Coal seam small structure imaging and stress inversion method based on drilling sound wave remote detection

Abstract

The invention discloses a coal seam small structure imaging and stress inversion method based on borehole sound wave remote detection, which comprises the following steps of: firstly, respectively arranging bedding boreholes in a top plate and a bottom plate of a coal seam, and then continuously transmitting sound waves to the coal seam and receiving reflected waves in the bedding boreholes to obtain reflected wave full-wave signal data of upper and lower interfaces of the coal seam; processing the data to obtain a two-dimensional imaging slice of the coal seam area at the current position; then sequentially detecting along the trend of the coal seam, combining different two-dimensional imaging slices, and establishing a three-dimensional geologic structure model of the coal seam; then, based on the three-dimensional geologic structure model, a specific processing mode is adopted to realize division of high-dynamic disaster risk areas; according to the method, the detection blind area existing between holes in the most common drilling method under a coal seam well is overcome, the detection range of a single hole is widened, full-coverage detection of a geological structure of a coal seam area is achieved, and a small geological structure image can be directly obtained; and the high-dynamic disaster risk area is identified through subsequent processing for guiding subsequent coal seam mining.

Description

Technical Field

[0001] The present invention belongs to the technical field of mine gas disaster prevention and control, and in particular relates to a coal seam small structure imaging and stress inversion method based on borehole acoustic wave remote detection. Background Art

[0002] Coal and gas outbursts are a major source of disasters in coal mines, often occurring in areas with unusual geological structures. As coal mining shifts to deeper depths, geological conditions become more complex, increasing the risk of outburst accidents. According to statistics, over 80% of outburst accidents occur in areas with unusual geological structures, with small geological structures measuring 3 to 5 meters in diameter being particularly prone to inducing them. Detailed detection of small geological structures in coal seams is crucial for preventing and controlling coal and gas outburst disasters.

[0003] Elastic wave detection exploits differences in wave impedance between different strata and offers significant advantages in detecting stratum interfaces and geological structures. However, low-frequency seismic wave detection methods, such as trenching seismic and slot wave seismic, have a large detection range but limited accuracy. High-frequency acoustic wave detection methods, such as conventional borehole acoustic logging, also have a very limited detection range, typically using only the acoustic time difference curve of the sliding longitudinal wave to identify the boundary between the coal seam and the roof and floor in the borehole.

[0004] The applicability of elastic wave detection technology depends largely on the elastic wave frequency used. To meet the demand for detailed detection of small geological structures within 3 to 5 meters of coal seams, it is necessary to select appropriate medium- and high-frequency acoustic waves as detection signals to achieve a balance between detection range and spatial resolution, thereby achieving both detection distance and detailed imaging results. However, there is currently no method for imaging and detecting hidden small geological structures in coal seams using medium- and high-frequency reflected acoustic waves.

[0005] Therefore, how to provide a new coal seam geological structure detection method that can detect small geological structures within a range of 3 to 5 meters while having a large detection distance and ensuring detection accuracy is the research direction required by the present invention. Summary of the Invention

[0006] In response to the problems existing in the above-mentioned prior art, the present invention provides a method for imaging and stress inversion of small coal seam structures based on borehole acoustic wave remote detection. It can detect small geological structures within a range of 3 to 5 meters while having a large detection distance, and ensure detection accuracy.

[0007] To achieve the above-mentioned purpose, the present invention adopts a technical solution: a method for imaging and stress inversion of coal seam microstructures based on borehole acoustic wave remote detection, comprising the following steps: ① Arrangement of bedding boreholes: In the high and low lanes on one side of the coal seam, construct one bedding borehole each in the roof and floor rock layers along the coal seam dip from the high and low lanes respectively. The two bedding boreholes are parallel to each other and located in the same lane cross section. The length of the bedding boreholes should cover the coal seam area that needs to be detected as much as possible. ② Acoustic wave detection: Reflection acoustic wave imaging instruments are placed in two bedding boreholes, each emitting acoustic waves toward the coal seam. The frequency of the excited acoustic wave signal is between 1kHz and 15kHz. The acoustic wave is reflected by the coal-rock interface and collected by the receiving end of the instrument. The instrument is gradually moved from the hole mouth to the bottom of the bedding borehole to complete the detection process of the two bedding boreholes, and the full-wave signal data of the reflected wave at the upper and lower interfaces of the coal seam are obtained. ③ Constructing a two-dimensional imaging slice: Processing the full-wave signal data of the reflected wave obtained in step ②, integrating the imaging results of the upper and lower interfaces of the coal seam, and obtaining a two-dimensional imaging slice of the coal seam area at the current location; ④ Construct a 3D geological structure model of the coal seam: Determine the next bedding drill hole location in the high-level and low-level lanes along the coal seam strike, and repeat steps ① to ③ to obtain a 2D imaging slice of the coal seam area at that location. Repeat this process to obtain 2D imaging slices at different locations along the coal seam strike. After combining these slices, a 3D geological structure model of the coal seam is constructed. ⑤ Determine geological structure: Based on the three-dimensional geological structure model of the coal seam, determine the small geological structures (faults, folds, coal seam dip change zones, coal seam thickness change zones, collapse columns, etc.) in the coal seam, and mark and warn potential high-dynamic disaster risk areas that may induce coal and gas outbursts to guide subsequent coal seam mining.

[0008] Furthermore, after the small geological structure is determined according to the three-dimensional geological structure model in step ⑤, reflection acoustic wave imaging of through-layer drilling is used for further verification, and a group of through-layer drilling holes are constructed upward at different angles in the bottom plate tunnel below the coal seam area, so that the through-layer drilling holes are constructed to the target coal seam area where the small geological structure is determined to exist; a reflection acoustic wave imaging instrument is arranged in each through-layer drilling hole, and the instrument is pushed gradually from the hole mouth of the through-layer drilling hole to the bottom of the hole to obtain reflection acoustic wave imaging data of the geological structure interface within 3 to 5 meters around each through-layer drilling hole; the reflection acoustic wave imaging results of the through-layer drilling holes are compared and verified with the reflection acoustic wave imaging results of the in-layer drilling holes to improve the detection accuracy of small geological structures.

[0009] Furthermore, in step 5, identifying high-dynamic disaster risk areas involves using a 3D geological structure model of the coal seam to generate a corresponding model in Rhino software. This model is then imported into numerical simulation software to calculate the volume stress distribution of the coal seam working face and identify high-stress areas within the coal seam. Based on the distribution of these high-stress areas, the coal seam working face is then divided into high-dynamic disaster risk areas. This provides further data guidance for subsequent safe coal seam mining.

[0010] Furthermore, the reflected acoustic wave imaging instrument is cylindrical and consists of a transmitter, a receiver and a sound insulator coaxially connected therebetween. Both the transmitter and the receiver are made of piezoelectric ceramics and stimulate medium and high frequency acoustic wave signals through the piezoelectric effect.

[0011] Furthermore, the number and angle of the through-bed drill holes are determined according to the actual coal seam area; the spacing between two adjacent through-bed drill holes along the coal seam is 6 to 10 meters.

[0012] Furthermore, the reflected wave full-wave signal data processing process in step ③ is as follows: first, the transmitted wave data at different depth positions in the same bedding borehole are classified according to the combination of common source distance and common center point, and then the coal seam geological structure interface imaging at different positions in the same bedding borehole is obtained through direct wave suppression, wave field separation, reflected wave enhancement and offset imaging. After performing the above processing on the two bedding boreholes respectively, the imaging results of the upper and lower interfaces of the coal seam are obtained.

[0013] Furthermore, a model is generated in Rhino software and imported into numerical simulation software. Specifically, after building a three-dimensional geological structure model of the coal seam in Rhino software, the model is meshed and exported to dxf format or stl format, and then imported into COMSOL software for finite element method simulation calculation; or it can be exported to f3grid format and then imported into Flac3D software for finite difference method simulation calculation.

[0014] Furthermore, the identification of high stress areas in the coal seam is specifically as follows: importing the three-dimensional model into the numerical simulation software, giving the corresponding boundary conditions, and correcting the model boundary conditions in combination with the measured ground stress, assigning values to the model geomechanical properties according to the measured core data, and then calculating the volume stress distribution of each area at static state and during tunnel excavation through the solid mechanics equation, where the volume stress is the sum of the first principal stress, the second principal stress and the third principal stress; according to the volume stress distribution of the coal seam, the stress average value σ is calculated, and 1.5σ is taken as the stress threshold.

[0015] Furthermore, the specific division criteria for the high-dynamic disaster risk area are as follows: when the stress value of the working face area exceeds the stress threshold, the area is identified as a high-stress area and determined as a high-dynamic disaster risk area; in addition, if the stress value change rate of a certain area exceeds 60%, the area is also identified as a high-dynamic disaster risk area.

[0016] Compared with the existing technology, the present invention first arranges the seam drill holes on the roof and bottom plates of the coal seam to be detected respectively, and then continuously transmits sound waves and receives reflected waves in the direction of the coal seam through the reflection acoustic wave imaging instrument in the seam drill hole, so as to obtain the full-wave signal data of the reflected waves of the upper interface of the coal seam (that is, the sound waves are transmitted and received in the seam drill hole of the roof) and the lower interface (that is, the sound waves are transmitted and received in the seam drill hole of the bottom plate); the full-wave signal data of the reflected waves of the upper and lower interfaces are combined and processed to obtain a two-dimensional imaging slice of the coal seam area at the current position; then, detection is carried out in sequence along the direction of the coal seam, and different two-dimensional imaging slices are combined to establish a three-dimensional geological structure model of the coal seam; then, based on the three-dimensional geological structure model, a specific processing method is used to realize the division of high-dynamic disaster risk areas; the method of the present invention overcomes the detection blind spots between holes in the most commonly used drilling method in coal seams, improves the detection range of a single hole, realizes full coverage detection of the geological structure of the coal seam area, and can directly obtain the ground Geological structure imaging; compared with conventional geophysical prospecting methods, it is not affected by electromagnetic interference in coal seams underground, and takes into account the requirements of small geological structures for detection range and accuracy; by emitting acoustic wave imaging, the geological structure imaging around the hole can be intuitively obtained, and the working face can be made transparent; it fully adapts to the detection needs of small geological structures in coal seams, and visualizes the three-dimensional geological structure of the coal seam and the stress distribution of the working face. Through subsequent processing, the complex geological structure areas and stress concentration areas are identified to guide subsequent coal seam mining; in addition, in order to ensure the accuracy of identification of high-dynamic disaster risk areas, the present invention uses through-layer drilling reflection acoustic wave imaging to further verify the identified high-dynamic disaster risk areas, constructs a through-layer drilling group around the area, and obtains the reflected acoustic wave imaging data of the surrounding geology in each through-layer drilling hole, and finally compares the imaging data with the reflected acoustic wave imaging results of the layer drilling holes for verification, and ultimately can achieve accurate imaging of small geological structures of 3~5m in the coal seam. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 2 is a schematic diagram of an overall detection process according to an embodiment of the present invention.

[0018] Figure 2 Schematic diagram of a time-domain finite-difference numerical model in an embodiment of the present invention.

[0019] Figure 3 Schematic diagram of acoustic wave excitation and reception during layer drilling in an embodiment of the present invention.

[0020] Figure 4 2. It is a schematic diagram of two-dimensional slice imaging of a coal seam in an embodiment of the present invention.

[0021] Figure 5 It is a schematic diagram of three-dimensional model reconstruction and small geological structure identification in an embodiment of the present invention.

[0022] Figure 6 Schematic diagram of the arrangement of through-layer drilling in an embodiment of the present invention.

[0023] Figure 7 It is a three-dimensional geological structure model diagram of the coal seam in an embodiment of the present invention.

[0024] Figure 8 Schematic diagram of stress distribution on the working surface in an embodiment of the present invention. DETAILED DESCRIPTION

[0025] The present invention will be further described below.

[0026] like Figure 1 As shown, the present invention includes the following steps: ① Arrangement of bedding boreholes: In the high-level and low-level lanes on one side of the coal seam, construct a bedding borehole 1-1# and 1-2# in the roof rock layer and floor rock layer along the coal seam dip from the high-level and low-level lanes respectively. The two bedding boreholes are parallel to each other and are located in the same lane section. The length of the bedding borehole should cover the coal seam area that needs to be detected as much as possible.

[0027] ②Acoustic detection: such as Figure 2 As shown in the figure, a time domain finite difference numerical model was constructed using MATLAB software. The longitudinal wave velocity in the coal seam area was set to 2000 m / s, and the longitudinal wave velocity in the roof and floor rock layers was set to 5000 m / s. Reflection acoustic imaging instruments were arranged in two bedding boreholes, and both emitted acoustic waves toward the coal seam. The frequency of the excited acoustic wave signal was between 1 kHz and 15 kHz. The acoustic wave was reflected by the coal-rock interface and collected by the receiving end of the instrument. Figure 3 As shown, the instrument is gradually moved from the borehole mouth to the bottom of the bed, completing the detection process of two bedholes and obtaining full-wave reflected wave signal data from the upper and lower interfaces of the coal seam. The reflected acoustic wave imaging instrument is cylindrical and consists of a transmitter, a receiver, and a sound insulator connected coaxially between them. Both the transmitter and receiver are made of piezoelectric ceramics, and they stimulate medium- and high-frequency acoustic signals through the piezoelectric effect. The following requirements must also be met: 1. The overall circuit design and power supply of the instrument must meet the intrinsic safety requirements for use in underground coal mines. 2. The diameter of the coal seam borehole is generally around 100 mm. To facilitate detection within the borehole, the instrument needs to be designed with a small diameter (70-80 mm). 3. Because underground detection of a single hole only requires detection within a range of 3-10 meters around the hole, and the underground tunnels are confined and operational, the distance between the transmitter and receiver needs to be shortened, and the instrument needs to be designed with a short source distance.

[0028] When performing in-bedding borehole detection, the instrument strives to achieve close contact with the borehole wall. This is because when the instrument source distance is short, Stoneley waves and reflected longitudinal waves may overlap, making signal separation difficult. Boreholes in coal mines are typically shallow, typically only a few to a dozen meters deep, allowing construction workers to adjust the instrument position directly underground. Therefore, when drilling underground, the instrument is closely aligned with the borehole wall as much as possible, allowing the sound waves to penetrate the formation directly as elastic waves, bypassing the aquifer. This prevents interference between Stoneley waves and reflected longitudinal waves in the full-wave signal at short source distances. If this close contact condition is not met during on-site construction, the borehole is first filled with fluid water. The transmitting source excites a monopolar longitudinal wave signal in the fluid water, which propagates as a pressure wave. Upon reaching the interface between the borehole and the formation, part of the pressure wave is converted into an elastic wave that is emitted into the surrounding formation. At this point, the received full-wave signal contains Stoneley waves, requiring targeted extraction of the reflected longitudinal wave during data inversion.

[0029] ③ Construct two-dimensional imaging slices: process the full-wave signal data of the reflected wave obtained in step ②, and integrate the imaging results of the upper and lower interfaces of the coal seam to obtain a two-dimensional imaging slice of the current coal seam area. Figure 4 As shown in the figure, the reflection wave full-wave signal data processing process is as follows: first, the transmission wave data at different depth positions in the same bedding borehole are classified according to the combination of common source distance and common center point, and then the direct wave suppression, wave field separation, reflection wave enhancement and offset imaging are performed to obtain the coal seam geological structure interface imaging at different positions in the same bedding borehole. After performing the above processing on two bedding boreholes respectively, the imaging results of the upper and lower interfaces of the coal seam are obtained.

[0030] ④ Construct a 3D geological structure model of the coal seam: determine the next bed drill hole position in the high-level and low-level lanes along the coal seam strike, with the spacing between two adjacent bed drill holes along the coal seam strike being 6 to 10 m; and repeat steps ① to ③ to obtain a 2D imaging slice of the coal seam area at that position; repeating this process can obtain 2D imaging slices at different positions along the coal seam strike, and after combining them, a 3D geological structure model of the coal seam is constructed. Figure 5 As shown, specifically: the upper interface imaging and lower interface imaging of the coal seam obtained by drilling along the layer are combined to obtain a two-dimensional imaging slice of the coal seam, and the geological interface imaging around different boreholes is combined according to the position coordinates to obtain the geological structure interface imaging slice of the coal seam; the geological structure interface imaging slices of the coal seam obtained by reflecting acoustic wave imaging at different drilling sites are combined to finally construct a three-dimensional geological structure model of the coal seam.

[0031] ⑤ Determine geological structure: Based on the 3D geological structure model of the coal seam, determine the small geological structures (faults, folds, coal seam dip change zones, coal seam thickness change zones, collapse columns, etc.) in the coal seam, and mark and warn potential high-dynamic disaster risk areas that may induce coal and gas outbursts, so as to guide subsequent coal seam mining. Specifically, use the 3D geological structure model of the coal seam to generate the corresponding model in Rhino software, and then import it into the numerical simulation software. Specifically, build a 3D geological structure model of the coal seam in Rhino software. Figure 7 As shown in the figure, the model is meshed and exported as dxf format or stl format, and then imported into COMSOL software for finite element method simulation calculation; or it can be exported as f3grid format and then imported into Flac3D software for finite difference method simulation calculation, so as to calculate the volume stress distribution of the coal seam working face and identify the high stress area in the coal seam. The identification process is as follows: import the three-dimensional model into the numerical simulation software, give the corresponding boundary conditions, and correct the model boundary conditions in combination with the measured ground stress. According to the measured core data, the geomechanical properties of the model are assigned, and then the volume stress distribution of each area at static state and during tunnel excavation is calculated by solid mechanics equations as shown below. Figure 8 As shown in Figure 2, the volume stress is the sum of the first principal stress, the second principal stress and the third principal stress. According to the volume stress distribution of the coal seam, the stress average value σ is calculated, and 1.5σ is taken as the stress threshold.

[0032] Based on the distribution of high-stress areas, coal seam working faces are divided into high-dynamic disaster risk zones. The specific classification criteria are as follows: when the stress value in the working face area exceeds the stress threshold, the area is identified as a high-stress area and determined to be a high-dynamic disaster risk zone. In addition, if the rate of change of stress value in a certain area exceeds 60%, the area is also identified as a high-dynamic disaster risk zone. This will further provide data guidance for subsequent safe coal seam mining.

[0033] In addition, after the small geological structure is determined based on the 3D geological structure model, the reflected acoustic wave imaging of the through-layer drilling is used for further verification. A group of through-layer drilling holes (2-1#~2-7#) are constructed upward at different angles in the floor roadway below the coal seam area. The through-layer drilling is carried out to the target coal seam area where the small geological structure is determined, such as Figure 6 As shown; the number and angle of the through-layer drill holes are determined according to the actual coal seam area; a reflection acoustic wave imaging instrument is arranged in each through-layer drill hole, and the instrument is pushed gradually from the hole mouth to the bottom of the through-layer drill hole to obtain the reflection acoustic wave imaging data of the geological structure interface within 3 to 5 meters around each through-layer drill hole; the reflection acoustic wave imaging results of the through-layer drill holes are compared and verified with the reflection acoustic wave imaging results of the bedding drill holes to improve the detection accuracy of small geological structures.

[0034] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A method for coal seam microstructure imaging and stress inversion based on borehole acoustic wave remote detection, characterized in that: The following steps are involved: ① Arrangement of bedding boreholes: In the high and low lanes on one side of the coal seam, construct one bedding borehole each from the high and low lanes in the roof and floor rock layers along the coal seam dip, and the two bedding boreholes are parallel to each other and located in the same lane cross section; ② Acoustic wave detection: Reflection acoustic wave imaging instruments are placed in two parallel-bedding boreholes, each of which transmits acoustic waves toward the coal seam. The acoustic waves are reflected by the coal-rock interface and collected by the instrument's receiving end. The instrument is gradually moved from the borehole mouth to the bottom of the parallel-bedding borehole to complete the detection process of the two parallel-bedding boreholes, obtaining full-wave signal data of the reflected waves at the upper and lower interfaces of the coal seam. ③ Constructing a two-dimensional imaging slice: Processing the full-wave signal data of the reflected wave obtained in step ②, integrating the imaging results of the upper and lower interfaces of the coal seam, and obtaining a two-dimensional imaging slice of the coal seam area at the current location; ④ Construct a 3D geological structure model of the coal seam: Determine the next bedding drill hole location in the high-level and low-level lanes along the coal seam strike, and repeat steps ① to ③ to obtain a 2D imaging slice of the coal seam area at that location. Repeat this process to obtain 2D imaging slices at different locations along the coal seam strike. After combining these slices, a 3D geological structure model of the coal seam is constructed. ⑤ Determine geological structure: Based on the three-dimensional geological structure model of the coal seam, determine the small geological structures existing in the coal seam, and identify high-dynamic disaster risk areas that may potentially induce coal and gas outbursts to guide subsequent coal seam mining.

2. The method for coal seam microstructure imaging and stress inversion based on borehole acoustic wave remote detection according to claim 1 is characterized in that: After the small geological structure is determined according to the three-dimensional geological structure model in step ⑤, reflection acoustic wave imaging of through-layer drilling is used for further verification. A group of through-layer drilling holes are constructed upward at different angles in the bottom roadway below the coal seam area, so that the through-layer drilling is constructed to the target coal seam area where the small geological structure is determined to exist; a reflection acoustic wave imaging instrument is arranged in each through-layer drilling hole, and the instrument is pushed gradually from the hole mouth of the through-layer drilling hole to the bottom of the hole to obtain reflection acoustic wave imaging data of the geological structure interface within 3 to 5 meters around each through-layer drilling hole; the reflection acoustic wave imaging results of the through-layer drilling hole are compared and verified with the reflection acoustic wave imaging results of the bedding drilling hole to improve the detection accuracy of small geological structures.

3. The method for coal seam microstructure imaging and stress inversion based on borehole acoustic wave remote detection according to claim 1 is characterized in that: The step ⑤ of identifying the high-dynamic disaster risk areas is specifically as follows: using the three-dimensional geological structure model of the coal seam, generating a corresponding model in the Rhino software, and then importing it into the numerical simulation software to calculate the volume stress distribution of the coal seam working face and identify the high-stress areas in the coal seam; and dividing the coal seam working face into high-dynamic disaster risk areas according to the distribution of the high-stress areas.

4. The method for coal seam microstructure imaging and stress inversion based on borehole acoustic wave remote detection according to claim 1 is characterized in that: The reflected acoustic wave imaging instrument is cylindrical and consists of a transmitter, a receiver and a sound insulator coaxially connected therebetween. Both the transmitter and the receiver are made of piezoelectric ceramics and stimulate medium and high frequency acoustic wave signals through the piezoelectric effect.

5. The method for coal seam microstructure imaging and stress inversion based on borehole acoustic wave remote detection according to claim 1 is characterized in that: The number and angle of the through-layer drill holes are determined according to the actual coal seam area; the spacing between two adjacent through-layer drill holes along the coal seam is 6 to 10 meters.

6. The method for coal seam microstructure imaging and stress inversion based on borehole acoustic wave remote detection according to claim 1, characterized in that: The process of processing the reflected wave full-wave signal data in step ③ is as follows: first, the transmitted wave data at different depth positions in the same bedding borehole are classified according to the combination of common source distance and common center point, and then the coal seam geological structure interface imaging at different positions in the same bedding borehole is obtained through direct wave suppression, wave field separation, reflected wave enhancement and offset imaging. After performing the above processing on the two bedding boreholes respectively, the imaging results of the upper and lower interfaces of the coal seam are obtained.

7. The method for coal seam microstructure imaging and stress inversion based on borehole acoustic wave remote detection according to claim 3 is characterized in that: Generate a model in Rhino software and import it into the numerical simulation software. Specifically, after building the three-dimensional geological structure model of the coal seam in Rhino software, mesh the model and export it in dxf format or stl format, and then import it into COMSOL software for finite element method simulation calculation; or choose to export it in f3grid format, and then import it into Flac3D software for finite difference method simulation calculation.

8. The method for coal seam microstructure imaging and stress inversion based on borehole acoustic wave remote detection according to claim 3 is characterized in that: The method for identifying high-stress areas in a coal seam specifically includes: importing a three-dimensional model into numerical simulation software, assigning corresponding boundary conditions, and correcting the model boundary conditions in combination with measured ground stress; assigning values to the model's geomechanical properties based on measured core data; and then calculating the volume stress distribution of each region at rest and during tunneling using solid mechanics equations, where the volume stress is the sum of the first principal stress, the second principal stress, and the third principal stress; and calculating the stress average value σ based on the volume stress distribution of the coal seam, taking 1.5σ as the stress threshold.

9. The method for coal seam microstructure imaging and stress inversion based on borehole acoustic wave remote detection according to claim 8, characterized in that: The specific classification criteria for the high-dynamic disaster risk area are as follows: when the stress value in the working face area exceeds the stress threshold, the area is identified as a high-stress area and is determined to be a high-dynamic disaster risk area; in addition, if the stress value change rate of a certain area exceeds 60%, the area is also identified as a high-dynamic disaster risk area.

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