Method for identifying impact danger zones based on in-hole impact and borehole stress distribution

Abstract

This invention discloses a method for identifying impact hazard areas based on in-hole impact and borehole stress distribution, belonging to the field of coal mine safety engineering technology. The method involves generating a stress distribution cloud map of the area to be evaluated based on borehole stress obtained during large-diameter borehole construction. The area is then discretized, and stress attributes are assigned to the discrete segments. This yields a set of discrete segments containing in-hole impact data. These discrete segments are then clustered, and the in-hole impact coverage rate of each sub-class is calculated. The number of effective segments in each cluster that meets the set in-hole impact coverage rate is calculated, and the set of effective segments in the cluster with the fewest segments is selected as the final predicted impact segments. Based on the clustering analysis results, the segments included in the predicted in-hole impact segment set are marked on the stress distribution cloud map of the area to be evaluated. The method is simple, easily quantifiable, and can provide guidance for subsequent impact prevention and control work.

Description

Technical Field

[0001] This invention relates to a method for identifying impact hazard zones based on in-hole impact and borehole stress distribution, belonging to the field of coal mine safety mining engineering technology. Background Technology

[0002] Rockburst is a severe dynamic disaster in mines, primarily related to high stress concentration in coal seams. Obtaining the stress state within the coal seam is fundamental to assessing its rockburst hazard. Large-diameter boreholes for stress relief are one of the main technical means of preventing rockbursts. For roadways prone to rockbursts, numerous large-diameter boreholes need to be constructed along the roadway. During the construction of these large-diameter boreholes, monitoring the working status of the drilling rig and drill rods allows for the inversion of stress magnitudes at different borehole depths. This inverted borehole stress can then be used to assess the rockburst hazard status of the coal seam near the borehole, providing a reference for rockburst prevention and control.

[0003] During the construction of large-diameter boreholes, certain sections may reach a stress state conducive to impact, resulting in in-bore impact. In-bore impact indicates that the stress state of the corresponding section of the borehole is already in a relatively dangerous state. Under drilling, unloading, and loading disturbances, it may induce impact-induced damage within the coal seam, releasing impact kinetic energy and threatening the stability of the coal face. Borehole sections and inter-bore coal seams with similar stress states to the location of in-bore impact may also pose a similar risk of in-bore impact. Furthermore, these areas are potential impact hazard zones during future longwall mining, making their identification essential.

[0004] Prior art, application number 201410422929.3, discloses a self-compensating controllable seismic source and a method for generating seismic sources for seismic wave CT detection in impact-hazardous areas of underground coal seam working faces. It involves drilling a row of boreholes along the sidewall of the underground coal seam working face roadway. A controllable seismic source is installed in each borehole. For hydraulic in-hole tensioning mechanisms, the seismic source is locked in the borehole by oil expansion. For pneumatic in-hole tensioning mechanisms, a hydraulic slit cutter is used to create a slit, and a cylinder drives a claw plate to open, pressing against the wall of the hydraulically cut slit to lock the seismic source. The energy and frequency of the seismic wave generated by the seismic source can be adjusted by regulating the air source parameters and electromagnetic parameters of the impact hammer. However, its implementation is complex, often requiring experience-based judgment, making it difficult to quantitatively identify specific areas. Summary of the Invention

[0005] Purpose of the invention: To address the shortcomings of existing technologies, this invention proposes a method for identifying impact hazard areas based on borehole impact and borehole stress distribution. The method is simple, easy to quantify, and highly operable. By utilizing borehole stress distribution information and borehole impact location information obtained during borehole decompression, potential borehole impact hazard areas in coal roadways can be identified, thereby guiding coal roadway rockburst prevention and control work.

[0006] Technical Solution: To achieve the above objectives, the present invention provides a method for identifying impact hazard areas based on in-hole impact and borehole stress distribution. The method is characterized by: utilizing borehole stress distribution information and in-hole impact location information obtained during borehole decompression, the area to be evaluated is discretized into discrete stress blocks. Using three stress attributes of each discrete stress block—stress magnitude, stress gradient along the borehole axis, and stress gradient perpendicular to the borehole axis—a clustering method is employed to evaluate the stress similarity between each discrete stress block and the stress block where in-hole impact has occurred, thereby identifying stress blocks potentially prone to in-hole impact.

[0007] The specific steps are as follows:

[0008] Step 1: Construct a large number of large-diameter pressure relief holes in the area to be evaluated, and at the same time obtain stress distribution data at different depths of all the large-diameter holes, including stress magnitude and distribution data of impact inside the hole.

[0009] Step 2: Generate a stress distribution cloud map of the area to be evaluated based on the stress distribution data of a single large-diameter borehole obtained during the construction of the large-diameter borehole, and obtain the stress distribution of the area between the large-diameter boreholes by interpolation.

[0010] Step 3: Then, discretize the stress distribution cloud map of the area to be evaluated, divide the stress distribution cloud map of the area to be evaluated into multiple blocks, assign stress attribute values ​​to all discrete blocks, and obtain a set of discrete blocks including in-hole impact.

[0011] Step 4: Based on the stress property values ​​of the discrete blocks in the region to be evaluated, cluster the discrete blocks in the region to be evaluated, and then calculate the in-hole impact coverage of each subclass.

[0012] Step 5: Calculate the number of effective cluster segments that meet the set in-hole impact coverage rate, and finally select the set of effective cluster segments with the fewest number of segments as the final predicted impact segments.

[0013] Step 6: Based on the cluster analysis results, mark the segments included in the predicted set of in-hole impact segments on the stress distribution cloud map of the area to be evaluated, so as to provide guidance for the subsequent impact prevention and control work.

[0014] Furthermore, the discrete stress block segment is specifically defined as follows: based on the evaluation accuracy requirements, the area to be evaluated is divided into a set C of rectangular blocks of size a×b. n The stress at the center of each segment is σ. n The stress gradient along the borehole axis is G. n-X Stress gradient G perpendicular to the borehole axis n-Y For block C n Stress property value (σ) n G n-X G n-Y The subscript n represents the total number of segments in the area to be evaluated, the subscript X represents the borehole axis, and the subscript Y represents the direction perpendicular to the borehole axis. Based on the in-hole impact distribution obtained during the construction of large-diameter boreholes, segments containing in-hole impact are obtained, forming a set of in-hole impact segments C. b The number of impacts inside the hole is N. b .

[0015] Furthermore, based on the stress attribute values ​​of the discrete segments in the region to be evaluated, the specific process of clustering all discrete segments is as follows:

[0016] First, the discrete blocks are clustered into two classes (C). 2-1 C 2-2 ), count the number of in-hole impact blocks (N) contained in each of the two subclasses. 2-1 N 2-2 The number of in-hole impact blocks (N) contained in each subclass 2-1 N 2-2 Divide by the total number of impact blocks inside the hole (N) b Let be the in-hole impact coverage rate of the corresponding subclass. Then, when clustering into 2 subclasses, the in-hole impact coverage rates of the two subclasses are respectively... and

[0017] Similarly, the in-pore impact coverage (K) for each cluster was calculated for clusters of 3, 4, ..., and m (m≤n). m-1 K m-2 ... K m-m );

[0018] Let the required in-hole impact coverage rate be K. Statistically calculate the number of subclass segments that satisfy the in-hole impact coverage rate K for clusters 2, 3, 4, ..., m: sum the subclasses in cluster m by combining them in different ways, find all combinations that satisfy a coverage rate greater than or equal to K, then calculate the number of segments in each combination, and select the combination with the fewest segments as the effective combination satisfying the in-hole impact coverage rate K for cluster m. The number of segments contained in this combination is the effective number of segments satisfying the in-hole impact coverage rate K for cluster m.

[0019] Furthermore, when the number of effective segments satisfying the in-hole impact coverage rate K in cluster m is greater than or equal to the number of effective segments satisfying the in-hole impact coverage rate K in cluster m-1, or when each subclass (C) in cluster m... m-1 C m-2 ..., C m-m When the in-hole impact coverage of all clusters is less than 50%, further clustering is stopped. The number of effective segments that satisfy the in-hole impact coverage K when clustering m-1 is taken as the final predicted number of in-hole impact segments, and the combination of effective segments that satisfy the in-hole impact coverage K when clustering m-1 is taken as the final predicted set of in-hole impact segments.

[0020] Beneficial effects: This method is simple to operate, easy to use, quantifiable, and highly operable; by utilizing the stress characteristics of the borehole section where in-hole impact occurs, it can assess and predict areas in the borehole construction area with in-hole impact risk, providing clear guidance for the prevention and control of rockburst during the later mining period. Attached Figure Description

[0021] Figure 1 This is a flowchart of the impact hazard zone identification method based on in-hole impact and borehole stress distribution of the present invention;

[0022] Figure 2 This is a stress curve diagram of a large-diameter pressure relief borehole in an embodiment of the present invention;

[0023] Figure 3 This is a schematic diagram of the stress distribution inverted in the pressure relief area and the monitored impact distribution inside the hole in an embodiment of the present invention;

[0024] Figure 4 This is a schematic diagram of the predicted distribution of impact blocks within the borehole in the pressure relief area according to an embodiment of the present invention. Detailed Implementation

[0025] The invention will now be further described with reference to the accompanying drawings.

[0026] Numerous large-diameter stress relief boreholes were constructed in a certain stress relief area, and the stress magnitudes and borehole impact distribution at different depths of these boreholes were obtained. Based on this data, the following steps were taken to identify the stress characteristics in the stress relief area that would lead to borehole impact, thereby providing guidance for the prevention and control of rockbursts during subsequent mining operations.

[0027] like Figure 1As shown, the present invention is a method for identifying impact hazard areas based on in-hole impact and borehole stress distribution. It uses borehole stress to generate a stress distribution cloud map; the area to be evaluated is discretized into stress blocks; and using the three stress attributes of each block (stress magnitude, stress gradient along the borehole axis, and stress gradient perpendicular to the borehole axis), a clustering method is used to evaluate the stress similarity between each discrete block and the block in which in-hole impact has occurred, thereby identifying stress blocks that may potentially experience in-hole impact. The coverage rate of in-hole impact is measured by the proportion of actual in-hole impact segments contained in each subclass after clustering to the total number of in-hole impact segments. All discrete segments are clustered from few to many (starting with cluster 2 and gradually increasing the number of clusters). The number of effective segments in each cluster that meet the given in-hole impact coverage rate is calculated. When the number of effective segments that meet the given in-hole impact coverage rate in a cluster starts to increase or the in-hole impact coverage rate of each subclass after clustering is less than 50%, the number of clusters is stopped from being increased further. The effective segments of the previous cluster are selected as the final predicted set of in-hole impact segments, and the region represented by it is the region where in-hole impact may occur as assessed.

[0028] Step 1: Discretization of the region to be evaluated and assignment of values ​​to discrete blocks

[0029] Stress distribution cloud maps of the area to be evaluated are generated based on the stress distribution of individual boreholes (stress magnitudes at different depths) obtained through inversion during large-diameter borehole construction. Stress distribution between boreholes is obtained through interpolation. According to the required evaluation accuracy, the area to be evaluated is divided into a set of rectangular blocks C of size a×b. n The magnitude of stress at the center of each segment (σ) n Stress gradient along the borehole axis (G) n-X Stress gradient perpendicular to the borehole axis (G) n-Y ) is block C n Stress property value (σ) n G n-X G n-Y Based on the in-hole impact distribution obtained during large-diameter drilling, segments containing in-hole impact are obtained, forming an in-hole impact segment set C. b The number of impacts inside the hole is N. b .

[0030] Step 2: Clustering of discrete blocks in the area to be evaluated and calculation of in-pore impact coverage for each subclass.

[0031] Based on the stress property values ​​of discrete segments in the region to be evaluated, all discrete segments are clustered. First, the discrete segments are clustered into two classes (C1, C2, C3, C4, C5, C6, C7, C8, C9, C1, C 2-1 C 2-2 ), count the number of in-hole impact blocks (N) contained in each of the two subclasses. 2-1 N 2-2The number of in-hole impact blocks (N) contained in each subclass 2-1 N 2-2 Divide by the total number of impact blocks inside the hole (N) b Let be the in-hole impact coverage rate of the corresponding subclass. Then, when clustering into 2 subclasses, the in-hole impact coverage rates of the two subclasses are respectively... and

[0032] Similarly, the in-pore impact coverage (K) for each category was calculated when clustering into 3, 4, ..., m categories. m-1 K m-2 ... K m-m Let K be the required borehole impact coverage rate required by the on-site enterprise. Statistically calculate the number of subclass segments that satisfy the borehole impact coverage rate K for clusters 2, 3, 4, ..., m. Specifically, sum the subclasses in cluster m using different combinations, find all combinations that satisfy a coverage rate greater than or equal to K, then calculate the number of segments in each combination. Select the combination with the fewest segments as the effective combination satisfying the borehole impact coverage rate K for cluster m. The number of segments contained in this combination is the effective number of segments satisfying the borehole impact coverage rate K for cluster m.

[0033] When the number of effective segments satisfying the in-hole impact coverage K in cluster m is greater than or equal to the number of effective segments satisfying the in-hole impact coverage K in cluster m-1, or when each subclass (C) in cluster m... m-1 C m-2 ..., C m-m When the in-hole impact coverage of all clusters is less than 50%, further clustering is stopped. The number of effective segments that satisfy the in-hole impact coverage K when clustering m-1 is taken as the final predicted number of in-hole impact segments, and the combination of effective segments that satisfy the in-hole impact coverage K when clustering m-1 is taken as the final predicted set of in-hole impact segments.

[0034] Step 3: Display of in-hole impact prediction blocks

[0035] Based on the cluster analysis results, the segments included in the predicted set of in-hole impact segments are marked on the stress distribution cloud map of the area to be evaluated, providing guidance for the subsequent impact prevention and control work.

[0036] The following examples illustrate this point:

[0037] Example Background: Large-diameter boreholes were drilled to relieve pressure in the sidewall area of ​​a coal mine roadway. The depth of the pressure relief holes was 25m, and the pressure relief range covered a strike of 46m. A total of 24 pressure relief holes were constructed, with a spacing of 2m between them. During the pressure relief construction, the stress magnitude in the boreholes was calculated using the stress sensing inversion system built into the pressure relief drilling rig. Figure 2As shown in the figure. Simultaneously, 15 impact events within the borehole were monitored during the pressure relief operation (marked with pentagrams in the figure), distributed as follows: Figure 3 As shown. The mine requires 100% coverage of borehole impact prediction. Based on the above information, the blocks in this area that meet the borehole impact stress state are predicted.

[0038] The specific steps are as follows:

[0039] Step 1:

[0040] Based on the borehole stress obtained during large-diameter borehole construction, a stress distribution cloud map of the pressure relief zone is drawn, such as... Figure 3 As shown, the large-diameter drilling area is divided into 1224 blocks (C). 1224 The block segment has a strike length of 2m and a dip length of 0.5m. The stress (σ) at the center of each block segment is obtained from the stress distribution contour map. n Stress gradient (G) at the center along the borehole axis n-X ), the stress gradient perpendicular to the borehole axis at the center position (G) n-Y This allows us to obtain the stress properties (σ) of each segment. n G n-X G n-Y Based on the in-hole impact distribution obtained during large-diameter drilling, segments containing in-hole impact are obtained, forming an in-hole impact segment set C. b The number of impacts inside the hole is 15.

[0041] Step Two:

[0042] First, the discrete block segment C is... 1224 Cluster 2 (C 2-1 C 2-2 ), C 2-1 The subclass contains 907 blocks, C 2-2 The subclass contains 317 segments. Among them, all 15 in-hole impact segments are located in C... 2-2 Within the subclass. Therefore, C 2-1 Subclasses and C 2-2 The in-hole impact coverage rates for the subclasses are 0% and 100%, respectively. Therefore, the efficient combination that satisfies 100% in-hole impact coverage when clustering into 2 classes is C. 2-2 When the subclass is clustered into two groups, the number of effective blocks that satisfy the 100% impact coverage rate in the hole is 317.

[0043] Continue with discrete block segment C 1224 Cluster 3 (C 3-1 C 3-2 C 3-3 ), C 3-1 The subclass contains 841 blocks, C 3-2 The subclass contains 82 blocks, C3-3 The subclass contains 301 segments. Among them, all 15 in-hole impact segments are located in C... 3-3 Within the subclass. Therefore, C 3-1 Subclass, C 3-2 Subclasses and C 3-3 The in-hole impact coverage rates for the subclasses are 0%, 0%, and 100%, respectively. Therefore, the efficient combination that satisfies 100% in-hole impact coverage when clustering into 3 classes is C. 3-3 When the subclass is clustered into three types, the number of effective blocks that satisfy the 100% impact coverage rate in the hole is 301.

[0044] Continue with discrete block segment C 1224 Cluster 4 (C 4-1 C 4-2 C 4-3 C 4-4 ), C 4-1 The subclass contains 604 blocks, C 4-2 The subclass contains 425 blocks, C 4-3 The subclass contains 52 blocks, C 4-4 The subclass contains 143 segments. Among them, two in-hole impacts are at C. 4-2 Within the subclass, 13 in-hole impact block segments are in C 4-4 Within the subclass. Therefore, C 4-1 Subclass, C 4-2 Subclass, C 4-3 Subclasses and C 4-4 The in-hole impact coverage rates for the subclasses are 0%, 13%, 0%, and 87%, respectively. Therefore, the efficient combination that satisfies 100% in-hole impact coverage when clustered into 4 classes is C. 4-2 and C 4-4 When the subclass is clustered into 4 types, the number of effective blocks that satisfy the 100% impact coverage rate in the hole is 568.

[0045] Since the number of effective segments satisfying 100% in-hole impact coverage (568) in cluster 4 is greater than the number of effective segments satisfying 100% in-hole impact coverage (301) in cluster 3, further clustering is stopped, and the effective segment C satisfying 100% in-hole impact coverage in cluster 3 is selected. 3-3 The final predicted in-hole impact segments are 301 in total.

[0046] The predicted impact segments within the borehole are projected onto the stress distribution cloud map of the pressure relief area to obtain the predicted distribution of impact segments within the borehole, such as... Figure 4 As shown.

Claims

1. A method for identifying impact hazard zones based on in-hole impact and borehole stress distribution, characterized in that: By utilizing borehole stress distribution information and in-hole impact location information obtained during borehole decompression, the area to be evaluated is discretized into discrete stress blocks. Using three stress attributes of each discrete stress block—stress magnitude, stress gradient along the borehole axis, and stress gradient perpendicular to the borehole axis—a clustering method is employed to evaluate the stress similarity between each discrete stress block and the stress blocks where in-hole impact occurred, thereby identifying stress blocks potentially prone to in-hole impact. The specific steps are as follows: Step 1: Construct a large number of large-diameter pressure relief holes in the area to be evaluated, and at the same time obtain stress distribution data at different depths of all large-diameter boreholes, including stress magnitude and distribution data of impact inside the hole. Step 2: Generate a stress distribution cloud map of the area to be evaluated based on the stress distribution data of a single large-diameter borehole obtained during the construction of the large-diameter borehole, and obtain the stress distribution of the area between the large-diameter boreholes by interpolation. Step 3: Then, discretize the stress distribution cloud map of the area to be evaluated, divide the stress distribution cloud map of the area to be evaluated into multiple blocks, assign stress attribute values ​​to all discrete blocks, and obtain a set of discrete blocks including in-hole impact. Step 4: Based on the stress property values ​​of the discrete blocks in the region to be evaluated, cluster the discrete blocks in the region to be evaluated, and then calculate the in-hole impact coverage of each subclass. Step 5: Calculate the number of effective segments in the cluster that meet the set impact coverage rate in the borehole, and finally select the set of effective segments in the cluster with the fewest segments as the final predicted impact segments. Step 6: Based on the cluster analysis results, mark the segments included in the predicted set of in-hole impact segments on the stress distribution cloud map of the area to be evaluated, so as to provide guidance for the subsequent impact prevention and control work. The discrete stress block segment is specifically defined as follows: based on the required evaluation accuracy, the area to be evaluated is divided into segments with dimensions of [size missing]. A collection of rectangular blocks The stress at the center of each segment is... The stress gradient along the borehole axis is Stress gradient perpendicular to the borehole axis For blocks Stress property value ( , , The subscript n represents the total number of segments in the area to be evaluated, the subscript X represents the borehole axis, and the subscript Y represents the direction perpendicular to the borehole axis. Based on the in-hole impact distribution obtained during the construction of large-diameter boreholes, segments containing in-hole impact are obtained, forming an in-hole impact segment set. The number of impacts inside the hole is .

2. The method for identifying impact hazard areas based on in-hole impact and borehole stress distribution according to claim 1, characterized in that, The specific process of clustering all discrete segments based on their stress property values ​​is as follows: First, the discrete blocks are clustered into two classes ( ), and count the number of in-hole impact blocks contained in the two subclasses respectively ( The number of in-hole impact blocks contained in each subclass ( Divide by the total number of impact blocks inside the hole ( Let be the in-hole impact coverage rate of the corresponding subclass. Then, when clustering into 2 subclasses, the in-hole impact coverage rates of the two subclasses are respectively... and ; Similarly, calculate the clusters of 3, 4, ..., m respectively. Impact coverage rate in the borehole for each category ( ) , … ); Assume the required in-hole impact coverage rate is To statistically calculate the number of subclass segments that satisfy the in-hole impact coverage rate K when clustering into clusters 2, 3, 4, ... m, the subclasses in cluster m are combined in different ways and summed. All combinations that satisfy the coverage rate greater than or equal to K are found. Then, the number of segments in each combination is calculated. The combination with the fewest segments is selected as the effective combination that satisfies the in-hole impact coverage rate K when clustering into cluster m. The number of segments contained in this combination is the effective number of segments that satisfy the in-hole impact coverage rate K when clustering into cluster m.

3. The method for identifying impact hazard areas based on in-hole impact and borehole stress distribution according to claim 2, characterized in that: When the number of effective blocks satisfying the in-hole impact coverage K in cluster m is greater than or equal to the number of effective blocks satisfying the in-hole impact coverage K in cluster m-1, or when each subclass of cluster m ( , … When the in-hole impact coverage of all clusters is less than 50%, further clustering is stopped. The number of effective segments that satisfy the in-hole impact coverage K when clustering into m-1 clusters is taken as the final predicted number of in-hole impact segments. The combination of effective segments that satisfy the in-hole impact coverage K when clustering into m-1 clusters is taken as the final predicted set of in-hole impact segments.

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