CN111784059B - Method for predicting dominant development azimuth of coal seam macroscopic crack - Google Patents

Abstract

The invention discloses a method for predicting a dominant development azimuth of coal seam macroscopic cracks, belonging to the technical field of coal seam macroscopic crack prediction, and comprising the following steps: selecting a coal wall picture, and processing the original coal wall image by adopting different gray threshold values, wherein the area with the gray value less than q is white, and the rest part is black; step two: information input and output, including single crack picture input, multiple crack picture input and crack information output; step three: the image preprocessing is characterized in that due to the limitation of underground shooting conditions, the crack images have poor definition, the structure is reasonable, the preprocessing images can be subjected to noise reduction processing, binarization optimization, image edge detection and the like automatically, so that the digital images reach the practical application standard, the manual and complex workload can be greatly reduced, and the efficiency and the accuracy of field identification are improved.

Description

Method for predicting dominant development azimuth of coal seam macroscopic crack

Technical Field

The invention relates to the technical field of coal seam macroscopic crack, in particular to a method for predicting the dominant development azimuth of the coal seam macroscopic crack.

Background

The research history of people on the coal bed macroscopic cracks is very long, and people have found that the development of the coal bed macroscopic cracks has a certain statistical rule in the same geological unit; coal seam fractures can directly contribute to coal seam permeability anisotropy. The data of the mining bureau of America show that under the influence of coal seam cracks, the permeability ratio of coal seams in different directions is up to 17:1, and the extraction amount of coal bed gas is different by 3-10 times. The gas extraction test of the coal mine underground in China shows that the gas extraction efficiency of gas extraction drill holes in different directions of the same coal seam is remarkably different, the limit extraction amount of the gas of the drill holes in the vertical plane cutting direction is 2.6 times that of the drill holes in the parallel plane cutting direction, and the drainage rate is 4.3 times higher.

Therefore, observation and statistical analysis are carried out on the coal seam macroscopic cracks, the crack dominant development direction is predicted, the coal seam permeability and the gas seepage dominant direction are favorably determined, and then the design of the coal seam gas extraction drill hole can be optimized and the extraction efficiency can be improved. However, the traditional method for measuring the coal seam fissure by means of tools such as a compass is labor-consuming and time-consuming, is limited by underground space or is interfered by a magnetic field, is difficult to effectively observe the coal seam macroscopic fissure, and is difficult to obtain important parameters such as the dominant development azimuth of the coal seam macroscopic fissure, so that the influence of the development characteristic of the coal seam macroscopic fissure on the extraction efficiency is not considered in the existing gas extraction engineering design of the coal mine in China.

MATLAB digital image recognition technology obtains extensive application in geotechnical engineering crack identification field, its all kinds of application tool cases, it has covered more than twenty field image processing algorithms, it is all very convenient to make all kinds of image processing and identification processes, and utilize the computer to build the algorithm on this platform of MATLAB, can fall the noise processing to the picture of preliminary treatment voluntarily, binary optimization, and image edge detection etc. thereby make the digital picture reach the actual application standard, can greatly reduce artifical loaded down with trivial details work load, improve on-the-spot recognition's efficiency and accuracy. In order to research a method suitable for observing, statistically analyzing and predicting coal seam fractures in a coal mine and improve the gas extraction efficiency of the coal seam of the mine in China, a novel method for observing and identifying the underground coal seam macroscopic fractures is provided, underground coal wall photography and fracture observation are respectively carried out on different gas geological units on the basis of knowing the development rule of geological structures in a research area and the basic development characteristics of the coal seam fractures, and then coal seam macroscopic fracture identification and statistical analysis are carried out by utilizing an MATLAB digital image identification technology.

Disclosure of Invention

This section is for the purpose of summarizing some aspects of embodiments of the invention and to briefly introduce some preferred embodiments. In this section, as well as in the abstract and the title of the invention of this application, simplifications or omissions may be made to avoid obscuring the purpose of the section, the abstract and the title, and such simplifications or omissions are not intended to limit the scope of the invention.

Therefore, the invention aims to provide a method for predicting the dominant development azimuth of the coal seam macroscopic crack, which can automatically perform noise reduction processing, binarization optimization, image edge detection and the like on a preprocessed picture, so that the digital picture reaches the practical application standard, the manual tedious workload can be greatly reduced, and the efficiency and the accuracy of field identification can be improved.

To solve the above technical problem, according to an aspect of the present invention, the present invention provides the following technical solutions:

a method for predicting the dominant development azimuth of coal seam macroscopic cracks comprises the following steps:

the method comprises the following steps: selecting a coal wall picture, and processing the original coal wall image by adopting different gray threshold values, wherein the area with the gray value less than q is white, and the rest part is black;

step two: information input and output, including single crack picture input, multiple crack picture input and crack information output;

step three: image preprocessing, wherein due to the limitation of underground shooting conditions, crack images have the problems of poor definition and low identification degree, the contrast of crack parts is enhanced manually by adopting white lines, and then the graying of the images is carried out;

step four: analyzing and identifying a coal seam fracture image, wherein in the process of analyzing and identifying the coal seam fracture image, fracture image threshold segmentation is firstly carried out, and then morphological treatment is carried out to realize fracture identification;

step five: fracture characteristic identification and parameter characterization, after morphological processing is carried out on a fracture image, the image is segmented, a bwable function is called to find a connected object of the fracture image which is processed currently, the default is 8 connected objects, namely, aiming at a certain pixel point in the image, if the pixel point is connected with 8 pixels of the upper, lower, left, right, upper, lower, left, lower, upper, right, lower, left, upper, lower, right, the pixel point is considered to be connected, a regionpros function is called to obtain fracture coordinate information, a jiontLength function calculates fracture trace length, and a jiontK function calculates a fracture dip angle;

step six: the fracture images are processed in batch, and because the coal seam joint fractures are statistical rules, a large number of fracture images need to be processed in batch by using the step 5, so that the purpose of statistics of fracture dominant development directions is achieved, and the gas extraction work is guided to be carried out;

step seven: and (3) drawing the rose flower map of the fracture dominant direction, calling polar function to draw the rose flower map under polar coordinates, setting the fracture dip angle interval to be 5 degrees in order to ensure the precision of the drawn rose flower map, dividing the fracture dip angle of 0-180 degrees into 36 small intervals, and calculating the fracture pixel point value.

Compared with the prior art, the invention has the beneficial effects that: 1. the method can identify the tiny fractures existing in the fracture pictures, and can accurately identify and represent parameters of the coal seam fractures. Considering that the traditional rose flower map with the fracture dominant development direction is drawn according to the number of the fractures developing in each direction, the fractures with different lengths are identified as one, so that a large error exists, and the real dominant development direction of the fractures cannot be counted.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the present invention will be described in detail with reference to the accompanying drawings and detailed embodiments, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings without inventive exercise. Wherein:

FIG. 1 is a schematic view of the process flow structure of the present invention.

Detailed Description

In order to make the aforementioned objects, features and advantages of the present invention comprehensible, embodiments accompanied with figures are described in detail below.

In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention, but the present invention may be practiced in other ways than those specifically described herein, and it will be apparent to those of ordinary skill in the art that the present invention may be practiced without departing from the spirit and scope of the present invention, and therefore the present invention is not limited to the specific embodiments disclosed below.

Next, the present invention will be described in detail with reference to the drawings, wherein for convenience of illustration, the cross-sectional view of the device structure is not enlarged partially according to the general scale, and the drawings are only examples, which should not limit the scope of the present invention. In addition, the three-dimensional dimensions of length, width and depth should be included in the actual fabrication.

In order to make the objects, technical solutions and advantages of the present invention more apparent, embodiments of the present invention will be described in detail with reference to the accompanying drawings.

The invention provides the following technical scheme: a method for predicting the dominant development azimuth of coal seam macroscopic crack comprises the following steps:

the method comprises the following steps: selecting a coal wall picture, and processing the original coal wall image by adopting different gray threshold values, wherein the area with the gray value less than q is white, and the rest part is black

(1) The coal seam cracks are mainly distributed in a strip shape

(2) The gray value of the part with cracks is lower than the background value

(3) In a crack pattern, there may be different gray values for the same crack. The images are processed by adopting different thresholds, and the sizes and the continuity of the same crack presented by the results can be different

(4) In the fracture image, the shape of the region where the fracture is located is greatly influenced by the threshold value. With the change of the gray threshold, the white area where the crack is positioned undergoes the transition from the point shape to the strip shape and then to the surface shape;

step two: and information input and output, including single-crack picture input, multi-crack picture input and crack information output, wherein in the consideration of shortening the image processing time, images in a JPG format are selected for processing and analysis, and the sizes of the images can be reduced as much as possible on the premise of maximally retaining image color information, so that after the working time is reduced, global variables need to be defined and can be referred by all objects or functions of the program. The core code of this section is as follows:

file _ path is an image folder path'; % image folder path?

img _ path _ list ═ dir (file _ path, '. JPG')); % images in all jpg formats in the folder?

img _ num ═ length (img _ path _ list); % total number of images acquired?

I＝cell(1,img_num)；

global s；

global tempb1；

global b1；

global pic；

global bw；

global hMainFig；

global hText；

global charpic；

global chars；

In an open folder, a fracture image or images may be contained. The single picture information obtained after processing can be presented in a Matlab command line window in a data form; the statistical rule information of the dip angles of the multiple fracture images is stored in a Matlab working area, wherein a juint is used for counting the development directions of the fractures, and a juntLength is used for counting the lengths of the fractures in each direction;

step three: image preprocessing, because of the limitation of underground shooting conditions, the crack images have the problems of poor definition and low identification degree, the crack parts are subjected to contrast enhancement by manually adopting white lines, then the images are grayed, all the images in a folder are traversed, and the graying of the images is carried out one by one. When drawing, attention needs to be paid to a photo scale;

the core code is as follows:

step four: and (3) analyzing and identifying the coal seam fracture image, wherein in the process of analyzing and identifying the coal seam fracture image, fracture image threshold segmentation is firstly carried out, and then morphological treatment is carried out, so that fracture identification is realized.

According to the processing experience of a large number of underground images, after different threshold processing effects are compared and analyzed, the threshold value is selected to be 0.99, the images are subjected to threshold segmentation, and the images are converted into the images with the binary values only including 0 and 1. The core code of this section is as follows:

% takes 0.99 as a threshold value, and the converted gray level image is binarized

bw＝im2bw(pic,0.99)；

％figure,imshow(bw),title('bw')；

％figure,imshow(pic),title('pic')；

bw＝bw；

% negating binary picture, i.e. 1 to 0,0 to 1

％bw＝～bw；

％figure,imshow(bw),title('～bw')；

Then, the binary image is processed by morphology. And calling imopen and imolse functions to perform opening operation and closing operation respectively to realize the bridging of the fracture. Due to the limitation of the underground environment, the coal seam image often has a reflection phenomenon, and a great amount of noise is presented in the binary image. Therefore, a bweraopen function needs to be called to eliminate small objects possibly existing in the binary image, so that interference of irrelevant factors on crack identification is avoided. The core code of this section is as follows:

% morphological treatment

％bw＝imopen(bw,strel('line',10,10))；

The% closure operation merges small gaps in the graph

% strel morphological structural element creation straight line length 4 angle 90

bw1＝imclose(bw,strel('line',4,90))；

％figure,imshow(bw1),title('bw1 imclose')

% bweraopen removes small objects with pixel values less than 200

bw2＝bwareaopen(bw1,500)；

％figure,imshow(bw2),title('bw2 bwareaopen')；

bwi2＝bwselect(bw2,368,483,4)；

％figure,imshow(bwi2),title('bwi2 bwselect')；

bw2(bwi2)＝0；

bw3＝bw.*bw2；

％figure,imshow(bw3),title('bw3.*')；

bw4＝imclose(bw3,strel('square',4))；

bw4＝bwareaopen(bw4,500)；

Step five: fracture characteristic identification and parameter characterization, after morphological processing is carried out on a fracture image, the image is segmented, a bwable function is called to find a connected object of the fracture image which is processed currently, the default is 8 connected objects, namely, for a certain pixel point in the image, if the pixel point is connected with 8 pixels of the upper, lower, left, upper, right, lower, upper, right, left, right, the pixel point is considered to be connected, a regionpros function is called to obtain fracture coordinate information, a pointLength function calculates fracture trace length, and a pointK function calculates fracture dip angle.

After the pixel points of all the points in the crack are found, fitting a straight line, calculating the crack inclination angle through k ═ tanX, wherein the crack trace length is the product of the number of the pixel points and the representative length of a single pixel point. The key code for this process is as follows:

the codes are adopted to respectively count the crack trace length and the crack inclination angle in a single picture so as to verify the accuracy of the codes;

step six: and (3) performing batch processing on the fracture images, wherein the coal seam joint fractures are statistical rules, so that the step 5 is required to be applied to perform batch processing on a large number of fracture images to realize the purpose of statistics on the fracture dominant development azimuth, thereby guiding the gas extraction work.

When manual preprocessing is carried out on the images in batches, the lengths of all image fracture pixels are required to be equal, and the accuracy of the recognition result is further ensured. In order to complete the finally drawn rose diagram, a function is called, and the crack inclination angle is converted into an arc system to be recorded, wherein 1 arc is 57.2958 degrees. The key codes are as follows:

in order to improve the space-time efficiency of the code, the data is discretized, namely limited individuals in an infinite space are mapped into a limited space. This process may also be considered as data pre-processing involving data mining. The key codes are as follows:

then, data consistency processing is carried out, and the found objects are marked.

Step seven: and (3) drawing the rose flower map of the fracture dominant direction, calling polar function to draw the rose flower map under polar coordinates, setting the fracture dip angle interval to be 5 degrees in order to ensure the precision of the drawn rose flower map, dividing the fracture dip angle of 0-180 degrees into 36 small intervals, and calculating the fracture pixel point value.

Part of the codes are as follows:

followed by rose mapping. And (4) filling the lower half area of the image with 0 for the image to be attractive, and drawing only the upper half area so as to draw a crack dominant development position rose diagram.

angle＝(0:72)*pi/36；

a＝[area0 area1 area2 area3 area4 area5 area6 area7 area8 area9 area10 area11 area12 area13 area14 area15 area16 area17 area18 area19 area20 area21 area22 area23 area24 area25 area26 area27 area28 area29 area30 area31 area32 area33 area34 area35 area36 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]；

polar(angle,a)；

％my_polar(angle,[area0 area1 area2 area3 area4 area5 area6 area7 0 0 0 0 0 0 0 0 area8])；end

And identifying the crack picture by using the code. Storing the pictures in a folder in a jpg format, and manually processing the crack pictures.

And processing the folder containing the coal seam fracture image by using the program code.

Wherein the fracture data in each region is stored in the software workspace. The discretized fracture dip angle and pixel length data are respectively stored in the working area join K and join Length and are in one-to-one correspondence.

While the invention has been described above with reference to an embodiment, various modifications may be made and equivalents may be substituted for elements thereof without departing from the scope of the invention. In particular, the various features of the disclosed embodiments of the invention may be used in any combination, provided that no structural conflict exists, and the combinations are not exhaustively described in this specification merely for the sake of brevity and resource conservation. Therefore, it is intended that the invention not be limited to the particular embodiments disclosed, but that the invention will include all embodiments falling within the scope of the appended claims.

Claims (1)

1. A method for predicting the dominant development azimuth of coal seam macroscopic crack is characterized by comprising the following steps: the method comprises the following steps:

the method comprises the following steps: selecting a coal wall picture, and processing the original coal wall image by adopting different gray threshold values, wherein the area with the gray value less than q is white, and the rest part is black;

step two: information input and output, including single crack picture input, multiple crack picture input and crack information output;

step three: image preprocessing, wherein due to the limitation of underground shooting conditions, crack images have the problems of poor definition and low identification degree, the contrast of crack parts is enhanced manually by adopting white lines, and then the graying of the images is carried out;

step four: analyzing and identifying a coal seam fracture image, wherein in the process of analyzing and identifying the coal seam fracture image, fracture image threshold segmentation is firstly carried out, and then morphological treatment is carried out to realize fracture identification;

step five: fracture characteristic identification and parameter characterization, after morphological processing is carried out on a fracture image, the image is segmented, a bwable function is called to find a connected object of the fracture image which is processed currently, the default is 8 connected objects, namely, aiming at a certain pixel point in the image, if the pixel point is connected with 8 pixels of the upper, lower, left, right, upper, lower, left, lower, upper, right, lower, left, upper, lower, right, the pixel point is considered to be connected, a regionpros function is called to obtain fracture coordinate information, a jiontLength function calculates fracture trace length, and a jiontK function calculates a fracture dip angle;

step six: the fracture images are processed in batch, and because the coal seam joint fractures are statistical rules, a large number of fracture images need to be processed in batch by using the step 5, so that the purpose of statistics of fracture dominant development directions is achieved, and the gas extraction work is guided to be carried out;

step seven: and (3) drawing the rose flower map of the fracture dominant direction, calling polar function to draw the rose flower map under polar coordinates, setting the fracture dip angle interval to be 5 degrees in order to ensure the precision of the drawn rose flower map, dividing the fracture dip angle of 0-180 degrees into 36 small intervals, and calculating the fracture pixel point value.

Images