In-situ coal body permeability distribution characteristic prediction method based on image processing

Abstract

The invention discloses an image processing-based in-situ coal body permeability distribution characteristic prediction method, which comprises the following steps of: drilling an in-situ coal body in front of an excavation working face by using a drilling technology and adopting a horizontal drilling operation mode, obtaining a coal body sample, and performing micro-disturbance cutting on the sample, a digital core CT image module is used for completing coal body sample cutting section image scanning to obtain a two-dimensional image set, an image parameter calculation module is used for achieving original image binarization conversion and particle diameter, pore tortuosity and surface porosity parameter calculation, and parameter data sets are transmitted to a permeability area identification module; and completing in-situ coal body permeability calculation based on the image parameter data set and identification and division of a low-permeability development area. On the basis, an image processing technology is introduced to be combined with a coal body permeability calculation theory so as to accurately describe in-situ complex coal body permeability distribution characteristics, and then accurate identification of the in-situ coal body gas low-permeability area is achieved.

Description

Technical Field

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

[0002] my country has a large annual coal output and serious coal mine disasters, among which coal and gas outburst accidents account for a large proportion. This is mainly due to the complex geological conditions of coal mining in my country and the relatively developed low-permeability coal seams, which poses a great challenge to the effective implementation of gas extraction and prevention and elimination measures. According to field 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 root causes of coal and gas outbursts. Therefore, accurate identification and division of low-permeability dangerous areas of in-situ coal bodies is the key to realizing the prediction of coal and gas outburst areas and the targeted formulation of regional prevention measures, reducing the blindness of coal and gas outburst work, and can effectively improve the safe and stable mining of complex coal seams.

[0003] However, the in-situ coal body in front of the mining face has the characteristics of being invisible and wide-ranging. At the same time, affected by the geological structure and mining stress, the coal seam structure is complex, the cross-layer development of soft and hard coal is common, and the pore and fracture structure of the coal body is complex and diverse, making it difficult to quantitatively and accurately describe the pore and fracture structure development characteristics of the in-situ coal body in front of the mining face. Based on this, the present invention introduces image processing technology combined with the permeability calculation theory of coal rock reservoirs to quantitatively describe the pore and fracture development characteristics of the in-situ coal body in the actual mining process of coal mines, reveal the permeability distribution law of the in-situ coal body in front of the mining face, and then accurately identify the low-permeability gas area and enrichment zone, and provide certain guidance for the formulation of precise 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 an in-situ coal permeability distribution characteristics prediction method based on image processing to solve or alleviate the problems existing in the prior art.

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

[0006] The present application provides an in-situ coal body permeability distribution characteristic prediction method based on image processing, characterized in that the method comprises 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 tunnel, and the horizontal drilling operation is adopted. The in-situ coal body 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 to obtain coal body samples;

[0008] 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;

[0009] 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;

[0010] 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 ;

[0011] 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 spatial coal permeability characteristics of the detection area. 1， K 2， K3……);

[0012] 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.

[0013] The in-situ coal body permeability distribution characteristics prediction method based on image processing is completed by relying on an in-situ coal body permeability distribution characteristics prediction device based on image processing, which 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 has a built-in high-resolution imager and 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 permeability calculation based on the image pore structure parameters, and on the basis of obtaining the coal 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.

[0015] Preferably, 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: the in-situ coal structure is complex due to the influence of geological structure, and there is often a phenomenon of local occurrence of 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 natural blocking areas and cause large amounts 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, the coal samples are cut to obtain the coal sample cross-section 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;

[0016] Preferably, the permeability data processor in the permeability region identification module can calculate the relationship between the pore structure and permeability of the cross-sectional image of the drilled coal body 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;

[0017] Preferably, 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, and 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 , repeat the above process until the segmentation and scanning of the coal body 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 body samples within the set drilling depth range of the borehole is obtained, and the pore structure parameters of all coal body cross-section images reflecting the borehole two-dimensional image set P are calculated by relying on the image processor, parameter processor and data storage in the image parameter calculation module, and then a parameter data set of in-situ coal body pore structure development information is obtained;

[0018] Preferably, 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 permeability data processing of each coal body sample 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 in-situ coal body 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 in-situ coal body in front of the mining working face, providing a certain basis for the precise prevention and control of local dangerous areas of coal and gas outbursts.

[0019] Due to the adoption of the above technical solution, the beneficial effects of the present invention are:

[0020] In the in-situ coal body permeability distribution feature identification scheme based on image processing provided by the present invention, firstly, through the borehole drilling technology, horizontal drilling operation is adopted to complete the in-situ coal body drilling sampling and information calibration in front of the mining working face; then, the digital core CT image module is used to complete the scanning of the cross-section information of the coal body sample cutting to obtain a two-dimensional image set P; the image parameter calculation module completes the conversion of the original image and the calculation of the pore structure parameters to obtain a data set of pore structure parameters; the permeability area identification module relies on the built-in permeability data processor to complete the in-situ coal body permeability calculation based on the pore structure parameter data set and the identification and division of the low permeability development zone. Based on this, the present invention adopts image processing technology combined with the permeability calculation theory of coal rock reservoirs to quantitatively describe the development characteristics of in-situ coal body pores and fractures during actual coal mining, and intuitively analyzes the coal body destruction characteristics in the mining space under geological structure and mining disturbance and the distribution law of soft and hard coal bodies with different structures, thereby revealing the evolution characteristics of in-situ coal body seepage distribution, accurately identifying gas low permeability areas and gas enriched zones, and providing a certain theoretical and on-site practical basis for the precise prevention and control of local dangerous areas of coal and gas outbursts. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 This is a flow chart of the in-situ coal body permeability distribution characteristic prediction method based on image processing of the present invention;

[0022] Figure 2 This is a schematic diagram of the in-situ coal body structure distribution of the present invention;

[0023] Figure 3 This is a cross-sectional morphology diagram of the same borehole at different positions of the in-situ coal body of the present invention;

[0024] Figure 4 This is a schematic diagram of the calculation of in-situ coal body permeability of the present invention;

[0025] Figure 5 Schematic diagram of image subsets of different cross sections of the same borehole according to the present invention;

[0026] Figure 6 This is a schematic diagram of the in-situ coal permeability data set of the present invention;

[0027] Figure 7 This is a schematic diagram of the division of low permeability areas of the in-situ coal body according to the present invention; DETAILED DESCRIPTION

[0028] In order to make the purpose, technical scheme and advantages of the embodiments of the present invention more clearly understood, the embodiments of the present invention are further described in detail below in conjunction with the embodiments and drawings. Here, the illustrative embodiments of the present invention and their descriptions are used to explain the present invention, but are not intended to limit the present invention. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0029] In the description of the present invention, it should be understood that terms such as “upper”, “lower”, “front”, “back”, “left”, “right”, “top”, “bottom”, “inside” and “outside” indicating directions or positional relationships are based on the directions or positional relationships 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 referred device, component or structure must have a specific direction, be constructed or operate in a specific direction, and should not be understood as a limitation on the present invention.

[0030] The specific implementation method of the present invention will be further described below in conjunction with the accompanying drawings.

[0031] like Figure 1-7 As shown, the present invention provides an in-situ coal body permeability distribution characteristic prediction method based on image processing, characterized in that the method comprises the following steps:

[0032] 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 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 to obtain coal body samples;

[0033] 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;

[0034] 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;

[0035] 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 ;

[0036] S105 Then, the pore structure parameter data set is transmitted to the permeability region identification module, and the 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 spatial coal permeability characteristics of the detection area. 1， K 2， K3……);

[0037] 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.

[0038] 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.

[0039] like Figure 1 and 4 As shown, the digital core CT image module has a built-in high-resolution imager and image storage; the image parameter calculation module is designed with: an image processor, a parameter processor and a data storage, 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 the data set specific threshold range according to the built-in program to achieve further division of the data set, so as to realize the identification of the target area.

[0040] like Figure 4 and 5 As shown in FIG. 1 , 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: the in-situ coal structure in front of the mining face is complex due to the influence of geological structure, and there is often a phenomenon of local occurrence of 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 natural blocking areas and cause large amounts of gas to accumulate; 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, the coal samples are cut to obtain the coal sample cross-section 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;

[0041] like Figure 1 and 4 As shown, 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;

[0042] like Figure 5 As shown in the figure, 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 coal body sample cross section 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, repeat the above process until the segmentation and scanning of the coal body 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 body samples within the set drilling depth range of the borehole is obtained, and the pore structure parameters of all coal body cross-section images reflecting the borehole two-dimensional image set P are calculated by relying on the image processor, parameter processor and data storage in the image parameter calculation module, and then a parameter data set of in-situ coal body pore structure development information is obtained;

[0043] like Figure 6 and 7 As shown, the permeability data processor in the permeability region identification module is based on the parameter data set of the in-situ coal pore structure development information transmitted by the image parameter calculation module, combined with formula (1), to complete the permeability data processing of each coal sample 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 in-situ coal body in front of the mining working face, providing a certain basis for the precise prevention and control of local dangerous areas of coal and gas outbursts.

[0044] 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 based on the contents disclosed in 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 recognized as covering all these 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 coal body sample cross section is scanned and photographed 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 1 is characterized by: 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 is used to arrange the drilling points, which effectively guarantees the comprehensive acquisition of the pore structure information of the in-situ coal body. The subset K of all drilling data in the in-situ coal body detection area 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 in-situ coal body in front of the mining working face, providing a certain basis for the precise prevention and control of local dangerous areas of coal and gas outbursts.

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