Prediction Method for In-situ Coal Permeability Distribution Characteristics Based on Image Processing

Abstract

The present invention discloses a method for predicting the in-situ coal permeability distribution characteristics based on image processing. The method includes: using the borehole drilling technology to implement horizontal drilling operations on the in-situ coal in front of the mining and excavation working face, obtaining coal samples and performing micro-disturbed cutting on the samples, scanning the cutting cross-section images of the coal samples through the digital core CT image module to obtain a two-dimensional image set, relying on the image parameter calculation module to realize the binary conversion of the original images and the calculation of parameters such as particle diameter, pore tortuosity, and surface porosity, and transmitting each parameter data set to the permeability region identification module to complete the calculation of the in-situ coal permeability and the identification and division of the low-permeability development area based on the image parameter data set. Based on this, the present invention introduces image processing technology combined with the coal permeability calculation theory to accurately describe the in-situ complex coal permeability distribution characteristics, and further realizes the accurate identification of the in-situ coal gas low-permeability area.

Description

Technical Field

[0001] This invention patent relates to the technical field of coal mining, specifically a method for predicting the distribution characteristics of in-situ coal permeability based on image processing. Background Art

[0002] China has a large annual coal output, and coal mine disasters are serious, among which the proportion of coal and gas outburst accidents is relatively large. This is mainly because the geological conditions for coal mining in China are complex, and low-permeability coal seams are relatively developed, which brings great challenges to the effective implementation of gas drainage and outburst prevention and elimination measures. According to on-site observations and experimental studies, tectonic soft coal containing high-energy gas is the key to inducing coal and gas outbursts. The high pulverization, low strength, high energy storage, and low permeability of tectonic soft coal itself are the fundamental reasons for coal and gas outbursts. Therefore, accurately identifying and dividing the low-permeability dangerous areas of in-situ coal is the key to realizing the regional prediction of coal and gas outbursts and formulating targeted regional outburst prevention measures, reducing the blindness of coal and gas outburst prevention work, and can effectively improve the safe and stable mining of complex coal seams.

[0003] However, the in-situ coal in front of the mining and excavation working face has the characteristics of being invisible and having a wide range. At the same time, affected by geological structures and mining and excavation stresses, the coal seam structure is complex, the phenomenon of alternating hard and soft coal layers is common, and the pore and fracture structure of the coal body is complex and diverse, making it quite difficult to quantitatively and accurately describe the development characteristics of the pore and fracture structure of the in-situ coal in front of the mining and excavation working face. Based on this, this invention introduces image processing technology combined with the theory of coal reservoir permeability calculation to quantitatively describe the development characteristics of the pore and fracture of in-situ coal in the actual coal mining process, reveal the permeability distribution law of in-situ coal in front of the mining and excavation working face, and then accurately identify the low-permeability gas areas and enrichment zones, providing certain guidance for formulating targeted prevention and control measures for local dangerous areas of coal and gas outbursts. Summary of the Invention

[0004] The purpose of this application is to provide a method for predicting the distribution characteristics of in-situ coal permeability based on image processing to solve or alleviate the problems existing in the prior art.

[0005] To achieve the above purpose, this application provides the following technical solutions:

[0006] The method for predicting the distribution characteristics of in-situ coal permeability based on image processing provided by this application is characterized in that: the method includes the following steps:

[0007] S101 Borehole drilling technology is mainly used to obtain underground coal and rock samples to obtain coal and rock properties and structural information. First, the drilling rig is arranged in the mining and excavation roadway, and the horizontal drilling operation method is adopted. The in-situ coal is broken by relying on the rotation of the drill bit and the drilling pressure, and the drill pipe is responsible for transmitting the rotational power and drilling pressure to the drill bit to complete the drilling of the in-situ coal to obtain the coal sample;

[0008] After completing the drilling of a coal sample, use a drill bit to cut the coal sample along the length of the borehole, remove the coal sample from the core barrel, and mark the borehole number, depth range, and date information of the coal sample;

[0009] S103 Subsequently, according to the drilling depth range of the borehole, the coal samples taken from the borehole are cut with micro-disturbance at the unit length, and the pore fissure structure of the cutting section hole is scanned and imaged by the high-resolution imager built in the digital core CT image module to obtain a two-dimensional image p reflecting the pore development characteristics of the coal sample cross-section at the unit length i , repeat the above process to complete the segmentation and scanning of the coal samples at the full distance of the borehole, and obtain a two-dimensional image set P (p 1 , p 2 , p 3 , ……) reflecting the pore development characteristics of the coal samples within the set drilling depth range of the borehole;

[0010] S104 Furthermore, the image information of the two-dimensional image set P (p 1 , p 2 , p 3 , ……) of the coal samples is transmitted to the image parameter calculation module through the image transmission system of the digital core CT image module. The image processor built in the image parameter calculation module first converts the two-dimensional original image obtained by scanning the coal samples into a binary image, and calculates the pore structure parameters of the binary image respectively relying on the built-in parameter processor: the surface porosity φ i , the pore diameter D i , and the pore tortuosity τ i ;

[0011] S105 Subsequently, the pore structure parameter data set is transmitted to the permeability region identification module, and the permeability k i under the pore structure parameters of the image is calculated according to the permeability calculation equation setting program. The coal cross-section images at different positions of the same borehole correspond to different permeabilities, and the permeability values k i of the coal cross-section images at different positions are calculated to further obtain a data subset K i (k 1 , k 2 , k 3 ……) reflecting the permeability of the coal in the borehole; Summarize all the borehole data subsets K i to obtain a data set K (K 1， K 2， K 3 ……) reflecting the size characteristics of the coal permeability in the three-dimensional space of the detection area;

[0012] S106 Finally, the data set K (K1， K 2， K 3 ……) is transmitted to the in-situ coal permeability data processor built in the permeability region identification module to complete the identification and division of the low-permeability development area of in-situ coal based on the magnitude of the permeability value.

[0013] The method for predicting the in-situ coal permeability distribution characteristics based on image processing is completed relying on a device for predicting the in-situ coal permeability distribution characteristics based on image processing, and is characterized in that: the device includes a digital core CT image module, an image parameter calculation module, and a permeability region identification module.

[0014] Preferably, the digital core CT image module is built with a high-resolution imager and an image storage; in the image parameter calculation module, there are designed: an image processor, a parameter processor, and a data memory, which are mainly used to convert the received two-dimensional original image into a binary image and complete the calculation and data storage of the pore structure parameters of the binary image according to the built-in calculation program; the permeability region identification module mainly further processes the data set obtained by the image parameter calculation module through a data processor to complete the calculation of the in-situ coal permeability based on the image pore structure parameters, and on the basis of obtaining the coal permeability data set, further divides the data set according to the specific threshold range set by the built-in program to realize the identification of the target region.

[0015] Preferably, the image parameter calculation module mainly realizes the image conversion, pore structure parameter calculation, and acquisition of the pore structure parameter data set of the two-dimensional image set of different cross-sections of the coal sample; the principle is as follows: affected by geological structures, the structure of in-situ coal is complex, and there is often a phenomenon of locally occurring crushed soft coal. Compared with the original hard coal, the tectonic soft coal affected by geological tectonic actions often shows characteristics such as high pulverization degree, high development degree of pores and fractures, and at the same time, generally has low permeability and is easy to form a natural sealing area, resulting in a large amount of gas accumulation; it is not difficult to see that there are significant differences in the coal body structure between tectonic soft coal and original hard coal; therefore, after micro-disturbance sampling of the coal body sample by drilling a borehole, the obtained coal body sample is cut to obtain the cross-section of the coal body sample per unit length, and the two-dimensional original image p containing the pore development information of this cross-section can be obtained through the high-resolution imager in the digital core CT image module i ; further through the image processor in the image parameter calculation module, the two-dimensional original image can be converted into a binary image, where the black part in the binary image represents the pore development situation of the two-dimensional original image. By combining the binary image representing the pore structure information with the built-in data processor, the pore structure parameters of this image can be completed: the surface porosity φ i 、pore diameter D i and pore tortuosity τ i calculation and acquisition and storage of the data set;

[0016] Preferably, based on the pore structure parameters transmitted by the image parameter calculation module, the permeability data processor in the permeability region identification module can complete the calculation of the relationship between the pore structure and permeability under the cross-sectional image of the borehole coal body by combining with Formula (1):

[0017]

[0018] In the formula, D is the pore diameter, m;

[0019] φ is the areal porosity;

[0020] τ is the pore tortuosity;

[0021] Preferably, the parameter processor in the image parameter calculation module can obtain the parameter data set of the in-situ coal body pore structure development information. The basic process is as follows: First, the coal body samples drilled from the same drilling borehole are cut in sequence according to the set unit length according to the drilling depth range, and the high-resolution imager built into the digital core CT image module is used to photograph and scan the cross-section of the coal body sample to obtain the two-dimensional original image p reflecting the pore structure development information of this cross-section i , and repeat the above process until the segmentation and scanning of the coal body samples under the full length of the drilling borehole are completed, and then a two-dimensional image set P (p 1 , p 2 , p 3 , ……) reflecting the fracture development characteristics of the coal body samples under the set drilling depth range of the borehole is obtained. Relying on the image processor, parameter processor and data memory in the image parameter calculation module, the calculation of the pore structure parameters of all coal body cross-sectional images reflecting the two-dimensional image set P of this borehole is completed, and then the parameter data set of the in-situ coal body pore structure development information is obtained;

[0022] Preferably, based on the parameter data set of the in-situ coal body pore structure development information transmitted by the image parameter calculation module, the permeability data processor in the permeability region identification module can complete the calculation of the permeability k i based on the K-C equation for each coal body sample cross-section p i , and then obtain the coal body permeability data subset K i (k 1 , k 2 , k 3 , ……) at different drilling distances of the same borehole; The drilling points are arranged in a grid layout, which effectively ensures the comprehensive acquisition of the in-situ coal body pore structure information. Summarize all the borehole data subsets K i in the in-situ coal body detection area in front of the working face, and then obtain the three-dimensional space data set K (K 1， K2， K 3 ……); According to the permeability k i value, combined with the built-in threshold division program of the permeability region identification module, the identification and division of the low-permeability development area of the in-situ coal body in front of the mining and excavation working face can be realized, providing a certain basis for the precise prevention and control of local dangerous areas of coal and gas outbursts.

[0023] Due to the adoption of the above technical solution, the beneficial effects of this invention patent are as follows:

[0024] In the in-situ coal body permeability distribution characteristic identification scheme based on image processing provided by the present invention, first, through the borehole drilling technology, in the way of horizontal drilling operation, the drilling sampling and information calibration of the in-situ coal body in front of the mining and excavation working face are completed; then, through the digital core CT image module, the two-dimensional image set P is obtained by scanning the cutting section information of the coal body sample; the image parameter calculation module completes the conversion of the original image and the calculation of the pore structure parameters to obtain the data set of pore structure parameters; the permeability region identification module relies on the built-in permeability data processor to complete the calculation of the in-situ coal body permeability and the identification and division of the low-permeability development area based on the data set of pore structure parameters. Based on this, the present invention combines image processing technology with the coal-rock reservoir permeability calculation theory to quantitatively describe the pore and fracture development characteristics of the in-situ coal body in the actual coal mining process, visually analyze the coal body damage characteristics in the mining and excavation space under geological structure and mining disturbance and the distribution law of different structural hard and soft coal bodies, and then reveal the seepage distribution evolution characteristics of the in-situ coal body, accurately identify the low-permeability gas area and gas enrichment zone, providing a certain theoretical and on-site practice basis for the precise prevention and control of local dangerous areas of coal and gas outbursts. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 It is a flow chart of the in-situ coal body permeability distribution characteristic prediction method based on image processing of the present invention;

[0026] Figure 2 It is a schematic diagram of the in-situ coal body structure distribution of the present invention;

[0027] Figure 3 It is a diagram of the borehole cross-section morphology at different positions of the same borehole of the in-situ coal body of the present invention;

[0028] Figure 4 It is a schematic diagram of the in-situ coal body permeability calculation of the present invention;

[0029] Figure 5 It is a schematic diagram of the image subset of different cross-sections of the same borehole of the present invention;

[0030] Figure 6 It is a schematic diagram of the in-situ coal body permeability data set of the present invention;

[0031] Figure 7Schematic diagram for dividing the low-permeability area of in-situ coal mass in the present invention; Detailed implementation manners

[0032] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer and more understandable, the embodiments of the present invention will be further described in detail below in conjunction with the embodiments and the accompanying drawings. Herein, the illustrative embodiments of the present invention and their descriptions are used to explain the present invention, but do not limit the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts fall within the scope of protection of the present invention.

[0033] In the description of the present invention, it should be understood that the terms "upper", "lower", "front", "rear", "left", "right", "top", "bottom", "inner", "outer", etc. indicating the orientation or positional relationship are based on the orientation or positional relationship shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device, component, or structure referred to must have a specific orientation, be constructed or operated in a specific orientation, and should not be construed as a limitation to the present invention.

[0034] The specific implementation method of the present invention will be further described below in conjunction with the accompanying drawings.

[0035] As Figure 1-7 shown, the present invention provides a method for predicting the permeability distribution characteristics of in-situ coal mass based on image processing, which is characterized in that the method includes the following steps:

[0036] S101 The drilling technology of the borehole is mainly used to obtain underground coal and rock samples to obtain coal and rock properties and structural information. First, the drilling rig is arranged in the mining roadway, and the horizontal drilling operation method is adopted. The in-situ coal mass is broken by relying on the rotation of the drill bit and the drilling pressure, and the drill pipe is responsible for transmitting the rotational power and the drilling pressure to the drill bit to complete the drilling of the in-situ coal mass to obtain the coal mass sample;

[0037] S102 After the coal mass sample of a borehole is drilled, the coal mass sample is cut along the length direction of the borehole using a drill bit, the coal mass sample is taken out of the core tube, and the coal mass sample is marked with borehole number, depth range, and date information;

[0038] S103 Subsequently, according to the drilling depth range of the borehole, the coal mass sample taken from the borehole is cut with micro-disturbance per unit length, and the cross-sectional pore fissure structure of the cut section is scanned and imaged by a high-resolution imager built in the digital core CT image module to obtain a two-dimensional image p reflecting the pore development characteristics of the coal mass sample cross-section under this unit length i , and the above process is repeated to complete the segmentation and scanning of the coal mass sample over the entire distance of the borehole to obtain a two-dimensional image set P(p1 , p 2 , p 3 , ……);

[0039] S104 Further, the image information of the two-dimensional image set P(p 1 , p 2 , p 3 , ……) of the coal sample is transmitted to the image parameter calculation module through the image transmission system of the digital core CT image module. The image processor built in the image parameter calculation module first converts the two-dimensional original image obtained by scanning the coal sample into a binary image, and respectively calculates the pore structure parameters of the binary image relying on the built-in parameter processor: the surface porosity φ i , the pore diameter D i , and the pore tortuosity τ i ;

[0040] S105 Subsequently, the pore structure parameter data set is transmitted to the permeability region identification module. According to the permeability calculation equation, the program is set to complete the calculation of the permeability k i under the pore structure parameters of the image. The coal body cross-section images at different positions in the same borehole correspond to different permeabilities. Calculate the permeability values k i of the coal body cross-section images at different positions, and further obtain the data subset K i (k 1 , k 2 , k 3 ……) reflecting the permeability of the coal body in the borehole; Summarize all the borehole data subsets K i , and the data set K(K 1， K 2， K 3 ……) reflecting the size characteristics of the coal body permeability in the three-dimensional space of the detection area can be obtained;

[0041] S106 Finally, the data set K(K 1， K 2， K 3 ……) is transmitted to the permeability data processor built in the permeability region identification module to complete the identification and division of the in-situ coal body low-permeability development area based on the numerical size of the permeability.

[0042] The in-situ coal body permeability distribution characteristic prediction device based on image processing is characterized in that: the device includes a digital core CT image module, an image parameter calculation module and a permeability region identification module.

[0043] As Figure 1 and 4As shown, the digital core CT image module is built with a high-resolution imager and an image storage; in the image parameter calculation module, there are designed: an image processor, a parameter processor, and a data memory, which are mainly used to convert the received two-dimensional original image into a binary image and complete the calculation and data storage of the pore structure parameters of the binary image according to the built-in calculation program; the permeability region identification module mainly further processes the data set obtained by the image parameter calculation module through a data processor, completes the in-situ coal permeability calculation based on the image pore structure parameters, and on the basis of obtaining the coal permeability data set, further divides the data set according to the specific threshold range set by the built-in program to achieve the identification of the target region.

[0044] As Figure 4 and 5 shown, the image parameter calculation module mainly realizes the image conversion, pore structure parameter calculation, and acquisition of the pore structure parameter data set of the two-dimensional image sets of different cross-sections of the coal sample; the principle is as follows: affected by geological structures, the structure of the in-situ coal in front of the mining face is complex, and there is often a phenomenon of locally occurring crushed soft coal. Compared with the original hard coal, the tectonic soft coal affected by geological structure actions often shows characteristics such as high pulverization degree, high development degree of pores and fractures, and at the same time, it generally has low permeability and is easy to form a natural sealing area, resulting in a large amount of gas accumulation; it is not difficult to see that there are significant differences in the coal body structure between the tectonic soft coal and the original hard coal; therefore, after taking micro-disturbed samples of the coal body by drilling boreholes, the taken coal samples are cut to obtain the cross-section of the coal sample per unit length, and the two-dimensional original image p containing the pore development information of this cross-section can be obtained through the high-resolution imager in the digital core CT image module. i ; further through the image processor in the image parameter calculation module, the two-dimensional original image can be converted into a binary image, where the black part in the binary image represents the pore development situation of the two-dimensional original image. By combining the binary image representing the pore structure information through the built-in data processor, the pore structure parameters of this image can be completed: the areal porosity φ i , the pore diameter D i and the pore tortuosity τ i calculation, acquisition, and storage of the data set;

[0045] As Figure 1 and 4 shown, the permeability data processor in the permeability region identification module, based on the pore structure parameters transmitted by the image parameter calculation module and combined with formula (1), can complete the calculation of the relationship between the pore structure and the permeability under the cross-section image of the borehole coal body:

[0046]

[0047] In the formula, D—the pore diameter, m;

[0048] φ —— pore porosity;

[0049] τ —— pore tortuosity;

[0050] As Figure 5 shown, the parameter processor in the image parameter calculation module can obtain the parameter dataset of the in-situ coal body pore structure development information, and the basic process is as follows: First, cut the coal body samples drilled from the same drilling hole according to the set unit length in the drilling depth range, and use the high-resolution imager built in the digital core CT image module to photograph and scan the cross-section of the coal body samples to obtain the two-dimensional original image p reflecting the pore structure development information of the cross-section i , repeat the above process until the segmentation and scanning of the coal body samples under the full length of the drilling hole are completed, and then obtain the two-dimensional image set P (p 1 , p 2 , p 3 ,...) reflecting the fracture development characteristics of the coal body samples in the set drilling depth range of the drilling hole. Relying on the image processor, parameter processor and data memory in the image parameter calculation module, complete the calculation of the pore structure parameters of all coal body cross-section images in the two-dimensional image set P reflecting the drilling hole, and then obtain the parameter dataset of the in-situ coal body pore structure development information;

[0051] As Figure 6 and 7 shown, the permeability data processor in the permeability region identification module, based on the parameter dataset of the in-situ coal body pore structure development information transmitted by the image parameter calculation module and combined with formula (1), can complete the calculation of the permeability magnitude k i based on the K-C equation for each coal body sample cross-section p i , and then obtain the coal body permeability data subset K i (k 1 , k 2 , k 3 ,...) at different drilling distances of the same drilling hole; The drilling points are arranged in a grid layout, effectively ensuring the comprehensive acquisition of the in-situ coal body pore structure information. Summarize all the drilling hole data subsets K i in the detection area in front of the working face, and then obtain the three-dimensional space dataset K (K 1， K 2， K 3 ...) reflecting the permeability characteristics of the in-situ coal body; According to the magnitude of the permeability k i value, combined with the threshold division program built in the permeability region identification module, the identification and division of the low-permeability development area of the in-situ coal body in front of the mining and excavation working face can be realized, providing a certain basis for the precise prevention and control of the local dangerous area of coal and gas outburst.

[0052] At this point, those skilled in the art should recognize that although the exemplary embodiments of the present invention have been shown and described in detail herein, many other variations or modifications that conform to the principles of the present invention can still be directly determined or derived from the disclosed content of the present invention without departing from the spirit and scope of the present invention. Therefore, the scope of the present invention should be understood and determined to cover all such other variations or modifications.

Claims

1. A method for predicting in-situ coal permeability distribution characteristics based on image processing, characterized in that: The method comprises the following steps: S101 borehole drilling technology is mainly used to obtain underground coal and rock samples to obtain coal and rock properties and structural information. First, the drilling rig is arranged in the mining tunnel, and the horizontal drilling operation is adopted. The in-situ coal body in front of the mining working face is broken by the rotation of the drill bit and the drilling pressure. The drill rod is responsible for transmitting the rotation power and drilling pressure to the drill bit to complete the drilling of the in-situ coal body and obtain coal body samples; S102 After completing the drilling of a coal sample in a borehole, the coal sample is cut along the length direction of the borehole using a drill bit, the coal sample is taken out from the core tube, and the coal sample is marked with the borehole number, depth range, and date information; S103 Then, according to the drilling depth range of the borehole, the coal sample taken from the borehole is micro-perturbed and cut according to unit length, and the pore and fracture structure of the cut section is scanned and imaged by the high-resolution imager built into the digital core CT image module to obtain a two-dimensional image p reflecting the pore development characteristics of the coal sample section under the unit length. i , repeat the above process to complete the segmentation and scanning of the coal body samples at the full distance of the borehole, and obtain a two-dimensional image set P (p1, p2, p3, ...) reflecting the pore development characteristics of the coal body samples within the set drilling depth range of the borehole; S104 Then, the image information of the two-dimensional image set P (p1, p2, p3, ...) of the coal sample is transmitted to the image parameter calculation module through the image transmission system of the digital core CT image module. The built-in image processor of the image parameter calculation module first converts the two-dimensional original image obtained by scanning the coal sample into a binary image, and calculates the pore structure parameters of the binary image respectively by relying on the built-in parameter processor: the surface porosity φ i , pore diameter D i and pore tortuosity τ i ; S105 Then, the pore structure parameter data set is transmitted to the permeability region identification module, and a program is set according to the permeability calculation equation to complete the permeability k under the pore structure parameters of the image. i Calculate the permeability of the coal cross-section images at different positions in the same borehole. Calculate the permeability values ​​k of the coal cross-section images at different positions. i , and further obtain the subset K reflecting the permeability of the borehole coal body i (k1, k2, k3...); all drilling data subsets K i By summarizing, we can obtain a data set K (K) that reflects the three-dimensional coal permeability characteristics of the detection area. 1， K 2， K3……); S106 Finally, the data set K(K 1， K 2， K3……) is transmitted to the built-in permeability data processor of the permeability area identification module to complete the identification and division of the low permeability development zone of the in-situ coal body based on the permeability value.

2. The in-situ coal permeability distribution characteristic prediction method based on image processing according to claim 1 is characterized in that: The digital core CT image module is built-in with a high-resolution imager and an image storage; the image parameter calculation module is designed with: an image processor, a parameter processor and a data storage device, which are mainly used to convert the received two-dimensional original image into a binary image and complete the calculation and data storage of the pore structure parameters of the binary image according to the built-in calculation program; the permeability area identification module mainly further processes the data set obtained by the image parameter calculation module through the data processor, completes the in-situ coal body permeability calculation based on the image pore structure parameters, and on the basis of obtaining the coal body permeability data set, sets a specific threshold range of the data set according to the built-in program to achieve further division of the data set, so as to realize the identification of the target area.

3. The in-situ coal permeability distribution characteristic prediction method based on image processing according to claim 1 is characterized in that: The image parameter calculation module mainly realizes the image conversion of two-dimensional image sets of different cross-sections of coal samples, the calculation of pore structure parameters and the acquisition of pore structure parameter data sets; The principle is as follows: Affected by geological structure, the in-situ coal structure in front of the mining face is complex, and there is often a phenomenon of localized broken soft coal. Compared with native hard coal, tectonic soft coal affected by geological structure often shows the characteristics of high degree of pulverization, high degree of pore and fracture development, and generally low permeability, which is easy to form a natural blocking area and lead to a large amount of gas accumulation; it is not difficult to see that there are significant differences in the coal structure of tectonic soft coal and native hard coal; therefore, after micro-disturbance sampling of coal samples by drilling holes, the coal samples are cut to obtain the cross section of coal samples per unit length, and the high-resolution imager in the digital core CT image module can be used to obtain the two-dimensional original image p containing the pore development information of the cross section. i ; Further, the image processor in the image parameter calculation module can convert the two-dimensional original image into a binary image, in which the black part in the binary image represents the pore development of the two-dimensional original image. The built-in data processor is combined with the binary image representing the pore structure information to complete the pore structure parameters of the image: the surface porosity φ i , pore diameter D i and pore tortuosity τ i Calculation and acquisition and storage of data sets.

4. The in-situ coal permeability distribution characteristic prediction method based on image processing according to claim 1 is characterized in that: The permeability data processor in the permeability region identification module can calculate the relationship between the pore structure and permeability of the drilled coal body cross-section image based on the pore structure parameters transmitted by the image parameter calculation module and in combination with formula (1): Where, D is the pore diameter, m; φ——face porosity; τ——pore tortuosity.

5. The in-situ coal permeability distribution characteristic prediction method based on image processing according to claim 1 is characterized by: The parameter processor in the image parameter calculation module can realize the acquisition of the parameter data set of the in-situ coal body pore structure development information. The basic process is as follows: first, the coal body samples drilled from the same drilling borehole are cut in sequence according to the unit length set in the drilling depth range, and the cross section of the coal body sample is photographed and scanned using the built-in high-resolution imager of the digital core CT image module to obtain a two-dimensional original image p reflecting the pore structure development information of the cross section. i The above process is repeated until the segmentation and scanning of the coal samples along the entire length of the drilling borehole are completed, and then a two-dimensional image set P (p1, p2, p3, ...) reflecting the fracture development characteristics of the coal samples within the set drilling depth range of the borehole is obtained. Relying on the image processor, parameter processor and data storage in the image parameter calculation module, the pore structure parameters of all coal cross-section images reflecting the borehole two-dimensional image set P are calculated, and then a parameter data set of in-situ coal pore structure development information is obtained.

6. The in-situ coal permeability distribution characteristic prediction method based on image processing according to claim 4 is characterized in that: The permeability data processor in the permeability region identification module is based on the parameter data set of the in-situ coal body pore structure development information transmitted by the image parameter calculation module, and combined with formula (1), it can complete the calculation of each coal body sample cross section p i The permeability k based on the KC equation i The coal permeability data subset K at different drilling distances in the same borehole is obtained by calculation. i (k1, k2, k3, ...); the grid layout method is used to arrange the drilling points, which effectively guarantees the comprehensive acquisition of the in-situ coal body pore structure information. The subset K of all drilling data in the detection area in front of the working face is i Summarize and then obtain the three-dimensional spatial data set K(K) reflecting the in-situ coal permeability characteristics 1， K 2， K3……); according to the permeability k i The numerical value, combined with the built-in threshold division program of the permeability area identification module, can realize the identification and division of the low permeability development zone of the overlying rock strata in the goaf, providing a certain basis for the precise prevention and control of local dangerous areas of coal and gas outbursts.

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