Micro-seismic monitoring method for rapid excavation construction of deep and large vertical shaft

Abstract

The invention relates to the technical field of micro-seismic sensor monitoring, in particular to a micro-seismic monitoring method for rapid excavation construction of a deep and large vertical shaft, and the method comprises the steps: judging the extreme distribution conditions of all frequencies of nearby signals of vibration abrupt change signals in a frequency domain and the discrete degree of all amplitudes; determining the rock stratum vibration weight by combining the energy distribution of the nearby signal at the fundamental frequency in the frequency domain; constructing a vibration area characterization value by analyzing the dispersion degree and accumulation condition of the rock stratum vibration weights of all neighbor vibration sudden change signals, and obtaining rock stratum vibration confidence in combination with the rock stratum vibration weights; if the rock stratum vibration confidence coefficient of the vibration abrupt change signal is greater than a preset threshold value, rock stratum vibration occurs at the corresponding micro-seismic sensor, and otherwise, rock stratum vibration does not occur at the corresponding micro-seismic sensor. The invention aims to improve the accuracy of micro-seismic monitoring in the construction process of the deep and large vertical shaft.

Description

Technical Field

[0001] The present application relates to the field of microseismic sensor monitoring technology, and in particular to a microseismic monitoring method for rapid excavation construction of deep and large vertical shafts. Background Art

[0002] Deep vertical shafts play a vital role in underground engineering, serving applications in areas such as underground transportation, groundwater resource development, and underground energy storage. During the excavation of deep vertical shafts, microseismic monitoring of the geological environment can provide real-time monitoring of microseismic signals generated by rock deformation or fracture, helping to promptly identify potential safety hazards.

[0003] The basic principle of microseismic monitoring technology is to use sensors to collect vibration wave signals emitted by rock destruction or rock fractures, process and analyze the vibration wave signals, and thus obtain information such as the location, magnitude, and energy of the mine earthquake. However, due to the depth of deep vertical shafts, microseismic signals at deeper locations are generally weaker and decay rapidly. In addition, groundwater flow itself has micro-vibrations, underground electrical equipment generates electrical interference during operation, and drilling and excavation generate mechanical interference. As a result, the collected vibration signals contain a lot of noise interference, making it difficult to accurately extract microseismic signals, reducing the accuracy of microseismic monitoring during deep vertical shaft construction. Summary of the Invention

[0004] In order to solve the above technical problems, the present application provides a microseismic monitoring method for rapid excavation construction of deep and large vertical shafts to solve the existing problems.

[0005] The microseismic monitoring method for rapid excavation of deep and large vertical shafts in this application adopts the following technical solutions:

[0006] One embodiment of the present application provides a microseismic monitoring method for rapid excavation of a deep and large vertical shaft, the method comprising the following steps:

[0007] Install microseismic sensors at different depths in the shaft, obtain the vibration signal from each microseismic sensor within a preset time period before the current moment, and use it as the vibration signal of each microseismic sensor at the current moment. Before the current moment, use the vibration signal within a preset time period adjacent to the current moment as the nearest signal of each vibration signal at the current moment;

[0008] Analyze the distribution of all amplitudes of each vibration signal and its neighboring signals in the frequency domain, construct the fluctuation variation coefficient of each vibration signal at the current moment, evaluate the abnormality of the fluctuation variation coefficient, and screen out vibration mutation signals from all vibration signals; determine the rock formation vibration weight of each vibration mutation signal at the current moment by judging the extreme distribution of all frequencies and the discrete degree of all amplitudes of the neighboring signals of each vibration mutation signal in the frequency domain, and combining the energy distribution of the neighboring signals at the fundamental frequency in the frequency domain;

[0009] Based on the distance between the microseismic sensor corresponding to each vibration mutation signal and the microseismic sensors of all other vibration mutation signals, all neighboring vibration mutation signals of each vibration mutation signal are obtained, and by analyzing the discrete degree and accumulation of the rock formation vibration weights of all neighboring vibration mutation signals, the vibration region representation value of each vibration mutation signal at the current moment is constructed, and combined with the rock formation vibration weight, the rock formation vibration confidence of each vibration mutation signal at the current moment is obtained;

[0010] According to the rock formation vibration confidence level, the microseismic sensors where the rock formation vibrates are detected from all the microseismic sensors corresponding to the vibration mutation signals, and the corresponding vibration mutation signals are recorded as rock formation vibration signals. The average distribution of all amplitudes and all frequencies of the nearest signals of each rock formation vibration signal in the frequency domain is evaluated respectively, and the microseismic level at the location of the microseismic sensor corresponding to each rock formation vibration signal is determined.

[0011] Preferably, the expression of the fluctuation variation coefficient of each vibration signal at the current moment is: Where W i represents the fluctuation coefficient of the i-th vibration signal at the current moment; q i represents the mean of all amplitudes of the nearest signal of the i-th vibration signal in the frequency domain; p i represents the mean value of all amplitudes of the i-th vibration signal in the frequency domain; t i Represents the number of all frequency components of the i-th vibration signal in the frequency domain.

[0012] Preferably, the process of screening out vibration mutation signals from all vibration signals is:

[0013] The fluctuation variation coefficients of all vibration signals at the current moment are used as the input of the anomaly detection algorithm, and the anomaly scores of all fluctuation variation coefficients are output. All anomaly scores are used as the input of the threshold segmentation algorithm, and the segmentation threshold is output. The vibration signal corresponding to the fluctuation variation coefficient with an anomaly score greater than the segmentation threshold is regarded as the vibration mutation signal.

[0014] Preferably, the anomaly detection algorithm is a z-score normalization method.

[0015] Preferably, the expression of the rock formation vibration weight of each vibration mutation signal at the current moment is: Where H i represents the rock formation vibration weight of the i-th vibration mutation signal at the current moment; C i 、s i They represent the range of all frequencies and the variance of all amplitudes of the i-th vibration mutation signal in the frequency domain at the current moment; u i represents the number of all frequency components of the nearest signal of the i-th vibration mutation signal in the frequency domain at the current moment; f i,max represents the maximum amplitude of the nearest signal of the i-th vibration mutation signal in the frequency domain at the current moment; e i Represents the energy intensity of the nearest signal of the i-th vibration mutation signal at the fundamental frequency in the frequency domain.

[0016] Preferably, the method for obtaining all neighboring vibration mutation signals of each vibration mutation signal is:

[0017] In the results of arranging the distances between each vibration mutation signal and all other vibration mutation signals corresponding to the microseismic sensors in ascending order, the vibration mutation signals in the microseismic sensors corresponding to the first preset number of distance values are used as the neighboring vibration mutation signals of each vibration mutation signal.

[0018] Preferably, the expression of the vibration region characterization value of each vibration mutation signal at the current moment is: A i =O i ×H i Where A i represents the vibration region characterization value of the i-th vibration mutation signal at the current moment; i represents the variance of the rock formation vibration weights of all neighboring vibration mutation signals of the i-th vibration mutation signal at the current moment; H i It represents the cumulative sum of the rock formation vibration weights of all neighboring vibration mutation signals of the i-th vibration mutation signal at the current moment.

[0019] Preferably, the rock formation vibration confidence of each vibration mutation signal at the current moment is a normalized value of the product of the rock formation vibration weight of each vibration mutation signal at the current moment and the vibration region characterization value.

[0020] Preferably, the microseismic sensor that detects the vibration of the rock formation from all microseismic sensors corresponding to the sudden vibration change signals includes:

[0021] If the rock formation vibration confidence of the vibration mutation signal at the current moment is greater than the preset threshold, then the rock formation vibration occurs at the microseismic sensor corresponding to the vibration mutation signal; otherwise, the rock formation vibration does not occur at the microseismic sensor corresponding to the vibration mutation signal.

[0022] Preferably, the method for determining the microseismic level at the location of the microseismic sensor corresponding to the vibration signal of each rock formation is:

[0023] The mean of all amplitudes and the mean of all frequencies of the nearest signal of the vibration signal of each rock layer in the frequency domain are calculated respectively, and recorded as the amplitude mean and frequency mean. The product of the amplitude mean and the frequency mean is taken as the microseismic level of the location of the microseismic sensor corresponding to the vibration signal of each rock layer.

[0024] This application has at least the following beneficial effects:

[0025] The present application constructs a rock formation vibration weight by screening out the vibration mutation signals that have mutated in the vibration signal, analyzing the distribution of the nearby signals of the vibration mutation signal in the frequency domain, which helps to eliminate the interference of electrical interference signals and mechanical interference signals on rock formation vibration monitoring, thereby improving the accuracy of the monitoring results; further, by analyzing the differences between each vibration mutation signal and its neighboring vibration mutation signals, as well as the rock formation vibration weights of the neighboring vibration mutation signals, a rock formation vibration confidence is constructed, which can more accurately reflect the degree to which the area near the microseismic sensor is affected by rock formation vibration, thereby more accurately locating the rock formation vibration intensity and improving the accuracy of microseismic monitoring during the construction of deep and large vertical shafts. By analyzing the frequency, amplitude and energy distribution of the vibration signal, the present application can more comprehensively evaluate the rock formation vibration characteristics, eliminate the influence of electrical interference signals and mechanical interference signals on microseismic monitoring, and improve the accuracy of microseismic monitoring during the construction of deep and large vertical shafts. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] In order to more clearly illustrate the technical solutions and advantages of the embodiments of the present application or the prior art, the following is a brief introduction to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0027] Figure 1 A flowchart of the steps of a microseismic monitoring method for rapid excavation of a deep and large vertical shaft provided in one embodiment of the present application;

[0028] Figure 2 A schematic diagram of the installation position of microseismic sensors in a deep vertical shaft provided in one embodiment of the present application. DETAILED DESCRIPTION

[0029] To further illustrate the technical means and effectiveness of this application to achieve the intended purpose of the invention, the following, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation, structure, features, and effectiveness of the microseismic monitoring method for rapid excavation of deep and large vertical shafts proposed in this application. In the following description, different references to "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics of one or more embodiments may be combined in any suitable manner.

[0030] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.

[0031] The specific scheme of the microseismic monitoring method for rapid excavation construction of deep and large vertical shafts provided by this application is described in detail below with reference to the accompanying drawings.

[0032] An embodiment of the present application provides a microseismic monitoring method for rapid excavation of a deep and large vertical shaft. Specifically, the following microseismic monitoring method for rapid excavation of a deep and large vertical shaft is provided. Figure 1 , the method comprises the following steps:

[0033] Step S1: Install microseismic sensors at different depths in the shaft, obtain the vibration signal from each microseismic sensor within a preset time period before the current moment, and use it as the vibration signal of each microseismic sensor at the current moment. Before the current moment, use the vibration signal within a preset time period adjacent to the current moment as the nearest signal of each vibration signal at the current moment.

[0034] In order to excavate deep and large vertical shafts quickly, it is necessary to monitor the microseismic signals near the shaft in real time during the construction process to ensure the safety of the construction process. During the excavation of deep and large vertical shafts, according to the size of the cross-section of the shaft inner wall, a microseismic sensor is installed at a certain distance in the cross-section at the same depth. As the shaft excavation depth increases, the number of microseismic sensors gradually increases. The installation position diagram of the microseismic sensor in the deep and large vertical shaft is shown in the figure below. Figure 2 As shown, Figure 2 Serial number 1 represents a deep vertical shaft, and serial number 2 represents a microseismic sensor.

[0035] Obtain the vibration signal from each microseismic sensor within a preset time period before the current moment, and use it as the vibration signal of each microseismic sensor at the current moment. Before the current moment, use the vibration signal in a preset time period adjacent to the current moment as the nearest signal of each vibration signal at the current moment, where the sampling frequency is set to f.

[0036] It should be noted that the values of the preset duration, sampling frequency f and the length of the preset period are all set manually. In this embodiment, the value of the preset duration is 5 minutes, the value of the sampling frequency f is 30 Hz, and the value of the preset duration is 60 seconds. The implementer can also set them according to the specific situation. This embodiment does not impose any special restrictions.

[0037] Furthermore, a filtering algorithm is used to denoise the vibration signal to obtain a preprocessed vibration signal. There are many commonly used filtering algorithms. In this embodiment, a median filtering algorithm is used to denoise the vibration signal. The implementer may also use other filtering algorithms such as Gaussian filtering or mean filtering. This embodiment does not impose any special restrictions on the selection of filtering algorithms.

[0038] Among them, the median filtering algorithm is a well-known technology, and the specific principle and process of its signal noise reduction are not described in detail.

[0039] Step S2: Analyze the distribution of all amplitudes of each vibration signal and its neighboring signals in the frequency domain respectively, construct the fluctuation variation coefficient of each vibration signal at the current moment, evaluate the abnormality of the fluctuation variation coefficient, and screen out vibration mutation signals from all vibration signals; by judging the extreme distribution of all frequencies of the neighboring signals of each vibration mutation signal in the frequency domain and the discrete degree of all amplitudes, and combining the energy distribution of the neighboring signal at the fundamental frequency in the frequency domain, determine the rock formation vibration weight of each vibration mutation signal at the current moment.

[0040] Rock vibration signals are generated by rock fractures or slippage. These signals have complex waveforms, with varying degrees of rock fracture generating signals of varying frequencies. The timing of rock vibration signals is irregular, appearing only briefly when the rock fractures. Groundwater flow, on the other hand, is continuous and uninterrupted, and the microseismic signals generated by groundwater flow manifest as continuous, regularly occurring vibration waveforms. Electrical interference primarily arises from electrical interference noise generated by various electrical equipment and power supplies underground, and occurs only when electrical equipment is operating. Mechanical interference is the noise generated by the drilling rig during excavation, and its duration is related to the machine's operating time.

[0041] In the vibration signal, the water flow interference signal is always present. When the vibration signal changes suddenly, it may be a rock vibration signal, or it may be an electrical interference signal or a mechanical interference signal. Therefore, in order to eliminate the interference of electrical and mechanical interference signals on rock vibration monitoring and improve the accuracy of rock vibration monitoring, the vibration mutation signal is determined by analyzing the abnormal fluctuation degree of the amplitude change of the vibration signal's nearest signal in the frequency domain. Based on the extreme distribution of all frequencies of the vibration mutation signal's nearest signal in the frequency domain and the discrete degree of all amplitudes, the rock vibration weight of each vibration mutation signal at the current moment is constructed. The specific process is as follows:

[0042] (1) In order to determine the possibility of sudden change of vibration signals, the distribution of all amplitudes of each vibration signal and its neighboring signals in the frequency domain is analyzed to construct the fluctuation variation coefficient of each vibration signal at the current moment, specifically:

[0043] The fluctuation variation coefficient W of the i-th vibration signal at the current moment i The expression is: Where q i represents the mean of all amplitudes of the nearest signal of the i-th vibration signal in the frequency domain; p i represents the mean value of all amplitudes of the i-th vibration signal in the frequency domain; t i Represents the number of all frequency components of the i-th vibration signal in the frequency domain.

[0044] It should be noted that, in this embodiment, the distribution of the signal in the frequency domain is analyzed by fast Fourier transform. The implementer may also use other methods such as wavelet transform or discrete Fourier transform, and this embodiment does not impose any special limitation.

[0045] The method of obtaining the frequency components and the principle of fast Fourier transform are both well-known technologies, and the statistical process of the number of frequency components and the principle of fast Fourier transform are not described in detail again.

[0046] According to the fluctuation variation coefficient of each vibration signal at the current moment, it can be understood that if the ratio between the mean of all amplitudes of the nearby signal of the vibration signal in the frequency domain and the mean of all amplitudes of the vibration signal in the frequency domain is larger, it means that the signal strength of the nearby signal relative to the vibration signal has increased, that is, the nearby signal has undergone a mutation relative to the vibration signal, and the number of frequency components of the vibration signal in the frequency domain has increased, which means that the vibration signal before the current moment and the vibration signal near the current moment have undergone a mutation, and the obtained fluctuation variation coefficient of the vibration signal is larger; on the contrary, if the ratio between the mean of all amplitudes of the nearby signal of the vibration signal in the frequency domain and the mean of all amplitudes of the vibration signal in the frequency domain is smaller, and the number of frequency components of the vibration signal in the frequency domain has not increased significantly, then the intensity and volatility of the nearby signal relative to the vibration signal may remain relatively stable, and the obtained fluctuation variation coefficient is smaller.

[0047] (2) Furthermore, in order to further determine whether the vibration signal has undergone a mutation, the fluctuation change coefficients of all vibration signals at the current moment are used as the input of the z-score normalization method, and the standard scores of all fluctuation change coefficients are output as the abnormality scores. All abnormality scores are used as the input of the threshold segmentation algorithm, and the segmentation threshold is output. The vibration signal corresponding to the fluctuation change coefficient with an abnormality score greater than the segmentation threshold is regarded as a vibration mutation signal.

[0048] Among them, the z-score standardization method is a well-known technology, and the specific process of obtaining the standard score of each fluctuation coefficient is not repeated here.

[0049] In addition, it should be understood that there are many commonly used threshold segmentation algorithms. In this embodiment, the Otsu threshold segmentation algorithm is used to obtain the segmentation threshold. The implementer may also use other threshold segmentation methods. This embodiment does not impose any special restrictions on the selection of the threshold segmentation algorithm.

[0050] Among them, the Otsu threshold segmentation algorithm is a well-known technology, and its specific principle is not repeated here.

[0051] (3) When a sudden change in the vibration signal before and close to the current moment is detected, the vibration signal is judged to be a rock formation vibration signal, an electrical interference signal, or a mechanical interference signal based on the characteristics of the nearest signal of the vibration signal. The reason for the appearance of the rock formation vibration signal is the vibration wave generated by the phenomenon of rock formation displacement, fracture, etc. Compared with the electrical interference signal and the mechanical interference signal, the amplitude of this vibration wave is relatively chaotic, sometimes large and sometimes small. Moreover, since the degree of fracture of the same rock formation fracture event is different at different locations, the frequency of the generated vibration wave is also different, so the rock formation vibration signal has a weaker periodicity and a wider bandwidth. The electrical interference signal is an interference wave generated by the operation of electrical equipment. The frequency of this signal is usually related to the operating frequency of the electrical equipment and will appear as a fixed frequency interference signal. The interference signal has a small amplitude, strong periodicity, and a large frequency. The mechanical interference signal is an interference signal generated during the excavation process of the drilling equipment. When a mechanical interference signal appears, it has the characteristics of strong periodicity and small amplitude.

[0052] Therefore, in order to eliminate the interference of electrical and mechanical interference signals on the rock formation vibration monitoring process and thus improve the rock formation vibration monitoring method, the rock formation vibration weight of the next vibration signal at the current moment is constructed based on the distribution of amplitude and frequency of the nearest signal of the vibration mutation signal in the frequency domain and combined with the energy distribution of the nearest signal at the fundamental frequency in the frequency domain. Specifically,

[0053] The rock formation vibration weight H of the i-th vibration mutation signal at the current moment i The expression is: Where C i 、s i They represent the range of all frequencies and the variance of all amplitudes of the i-th vibration mutation signal in the frequency domain at the current moment; u i represents the number of all frequency components of the nearest signal of the i-th vibration mutation signal in the frequency domain at the current moment; f i,max represents the maximum amplitude of the nearest signal of the i-th vibration mutation signal in the frequency domain at the current moment; e i Represents the energy intensity of the nearest signal of the i-th vibration mutation signal at the fundamental frequency in the frequency domain.

[0054] The method for calculating the energy intensity of a signal at a certain frequency is a well-known technique, and the specific calculation principle thereof will not be described in detail.

[0055] According to the rock formation vibration weight of each vibration mutation signal at the current moment, it can be understood that when the range of all frequencies of the vibration mutation signal in the frequency domain is larger, it means that the frequency range of the vibration signal is wider, that is, the bandwidth of the signal is wider, and rock formation vibration usually produces a signal with a wider frequency band, so the larger the range, the more likely the cause of the mutation of the vibration mutation signal is to be caused by rock formation vibration; if the degree of dispersion of all amplitudes of the vibration mutation signal in the frequency domain is greater, that is, the variance is greater, it means that the amplitude difference of different frequency components is large, the signal is unevenly distributed in the frequency domain, and shows a chaotic feature, and rock formation vibration is often non-periodic and complex, so it shows a larger variance in the frequency domain, so the larger the variance, the more likely the mutation of the vibration mutation signal is to be caused by rock formation vibration; when the vibration mutation signal The more frequency components it contains, the wider the signal is distributed in the frequency domain and contains multiple frequency components. Rock formation vibration usually involves multiple physical processes, which can generate rich frequency components in the frequency domain. Therefore, the more frequency components it contains, the more complex the signal is. The more likely it is that the mutation of the vibration mutation signal is caused by rock formation vibration. The larger the maximum amplitude of the nearest signal of the vibration mutation signal in the frequency domain, the more likely it is that the mutation of the vibration mutation signal is caused by rock formation vibration. In addition, the smaller the energy intensity of the nearest signal of the vibration mutation signal at the fundamental frequency in the frequency domain, the weaker the periodicity of the vibration mutation signal. Rock formation vibration is often non-periodic, which means that the mutation of the vibration mutation signal is more likely to be caused by rock formation vibration, and the greater the rock formation vibration weight is.

[0056] On the contrary, if the range of all frequencies of the vibration mutation signal in the frequency domain is smaller, the variance of all amplitudes of the vibration mutation signal in the frequency domain is smaller, the frequency components contained in the vibration mutation signal are fewer, the maximum amplitude of the nearest signal of the vibration mutation signal in the frequency domain is smaller, and the energy intensity of the nearest signal of the vibration mutation signal at the fundamental frequency in the frequency domain is greater, then the rock formation vibration weight is smaller, which means that the mutation of the vibration mutation signal is less likely to be caused by rock formation vibration.

[0057] Step S3: Based on the distance between the microseismic sensor corresponding to each vibration mutation signal and the microseismic sensors of all other vibration mutation signals, all neighboring vibration mutation signals of each vibration mutation signal are obtained, and by analyzing the discrete degree and accumulation of the rock formation vibration weights of all neighboring vibration mutation signals, the vibration area characterization value of each vibration mutation signal at the current moment is constructed, and combined with the rock formation vibration weight, the rock formation vibration confidence of each vibration mutation signal at the current moment is obtained.

[0058] When rock fractures deep underground, energy is released. These vibration waves propagate at varying speeds and intensities, causing microseismic sensors located near the fracture site to record variations in the intensity, frequency, and duration of the vibration signal. The varying distances between microseismic sensors and the varying geological conditions they encounter result in varying degrees of impact. Closer sensors register stronger vibration signals, while farther sensors, blocked by geological structures and other factors, register weaker signals.

[0059] Therefore, by analyzing the differences between the vibration mutation signals of each microseismic sensor and its adjacent microseismic sensors, the rock formation vibration confidence of the vibration mutation signal can be determined, thereby accurately monitoring the rock formation vibration. Specifically:

[0060] (1) In the results of arranging the distances between the microseismic sensors corresponding to each vibration mutation signal and the microseismic sensors of all other vibration mutation signals in ascending order, the vibration mutation signals in the microseismic sensors corresponding to the first preset number of distance values are taken as the neighboring vibration mutation signals of each vibration mutation signal.

[0061] It should be noted that the value of the preset number is set artificially. In this embodiment, the value of the preset number is 8. The reason why the value of the preset number is set to 8 in this embodiment is that if the number of selected vibration mutation signals is small, there will be a lack of sufficient data to accurately reflect the actual vibration conditions of the rock formation. If the value of the preset number is too large, the difference between the vibration mutation signals in the microseismic sensors at a farther distance and the vibration mutation signals in the microseismic sensors at a closer distance is large, which will cover up the actual vibration conditions. Therefore, in this embodiment, the value of the preset number is 8. The implementer can also reasonably set it based on the specific situation. This embodiment does not impose any special restrictions.

[0062] (2) By analyzing the discreteness and accumulation of the rock formation vibration weights of all neighboring vibration mutation signals and combining the rock formation vibration weights, the rock formation vibration confidence of each vibration mutation signal at the current moment is obtained. Specifically:

[0063] In order to determine the possibility that the vibration mutation signal is affected by the rock formation vibration, the discrete degree and accumulation of the rock formation vibration weights of all neighboring vibration mutation signals are analyzed to construct the vibration region representation value of each vibration mutation signal at the current moment. Specifically,

[0064] The vibration area representation value A of the i-th vibration signal at the current moment i The expression is: A i =O i ×H i Where, O irepresents the variance of the rock formation vibration weights of all neighboring vibration mutation signals of the i-th vibration mutation signal at the current moment; H i It represents the cumulative sum of the rock formation vibration weights of all neighboring vibration mutation signals of the i-th vibration mutation signal at the current moment.

[0065] According to the vibration region characterization value of each vibration signal at the current moment, it can be understood that the greater the cumulative sum of the rock formation vibration weights of all neighboring vibration mutation signals of the vibration signal, the greater the possibility that the vibration mutation signal collected by the microseismic sensor near the microseismic sensor is affected by the rock formation vibration, and the greater the vibration region characterization value; at the same time, when the vibration signals of the microseismic sensors near the microseismic sensor are greatly different, it is more likely that they are caused by different degrees of rock formation fracture, and the vibration mutation signal is more likely to be affected by rock formation vibration, and the final rock formation vibration confidence is also greater;

[0066] On the contrary, when the cumulative sum of the rock formation vibration weights of all neighboring vibration mutation signals of the vibration signal is small, it means that the vibration mutation signal collected by the microseismic sensor near the microseismic sensor is less likely to be affected by the rock formation vibration, and the representation value of the vibration area is also correspondingly smaller; at the same time, if the vibration signal difference of the microseismic sensors near the microseismic sensor is small, this may indicate that the vibration source is relatively uniform or the vibration propagation path is similar. In this case, the probability of the vibration mutation signal being affected by the rock formation vibration may be low, and the final rock formation vibration confidence will also be small.

[0067] Furthermore, the normalized value of the product of the formation vibration weight and the vibration region representation value of each vibration mutation signal at the current moment is used as the formation vibration confidence level of each vibration mutation signal at the current moment. The larger the formation vibration weight and the larger the vibration region representation value, the greater the formation vibration confidence level, indicating that the mutation in the vibration mutation signal is more likely to be caused by formation vibration. Conversely, the smaller the formation vibration weight and the smaller the vibration region representation value, the smaller the formation vibration confidence level, indicating that the mutation in the vibration signal is less likely to be caused by formation vibration.

[0068] Step S4: Based on the rock formation vibration confidence, the microseismic sensors where the rock formation vibrates are detected from all the microseismic sensors corresponding to the vibration mutation signals, and the corresponding vibration mutation signals are recorded as rock formation vibration signals. The average distribution of all amplitudes and all frequencies of the nearest signals of each rock formation vibration signal in the frequency domain is evaluated respectively, and the microseismic level of the location of the microseismic sensor corresponding to each rock formation vibration signal is determined.

[0069] Based on the rock formation vibration confidence obtained in step S3, further, it is determined whether the vibration mutation signal is a rock formation vibration signal caused by rock formation vibration according to the rock formation vibration confidence, specifically:

[0070] If the rock formation vibration confidence of the vibration mutation signal at the current moment is greater than the preset threshold, it means that the rock formation vibration occurs at the microseismic sensor corresponding to the vibration mutation signal, and the vibration mutation signal in the microseismic sensor corresponding to the rock formation vibration is recorded as the rock formation vibration signal. Further, the mean of all amplitudes and the mean of all frequencies of the nearest signal of each rock formation vibration signal in the frequency domain are calculated respectively, and recorded as the amplitude mean and the frequency mean. The product of the amplitude mean and the frequency mean is used as the microseismic level of the location where the microseismic sensor corresponding to each rock formation vibration signal is located;

[0071] On the contrary, if the rock formation vibration confidence of the vibration mutation signal at the current moment is greater than the preset threshold, it means that no rock formation vibration occurs at the microseismic sensor corresponding to the vibration mutation signal.

[0072] It should be noted that the value of the preset threshold is set manually. In this embodiment, the value of the preset threshold is 0.4. The implementer can also set it by himself based on the specific actual situation. This embodiment does not impose any special restrictions.

[0073] At this point, this embodiment eliminates the interference of water flow signals, electrical signals and mechanical signals by analyzing the vibration signals in the frequency domain and analyzing the differences in vibration signals between different microseismic sensors, so that the microseismic monitoring results can more accurately monitor the location of rock formation vibration and the microseismic level at the rock formation vibration.

[0074] It should be noted that the order in which the embodiments of the present application are presented is for illustrative purposes only and does not necessarily represent the superiority or inferiority of the embodiments. Furthermore, the foregoing descriptions of specific embodiments of this specification are provided. Furthermore, the processes depicted in the accompanying drawings do not necessarily require the specific order or sequential sequence shown to achieve the desired results. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0075] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on the differences from other embodiments.

[0076] The above-described embodiments are only used to illustrate the technical solutions of the present application, and not to limit them. Modifications to the technical solutions described in the aforementioned embodiments, or equivalent replacements of some of the technical features therein, do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present application, and should all be included in the scope of protection of the present application.

Claims

1. A microseismic monitoring method for rapid excavation of deep and large vertical shafts, characterized in that: The method comprises the following steps: Install microseismic sensors at different depths in the shaft, obtain the vibration signal from each microseismic sensor within a preset time period before the current moment, and use it as the vibration signal of each microseismic sensor at the current moment. Before the current moment, use the vibration signal within a preset time period adjacent to the current moment as the nearest signal of each vibration signal at the current moment; Analyze the distribution of all amplitudes of each vibration signal and its neighboring signals in the frequency domain, construct the fluctuation variation coefficient of each vibration signal at the current moment, evaluate the abnormality of the fluctuation variation coefficient, and screen out vibration mutation signals from all vibration signals; determine the rock formation vibration weight of each vibration mutation signal at the current moment by judging the extreme distribution of all frequencies and the discrete degree of all amplitudes of the neighboring signals of each vibration mutation signal in the frequency domain, and combining the energy distribution of the neighboring signals at the fundamental frequency in the frequency domain; Based on the distance between the microseismic sensor corresponding to each vibration mutation signal and the microseismic sensors of all other vibration mutation signals, all neighboring vibration mutation signals of each vibration mutation signal are obtained, and by analyzing the discrete degree and accumulation of the rock formation vibration weights of all neighboring vibration mutation signals, the vibration region representation value of each vibration mutation signal at the current moment is constructed, and combined with the rock formation vibration weight, the rock formation vibration confidence of each vibration mutation signal at the current moment is obtained; According to the rock formation vibration confidence level, the microseismic sensors where the rock formation vibrates are detected from all the microseismic sensors corresponding to the vibration mutation signals, and the corresponding vibration mutation signals are recorded as rock formation vibration signals. The average distribution of all amplitudes and all frequencies of the nearest signals of each rock formation vibration signal in the frequency domain is evaluated respectively, and the microseismic level at the location of the microseismic sensor corresponding to each rock formation vibration signal is determined.

2. The microseismic monitoring method for rapid excavation of deep and large vertical shafts according to claim 1, characterized in that: The expression of the fluctuation variation coefficient of each vibration signal at the current moment is: Where W i represents the fluctuation coefficient of the i-th vibration signal at the current moment; q i represents the mean value of all amplitudes of the nearest signal of the i-th vibration signal in the frequency domain; p i represents the mean of all amplitudes of the i-th vibration signal in the frequency domain; t i Represents the number of all frequency components of the i-th vibration signal in the frequency domain.

3. The microseismic monitoring method for rapid excavation of deep and large vertical shafts according to claim 1, characterized in that: The process of screening out vibration mutation signals from all vibration signals is as follows: The fluctuation variation coefficients of all vibration signals at the current moment are used as the input of the anomaly detection algorithm, and the anomaly scores of all fluctuation variation coefficients are output. All anomaly scores are used as the input of the threshold segmentation algorithm, and the segmentation threshold is output. The vibration signal corresponding to the fluctuation variation coefficient with an anomaly score greater than the segmentation threshold is regarded as the vibration mutation signal.

4. The microseismic monitoring method for rapid excavation of deep and large vertical shafts according to claim 3, characterized in that: The anomaly detection algorithm is the z-score normalization method.

5. The microseismic monitoring method for rapid excavation of deep and large vertical shafts according to claim 1, characterized in that: The expression of the rock formation vibration weight of each vibration mutation signal at the current moment is: Where H i Indicates the rock formation vibration weight of the i-th vibration mutation signal at the current moment; C i 、s i They represent the range of all frequencies and the variance of all amplitudes of the i-th vibration mutation signal in the frequency domain at the current moment; u i represents the number of all frequency components of the nearest signal of the i-th vibration mutation signal in the frequency domain at the current moment; f i,max represents the maximum amplitude of the nearest signal of the i-th vibration mutation signal in the frequency domain at the current moment; e i Represents the energy intensity of the nearest signal of the i-th vibration mutation signal at the fundamental frequency in the frequency domain.

6. The microseismic monitoring method for rapid excavation of deep and large vertical shafts according to claim 1, characterized in that: The method for obtaining all neighboring vibration mutation signals of each vibration mutation signal is as follows: In the results of arranging the distances between each vibration mutation signal and all other vibration mutation signals corresponding to the microseismic sensors in ascending order, the vibration mutation signals in the microseismic sensors corresponding to the first preset number of distance values are used as the neighboring vibration mutation signals of each vibration mutation signal.

7. The microseismic monitoring method for rapid excavation of deep and large vertical shafts according to claim 1, characterized in that: The expression of the vibration region characterization value of each vibration mutation signal at the current moment is: i =O i ×H i Where A i represents the vibration region characterization value of the i-th vibration mutation signal at the current moment; i represents the variance of the rock formation vibration weights of all neighboring vibration mutation signals of the i-th vibration mutation signal at the current moment; H i It represents the cumulative sum of the rock formation vibration weights of all neighboring vibration mutation signals of the i-th vibration mutation signal at the current moment.

8. The microseismic monitoring method for rapid excavation of deep and large vertical shafts according to claim 1, characterized in that: The rock formation vibration confidence of each vibration mutation signal at the current moment is a normalized value of the product of the rock formation vibration weight of each vibration mutation signal at the current moment and the vibration region characterization value.

9. The microseismic monitoring method for rapid excavation of deep and large vertical shafts according to claim 1, characterized in that: The microseismic sensor for detecting the vibration of the rock formation from the microseismic sensors corresponding to all the sudden vibration signals includes: If the rock formation vibration confidence of the vibration mutation signal at the current moment is greater than the preset threshold, then the rock formation vibration occurs at the microseismic sensor corresponding to the vibration mutation signal; otherwise, the rock formation vibration does not occur at the microseismic sensor corresponding to the vibration mutation signal.

10. The microseismic monitoring method for rapid excavation of deep and large vertical shafts according to claim 1, characterized in that: The method for determining the microseismic level at the location of the microseismic sensor corresponding to the vibration signal of each rock layer is as follows: The mean of all amplitudes and the mean of all frequencies of the nearest signal of the vibration signal of each rock layer in the frequency domain are calculated respectively, and recorded as the amplitude mean and frequency mean. The product of the amplitude mean and the frequency mean is taken as the microseismic level of the location of the microseismic sensor corresponding to the vibration signal of each rock layer.

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