zero, the connection line returns to the circle center, and then the connection line is led out from the circle center to be connected with the next group;
2.8.7: drawing a rose picture of the joint inclination angle;
3) the intelligent generation and sectioning system of the rock three-dimensional fracture network model is developed and developed, and the process is as follows;
the intelligent generation of three-dimensional fracture network model of rock mass and the system research and development of dissecting mainly include 5 modules, do respectively: the system comprises a data intelligent importing module, a random number intelligent solving module, a three-dimensional fracture network model intelligent generating module and a two-dimensional fracture network model intelligent cutting module;
3.1: intelligent data import module
The system is used for intelligently importing the processed structural surface data into a software system;
3.2: intelligent random number solving module
Based on the Monte Carlo method and the joint distribution form, the random number is solved intelligently, and the process is as follows:
3.2.1: the generation of pseudo random numbers, the mathematical method for generating random numbers should satisfy the following conditions: the generated random number sequence is uniformly distributed in the (0, 1) interval; there should be no correlation between sequences; the random sequence has a long enough repetition period, the generation speed on a computer is high, the occupied memory space is small, and the repeatability is complete;
3.2.2: the Monte Carlo method is to reproduce a structural plane network model obeying the model according to a determined structural plane geometric probability model, the core of the method is the randomness of sampling numbers, high-quality random numbers can obtain good simulation results, namely, uniformly distributed random variables ri are generated in a (0, 1) interval, and random numbers obeying other distributions are generated by utilizing the uniform random variables;
3.2.3: the density function of the joint geometric parameters generally comprises normal distribution, log-normal distribution, negative exponential distribution and uniform distribution;
3.2.4: determining basic geometric parameters for generating joints according to the obtained random numbers;
3.3: intelligent generation module for three-dimensional fracture network model
According to the established structural surface geometric probability model, determining basic geometric parameters for generating joints by using the obtained random numbers, and intelligently reproducing a structural surface network model complying with the model, wherein the process is as follows;
3.3.1: storing the data of each group of structural surfaces into a text file according to the structural surface data intelligent statistical result and the obtained random number, and expressing the data by st.dat;
3.3.2: and the content format of dat data is as follows: the coordinates (x, y and z) of the center point of the disc of each structural plane, the radius D of the disc, the inclination angle DA, the inclination DD, the trend SD, the thickness thin, the normal directions NX, NY and NZ and joints are grouped;
3.3.3: in order to distinguish the structural surfaces of different groups, the structural surface discs of the same group are endowed with the same color and are represented by a number array GID;
3.3.4: writing a program by using Matlab software, reading a structural plane data file st.dat, and intelligently generating a rock three-dimensional fracture network model after running;
3.3.5: obtaining a rock three-dimensional fracture network model;
3.4: two-dimensional fracture network model intelligent cutting module
On the basis of the three-dimensional fracture network model, intelligently cutting the two-dimensional fracture network model at any angle and any direction in an intelligent manner, wherein the process is as follows;
3.4.1: combining a Matlab software programming tool on the three-dimensional fracture network model, and taking the central point of the three-dimensional fracture network model as a center to realize the section cutting function at any angle;
3.4.2: obtaining a two-dimensional fracture network model of any angle passing through a central point;
3.4.3: combining a Matlab software programming tool on the three-dimensional fracture network model, and realizing the section cutting function of any angle and any direction on any position of the three-dimensional fracture network model;
3.4.4: obtaining a two-dimensional fracture network model of any angle and any direction, as shown in FIG. 5;
3.4.5: and storing the data on the cut section into an st1.dat file, wherein the section is in a three-dimensional coordinate system, and the data formats in the file are as follows from left to right: joint center point coordinates (x, y, z), joint length D, inclination DA, inclination DD, strike SD, thickness thin, normal directions NX, NY, NZ;
3.4.6: converting the three-dimensional coordinate system into a two-dimensional coordinate system, and storing the two-dimensional profile data into a st2.dat file, wherein the data formats in the file are as follows from left to right: joint center point coordinates (x, y), joint length D, inclination DA, inclination DD, thickness thin, normal directions NX, NY, NZ;
3.5: intelligent data output module
The data output of the three-dimensional fracture network model and the data output of any two-dimensional fracture network model are intelligently realized, and the process is as follows;
3.5.1: intelligently outputting st.dat file data information;
3.5.2: intelligently outputting data information of the st1.dat file;
3.5.3: and intelligently outputting the data information of the st2.dat file.

Claims (3)

1. A method for rapidly and intelligently generating and sectioning a rock three-dimensional fracture network model is characterized by comprising the following steps:
(1) the method comprises the following steps of (1) quickly obtaining the digital photogrammetry of the structural surface:
1.1: selecting a rock mass with good surface joint development and no obstacles as a photogrammetric region according to the rock mass range and the spatial position of the observation region, and vertically erecting a marker post on one side of the measurement region for calibrating the distance between any two points on the finally generated three-dimensional image;
1.2: selecting a structural surface which is exposed, has a large area and is smooth on the surface of the rock mass as a calibration point, measuring the inclination and the dip angle by using a compass, and marking the structural surface for orientation reality of an image during post-processing;
1.3: sequentially photographing a rock mass at the left and right positions right in front of the selected region by using a high-resolution camera, wherein the distance D between a lens and the measured rock mass and the distance B between two imaging positions satisfy the relation B of D/8-D/5 when the two times of photographing are carried out;
1.4: after the measurement point data are collected, the marker post is taken back, and the marker post returns to the room for further post-processing operation;
1.5: importing the left and right views obtained by field photogrammetry into a software analysis system, matching the pixels in the left and right views by adopting reference calibration, pixel matching and image deformation correction to synthesize a three-dimensional solid model of the rock surface;
1.6: according to the size of the marker post and the appearance of the calibration point measured by the compass, the orientation, the size and the distance of the three-dimensional solid model are realized;
1.7: identifying and positioning each structural surface based on a realistic entity model, and deriving structural surface data information;
(2) research and development of an intelligent drawing system for a rock mass structural plane polar diagram and a production rose diagram;
(3) intelligent generation and sectioning system research and development of a rock three-dimensional fracture network model.
2. The method for rapidly and intelligently generating and sectioning the three-dimensional rock fracture network model according to claim 1, wherein in the step (3), the development process of the intelligent generation and sectioning system of the three-dimensional rock fracture network model is as follows:
the intelligent generation of three-dimensional fracture network model of rock mass and the system research and development of dissecting mainly include 5 modules, do respectively: the system comprises a data intelligent importing module, a random number intelligent solving module, a three-dimensional fracture network model intelligent generating module and a two-dimensional fracture network model intelligent cutting module;
3.1: intelligent data import module
The system is used for intelligently importing the processed structural surface data into a software system;
3.2: intelligent random number solving module
Based on the Monte Carlo method and the joint distribution form, the random number is solved intelligently, and the process is as follows:
3.2.1: the generation of pseudo random numbers, the mathematical method for generating random numbers should satisfy the following conditions: the generated random number sequence is uniformly distributed in the (0, 1) interval; there should be no correlation between sequences; the random sequence has a long enough repetition period, the generation speed on a computer is high, the occupied memory space is small, and the repeatability is complete;
3.2.2: the Monte Carlo method is to reproduce a structural plane network model obeying the model according to a determined structural plane geometric probability model, the core of the method is the randomness of sampling numbers, high-quality random numbers can obtain good simulation results, namely, uniformly distributed random variables ri are generated in a (0, 1) interval, and random numbers obeying other distributions are generated by utilizing the uniform random variables;
3.2.3: the density function of the joint geometric parameters generally comprises normal distribution, log-normal distribution, negative exponential distribution and uniform distribution;
3.2.4: determining basic geometric parameters for generating joints according to the obtained random numbers;
3.3: intelligent generation module for three-dimensional fracture network model
According to the established structural surface geometric probability model, determining basic geometric parameters for generating joints by using the obtained random numbers, and intelligently reproducing a structural surface network model complying with the model, wherein the process is as follows;
3.3.1: storing the data of each group of structural surfaces into a text file according to the structural surface data intelligent statistical result and the obtained random number, and expressing the data by st.dat;
3.3.2: and the content format of dat data is as follows: the coordinates (x, y and z) of the center point of the disc of each structural plane, the radius D of the disc, the inclination angle DA, the inclination DD, the trend SD, the thickness thin, the normal directions NX, NY and NZ and joints are grouped;
3.3.3: in order to distinguish the structural surfaces of different groups, the structural surface discs of the same group are endowed with the same color and are represented by a number array GID;
3.3.4: writing a program by using Matlab software, reading a structural plane data file st.dat, and intelligently generating a rock three-dimensional fracture network model after running;
3.3.5: obtaining a rock three-dimensional fracture network model;
3.4: two-dimensional fracture network model intelligent cutting module
On the basis of the three-dimensional fracture network model, intelligently cutting the two-dimensional fracture network model at any angle and any direction in an intelligent manner, wherein the process is as follows;
3.4.1: combining a Matlab software programming tool on the three-dimensional fracture network model, and taking the central point of the three-dimensional fracture network model as a center to realize the section cutting function at any angle;
3.4.2: obtaining a two-dimensional fracture network model of any angle passing through a central point;
3.4.3: combining a Matlab software programming tool on the three-dimensional fracture network model, and realizing the section cutting function of any angle and any direction on any position of the three-dimensional fracture network model;
3.4.4: obtaining a two-dimensional fracture network model at any angle and any direction;
3.4.5: and storing the data on the cut section into an st1.dat file, wherein the section is in a three-dimensional coordinate system, and the data formats in the file are as follows from left to right: joint center point coordinates (x, y, z), joint length D, inclination DA, inclination DD, strike SD, thickness thin, normal directions NX, NY, NZ;
3.4.6: converting the three-dimensional coordinate system into a two-dimensional coordinate system, and storing the two-dimensional profile data into a st2.dat file, wherein the data formats in the file are as follows from left to right: joint center point coordinates (x, y), joint length D, inclination DA, inclination DD, thickness thin, normal directions NX, NY, NZ;
3.5: intelligent data output module
The data output of the three-dimensional fracture network model and the data output of any two-dimensional fracture network model are intelligently realized, and the process is as follows;
3.5.1: intelligently outputting st.dat file data information;
3.5.2: intelligently outputting data information of the st1.dat file;
3.5.3: and intelligently outputting the data information of the st2.dat file.
3. The method for rapidly and intelligently generating and sectioning the rock mass three-dimensional fracture network model according to claim 1 or 2, wherein in the step (2), the processes of the development of the rock mass structural plane polar diagram and the productive rosette diagram intelligent drawing system are as follows:
the intelligent drawing system for the polar point diagram and the occurrence rose flower diagram of the rock mass structural plane comprises 8 modules which are respectively: the system comprises a data intelligent import module, a fuzzy equivalent clustering algorithm intelligent calculation module, a polar diagram intelligent drawing module, a structural surface intelligent statistical analysis module, a data intelligent output module, a trend rose diagram intelligent drawing module and an inclination rose diagram intelligent drawing module;
2.1: intelligent data import module
The system is used for intelligently importing structural surface data obtained by digital photogrammetry into a software system;
2.2: intelligent computing module for fuzzy equivalent clustering algorithm
Based on a fuzzy equivalent clustering algorithm, the fuzzy equivalent clustering of the structural plane occurrence is intelligently realized, and the process is as follows:
2.2.1: let the number of actual measurement samples of the structural surface be N, and the ith sample be (x)i1，xi2)，xi1For structural orientation, xi2The structural plane inclination angle is shown as the fuzzy relation matrix R:
Figure FSA0000216906340000041
element r in the matrixijRepresenting the similarity degree between the ith sample and the jth sample for the similarity coefficient between the ith sample and the jth sample; r isijLarger indicates that sample i is more similar to sample j;
2.2.2: calculating a similarity coefficient rij：
Figure FSA0000216906340000042
Wherein i is 1, 2.. N; n ═ 1, 2.. N; c is a calculation parameter (c is more than or equal to 0 and less than or equal to 1), and the value of c is properly selected to ensure that r isijIn [0, 1 ]]Disperse from the middle;
2.2.3: solving the closure t (R):
R2＝RR
R4＝R2R2
…
2.2.4: and (3) carrying out structural surface grouping judgment: the fuzzy matrix multiplication steps are similar to the common matrix multiplication, and the difference is that the multiplication of two terms is not carried out first and then the addition is carried out, but the multiplication is carried out first and then the multiplication is carried out; if C ═ AB, then the elements in C
Figure FSA0000216906340000043
n-level fuzzy relation matrix R is n R continuous multiplication; namely, it is
Figure FSA0000216906340000044
When R isn＝Rn+1＝Rn+2When equal to …
There, the fuzzy equivalence matrix t (R) ═ Rn
Taking the definite intercept set level lambda belongs to [0, 1 ]]If r in t (R)ijIf the structural plane i and the structural plane j belong to the same class, the structural plane i and the structural plane j belong to the same class; namely, it is
rij≥λ
2.3: intelligent pole point drawing module
Intelligently drawing a structural plane occurrence polar point diagram according to the clustering result and the structural plane grouping result, wherein the process is as follows;
2.3.1: drawing a polar point diagram by adopting a lower hemisphere equal-angle projection method;
2.3.2: will tend to be alphadAnd angle of inclination betadThe represented joint attitude data is converted into structural plane attitude data expressed by normal vector of joint unit, and alpha is setnAnd betanThe inclination direction and the inclination angle are respectively the unit normal vector of the structural plane, and the unit normal vector of any structural plane is expressed as X ═ X (X1，x2，x3) At this time, each point on the hemispherical surface corresponds to a joint occurrence form, and the formula is as follows:
X＝(x1，x2，x3)
Figure FSA0000216906340000051
Figure FSA0000216906340000052
αd∈(0，360)，βd∈(0，90)
2.3.3: obtaining structural surface attitude data expressed by unit normal vectors;
2.3.4: based on normal attitude data of the structural plane and based on the longitudinal section principle diagram of the spatial planogrammatic projection diagram of the structural plane, the point A 'is the planogrammatic projection of the plane normal, and the coordinate x of the point A' on the planogrammatic projection diagram is calculated by combining the planogrammatic projection principle diagramnAnd ynThe formula is as follows:
Figure FSA0000216906340000053
Figure FSA0000216906340000054
2.3.5: solving the coordinate point (x) of the declination projection of all the structural surface normalsn，yn)；
2.3.6: drawing a base circle with the diameter as the unit length, drawing two diameters of vertical and horizontal, and marking E, S, W, N;
2.3.7: the coordinate (x) of the declination plane of all the structural surfaces is measuredn，yn) Plotted on a base circle graph;
2.3.8: intelligently drawing a pole point diagram of the structural plane;
2.4: structural surface intelligent statistical analysis module
The method is used for carrying out intelligent statistical analysis on the clustered structural surfaces, and obtaining the mean value and variance of the tendency, the inclination angle, the trace length, the spacing and the fault distance of each group of structural surfaces, and the process is as follows:
2.4.1: determining a sample partition interval m;
2.4.2: solving sample range
Figure FSA0000216906340000061
Figure FSA0000216906340000062
2.4.3: calculate each partition IntervalMm：
Figure FSA0000216906340000063
2.4.4: determining the probability of the sample falling in each partition interval, and counting the number N of the samples falling in each interval by using a computer circulation languagemCalculating the probability P of the number of samples by combining the total number N of samplesm：
Figure FSA0000216906340000064
2.4.5: solving sample mean
Figure FSA0000216906340000065
Figure FSA0000216906340000066
2.4.6: solving for sample variance S2Wherein S is the standard deviation:
Figure FSA0000216906340000067
2.4.7: according to the probability PmAutomatically drawing the probability distribution forms of the inclination, the dip angle, the trace length, the spacing and the fault distance of each group of structural surfaces;
2.5: intelligent data output module
Intelligently outputting classification information of the occurrence of the structural surfaces, including the mean value and the variance of the inclination, the inclination angle, the trace length, the spacing and the fault distance of each group of structural surfaces;
2.6: intelligent drawing module for trend rose diagram
According to the trend rose diagram drawing method, intelligently drawing the structural surface trend rose diagram, and the process is as follows;
2.6.1: will be jointedThe trend data is converted into northeast and northwest directions, the data are sequentially sorted according to the size of the joint trend azimuth angles, the data are grouped at an angle of 10 degrees every alpha, and each group is named Ti；
Ti＝{α，α+9°}
α＝10(i-1)
i∈(1，10)∪(27，36)
2.6.2: counting the number of joints in each group
Figure FSA0000216906340000071
And average orientation of each set of joints
Figure FSA0000216906340000072
Figure FSA0000216906340000073
i∈(1，10)∪(27，36)
2.6.3: according to the size of the drawing and the number of each group of joints, selecting a line segment with a certain length to represent a group of joints, and determining the scale L of the line segmentT；
2.6.4: to equal to the scale LTRepresented, most numerous set of joints
Figure FSA0000216906340000074
Length of line segment
Figure FSA0000216906340000075
Making a semicircle by taking the radius, making a north-south line and an east-west line by crossing the circle center, and marking an azimuth angle on the circumference;
Figure FSA0000216906340000076
NTis a constant
2.6.5: for each group of joints TiAccording to the average trend
Figure FSA0000216906340000077
Making marks on the semi-circle for the azimuth angle, from the center of the circle to the radius of the mark point on the circumference, according to the number in the group
Figure FSA0000216906340000078
And scale LTSet out a point
Figure FSA0000216906340000079
The point represents the average trend and the number of joints of the group of joints;
Figure FSA00002169063400000710
2.6.6: are connected in sequence
Figure FSA00002169063400000711
And
Figure FSA00002169063400000712
if the certain group of the rational numbers is zero, the connection line returns to the circle center, and then the connection line is led out from the circle center to be connected with the next group;
2.6.7: drawing a joint trend rose diagram;
2.7: intelligent drawing module for trend rose chart
The module has the function of intelligently drawing the structural surface tendency rose diagram according to the tendency rose diagram drawing method;
2.7.1: sequencing the joint tendency data in sequence according to the size of the joint tendency azimuth angle, grouping every theta as 10 degrees, and naming D in each groupj；
Dj＝{θ，θ+9°}
θ＝10(j-1)
j∈(1，36)
2.7.2: counting the number of joints in each group
Figure FSA00002169063400000713
And average of each set of jointsTendency to
Figure FSA00002169063400000714
Figure FSA0000216906340000081
j∈(1，36)
2.7.3: according to the size of the drawing and the number of each group of joints, selecting a line segment with a certain length to represent a group of joints, and determining the scale L of the line segmentD；
2.7.4: to equal to the scale LDRepresented, most numerous set of joints
Figure FSA0000216906340000082
Length of line segment
Figure FSA0000216906340000083
Making a circle for the radius, making a north-south line and an east-west line through the circle center, and marking an azimuth angle on the circumference;
Figure FSA0000216906340000084
NDis a constant
2.7.5: for each group of joints DjIn average tendency
Figure FSA0000216906340000085
Making marks on the semi-circle for the azimuth angle, from the center of the circle to the radius of the mark point on the circumference, according to the number in the group
Figure FSA0000216906340000086
And scale LDSet out a point
Figure FSA0000216906340000087
The point represents the set of joint mean tendency and the number of joints;
Figure FSA0000216906340000088
2.7.6: are connected in sequence
Figure FSA0000216906340000089
And
Figure FSA00002169063400000810
if the certain group of the rational numbers is zero, the connection line returns to the circle center, and then the connection line is led out from the circle center to be connected with the next group;
2.7.7: drawing a structural surface trend rose diagram;
2.8: intelligent drawing module for rose diagram at inclination angle
According to the inclination angle rose diagram drawing method, intelligently drawing the inclination angle rose diagram of the structural plane, and the process is as follows;
2.8.1: sequentially ordering the joint data according to the size of the joint inclination azimuth angle, grouping every theta as 10 degrees, and naming each group as Qj；
Qj＝{θ，θ+9°}
θ＝10(j-1)
j∈(1，36)
2.8.2: counting the number of joints in each group
Figure FSA00002169063400000811
Average propensity of each group of joints
Figure FSA00002169063400000812
And average tilt angle
Figure FSA00002169063400000813
Figure FSA00002169063400000814
j∈(1，36)
Figure FSA00002169063400000815
2.8.3: selecting a certain inclination angle to represent a group of joints according to the size of the drawing and the number of the joints, and determining a scale L of the line segmentQ；
2.8.4: to equal to the scale LQRepresented, most numerous set of joints
Figure FSA0000216906340000091
Line segment inclination angle
Figure FSA0000216906340000092
Making a circle for the radius, making a north-south line and an east-west line through the circle center, and marking an azimuth angle on the circumference;
Figure FSA0000216906340000093
NQis a constant
2.8.5: for each group of joints DjIn average tendency
Figure FSA0000216906340000094
Making marks on the semi-circle for the azimuth angle, from the center of the circle to the radius of the mark point on the circumference, according to the number in the group
Figure FSA0000216906340000095
And scale LQSet out a point
Figure FSA0000216906340000096
The point represents the set of joint mean inclination angles and the number of joints;
Figure FSA0000216906340000097
2.8.6: are connected in sequence
Figure FSA0000216906340000098
And
Figure FSA0000216906340000099
if the certain group of the rational numbers is zero, the connection line returns to the circle center, and then the connection line is led out from the circle center to be connected with the next group;
2.8.7: and drawing a rose picture of the joint inclination angle.
CN202010822751.7A 2020-08-05 2020-08-05 Rapid intelligent generation and sectioning method for rock three-dimensional fracture network model Withdrawn CN114088015A (en)

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Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116341294A (en) * 2023-05-30 2023-06-27 煤炭科学研究总院有限公司 Three-dimensional stress field construction method and device
CN116796455A (en) * 2023-05-16 2023-09-22 长安大学 Rock mass fracture occurrence characterization method

Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116796455A (en) * 2023-05-16 2023-09-22 长安大学 Rock mass fracture occurrence characterization method
CN116796455B (en) * 2023-05-16 2024-01-09 长安大学 Rock mass fracture occurrence characterization method
CN116341294A (en) * 2023-05-30 2023-06-27 煤炭科学研究总院有限公司 Three-dimensional stress field construction method and device
CN116341294B (en) * 2023-05-30 2023-08-11 煤炭科学研究总院有限公司 Three-dimensional stress field construction method and device

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