A method for deep mining wave velocity tomography and ground pressure monitoring based on a three-dimensional array

Abstract

This invention provides a method for deep mining wave velocity tomography and ground pressure monitoring based on a three-dimensional array, belonging to the field of wave velocity tomography technology. First, the boundary of the monitoring area is determined, hydrogeological data within the monitoring area is collected and integrated, and a stratigraphic wave velocity model is constructed based on the wave propagation speed in different media. A three-dimensional monitoring network is established to collect blasting construction information, recording the spatial coordinates, time, and charge amount of blasting events, and constructing a blasting event database. The waveform data collected by the detector is matched with the blasting events in the database. The theoretical arrival time of the wave is predicted using the stratigraphic wave velocity model, compared with the actual observation time of the detector, and the time residual is calculated. The stratigraphic wave velocity model parameters are adjusted based on the time residual, and a high-precision stratigraphic wave velocity model is output based on the optimized parameters to support accurate location and matching of blasting events. Finally, the stability of the stratigraphic ground pressure is analyzed by combining wave velocity changes with calculated ground pressure change data.

Description

Technical Field

[0001] This invention relates to the field of wave velocity tomography technology, and in particular to a method for deep mining wave velocity tomography and ground pressure monitoring based on a three-dimensional array. Background Technology

[0002] As mining depths increase, traditional geophysical methods alone are insufficient to accurately detect geological anomalies such as goafs, fault structures, and aquifers. Wave velocity tomography, however, can dynamically reveal the internal structure of strata through three-dimensional inversion, providing transparency of hydrogeological conditions. Furthermore, the wave velocity images obtained from the inversion can reflect the distribution of ground pressure within the surrounding rock, thus providing early warnings of potential disasters such as rock bursts and water inrushes, significantly improving construction safety.

[0003] Currently, equipment capable of performing wave velocity tomography employs a linear, dense array of seismographs on the surface. These seismographs lack interoperability, and the monitored depth depends entirely on the source intensity and the accuracy of the monitoring equipment. However, as the required depth of detection increases, high-frequency signals suffer severe attenuation within the strata and become unusable, while low-frequency signals also exhibit distortion and dissipation, failing to meet the required detection accuracy. Therefore, there is an urgent need to develop a wave velocity tomography system with greater depth and higher accuracy. This invention addresses this problem by proposing a three-dimensional array-based mining wave velocity tomography and ground pressure monitoring system. Furthermore, it utilizes machine learning principles, employing supervised learning to iterate the strata model multiple times, ultimately achieving a refined model of the strata and using this model to dynamically monitor ground pressure. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention provides a method for deep mining wave velocity tomography and ground pressure monitoring based on a three-dimensional array, aiming to achieve refined exploration of strata to enable dynamic monitoring of deep ground pressure.

[0005] A method for deep mining wave velocity tomography and ground pressure monitoring based on a three-dimensional array includes the following steps:

[0006] Step 1: Determine the boundaries of the monitoring area, specifically including the surface projection area and monitoring depth;

[0007] Step 2: Collect and integrate hydrogeological data within the monitoring area, including the distribution of aquifers, lithological detection results, and borehole core images, and construct a formation wave velocity model based on the wave propagation speed in different media;

[0008] The formation wave velocity model specifically assigns values ​​to the three-dimensional map of lithological detection results based on the different propagation speeds of waves in different media, and modifies the assigned values ​​in combination with the distribution of aquifers and the structural surfaces and fault occurrences reflected in the borehole core images;

[0009] Step 3: Deploy dense linear geophone arrays and mobile geophone stations on the surface and underground to form a three-dimensional monitoring network;

[0010] Specifically, linear geophone arrays are arranged at 5m intervals on the ground surface and at locations of stress concentration underground; the sampling frequency of the geophones deployed on the ground surface is set to 5Hz, and the sampling frequency of the geophones deployed underground is set to 50Hz; the location of the mobile geophone stations is not fixed.

[0011] The stress concentration locations are the excavation faces of roadways and shafts, as well as areas with dense faults or fractured lithology within the construction operation range; the geophone stations are evenly distributed along the construction excavation direction;

[0012] Step 4: Collect blasting construction information, record the spatial coordinates, time, and charge amount of blasting events, and build a blasting event database;

[0013] Step 5: Match the waveform data collected by the detector with the blasting events in the blasting event database;

[0014] Specifically, the process involves: first, performing wavelet transform noise reduction on the waveform data and then automatically picking up the waveform based on neural network recognition; then comparing the waveform data with the PEER waveform template library to filter out suspected blasting events; and finally, associating the data with the blasting event library.

[0015] Step 6: Predict the theoretical arrival time of the wave using the formation wave velocity model established in Step 2, compare it with the actual observation time of the detector, and calculate the time residual.

[0016] Step 7: Determine whether the time residual reaches the set residual threshold; if the time residual is greater than the residual threshold, proceed to step 8; if the time residual is less than the residual threshold, proceed to step 9.

[0017] Step 8: Adjust the formation wave velocity model parameters based on the time residual, return to step 6 for iterative optimization, until the time residual is less than the residual threshold;

[0018] In step 8, if multiple solutions are encountered, redundant solutions are eliminated by deploying mobile geophone stations to perform local high-precision modeling.

[0019] The aforementioned multiple solutions problem specifically refers to the following: the same waveform data corresponds to multiple geological structure models. When generating the final image, a local high-precision model is performed by combining the mobile geophone station. When monitoring the geological conditions of the monitoring area, a borehole sampling method is further used for joint verification. The deployment location of the mobile geophone station is determined according to the parameters of the formation wave velocity model, and is specifically set in the abnormally low velocity zone in the formation wave velocity model.

[0020] Step 9: Output a high-precision formation wave velocity model based on the optimized parameters to support accurate location and matching of blasting events;

[0021] Step 10: Calculate the ground pressure distribution based on the high-precision formation wave velocity model and continuously collect waveform data to correct the high-precision formation wave velocity model in real time;

[0022] The formula for calculating the ground pressure distribution is the Elksen formula, as follows:

[0023] V p =V p0 +aσ+bσ 2 ;

[0024] Where V p V is the longitudinal wave velocity, a and b are constants related to rock properties, σ is the ground pressure, and V is the longitudinal wave velocity. p0 It is the longitudinal wave velocity under no pressure, pores, and cracks;

[0025] Step 11: Combine wave velocity changes with the calculated ground pressure changes to analyze the formation ground pressure stability; the stability includes whether ground pressure fluctuations occur, whether the ground pressure is greater than the elastic-plastic deformation boundary of the surrounding rock, and output a ground pressure monitoring report for decision-making reference.

[0026] The beneficial effects of adopting the above technical solution are as follows:

[0027] This invention provides a method for deep mining wave velocity tomography and ground pressure monitoring based on a three-dimensional array, capable of providing detection data support for deep underground engineering development exceeding 800m in depth. Existing technologies all deploy geophone stations on the surface, relying on continuously improving the monitoring accuracy of the geophones to increase the detection depth. However, waves, especially high-frequency waves, attenuate rapidly in the strata, resulting in the loss of a large amount of data. This technical solution innovatively introduces a three-dimensional geophone array deployment method, breaking through the accuracy and detection depth barriers caused by traditional deployment methods. It utilizes high-frequency wave information from the wave signals monitored by underground geophone stations to effectively supplement the overall stratum wave velocity tomography, improving the clarity of deep stratum wave velocity tomography by 10% to 20%. Attached Figure Description

[0028] Figure 1 This is a flowchart of the deep mining wave velocity tomography and ground pressure monitoring method of the present invention;

[0029] Figure 2 This is a schematic diagram of the underground array layout of the present invention;

[0030] In the figure, (a) is a schematic diagram of the tunnel layout method, and (b) is a schematic diagram of the shaft layout method.

[0031] Figure 3This is a result obtained by stereoscopic array wave velocity tomography in Embodiment 1 of the present invention;

[0032] Wherein (a) - waveform data in Example 1, (b) - ground pressure waveform image in Example 1;

[0033] Figure 4 This is a result obtained by using stereoscopic array wave velocity tomography in Embodiment 2 of the present invention;

[0034] Wherein (a) - waveform data in Example 2, (b) - ground pressure waveform image in Example 2. Detailed Implementation

[0035] The specific embodiments of the present invention will be described in further detail below with reference to the accompanying drawings and examples. The following examples are for illustrative purposes only and are not intended to limit the scope of the invention.

[0036] A method for deep mining wave velocity tomography and ground pressure monitoring based on a three-dimensional array, such as... Figure 1 As shown, it includes the following steps:

[0037] Step 1: Determine the boundaries of the monitoring area, specifically including the surface projection area and monitoring depth;

[0038] Step 2: Collect and integrate hydrogeological data within the monitoring area, including the distribution of aquifers, lithological detection results, and borehole core images, and construct a formation wave velocity model based on the wave propagation speed in different media;

[0039] The formation wave velocity model specifically assigns values ​​to the three-dimensional map of lithological detection results based on the different propagation speeds of waves in different media, and modifies the assigned values ​​in combination with the distribution of aquifers and the structural surfaces and fault occurrences reflected in the borehole core images;

[0040] Step 3: Deploy dense linear geophone arrays and mobile geophone stations on the surface and underground to form a three-dimensional monitoring network;

[0041] Specifically, linear geophone arrays are deployed at 5m intervals on the ground surface and at locations of stress concentration underground for localized high-precision imaging. The surface-mounted geophones are set to a sampling frequency of 5Hz to primarily acquire low-frequency waveform signals, while the underground geophones are set to a sampling frequency of 50Hz to acquire mid-to-high-frequency waveform signals. The mobile geophone stations are deployed in non-fixed locations to eliminate multiple or incorrect solutions in subsequent steps when ambiguity issues arise.

[0042] The stress concentration locations are the excavation faces of roadways and shafts, as well as areas with dense faults or fractured rock within the construction area; such as Figure 2As shown, the geophone stations are evenly arranged along the construction excavation direction; it is not required that all geophone stations be in a straight line, just find a suitable place to place them in the excavation direction, where (a) is a schematic diagram of the tunnel layout method and (b) is a schematic diagram of the shaft layout method.

[0043] Step 4: Collect blasting construction information, record the spatial coordinates, time, and charge amount of blasting events, and build a blasting event database;

[0044] Step 5: Match the waveform data collected by the detector with the blasting events in the blasting event database;

[0045] Specifically, the process involves: first, performing wavelet transform noise reduction on the waveform data and then automatically picking up the waveform based on neural network recognition; then, comparing the waveform data with the PEER waveform template library to filter out suspected blasting events, and finally associating the data with the blasting event library.

[0046] Step 6: Predict the theoretical arrival time of the wave using the formation wave velocity model established in Step 2, compare it with the actual observation time of the detector, and calculate the time residual.

[0047] Step 7: Determine if the time residual has reached the set residual threshold; the residual threshold is set according to the user's equipment performance and the accuracy requirements of the construction party. The residual threshold is generally set to 10. -5 If the time residual is greater than the residual threshold, proceed to step 8; if the time residual is less than the residual threshold, proceed to step 9.

[0048] Step 8: Adjust the formation wave velocity model parameters based on the time residual, return to step 6 for iterative optimization, until the time residual is less than the residual threshold;

[0049] In step 8, if multiple solutions are encountered, redundant solutions are eliminated by deploying mobile geophone stations to perform local high-precision modeling.

[0050] The aforementioned multiple-solution problem specifically refers to the fact that the same waveform data corresponds to multiple geological structure models. For example, a low-velocity anomaly can be interpreted as fractured water aquifers or loose sediments. Therefore, to avoid multiple or incorrect solutions, local high-precision modeling is performed using mobile geophone stations when generating the final image. Furthermore, borehole sampling is used for joint verification when monitoring the geological conditions of the monitoring area. The deployment location of the mobile geophone stations is determined based on the parameters of the formation wave velocity model, specifically set in the anomalous low-velocity zone within the formation wave velocity model.

[0051] Step 9: Output a high-precision formation wave velocity model based on the optimized parameters to support accurate location and matching of blasting events;

[0052] Step 10: Calculate the ground pressure distribution based on the high-precision formation wave velocity model and continuously collect waveform data. Correct the high-precision formation wave velocity model in real time to reflect changes in the real-time formation structure and ground pressure state.

[0053] The formula for calculating the ground pressure distribution is the Elksen formula, as follows:

[0054] V p =V p0 +aσ+bσ 2 ;

[0055] Where V p V is the longitudinal wave velocity, a and b are constants related to rock properties, σ is the ground pressure, and V is the longitudinal wave velocity. p0 It is the longitudinal wave velocity under no pressure, pores, and cracks; a, b, V p0 Determined based on the lithological detection results in step 2.

[0056] Step 11: Combine wave velocity changes with the calculated ground pressure changes to analyze the formation ground pressure stability; the stability includes whether ground pressure fluctuations occur, whether the ground pressure is greater than the elastic-plastic deformation boundary of the surrounding rock, and output a ground pressure monitoring report for decision-making reference.

[0057] Example 1:

[0058] Taking the measured results obtained by stereoscopic array wave velocity tomography in a gold mine in Shandong Province as an example, such as Figure 3 The image shown is a result obtained by stereoscopic array wave velocity tomography in Example 1; where (a) is the waveform data in Example 1 and (b) is the ground pressure waveform image in Example 1.

[0059] Example 2:

[0060] Taking the measured results obtained by stereoscopic array wave velocity tomography in a gold mine in Shandong Province as an example, such as Figure 4 The image shown is a result obtained by stereoscopic array wave velocity tomography in Example 2; where (a) is the waveform data in Example 2 and (b) is the ground pressure waveform image in Example 2.

[0061] Through Examples 1 and 2, the seismic source used was a blasting seismic source. It can be seen that the obtained ground pressure imaging effect can better conform to the law of the influence of mining process on the ground pressure of the strata. The imaging accuracy is high and the ground pressure boundary is clear, which is an improvement over the existing technology.

[0062] The above description is merely a preferred embodiment of this disclosure and an explanation of the technical principles employed. Those skilled in the art should understand that the scope of the invention involved in the embodiments of this disclosure is not limited to technical solutions formed by specific combinations of the above-described technical features, but should also cover other technical solutions formed by arbitrary combinations of the above-described technical features or their equivalents without departing from the above-described inventive concept. For example, technical solutions formed by substituting the above-described features with (but not limited to) technical features with similar functions disclosed in the embodiments of this disclosure.

Claims

1. A method for deep mining wave velocity tomography and ground pressure monitoring based on a three-dimensional array, characterized in that, Includes the following steps: Step 1: Determine the boundaries of the monitoring area, specifically including the surface projection area and monitoring depth; Step 2: Collect and integrate hydrogeological data within the monitoring area, and construct a stratigraphic wave velocity model based on the wave propagation speed in different media; Step 3: Deploy dense linear geophone arrays and mobile geophone stations on the surface and underground to form a three-dimensional monitoring network; Step 3 specifically involves: arranging linear geophone arrays at 5m intervals on the ground surface and arranging linear geophone arrays at locations of stress concentration underground; setting the sampling frequency of the geophones deployed on the ground surface to 5Hz and the sampling frequency of the geophones deployed underground to 50Hz; and the location of the mobile geophone stations is not fixed. Step 4: Collect blasting construction information, record the spatial coordinates, time, and charge amount of blasting events, and build a blasting event database; Step 5: Match the waveform data collected by the detector with the blasting events in the blasting event database; Step 6: Predict the theoretical arrival time of the wave using the formation wave velocity model established in Step 2, compare it with the actual observation time of the detector, and calculate the time residual. Step 7: Determine whether the time residual reaches the set residual threshold; if the time residual is greater than the residual threshold, proceed to step 8; if the time residual is less than the residual threshold, proceed to step 9. Step 8: Adjust the formation wave velocity model parameters based on the time residual, return to step 6 for iterative optimization, until the time residual is less than the residual threshold; Step 9: Output a high-precision formation wave velocity model based on the formation wave velocity model parameters to support accurate location and matching of blasting events; Step 10: Calculate the ground pressure distribution based on the high-precision formation wave velocity model and continuously collect waveform data to correct the high-precision formation wave velocity model in real time; Step 11: Combine wave velocity changes with the calculated ground pressure changes to analyze the formation's ground pressure stability; The stability includes whether ground pressure fluctuations occur, whether the ground pressure exceeds the elastic-plastic deformation boundary of the surrounding rock, and outputs a ground pressure monitoring report for decision-making reference.

2. The method for deep mining wave velocity tomography and ground pressure monitoring based on a three-dimensional array as described in claim 1, characterized in that, The hydrogeological data mentioned in step 2 includes the distribution of aquifers in the monitoring area, lithological detection results, and borehole core images.

3. The method for deep mining wave velocity tomography and ground pressure monitoring based on a three-dimensional array as described in claim 1, characterized in that, The stress concentration locations are the excavation faces of roadways and shafts, as well as areas with dense faults or fractured lithology within the construction operation range; the geophone stations are evenly distributed along the construction excavation direction.

4. The method for deep mining wave velocity tomography and ground pressure monitoring based on a three-dimensional array as described in claim 1, characterized in that, Step 5 specifically involves: first performing wavelet transform noise reduction on the waveform data and then automatically picking up the waveform based on neural network recognition, comparing it with the PEER waveform template library to filter out suspected blasting events, and then associating it with the blasting event library.

5. The method for deep mining wave velocity tomography and ground pressure monitoring based on a three-dimensional array according to claim 1, characterized in that, In step 8, if multiple solutions are encountered, redundant solutions are eliminated by arranging mobile detector stations to perform local high-precision modeling.

6. The method for deep mining wave velocity tomography and ground pressure monitoring based on a three-dimensional array according to claim 5, characterized in that, The aforementioned multiple solutions problem specifically refers to the following: the same waveform data corresponds to multiple geological structure models. When generating the final image, a local high-precision model is performed by combining a mobile geophone station. When monitoring the geological conditions of the monitoring area, a borehole sampling method is further used for joint verification. The deployment location of the mobile geophone station is determined according to the parameters of the formation wave velocity model, and is specifically set in the abnormally low velocity zone in the formation wave velocity model.

7. The method for deep mining wave velocity tomography and ground pressure monitoring based on a three-dimensional array as described in claim 1, characterized in that, The formula for calculating the ground pressure distribution in step 10 is the Elksen formula, as follows: V p =V p0 +aσ+bσ 2 ; Where V p V is the longitudinal wave velocity, a and b are constants related to rock properties, σ is the ground pressure, and V is the longitudinal wave velocity. p0 It is the longitudinal wave velocity under no pressure, pores, and cracks.

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