A microseismic positioning method based on inversion results of blast seismic source wave velocity CT

Abstract

The application discloses a microseismic positioning method based on blasting seismic source wave velocity CT inversion results, first, a plurality of microseismic sensors are arranged in the crossheading on both sides of a working face to be mined, roof pre-splitting blasting holes are arranged between every two adjacent microseismic sensors; then, roof pre-splitting blasting is carried out on the working face to be mined, and a seismic source generated by pre-splitting blasting is taken as an active source to carry out vibration wave CT inversion, so that the wave velocity distribution of the working face to be mined is determined, and the method has high accuracy; microseismic information generated in the production process of the working face is recorded, including the microseismic waveform and P-wave arrival time data received by each microseismic sensor; then, a displacement-wave velocity-time equation group is established, the vibration wave velocity CT inversion result is brought into the equation group, and the positioning result of each sensor combination is solved, the positioning coordinates are solved for multiple times, the abnormal positioning values are eliminated, the central coordinates are taken as the final coordinate points, the positioning error is further reduced, and the microseismic positioning precision is ensured.

Description

Technical Field

[0001] This invention relates to a microseismic location method based on CT inversion results of blast source wave velocity, belonging to the field of coal mining and coal mine safety monitoring technology. Background Technology

[0002] With the depletion of shallow, high-quality coal resources, deep mining is an inevitable trend. However, deep rock mining disrupts the initial stability of the rock mass, causing instability and releasing a large amount of elastic energy, which is transmitted outward in the form of seismic waves. Microseismic monitoring, based on seismology, evaluates the stability of underground rock mass structures by analyzing low-frequency, high-energy seismic waves generated by the deformation and failure of rock masses during underground engineering operations. It is currently widely used in the intelligent monitoring of dynamic disasters such as mine rockbursts, rock bursts, and water inrushes. Microseismic monitoring technology involves deploying microseismic sensors in the underground detection area to receive seismic wave signals generated by coal and rock mass fracturing. Corresponding data analysis software is used to identify, denoise, and mark the arrival times of the acquired seismic wave signals. Then, parameters such as the location, time of occurrence, and energy of the seismic source are obtained by inversion using a corresponding wave velocity model. However, most commonly used wave velocity models are hypothetical function models. Underground rock strata structures are influenced by geological structures and sedimentary environments, and are generally heterogeneous. Using hypothetical function models to locate microseismic signals results in significant errors. Therefore, it is urgent to determine a known wave velocity model for microseismic information localization in order to improve the accuracy of microseismic location.

[0003] Seismic wave CT inversion technology inverts the wave velocity distribution along the propagation path based on the distance between the seismic source and the sensor, as well as the initial motion and travel time of the seismic wave. If there are enough seismic sources to form an envelope over the detection area, the wave velocity distribution within the detection area can be analyzed, which can meet the requirements well. However, due to the existence of wave velocity inversion errors, using a known wave velocity model to solve for microseismic location will still introduce certain errors, especially when there are too many microseismic sensors, which may result in no solution or multiple solutions.

[0004] Therefore, one of the research directions in this industry is to provide a new method that can accurately determine the wave velocity distribution in the detection area and solve the positioning coordinates multiple times to ensure the accuracy of microseismic positioning. Summary of the Invention

[0005] To address the problems existing in the prior art, this invention provides a microseismic location method based on CT inversion results of blast source wave velocity. This method can accurately determine the wave velocity distribution in the detection area and solve the location coordinates multiple times. By eliminating abnormal location values, the center coordinates are determined as the final coordinate point, further reducing the location error and ensuring the accuracy of microseismic location.

[0006] To achieve the above objectives, the technical solution adopted by this invention is: a microseismic location method based on CT inversion results of blast source wave velocity, the specific steps of which are as follows:

[0007] S1. Multiple micro-vibration sensors are arranged in the roadways on both sides of the working face to be mined. Each micro-vibration sensor is arranged in a row at equal intervals along the direction of the roadway in each roadway. A roof pre-splitting blasting hole is opened between two adjacent micro-vibration sensors to generate blasting vibration sources. After the arrangement is completed, the position coordinates of each micro-vibration sensor are recorded.

[0008] S2. Explosives are loaded into each pre-splitting blasting hole in the roof, and the roof is pre-splitting blasted in the working face to be mined. Then, the blasting source generated by the pre-splitting blast is used as the active source to perform vibration wave CT inversion to determine the wave velocity distribution of the working face to be mined.

[0009] S3. Record the micro-vibration information generated during the production process at the working face, including the micro-vibration waveforms received by each micro-vibration sensor and the data when the P-wave arrives;

[0010] S4. Establish a set of displacement-wave velocity-time equations, and substitute the seismic wave propagation velocities of each region determined by CT inversion obtained in step S2 and the microseismic data obtained in step S3 into the set of equations to solve the positioning results of each microseismic sensor combination. Then, use the standard deviation principle to remove abnormal values ​​and finally determine the location of the microseismic source.

[0011] Furthermore, in step S1, the distance between the pre-splitting blast hole and each of the two adjacent microseismic sensors is equal.

[0012] Furthermore, the determination of the wave velocity distribution of the working face to be mined in step S2 specifically involves:

[0013] ① Select the waveform file of the blast shock wave and perform P-wave arrival time calibration;

[0014] ②Based on the distribution characteristics of the blasting sources, determine the size of the inversion model and perform mesh generation;

[0015] ③ Connect the blasting source and the micro-seismic sensor to form a network of ray paths for the propagation of vibration waves;

[0016] ④ Based on the actual blasting time and the arrival time of the P-wave received by the microseismic sensor, the wave velocity distribution of each grid on the propagation path is calculated by inversion.

[0017] ⑤ Finally, an interpolation algorithm is used to draw a cloud map of the vibration wave velocity distribution, determine the wave velocity distribution of the working face to be mined, and then obtain the vibration wave propagation velocity in each area.

[0018] Furthermore, step S4 specifically includes:

[0019] Let the coordinates of the microseismic source be (x0, y0, z0), the initiation time of the source be T0, and the initiation time recorded by each sensor be T. ci The displacement-wave velocity-time equations are established as follows:

[0020]

[0021] In the formula, D ci Let be the distance between the microseismic sensor i and the location (x0, y0, z0) of the microseismic source; (x ci ,y ci ,z ci Ti represents the position coordinates of the microseismic sensor i; T0 represents the initiation time of the seismic source. ci V represents the onset time recorded by the micro-seismic sensor i; ci Let be the wave velocity along the propagation path between the microseismic source and the microseismic sensor i, which is related to the position of the microseismic source (x0, y0, z0) by the function f(x0, y0, z0).

[0022] From the above formula, we obtain that the source coordinate equations have four unknowns (x0, y0, z0, T0), requiring four functions to solve. Therefore, the required number of microseismic sensors j is at least 4. However, as n increases, errors or no solutions may appear in the microseismic source coordinates (x0, y0, z0, T0). Therefore, iterative solutions are needed for the microseismic source coordinates (x0, y0, z0, T0), i.e., for... Solve using one of these methods;

[0023] To further reduce positioning errors, outliers are eliminated using the standard deviation principle of coordinate points (i.e., the 3σ principle). The specific steps are as follows:

[0024] I. Calculate the average value of each positioning coordinate point:

[0025]

[0026] II. Calculate the standard deviation of each positioning coordinate point:

[0027]

[0028] III. Outlier values ​​are eliminated using the standard deviation principle. That is, any deviation between the positioning coordinates and the average positioning value is considered an outlier if it is greater than 3 times the standard deviation.

[0029]

[0030] IV. After removing outlier values, the average value is used to calculate the center coordinates of all positioning coordinates, which are then used as the final positioning coordinates to determine the location of each microseismic source.

[0031] Compared with existing technologies, this invention first arranges multiple microseismic sensors in the roadways on both sides of the working face to be mined, with pre-fracture blasting holes for the roof between adjacent microseismic sensors; then, pre-fracture blasting is performed on the roof of the working face to be mined, and the seismic source generated by the pre-fracture blasting is used as the active source for seismic wave CT inversion to determine the wave velocity distribution of the working face to be mined; next, the microseismic information generated during the working face production process is recorded, including the microseismic waveforms received by each microseismic sensor and the data on the arrival time of the P-wave; finally, a displacement-wave velocity-time equation system is established, and the seismic wave velocity CT inversion results are substituted into the equation system to solve for the positioning results of each sensor combination, and outlier values ​​are eliminated using the standard deviation principle, finally determining the position coordinates of the microseismic source, thus ensuring the accuracy of microseismic positioning.

[0032] In summary, this invention utilizes microseismic events induced by pre-splitting blasting of the roof slab for CT inversion of seismic wave velocity. It eliminates the need for additional artificial excitation sources, resulting in low costs. It can not only accurately determine the wave velocity distribution in the detection area, but also solve the positioning coordinates multiple times. By eliminating abnormal positioning values, the center coordinates are determined as the final coordinate point, further reducing positioning errors and ensuring the accuracy of microseismic positioning. It has wide applicability and strong application value. Attached Figure Description

[0033] Figure 1 This is an overall flowchart of the present invention;

[0034] Figure 2 This is a ray network diagram showing the roof blasting vibration source and micro-vibration sensor in an embodiment of the present invention;

[0035] Figure 3 This is a CT inversion image of the vibration wave velocity from the roof blasting source in an embodiment of the present invention;

[0036] Figure 4 This is a diagram showing the deployment of microseismic sensors and the propagation path of microseismic events according to an embodiment of the present invention.

[0037] Figure 5 This is a schematic diagram illustrating the identification of microseismic events and the removal of abnormal data by the microseismic sensor provided in an embodiment of the present invention. Detailed Implementation

[0038] The present invention will be further described below.

[0039] The 802 working face of a certain coal mine is a working face to be mined. The method of this invention is used to determine the wave velocity distribution in this working face area and to locate the microseismic source of the pre-splitting blasting ultrasonic waves. Figure 1 As shown, the specific steps are as follows:

[0040] S1. Multiple micro-vibration sensors are arranged in the roadways on both sides of the 802 working face. Within each roadway, the micro-vibration sensors are arranged in a row at equal intervals along the roadway direction. Pre-splitting blasting holes are drilled between adjacent micro-vibration sensors, with each pre-splitting blasting hole equidistant from the adjacent micro-vibration sensor, to generate blasting vibration sources. Figure 2 As shown; after deployment, record the position coordinates of each microseismic sensor;

[0041] S2. Explosives are loaded into each pre-splitting blast hole in the roof, and pre-splitting blasting is performed on the 802 working face. Then, the blasting vibration source generated by the pre-splitting blast is used as the active source for seismic wave CT inversion to determine the wave velocity distribution of the 802 working face. Figure 3 As shown, specifically:

[0042] ① Select the waveform file of the blast shock wave and perform P-wave arrival time calibration;

[0043] ②Based on the distribution characteristics of the blasting sources, determine the size of the inversion model and perform mesh generation;

[0044] ③ Connect the blasting source and the micro-seismic sensor to form a network of ray paths for the propagation of vibration waves;

[0045] ④ Based on the actual blasting time and the arrival time of the P-wave received by the microseismic sensor, the wave velocity distribution of each grid on the propagation path is calculated by inversion.

[0046] ⑤ Finally, an interpolation algorithm is used to draw a cloud map of the vibration wave velocity distribution, determine the wave velocity distribution of the 802 working surface, and then obtain the vibration wave propagation velocity in each region.

[0047] S3. Record the micro-vibration information generated during the production process of the 802 working face, including the micro-vibration waveforms received by each micro-vibration sensor and the data when the P-wave arrives;

[0048] S4. Let the coordinates of the microseismic source be (x0, y0, z0), the initiation time of the source be T0, and the initiation time recorded by each sensor be T. ci ,like Figure 4 The displacement-wave velocity-time equation system is established as follows:

[0049]

[0050] In the formula, D ci Let be the distance between the microseismic sensor i and the location (x0, y0, z0) of the microseismic source; (x ci ,y ci ,z ci Ti represents the position coordinates of the microseismic sensor i; T0 represents the initiation time of the seismic source. ci V represents the onset time recorded by the micro-seismic sensor i; ciLet be the wave velocity along the propagation path between the microseismic source and the microseismic sensor i, which is related to the position of the microseismic source (x0, y0, z0) by the function f(x0, y0, z0).

[0051] From the above formula, we obtain that the source coordinate equations have four unknowns (x0, y0, z0, T0), requiring four functions to solve. Therefore, the required number of microseismic sensors j is at least 4. However, as n increases, errors or no solutions may appear in the microseismic source coordinates (x0, y0, z0, T0). Therefore, iterative solutions are needed for the microseismic source coordinates (x0, y0, z0, T0), i.e., for... Solve using one of these methods;

[0052] After solving the above problem, we can obtain the following results. The positioning results are used to further reduce positioning errors. Figure 5 This diagram illustrates the identification of microseismic events and the removal of abnormal data using microseismic sensors. Four microseismic sensors are sufficient to determine the coordinates of a microseismic source. As the number of microseismic sensors increases, some error will occur in the microseismic location. After removing abnormal data, the center coordinates of the remaining location points are calculated to obtain the final location coordinates. The specific steps for removing abnormal values ​​are as follows:

[0053] I. Calculate the average value of each positioning coordinate point:

[0054]

[0055] II. Calculate the standard deviation of each positioning coordinate point:

[0056]

[0057] III. Outlier values ​​are eliminated using the standard deviation principle. That is, any deviation between the positioning coordinates and the average positioning value is considered an outlier if it is greater than 3 times the standard deviation.

[0058]

[0059] IV. After removing outlier values, the average value is used to calculate the center coordinates of all positioning coordinates, which are then used as the final positioning coordinates to determine the location of each microseismic source.

[0060] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A microseismic location method based on CT inversion results of blast source wave velocity, characterized in that, The specific steps are as follows: S1. Multiple micro-vibration sensors are arranged in the roadways on both sides of the working face to be mined. Each micro-vibration sensor is arranged in a row at equal intervals along the direction of the roadway in each roadway. A roof pre-splitting blasting hole is opened between two adjacent micro-vibration sensors to generate blasting vibration sources. After the arrangement is completed, the position coordinates of each micro-vibration sensor are recorded. S2. Explosives are loaded into each pre-splitting blasting hole in the roof, and the roof is pre-splitting blasted in the working face to be mined. Then, the blasting source generated by the pre-splitting blast is used as the active source to perform vibration wave CT inversion to determine the wave velocity distribution of the working face to be mined. S3. Record the micro-vibration information generated during the production process at the working face, including the micro-vibration waveforms received by each micro-vibration sensor and the data when the P-wave arrives; S4. Establish a displacement-wave velocity-time equation system, and substitute the seismic wave propagation velocities of each region determined by CT inversion obtained in step S2 and the microseismic data obtained in step S3 into the equation system to solve for the positioning results of each microseismic sensor combination. Then, use the standard deviation principle to eliminate outlier values, and finally determine the location of the microseismic source. Specifically: Let the coordinates of the microseismic source be (x0, y0, z0), the initiation time of the source be T0, and the initiation time recorded by each sensor be T. ci The displacement-wave velocity-time equations are established as follows: ； In the formula, D ci Let be the distance between the microseismic sensor i and the location (x0, y0, z0) of the microseismic source; (x ci , y ci , z ci Ti represents the position coordinates of the microseismic sensor i; T0 represents the initiation time of the seismic source. ci V represents the onset time recorded by the micro-seismic sensor i; ci Let be the wave velocity along the propagation path between the microseismic source and the microseismic sensor i, which is related to the position of the microseismic source (x0, y0, z0) by the function f(x0, y0, z0). From the above formula, the source coordinate equations have four unknowns (x0, y0, z0, T0), requiring four functions to solve, meaning the required number of microseismic sensors j is at least 4. However, as n increases, errors or no solutions will appear for the microseismic source coordinates (x0, y0, z0, T0). Therefore, iterative solutions are needed for the microseismic source coordinates (x0, y0, z0, T0), i.e., for... Solve using one of these methods; To further reduce positioning errors, outliers are eliminated using the standard deviation of coordinate points. The specific steps are as follows: I. Calculate the average value of each positioning coordinate point: ； II. Calculate the standard deviation of each positioning coordinate point: ； III. Outlier values ​​are eliminated using the standard deviation principle. That is, any deviation between the positioning coordinates and the average positioning value is considered an outlier if it is greater than 3 times the standard deviation. ； IV. After removing outlier values, the average value is used to calculate the center coordinates of all positioning coordinates, which are then used as the final positioning coordinates to determine the location of each microseismic source.

2. The microseismic location method based on CT inversion results of blast source wave velocity according to claim 1, characterized in that, In step S1, the distance between the pre-splitting blast hole and each of the two adjacent microseismic sensors is equal.

3. The microseismic location method based on CT inversion results of blast source wave velocity according to claim 1, characterized in that, The specific steps for determining the wave velocity distribution of the working face to be mined in step S2 are as follows: ① Select the waveform file of the blast shock wave and perform P-wave arrival time calibration; ②Based on the distribution characteristics of the blasting sources, determine the size of the inversion model and perform mesh generation; ③ Connect the blasting source and the micro-seismic sensor to form a network of ray paths for the propagation of vibration waves; ④ Based on the actual blasting time and the arrival time of the P-wave received by the microseismic sensor, the wave velocity distribution of each grid on the propagation path is calculated by inversion. ⑤ Finally, an interpolation algorithm is used to draw a cloud map of the vibration wave velocity distribution, determine the wave velocity distribution of the working face to be mined, and then obtain the vibration wave propagation velocity in each area.

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