Fracture source positioning method and system based on multi-information fusion

Abstract

The embodiment of the invention provides a fracture source positioning method and system based on multi-information fusion, and can solve the problems that in dam or underground water tunnel construction, surrounding rock fracture may cause leakage or collapse, the engineering safety is affected, and the positioning precision and accuracy need to be improved. The method comprises the following steps: acquiring micro-seismic waveform data based on a sensor network arranged in a surrounding rock, and inverting position information of a fracture source according to the micro-seismic waveform data; calculating crustal stress distribution based on the initial crustal stress field of the surrounding rock in combination with a geologic model, and simulating a disturbance stress field according to an excavation scheme to identify a high stress concentration area; and performing fracture source positioning verification according to the position information, obtained by inversion, of the fracture source and the identified position relation of the high stress concentration area.

Description

Technical Field

[0001] The present application relates to the field of computer technology, and in particular to a method and system for locating a rupture source based on multi-information fusion. Background Art

[0002] During mining, surrounding rock may crack or collapse due to the redistribution of ground stress. Accurately locating the source of cracks can help assess the stability of mines and formulate support measures. Underground projects such as tunnels require real-time monitoring of the mechanical behavior of surrounding rock, and locating the source of cracks can identify potential dangerous areas. In the construction of dams or underground hydraulic tunnels, surrounding rock cracks may cause leakage or collapse, affecting project safety. Summary of the invention

[0003] The embodiment of the present application provides a method and system for locating a rupture source based on multi-information fusion, which can solve the problem that in the construction of dams or underground hydraulic tunnels, surrounding rock rupture may cause leakage or collapse, affecting the safety of the project and the positioning precision and accuracy need to be improved.

[0004] A first aspect of an embodiment of the present application provides a method for locating a rupture source based on multi-information fusion, comprising:

[0005] Acquiring microseismic waveform data based on a sensor network arranged in the surrounding rock, so as to invert the location information of the rupture source according to the microseismic waveform data;

[0006] The initial geostress field of the surrounding rock is combined with the geological model to calculate the geostress distribution, and the disturbed stress field is simulated according to the excavation plan to identify the high stress concentration area;

[0007] The location of the rupture source is verified based on the position information of the rupture source obtained by inversion and the positional relationship between the identified high stress concentration area.

[0008] Optionally, it also includes:

[0009] Acquiring groundwater monitoring data, wherein the groundwater monitoring data is obtained based on sensors of groundwater monitoring holes arranged in the surrounding rock area;

[0010] Extracting abnormal change areas associated with abnormal change data in monitoring data;

[0011] The location of the rupture source is verified based on the positional relationship between the position information of the rupture source obtained by inversion and the extracted abnormal change area.

[0012] Optionally, the extracting the abnormal change area associated with the abnormal change data in the monitoring data includes:

[0013] Extracting abnormally elevated areas associated with permeability in monitoring data;

[0014] The rupture source location verification is performed based on the positional relationship between the positional information of the rupture source obtained by inversion and the extracted abnormally elevated area, including:

[0015] The location of the rupture source is verified based on the positional relationship between the position information of the rupture source obtained by inversion and the extracted abnormally elevated area.

[0016] Optionally, the extracting the abnormal change area associated with the abnormal change data in the monitoring data includes:

[0017] Extracting abnormally elevated areas associated with flow velocity in monitoring data;

[0018] The rupture source location verification is performed based on the positional relationship between the positional information of the rupture source obtained by inversion and the extracted abnormally elevated area, including:

[0019] The location of the rupture source is verified based on the positional relationship between the position information of the rupture source obtained by inversion and the extracted abnormally elevated area.

[0020] Optionally, the extracting the abnormal change area associated with the abnormal change data in the monitoring data includes:

[0021] Extract abnormal fluctuation areas associated with water levels in monitoring data;

[0022] The rupture source location verification is performed based on the positional relationship between the positional information of the rupture source obtained by inversion and the extracted abnormally elevated area, including:

[0023] The location of the rupture source is verified based on the positional relationship between the rupture source obtained by inversion and the extracted abnormal fluctuation area.

[0024] Optionally, also include:

[0025] Extracting waveform features from the microseismic waveform data, wherein the waveform features include a P-wave and an S-wave amplitude ratio;

[0026] The fracture type of the surrounding rock is determined based on the waveform characteristics, and the fracture direction and extension trend are analyzed in combination with the ground stress distribution.

[0027] Optionally, also include:

[0028] Extract the stress drop, focal radius and rupture energy of the rupture source;

[0029] The potential extension risk of the rupture area is evaluated based on at least one parameter of stress drop, focal radius and rupture energy combined with the disturbed stress field.

[0030] A second aspect of the embodiment of the present application provides a rupture source positioning device based on multi-information fusion, comprising:

[0031] A positioning unit, used to obtain microseismic waveform data based on a sensor network arranged in the surrounding rock, so as to invert the position information of the rupture source according to the microseismic waveform data;

[0032] Identification unit, used to calculate the ground stress distribution based on the initial ground stress field of the surrounding rock combined with the geological model, and simulate the disturbance stress field according to the excavation plan to identify the high stress concentration area;

[0033] The verification unit is used to verify the location of the rupture source based on the position information of the rupture source obtained by inversion and the position relationship of the identified high stress concentration area.

[0034] A third aspect of an embodiment of the present application provides an electronic system, including a memory and a processor, wherein the processor is configured to implement the steps of the above-mentioned method for locating a rupture source based on multi-information fusion when executing a computer program stored in the memory.

[0035] A fourth aspect of the embodiments of the present application provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the steps of the above-mentioned method for locating a rupture source based on multi-information fusion are implemented.

[0036] In summary, the method for locating the rupture source based on multi-information fusion provided in the embodiment of the present application obtains microseismic waveform data based on a sensor network arranged in the surrounding rock, so as to invert the position information of the rupture source according to the microseismic waveform data; calculates the ground stress distribution based on the initial ground stress field of the surrounding rock combined with the geological model, and simulates the disturbance stress field according to the excavation plan to identify the high stress concentration area; and verifies the location of the rupture source according to the position relationship between the position information of the rupture source obtained by inversion and the identified high stress concentration area. Thus, by combining microseismic signals and stress field data, the positioning error is significantly reduced (from 10 meters to 1 meter). Stress field analysis provides the physical mechanism of the formation of the rupture source, which helps to predict the rupture trend. Accurately locating the rupture source helps to timely reinforce high-risk areas and prevent instability or disasters.

[0037] Correspondingly, the rupture source positioning device based on multi-information fusion, the electronic system and the computer-readable storage medium provided in the embodiments of the present invention also have the above-mentioned technical effects. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 A schematic flow chart of a possible method for locating a rupture source based on multi-information fusion provided in an embodiment of the present application;

[0039] Figure 2 A schematic structural block diagram of a possible rupture source positioning device based on multi-information fusion provided in an embodiment of the present application;

[0040] Figure 3A schematic diagram of the hardware structure of a possible rupture source positioning device based on multi-information fusion provided in an embodiment of the present application;

[0041] Figure 4 A schematic structural block diagram of a possible electronic system provided in an embodiment of the present application;

[0042] Figure 5 A schematic structural block diagram of a possible computer-readable storage medium provided for an embodiment of the present application. DETAILED DESCRIPTION

[0043] The embodiments of the present application provide a method and system for locating a rupture source based on multi-information fusion, which can solve the problem that in the construction of dams or underground hydraulic tunnels, surrounding rock rupture may cause leakage or collapse, affecting the safety of the project.

[0044] The terms "first", "second", "third", "fourth", etc. (if any) in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments described herein can be implemented in an order other than that illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices. The technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all of the embodiments.

[0045] See also Figure 1 , which is a flow chart of a rupture source positioning method based on multi-information fusion provided in an embodiment of the present application, and may specifically include: S110-S130.

[0046] S110, acquiring microseismic waveform data based on a sensor network arranged in the surrounding rock, so as to invert position information of the rupture source according to the microseismic waveform data.

[0047] S120, calculating the ground stress distribution based on the initial ground stress field of the surrounding rock combined with the geological model, and simulating the disturbed stress field according to the excavation plan to identify the high stress concentration area.

[0048] S130, verifying the location of the rupture source according to the position information of the rupture source obtained by inversion and the position relationship of the identified high stress concentration area.

[0049] It is understandable that the sensor network is used to collect microseismic waveform data in the surrounding rock, and the propagation characteristics of the seismic wave (arrival time difference, amplitude attenuation, etc.) are analyzed to invert the preliminary position of the rupture source. Based on the initial geostress field and geological model of the surrounding rock, the disturbance stress field caused by excavation or construction is simulated to identify the stress concentration area and its changes. The location of the rupture source obtained by microseismic inversion is compared with the location of the high stress concentration area, and coupling verification is performed to improve the positioning accuracy.

[0050] Exemplarily, a three-dimensional monitoring sensor network can be arranged in the engineering area (such as around the tunnel or the mining area) to form a monitoring system covering the target area. The points need to be evenly distributed, but more sensors are arranged in possible high stress concentration areas (such as corners or rock formation interfaces). Microseismic detectors can be used to collect microseismic waveforms (the measured bandwidth includes 1HZ-4000Hz), and the sampling frequency is at least 8kHz. The acquisition time of multiple sensors can be synchronized by the GPS clock. Short-time Fourier transform (STFT) or wavelet transform can be used to filter out background noise. Significant events are extracted by the STA / LTA algorithm and the arrival time and amplitude of the seismic wave are recorded. The source position is calculated using the wave propagation velocity v and the arrival time difference Δt. According to the wave attenuation principle, the source position is inferred by multi-point amplitude calculation. Then, the initial ground stress data is obtained through field tests (such as hydraulic fracturing and acoustic wave testing). The geological model provides rock formation distribution and mechanical parameters (such as elastic modulus, Poisson's ratio, etc.). The finite element method (FEM) or boundary element method (BEM) can be used to simulate the initial geostress field distribution. According to the engineering design, the excavation plan (such as tunnel section size, footage speed, etc.) and construction method (such as blasting, tunnel boring machine, etc.) can be input. Numerical methods (such as FEM) can be used to simulate the stress disturbance caused by excavation or construction. Identify the stress concentration area and define the location and range of the high stress area. The location of the rupture source from the microseismic inversion can be spatially compared with the high stress concentration area. If the location of the rupture source coincides with the high stress area, the accuracy of the rupture source positioning is verified. If the microseismic positioning deviates from the high stress area, the positioning result is optimized by adjusting the initial geostress field parameters (such as elastic modulus) or iteratively optimizing the perturbation stress field model.

[0051] For example, in the process of locating the source of surrounding rock fracture, there is a close relationship between the distribution of geostress and the source wave velocity model. The wave velocity characteristics (such as P-wave and S-wave velocities) in the rock mass are significantly affected by the geostress field, especially in areas of high stress concentration. This relationship can be introduced into the model of source location and stress field analysis to further optimize the accuracy and physical rationality of fracture source location. In the process of source location, geostress distribution information is introduced to dynamically adjust the wave velocity model so that the positioning results are more in line with actual physical conditions. Combined with geostress and disturbance stress field analysis, the spatial distribution of the velocity model is optimized. A non-uniform wave velocity model is established by coupling the geostress field to eliminate the influence of stress gradient on wave velocity. Through the coupling of the stress-velocity model, the positioning accuracy is improved from 10 meters to 1 meter, providing a more reliable basis for the risk assessment of fracture source expansion.

[0052] For example, there is a close physical relationship between the perturbed stress field and the apparent stress field (stress drop). The apparent stress field describes the magnitude of stress release in the source area, while the perturbed stress field reflects the impact range of the rupture on the surrounding rock and the stress redistribution. The coupling analysis of the two can more accurately describe the occurrence mechanism and expansion risk of surrounding rock rupture. The stress release in the source area (apparent stress field) is associated with the change in the surrounding stress distribution (perturbed stress field) to comprehensively describe the surrounding rock rupture mechanism. By simulating the perturbed stress field, high stress concentration areas are identified, and the possible extension direction and range of the rupture are accurately predicted. The apparent stress field corrects the velocity model to improve the accuracy of microseismic positioning. By coupling the apparent stress field with the perturbed stress field, the rupture parameters are dynamically corrected to improve the adaptability of the model.

[0053] In summary, the method for locating the rupture source based on multi-information fusion provided in the above-mentioned embodiment obtains microseismic waveform data based on a sensor network arranged in the surrounding rock, so as to invert the location information of the rupture source according to the microseismic waveform data; calculates the ground stress distribution based on the initial ground stress field of the surrounding rock combined with the geological model, and simulates the disturbance stress field according to the excavation plan to identify the high stress concentration area; and verifies the location of the rupture source according to the position relationship between the position information of the rupture source obtained by inversion and the identified high stress concentration area. Thus, by combining microseismic signals and stress field data, the positioning error is significantly reduced (from 10 meters to 1 meter). Stress field analysis provides the physical mechanism of the formation of the rupture source, which helps to predict the rupture trend. Accurately locating the rupture source helps to timely reinforce high-risk areas and prevent instability or disasters.

[0054] In one embodiment, it also includes:

[0055] Acquiring groundwater monitoring data, wherein the groundwater monitoring data is obtained based on sensors of groundwater monitoring holes arranged in the surrounding rock area;

[0056] Extracting abnormal change areas associated with abnormal change data in monitoring data;

[0057] The location of the rupture source is verified based on the positional relationship between the position information of the rupture source obtained by inversion and the extracted abnormal change area.

[0058] It is understandable that surrounding rock fractures will lead to the expansion and opening of rock mass fissures, significantly changing local permeability. Parameters such as groundwater velocity, water level, and seepage pressure change abnormally in the fracture area. The abnormal change area is extracted from the groundwater monitoring data to infer the range of disturbance of the fracture on the water flow. The spatial position of the microseismic fracture source obtained by inversion is compared with the abnormal groundwater change area to verify the positioning result.

[0059] For example, groundwater monitoring holes can be arranged in the surrounding rock area to cover the main fracture zones and potential fracture source locations in the target area. The monitoring holes need to cover multiple layers of hydrogeological units, and the arrangement density is determined according to the geological conditions and the scale of the project. Monitoring equipment such as water level gauges, seepage pressure sensors, and flow meters can be used. A real-time data acquisition and transmission system can be equipped to achieve continuous monitoring. Parameters such as groundwater level, water flow rate, and seepage pressure can be detected. High-frequency sampling (such as minute level) can be set to capture dynamic changes caused by fractures. Background fluctuation noise can be removed by sliding average method or Kalman filtering. Significant abnormal change data can be extracted by time series analysis (such as trend decomposition and mutation point detection). Abnormal features may include: water level changes, fractures may cause sudden increases or decreases in water levels; seepage pressure changes, fractures form hyperpermeable channels, and pressure fields are redistributed; flow rate abnormalities, and water flow is significantly accelerated in the fracture area. Project the abnormal points of the monitoring data into the spatial model to extract the spatial distribution of the abnormal change area. Use spatial interpolation methods (such as Kriging interpolation) to calibrate the range of the abnormal change area. Compare the spatial positions of the rupture sources obtained by microseismic inversion with the areas of abnormal groundwater changes. Positional relationships can include: coincidence, whether the rupture source is located in the area of ​​abnormal changes. And correlation, the distance relationship and trend direction between the rupture source and the abnormal area. Compare the degree of overlap between the rupture source location and the high stress concentration area and the groundwater abnormal area. If the three are consistent, verify the reliability of the rupture source positioning results. Therefore, abnormal groundwater changes provide an independent observation perspective for the rupture effect, which complements microseismic positioning. Combined with ground stress, high stress area distribution and abnormal groundwater changes, the credibility and scientificity of the positioning results are improved. Groundwater data not only verifies the location of the rupture source, but also provides a basis for risk assessment of rock permeability changes.

[0060] For example, suppose a rock burst occurs during mining in a deep mining area, and the rupture causes a sudden change in the flow direction of groundwater, and the location of the rupture source needs to be verified. Microseismic monitoring and positioning initially determined that the rupture source is located in a main stress concentration area at a certain depth. Groundwater monitoring found that the water level in the area suddenly dropped and the flow rate increased significantly. Through multi-information fusion analysis, it was confirmed that the location of the rupture source is highly coincident with the groundwater abnormal area. The positioning verification is accurate, providing a basis for construction adjustment and support reinforcement.

[0061] In one embodiment, extracting the abnormal change area associated with the abnormal change data in the monitoring data includes:

[0062] Extracting abnormally elevated areas associated with permeability in monitoring data;

[0063] The rupture source location verification is performed based on the positional relationship between the positional information of the rupture source obtained by inversion and the extracted abnormally elevated area, including:

[0064] The location of the rupture source is verified based on the positional relationship between the position information of the rupture source obtained by inversion and the extracted abnormally elevated area.

[0065] In one embodiment, extracting the abnormal change area associated with the abnormal change data in the monitoring data includes:

[0066] Extracting abnormally elevated areas associated with flow velocity in monitoring data;

[0067] The rupture source location verification is performed based on the positional relationship between the positional information of the rupture source obtained by inversion and the extracted abnormally elevated area, including:

[0068] The location of the rupture source is verified based on the positional relationship between the position information of the rupture source obtained by inversion and the extracted abnormally elevated area.

[0069] According to some embodiments, extracting the abnormal change area associated with the abnormal change data in the monitoring data includes:

[0070] Extract abnormal fluctuation areas associated with water levels in monitoring data;

[0071] The rupture source location verification is performed based on the positional relationship between the positional information of the rupture source obtained by inversion and the extracted abnormally elevated area, including:

[0072] The location of the rupture source is verified based on the positional relationship between the rupture source obtained by inversion and the extracted abnormal fluctuation area.

[0073] According to some embodiments, further comprising:

[0074] Extracting waveform features from the microseismic waveform data, wherein the waveform features include a P-wave and an S-wave amplitude ratio;

[0075] The fracture type of the surrounding rock is determined based on the waveform characteristics, and the fracture direction and extension trend are analyzed in combination with the ground stress distribution.

[0076] It is understandable that by extracting microseismic waveform features (including the amplitude ratio of P waves and S waves), the type of surrounding rock fracture is determined, and the fracture direction and expansion trend are analyzed in combination with the ground stress distribution. This method further improves the accuracy of fracture source positioning and helps predict the evolution path of surrounding rock fracture. The amplitude ratio of P waves (compression waves) and S waves (shear waves) is an important indicator for judging the type of fracture. High P wave amplitude ratios are mostly tension-type fractures. High S wave amplitude ratios are mostly shear-type fractures. The waveform characteristics also reflect the source mechanism of the fracture, such as double couples, blasting sources or composite fractures. The ground stress field controls the directionality and expansion trend of surrounding rock fractures. Combined with the fracture type, the possible development path of the fracture in the local stress concentration area can be inferred. Therefore, through the fusion analysis of waveform characteristics and stress distribution, the location error of the fracture source is significantly reduced. The positioning accuracy is improved from 10 meters for single microseismic positioning to 1-3 meters. Waveform feature analysis provides detailed information on the fracture mechanism (tension, shear, composite type) and reveals the cause of the fracture. The analysis of ground stress distribution combined with the rupture type can predict the development direction and impact range of the rupture, providing a basis for engineering prevention and control.

[0077] In some examples, the arrival time information of P and S waves and the choice of velocity model are key to optimizing the location of the rupture source. In particular, in the same medium, the influence of the ground stress field on the wave velocity is significant, so it is necessary to establish a coupling relationship between wave velocity and stress, so as to more accurately invert the location of the rupture source and optimize the physical rationality of the model.

[0078] According to some embodiments, further comprising:

[0079] Extract the stress drop, focal radius and rupture energy of the rupture source;

[0080] The potential extension risk of the rupture area is evaluated based on at least one parameter of stress drop, focal radius and rupture energy combined with the disturbed stress field.

[0081] It can be understood that stress drop is the magnitude of stress release in the source area, reflecting the severity of the rupture. The source radius is used to indicate the spatial range of the rupture area. The rupture energy can reflect the elastic energy released during the rupture process, indicating the rupture strength and the range of influence on the surrounding rock mass. The redistribution of stress fields caused by engineering excavation or other external disturbances will change the mechanical equilibrium state of the surrounding rock. The expansion risk of the rupture area depends on the interaction between the energy released by the rupture source and the area of ​​disturbed stress concentration. Therefore, through the coupling analysis of the rupture source parameters (stress drop, source radius, rupture energy) and the disturbed stress field, the possibility and risk level of rupture extension can be accurately quantified. On the basis of locating the rupture source, the possible evolution path of the rupture is predicted through parametric analysis to support dynamic adjustments in engineering construction. Based on the evaluation results, the surrounding rock reinforcement measures (such as anchor density and support strengthening) are optimized or the construction plan is adjusted.

[0082] Exemplarily, in the process of stress field modeling, the stress field modeling can also be optimized by the following methods: by discretizing the surrounding rock mechanical model, the three-dimensional distribution and change of the stress field are simulated. The boundary conditions are optimized in combination with the location of the fracture source to improve the physical rationality of the simulation. A coupling simulation is performed between the large scale (whole surrounding rock) and the small scale (local fracture source). The sub-model method is used to reduce the computational complexity. The actual measured values ​​of the ground stress field are used to optimize the initial stress field model through inversion to reduce the error of the disturbance stress field simulation. Among them, an overall finite element model (called the overall model) covering the entire engineering area can be established. Larger unit divisions are used in the overall model to reduce the amount of calculation. The stress, displacement and other physical quantities of the overall model are calculated. A high-precision local model (called a sub-model) is established in the area of ​​interest (such as the fracture source or high stress concentration area). The sub-model uses finer grid division and higher calculation accuracy to focus on analyzing the mechanical behavior of the local area. The calculation results of the overall model (such as displacement or force) are input as the boundary conditions of the sub-model. The boundary conditions of the sub-model are kept consistent with the overall model to ensure the coordination of local analysis and global behavior. Therefore, by combining the overall and local models, the sub-model method significantly reduces the calculation time and improves the overall efficiency by 30%-50%. Stress field inversion reduces simulation errors, and the sub-model accurately captures the stress concentration effect in the fracture source area, and the positioning accuracy is improved to 1-2 meters. Accurately predict the direction and range of fracture extension, providing a scientific basis for engineering design and risk control. The solution is applicable to a variety of engineering scenarios (such as mining, tunnel construction, etc.), and provides strong technical support for surrounding rock fracture monitoring and prevention.

[0083] For example, based on the sub-model results, combined with the rupture propagation equation: Where K I is the crack opening modulus, σ is the stress, α is the crack length, and Y is the geometric factor. I >K Ic (critical fracture toughness), the fracture is predicted to extend in the direction of high stress. Based on the detailed calculation results of the sub-model, the potential fracture extension risk area is calibrated.

[0084] See also Figure 2 In the embodiment of the present application, an embodiment of a rupture source positioning device based on multi-information fusion may include:

[0085] A positioning unit 201 is used to obtain microseismic waveform data based on a sensor network arranged in the surrounding rock, so as to invert the position information of the rupture source according to the microseismic waveform data;

[0086] An identification unit 202 is used to calculate the in-situ stress distribution based on the initial in-situ stress field of the surrounding rock in combination with the geological model, and simulate the disturbance stress field according to the excavation plan to identify the high stress concentration area;

[0087] The verification unit 203 is used to verify the location of the rupture source according to the position information of the rupture source obtained by inversion and the position relationship of the identified high stress concentration area.

[0088] In summary, the rupture source positioning device based on multi-information fusion provided in the above-mentioned embodiment obtains microseismic waveform data based on a sensor network arranged in the surrounding rock, so as to invert the location information of the rupture source according to the microseismic waveform data; calculates the ground stress distribution based on the initial ground stress field of the surrounding rock combined with the geological model, and simulates the disturbance stress field according to the excavation plan to identify the high stress concentration area; and verifies the location of the rupture source according to the position relationship between the position information of the rupture source obtained by inversion and the identified high stress concentration area. Thus, by combining microseismic signals and stress field data, the positioning error is significantly reduced (from 10 meters to 1 meter). Stress field analysis provides the physical mechanism of the formation of the rupture source, which helps to predict the rupture trend. Accurately locating the rupture source helps to timely reinforce high-risk areas and prevent instability or disasters.

[0089] above Figure 2 The rupture source locating device based on multi-information fusion in the embodiment of the present application is described from the perspective of modular functional entity. The rupture source locating device based on multi-information fusion in the embodiment of the present application is described in detail from the perspective of hardware processing. Please refer to Figure 3 , an embodiment of a rupture source positioning device 300 based on multi-information fusion in the embodiment of the present application includes:

[0090] An input device 301, an output device 302, a processor 303 and a memory 304, wherein the number of the processor 303 can be one or more. Figure 3 In some embodiments of the present application, the input device 301, the output device 302, the processor 303 and the memory 304 may be connected via a bus or other means, wherein: Figure 3 The example of connecting through bus is taken in the following.

[0091] By calling the operation instruction stored in the memory 304, the processor 303 is used to perform the following steps:

[0092] Acquiring microseismic waveform data based on a sensor network arranged in the surrounding rock, so as to invert the location information of the rupture source according to the microseismic waveform data;

[0093] The initial geostress field of the surrounding rock is combined with the geological model to calculate the geostress distribution, and the disturbed stress field is simulated according to the excavation plan to identify the high stress concentration area;

[0094] The location of the rupture source is verified based on the position information of the rupture source obtained by inversion and the positional relationship between the identified high stress concentration area.

[0095] By calling the operation instructions stored in the memory 304, the processor 303 is also used to execute Figure 1 Any method in the corresponding embodiment.

[0096] See also Figure 4 , Figure 4 A schematic diagram of an electronic system according to an embodiment of the present application.

[0097] like Figure 4 As shown, an embodiment of the present application provides an electronic system, including a memory 410, a processor 420, and a computer program 411 stored in the memory 410 and executable on the processor 420. When the processor 420 executes the computer program 411, the following steps are implemented:

[0098] Acquiring microseismic waveform data based on a sensor network arranged in the surrounding rock, so as to invert the location information of the rupture source according to the microseismic waveform data;

[0099] The initial geostress field of the surrounding rock is combined with the geological model to calculate the geostress distribution, and the disturbed stress field is simulated according to the excavation plan to identify the high stress concentration area;

[0100] The location of the rupture source is verified based on the position information of the rupture source obtained by inversion and the positional relationship between the identified high stress concentration area.

[0101] In the specific implementation process, when the processor 420 executes the computer program 411, it can achieve Figure 1 Any implementation manner in the corresponding embodiments.

[0102] Since the electronic system introduced in this embodiment is a device used to implement a rupture source positioning device based on multi-information fusion in the embodiment of the present application, based on the method introduced in the embodiment of the present application, the technical personnel in this field can understand the specific implementation mode of the electronic system of this embodiment and its various variations. Therefore, how the electronic system implements the method in the embodiment of the present application is not introduced in detail here. As long as the technical personnel in this field implement the method in the embodiment of the present application, the device adopted by the technical personnel in this field belongs to the scope of protection of this application.

[0103] See also Figure 5 , Figure 5 A schematic diagram of an embodiment of a computer-readable storage medium provided in an embodiment of the present application.

[0104] like Figure 5 As shown, this embodiment provides a computer-readable storage medium 500, on which a computer program 511 is stored. When the computer program 511 is executed by a processor, the following steps are implemented:

[0105] Acquiring microseismic waveform data based on a sensor network arranged in the surrounding rock, so as to invert the location information of the rupture source according to the microseismic waveform data;

[0106] The initial geostress field of the surrounding rock is combined with the geological model to calculate the geostress distribution, and the disturbed stress field is simulated according to the excavation plan to identify the high stress concentration area;

[0107] The location of the rupture source is verified based on the position information of the rupture source obtained by inversion and the positional relationship between the identified high stress concentration area.

[0108] In the specific implementation process, when the computer program 511 is executed by the processor, it can achieve Figure 1 Any implementation manner in the corresponding embodiments.

[0109] It should be noted that in the above embodiments, the description of each embodiment has its own emphasis, and for parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0110] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0111] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded computer, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0112] These computer program instructions may also be stored in a computer readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0113] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0114] The present application also provides a computer program product, which includes computer software instructions. When the computer software instructions are executed on a processing device, the processing device is caused to execute the following Figure 1 The process of the rupture source positioning method based on multi-information fusion in the corresponding embodiment.

[0115] The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions may be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions may be transmitted from a website site, a computer, a server, or a data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line (digital subscriber line, DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) mode to another website site, computer, server, or data center. The computer-readable storage medium may be any available medium that a computer can store or a data storage device such as a server or a data center that includes one or more available media integrated. The available medium may be a magnetic medium, (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a solid state disk (SSD)), etc.

[0116] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0117] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or units, which can be electrical, mechanical or other forms.

[0118] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0119] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0120] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (Read-Only Memory, ROM), random access memory (Random Access Memory, RAM), disk or optical disk and other media that can store program codes.

[0121] As described above, the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A method for locating a rupture source based on multi-information fusion, characterized in that: include: Acquiring microseismic waveform data based on a sensor network arranged in the surrounding rock, so as to invert the location information of the rupture source according to the microseismic waveform data; The initial geostress field of the surrounding rock is combined with the geological model to calculate the geostress distribution, and the disturbed stress field is simulated according to the excavation plan to identify the high stress concentration area; The location of the rupture source is verified based on the position information of the rupture source obtained by inversion and the positional relationship between the identified high stress concentration area.

2. The method according to claim 1, characterized in that Also includes: Acquiring groundwater monitoring data, wherein the groundwater monitoring data is obtained based on sensors of groundwater monitoring holes arranged in the surrounding rock area; Extracting abnormal change areas associated with abnormal change data in monitoring data; The location of the rupture source is verified based on the positional relationship between the position information of the rupture source obtained by inversion and the extracted abnormal change area.

3. The method according to claim 2, characterized in that The step of extracting the abnormal change area associated with the abnormal change data in the monitoring data includes: Extracting abnormally elevated areas associated with permeability in monitoring data; The rupture source location verification is performed based on the positional relationship between the positional information of the rupture source obtained by inversion and the extracted abnormally elevated area, including: The location of the rupture source is verified based on the positional relationship between the position information of the rupture source obtained by inversion and the extracted abnormally elevated area.

4. The method according to claim 2, characterized in that: The step of extracting the abnormal change area associated with the abnormal change data in the monitoring data includes: Extracting abnormally elevated areas associated with flow velocity in monitoring data; The rupture source location verification is performed based on the positional relationship between the positional information of the rupture source obtained by inversion and the extracted abnormally elevated area, including: The location of the rupture source is verified based on the positional relationship between the position information of the rupture source obtained by inversion and the extracted abnormally elevated area.

5. The method according to claim 2, characterized in that: The step of extracting the abnormal change area associated with the abnormal change data in the monitoring data includes: Extract abnormal fluctuation areas associated with water levels in monitoring data; The rupture source location verification is performed based on the positional relationship between the positional information of the rupture source obtained by inversion and the extracted abnormally elevated area, including: The location of the rupture source is verified based on the positional relationship between the rupture source obtained by inversion and the extracted abnormal fluctuation area.

6. The method according to claim 1, characterized in that Also includes: Extracting waveform features from the microseismic waveform data, wherein the waveform features include a P-wave and an S-wave amplitude ratio; The fracture type of the surrounding rock is determined based on the waveform characteristics, and the fracture direction and extension trend are analyzed in combination with the ground stress distribution.

7. The method according to claim 6, characterized in that Also includes: Extract the apparent stress, focal radius and rupture energy of the rupture source; The potential extension risk of the rupture area is evaluated based on at least one parameter of stress drop, focal radius and rupture energy combined with the disturbed stress field.

8. A rupture source positioning device based on multi-information fusion, characterized in that: include: A positioning unit, used to obtain microseismic waveform data based on a sensor network arranged in the surrounding rock, so as to invert the position information of the rupture source according to the microseismic waveform data; Identification unit, used to calculate the ground stress distribution based on the initial ground stress field of the surrounding rock combined with the geological model, and simulate the disturbance stress field according to the excavation plan to identify the high stress concentration area; The verification unit is used to verify the location of the rupture source based on the position information of the rupture source obtained by inversion and the position relationship of the identified high stress concentration area.

9. An electronic system, comprising a memory and a processor, characterized in that: The processor is used to implement the steps of the rupture source positioning method based on multi-information fusion as described in any one of claims 1 to 7 when executing the computer program stored in the memory.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method for locating a rupture source based on multi-information fusion according to any one of claims 1 to 7 are implemented.

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