Micro-seismic outrange waveform reconstruction method based on multi-station joint calibration

Abstract

The invention discloses a micro-seismic outrange waveform reconstruction method based on multi-station joint calibration, and the method comprises the steps: firstly obtaining outrange sections and outrange stations corresponding to different micro-seismic events of each station, and then for the same micro-seismic event, selecting a station which does not generate outrange saturation as a reference station, and carrying out the calibration of the outrange waveform. Carrying out time alignment on a seismic phase time window of the reference station and a corresponding time period of the outrange station, and then calculating an equivalent attenuation coefficient corresponding to the micro-seismic event by adopting a multi-station joint inversion mode, so as to avoid the use of missing data; and finally, mapping the complete waveform amplitude of the reference station in the outrange section to the outrange station by using the equivalent attenuation coefficient to realize the real waveform amplitude of the outrange station in the outrange section, so that each station can obtain continuous microseismic waveforms in different microseismic events. Through the method, the physical consistency and availability of the outrange micro-seismic waveform are improved, and a reliable data basis is provided for micro-seismic energy evaluation, risk analysis and a subsequent intelligent early warning model.

Description

Technical Field

[0001] This invention belongs to the field of microseismic monitoring signal processing technology, and in particular relates to a method for microseismic overrange waveform reconstruction based on joint calibration of multiple stations. Background Technology

[0002] Microseismic monitoring technology, which simultaneously acquires elastic wave signals released during rock fracturing at multiple stations, has significant application value in safety monitoring and disaster early warning in coal mines, metal mines, and underground engineering. Because monitoring systems typically employ high-sensitivity sensors and fixed-gain acquisition links, when the energy of a microseismic event is large or the source location is close to the monitoring station, the recorded waveform amplitude can easily exceed the system's dynamic range (i.e., exceed the sensor's maximum range), resulting in over-range saturation. This leads to waveform amplitude clipping, loss of energy information, and further affects the analysis results such as phase identification, energy calculation, and source parameter inversion. Specifically, the appearance of over-range waveforms causes the clipping and loss of key amplitude information in the microseismic record, making it impossible to accurately obtain the true amplitude, envelope shape, and energy characteristics. It also destroys the original waveform morphology, thus affecting the accuracy of identifying P-waves, S-waves, and other phases. Furthermore, the event energy and magnitude calculation results based on amplitude or energy integrals are often significantly underestimated, further reducing the reliability of higher-order analysis results such as source parameter inversion, spectral analysis, and moment tensor inversion. Existing methods for processing over-range waveforms mostly rely on interpolation, empirical fitting, or single-station frequency domain repair, lacking clear propagation physical constraints, making it difficult to reliably recover the amplitude at each moment within the over-range segment.

[0003] Therefore, the research direction of this invention is to provide a new method for reconstructing microseismic waveforms over the range, which can reconstruct the waveform amplitude in the over-range section by time step, thereby significantly improving the physical consistency and usability of the over-range microseismic waveforms and providing a more reliable data foundation for microseismic energy assessment, hazard analysis and subsequent intelligent early warning models. Summary of the Invention

[0004] To address the problems of the existing technologies, this invention provides a microseismic overrange waveform reconstruction method based on multi-station joint calibration. This method utilizes complete records of the same microseismic event at reference stations where overrange did not occur, inverts the event-level equivalent attenuation coefficient within the seismic phase time window, and reconstructs the waveform amplitude in the overrange section time-by-time under the premise of time alignment. This significantly improves the physical consistency and usability of overrange microseismic waveforms without increasing hardware costs, providing a more reliable data foundation for microseismic energy assessment, hazard analysis, and subsequent intelligent early warning models.

[0005] To achieve the above objectives, the technical solution adopted by this invention is: a microseismic overrange waveform reconstruction method based on multi-station joint calibration, comprising the following steps: Step 1: Over-range waveform identification: The microseismic monitoring system collects waveform data from n stations over a period of time. When the waveform of a certain station reaches or exceeds the upper limit of the range of that station at continuous sampling points, the corresponding time segment is determined to be an over-range segment, thereby obtaining the over-range segments and over-range stations corresponding to different microseismic events.

[0006] Step 2: Reference Station Selection: Select the same microseismic event, and from the n stations participating in the microseismic event location, select the stations that did not experience over-range saturation during the acquisition process of that microseismic event as reference stations, according to Step 1; Let m be the number of stations that experienced over-range saturation, then the number of stations that did not experience over-range saturation is... One serves as a reference station.

[0007] Step 3: Determine the phase time window and align the time: Determine the phase time window of the microseismic event selected in Step 2 from the waveforms of each reference station, and align the waveforms of the over-range station and the reference station under the same phase of the microseismic event.

[0008] Step 4: Attenuation Coefficient Inversion: Within the same seismic phase time window, based on the complete waveform amplitude of each reference station, the propagation distance from the event to each station, and the instrument gain parameters, the equivalent attenuation coefficient corresponding to the microseismic event is calculated using a multi-station joint inversion method.

[0009] Step 5: Overrange Waveform Reconstruction: Using the equivalent attenuation coefficient obtained in Step 4, the complete waveform amplitude of the reference station in the overrange section is mapped to the overrange station, and the true waveform amplitude in the overrange section of the overrange station is reconstructed by reverse calculation.

[0010] Step 6: Output reconstructed waveforms: The reconstructed waveforms of the overrange sections from each overrange station are spliced ​​together with the original unsaturated section waveforms to form continuous microseismic reconstructed waveforms for the same microseismic event.

[0011] Step 7: Reconstructed waveforms for different microseismic events: Select different microseismic events and repeat steps 2 to 6 respectively, so as to reconstruct the waveforms of overrange stations in different microseismic events, and realize that each station can obtain continuous microseismic waveforms for different microseismic events.

[0012] Furthermore, the specific process for determining the over-range section in step one is as follows: When the waveform at the station satisfies the following at N consecutive sampling points: in, For the station The amplitude of the digital waveform. For the station The upper limit of the range, and .

[0013] The above formula is used to determine whether each sampling point is in the over-range section, and the time intervals corresponding to all sampling points in the over-range section are selected to obtain the over-range section.

[0014] Furthermore, the inversion process of the equivalent attenuation coefficient in step four is specifically as follows: Within the seismic phase time window, for each reference station Calculate its characteristic amplitude And establish the following amplitude propagation model: in, For micro-seismic events to the station The distance of transmission The equivalent attenuation coefficient to be inverted is... This is a constant term that includes the source intensity and instrument gain; Equivalent attenuation coefficient The results are obtained through logarithmic linearization and least squares method, specifically: in By performing least-squares fitting on the data from all reference stations, the equivalent attenuation coefficient for the same microseismic event can be obtained. .

[0015] Furthermore, the characteristic amplitude The root mean square value of the waveform envelope within the time window of the microseismic event phase is given by the following formula: in, For the station The instantaneous amplitude or envelope value, The number of sampling points within the seismic phase time window; where the seismic phase time window is the time interval [t1,t2] covering the main seismic phase energy, starting from the first arrival of the P wave.

[0016] Furthermore, in step five, the actual waveform amplitude within the over-range section of the over-range station is reconstructed by reverse calculation, specifically as follows: Over-range station time The reconstructed waveform amplitude satisfies: in, Reference station The complete waveform amplitude at the same moment, The instrument gains for the overrange station and the reference station are respectively. These represent the propagation distances from microseismic events to overrange stations and reference stations, respectively.

[0017] Furthermore, if multiple reference stations exist, a weighted fusion method is used to calculate the reconstruction results: in The weights of each reference station are related to the signal-to-noise ratio of the reference station.

[0018] Furthermore, the weights of each reference station The process of determining is as follows: Calculate and normalize the signal-to-noise ratio of each reference station: for the ... The characteristic amplitudes of the microseismic waveforms from each reference station are calculated within the effective signal window and background noise window of the P-wave, respectively. and The signal-to-noise ratio is obtained as follows: And normalize using the following formula: in, For the first Normalized signal-to-noise ratio for each station.

[0019] Construct a diagonal weight matrix using the signal-to-noise ratio values ​​of the reference stations: The weights of each reference station are determined using the above formula. .

[0020] Compared with the prior art, the present invention has the following advantages: 1. This invention first obtains the overrange sections and overrange stations corresponding to different microseismic events at various stations. Then, for the same microseismic event, a station that has not experienced overrange saturation is selected as a reference station, and the phase time window of the reference station is time-aligned with the corresponding time period of the overrange station. Next, a multi-station joint inversion method is used to calculate the equivalent attenuation coefficient corresponding to the microseismic event, avoiding the use of missing data. Finally, the equivalent attenuation coefficient is used to map the complete waveform amplitude of the reference station in the overrange section to the overrange station, realizing the true waveform amplitude within the overrange section of the overrange station. The entire overrange waveform reconstruction process has clear physical meaning. Through the above process, the physical consistency and usability of the overrange microseismic waveform are improved, providing a more reliable data foundation for microseismic energy assessment, hazard analysis, and subsequent intelligent early warning models.

[0021] 2. The entire process of this invention is based on the existing hardware of the microseismic monitoring system. The technical solution of this invention can be realized without adding new hardware, and the required technical effect can be achieved. Therefore, this invention is applicable to coal mines, tunnels and underground engineering environments where microseismic monitoring systems have been installed, and has wide applicability. Attached Figure Description

[0022] Figure 1 This is the overall flowchart of the present invention. Detailed Implementation

[0023] The present invention will be further described below.

[0024] like Figure 1 As shown, the present invention includes the following steps: Step 1: Over-range waveform identification: The microseismic monitoring system collects waveform data from n stations over a period of time. When the waveform at a certain station reaches or exceeds the upper limit of the measurement range at consecutive sampling points, the corresponding time segment is determined to be an over-range segment. The specific determination process is as follows: When the waveform at the station satisfies the following at N consecutive sampling points: in, For the station The amplitude of the digital waveform. For the station The upper limit of the range, and .

[0025] The above formula is used to determine whether each sampling point is in the overrange section, and the time segment corresponding to all sampling points in the overrange section is selected to obtain the overrange section, thereby obtaining the overrange section and overrange station corresponding to different microseismic events.

[0026] Step 2: Reference Station Selection: Select the same microseismic event, and from the n stations participating in the microseismic event location, select the stations that did not experience over-range saturation during the acquisition process of that microseismic event as reference stations, according to Step 1; Let m be the number of stations that experienced over-range saturation, then the number of stations that did not experience over-range saturation is... One serves as a reference station.

[0027] Step 3: Determine the phase time window and align the time: Determine the phase time window of the microseismic event selected in Step 2 from the waveforms of each reference station, and align the waveforms of the over-range station and the reference station under the same phase of the microseismic event.

[0028] Step 4: Attenuation Coefficient Inversion: Within the same phase time window, based on the complete waveform amplitude of each reference station, the propagation distance from the event to each station, and the instrument gain parameters, the equivalent attenuation coefficient corresponding to the microseismic event is calculated using a multi-station joint inversion method. Specifically: Within the seismic phase time window, for each reference station Calculate its characteristic amplitude And establish the following amplitude propagation model: in, For micro-seismic events to the station The distance of transmission The equivalent attenuation coefficient to be inverted is... This is a constant term that includes the source intensity and instrument gain.

[0029] Equivalent attenuation coefficient The results are obtained through logarithmic linearization and least squares method, specifically: in By performing least-squares fitting on the data from all reference stations, the equivalent attenuation coefficient for the same microseismic event can be obtained. .

[0030] characteristic amplitude The root mean square value of the waveform envelope within the time window of the microseismic event phase is given by the following formula: in, For the station The instantaneous amplitude or envelope value, The number of sampling points within the seismic phase time window; where the seismic phase time window is the time interval [t1,t2] covering the main seismic phase energy, starting from the first arrival of the P wave.

[0031] Step 5, Over-range Waveform Reconstruction: Using the equivalent attenuation coefficient obtained in Step 4, the complete waveform amplitude of the reference station in the over-range section is mapped to the over-range station. The true waveform amplitude within the over-range section of the over-range station is then reconstructed by reverse calculation. Specifically: Over-range station time The reconstructed waveform amplitude satisfies: in, Reference station The complete waveform amplitude at the same moment, The instrument gains for the overrange station and the reference station are respectively. These represent the propagation distances from microseismic events to overrange stations and reference stations, respectively.

[0032] In this embodiment, the instrument gain refers to the equivalent system gain of the microseismic monitoring station from the actual ground vibration magnitude to the recorded waveform amplitude. This parameter can be determined by the sensor sensitivity, preamplifier gain, and quantization ratio of the acquisition system, or it can be obtained through manual excitation calibration or statistical methods based on historical microseismic events. In overrange waveform reconstruction calculations, only the relative gain ratio between different stations needs to be used. This avoids dependence on absolute gain accuracy.

[0033] If multiple reference stations exist, a weighted fusion method is used to calculate the reconstruction results: in The weights of each reference station are related to its signal-to-noise ratio; the weights of each reference station... The process of determining is as follows: Calculate and normalize the signal-to-noise ratio of each reference station: for the ... The characteristic amplitudes of the microseismic waveforms from each reference station are calculated within the effective signal window and background noise window of the P-wave, respectively. and The signal-to-noise ratio is obtained as follows: And normalize using the following formula: in, For the first Normalized signal-to-noise ratio for each station.

[0034] Construct a diagonal weight matrix using the signal-to-noise ratio values ​​of the reference stations: The weights of each reference station are determined using the above formula. Finally, the true waveform amplitude reconstruction results within the overrange section of the overrange station were obtained.

[0035] Step 6: Output reconstructed waveforms: The reconstructed waveforms of the overrange sections from each overrange station are spliced ​​together with the original unsaturated section waveforms to form continuous microseismic reconstructed waveforms for the same microseismic event.

[0036] Step 7: Reconstructed waveforms for different microseismic events: Select different microseismic events and repeat steps 2 to 6 respectively, so as to reconstruct the waveforms of overrange stations in different microseismic events, and realize that each station can obtain continuous microseismic waveforms for different microseismic events.

[0037] 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 method for reconstructing microseismic overrange waveforms based on joint calibration of multiple stations, characterized in that, Includes the following steps: Step 1: Over-range waveform identification: Detect waveform data from n stations collected by the microseismic monitoring system over a period of time, and filter out the over-range sections and over-range stations corresponding to different microseismic events; Step 2, Reference Station Selection: Select the same microseismic event, and select the station that did not experience over-range saturation during the acquisition process of the microseismic event from the n stations involved in the microseismic event location according to Step 1; Step 3: Determine and align the phase time window of the seismic event selected in Step 2 from the waveforms of each reference station, and align the waveforms of the over-range station and the reference station under the same phase of the seismic event. Step 4: Attenuation coefficient inversion: Within the same phase time window, based on the complete waveform amplitude of each reference station, the propagation distance from the event to each station, and the instrument gain parameters, the equivalent attenuation coefficient corresponding to the microseismic event is calculated using a multi-station joint inversion method. Step 5, Over-range waveform reconstruction: Using the equivalent attenuation coefficient obtained in Step 4, the complete waveform amplitude of the reference station in the over-range section is mapped to the over-range station, and the true waveform amplitude in the over-range section of the over-range station is reconstructed by back-calculation. Step 6: Output reconstructed waveforms: The reconstructed waveforms of the overrange sections of each overrange station are spliced ​​with the original unsaturated section waveforms to form continuous microseismic reconstructed waveforms of the same microseismic event. Step 7: Reconstructed waveforms for different microseismic events: Select different microseismic events and repeat steps 2 to 6 respectively, so as to reconstruct the waveforms of overrange stations in different microseismic events, and realize that each station can obtain continuous microseismic waveforms for different microseismic events.

2. The microseismic overrange waveform reconstruction method based on multi-station joint calibration according to claim 1, characterized in that, The specific process for determining the over-range section in step one is as follows: When the waveform at the station satisfies the following at N consecutive sampling points: in, For the station The amplitude of the digital waveform. For the station The upper limit of the range, and ; The above formula is used to determine whether each sampling point is in the over-range section, and the time intervals corresponding to all sampling points in the over-range section are selected to obtain the over-range section.

3. The microseismic overrange waveform reconstruction method based on multi-station joint calibration according to claim 1, characterized in that, The inversion process of the equivalent attenuation coefficient in step four is as follows: Within the seismic phase time window, for each reference station Calculate its characteristic amplitude And establish the following amplitude propagation model: in, For micro-seismic events to the station The distance of transmission The equivalent attenuation coefficient to be inverted is... This is a constant term that includes the source intensity and instrument gain; Equivalent attenuation coefficient The results are obtained through logarithmic linearization and least squares method, specifically: in By performing least-squares fitting on the data from all reference stations, the equivalent attenuation coefficient for the same microseismic event can be obtained. .

4. The microseismic overrange waveform reconstruction method based on multi-station joint calibration according to claim 3, characterized in that, The characteristic amplitude The root mean square value of the waveform envelope within the time window of the microseismic event phase is given by the following formula: in, For the station The instantaneous amplitude or envelope value, The number of sampling points within the seismic phase time window; where the seismic phase time window is the time interval [t1,t2] covering the main seismic phase energy, starting from the first arrival of the P wave.

5. The microseismic overrange waveform reconstruction method based on multi-station joint calibration according to claim 1, characterized in that, Step five involves reconstructing the true waveform amplitude within the over-range section of the over-range station by reverse calculation, specifically as follows: Over-range station time The reconstructed waveform amplitude satisfies: in, Reference station The complete waveform amplitude at the same moment, The instrument gains for the overrange station and the reference station are respectively. These represent the propagation distances from microseismic events to overrange stations and reference stations, respectively.

6. The microseismic overrange waveform reconstruction method based on multi-station joint calibration according to claim 5, characterized in that, If multiple reference stations exist, a weighted fusion method is used to calculate the reconstruction results: in The weights of each reference station are related to the signal-to-noise ratio of the reference station.

7. The microseismic overrange waveform reconstruction method based on multi-station joint calibration according to claim 6, characterized in that, The weights of each reference station The process of determining is as follows: Calculate and normalize the signal-to-noise ratio of each reference station: for the ... The characteristic amplitudes of the microseismic waveforms from each reference station are calculated within the effective signal window and background noise window of the P-wave, respectively. and The signal-to-noise ratio is obtained as follows: And normalize using the following formula: in, For the first Normalized signal-to-noise ratio for each station; Construct a diagonal weight matrix using the signal-to-noise ratio values ​​of the reference stations: The weights of each reference station are determined using the above formula. .

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