Well-ground combined micro-seismic monitoring method and device

Abstract

The invention discloses a well-ground combined micro-seismic monitoring method and device. The well-ground combined micro-seismic monitoring method comprises the following steps: constructing an underground monitoring network and a ground monitoring network; acquiring first vibration data monitored by the underground monitoring network, and performing time synchronization on the first vibration data through a GPS to obtain second vibration data; identifying a micro-seismic event based on the second vibration data to obtain first micro-seismic event data; acquiring third vibration data monitored by the ground monitoring network, and identifying a micro-seismic event based on the third vibration data to obtain second micro-seismic event data; and based on the first micro-seismic event data and the second micro-seismic event data, performing calculation and positioning by using an equivalent gradient velocity model, and determining a seismic source coordinate. According to the method, the micro-seismic positioning precision is improved, and the method plays a positive role in promoting the development of rock burst prediction and prevention and control technologies.

Description

Technical Field

[0001] This invention relates to the field of microseismic monitoring technology, and in particular to a well-ground combined microseismic monitoring method and device. Background Technology

[0002] During underground coal mining, the original stress balance is disrupted after the coal seam is extracted. Stress is redistributed and acts on the surrounding coal and rock mass and the roadway support structure, thus creating mine pressure. When the mine pressure borne by the surrounding rock exceeds the support resistance provided by the support structure, it can lead to roadway deformation, floor heave, spalling, or even complete collapse, easily triggering serious safety accidents and threatening miners' lives and normal mine production. Therefore, mine monitoring is necessary to determine the coordinates of seismic sources and prevent safety accidents.

[0003] In related technologies, sensor arrays deployed around mining areas capture micro-seismic waves generated when coal and rock masses fracture. These waves are then used to calculate the location, timing, and energy parameters of dynamic loads. Analysis of these parameters allows for real-time monitoring of high-stress concentration zones and rock strata activity patterns underground, providing a scientific basis for predicting and preventing dynamic disasters such as rockbursts and coal and gas outbursts. However, in near-horizontal coal seam mining, underground roadways are typically located within approximately the same level of coal or rock strata. Consequently, the microseismic sensor arrays used to receive signals can only be deployed on an approximately two-dimensional plane, resulting in a very limited vertical coverage of the monitoring network and a small vertical drop between sensors. This reduces the accuracy of microseismic positioning, failing to meet the needs of on-site monitoring, hindering the application of microseismic monitoring technology, and impacting research and prevention efforts for mine rockbursts. Summary of the Invention

[0004] The present invention aims to at least partially solve one of the technical problems in the related art.

[0005] To this end, the present invention proposes a well-ground combined microseismic monitoring method and device, which can calculate and locate the source coordinates based on the first microseismic event data obtained from the downhole monitoring network and the second microseismic event data obtained from the ground monitoring network, using an equivalent gradient velocity model. This effectively improves the accuracy of microseismic location and will play a positive role in promoting the development of rockburst prediction, forecasting and prevention technology.

[0006] To achieve the above objectives, the present invention proposes a well-ground combined microseismic monitoring method, the method comprising: Construct downhole monitoring networks and surface monitoring networks; The first vibration data monitored by the downhole monitoring network is acquired, and the second vibration data is obtained by time synchronization of the first vibration data with GPS. Micro-seismic events are identified based on the second vibration data to obtain the first micro-seismic event data; The third vibration data monitored by the ground monitoring network is acquired, and micro-vibration events are identified based on the third vibration data to obtain the second micro-vibration event data; Based on the first and second microseismic event data, the equivalent gradient velocity model is used for calculation and location to determine the source coordinates.

[0007] The well-to-surface combined microseismic monitoring method of this invention may also have the following additional technical features: In one embodiment of the present invention, the step of identifying microseismic events based on the second vibration data to obtain first microseismic event data includes: Based on the first average amplitude of the second vibration data within a first time window and the second average amplitude of the second vibration data within a second time window, wherein the time of the second time window is longer than that of the first time window; The first micro-vibration event is identified based on the ratio of the first average amplitude to the second average amplitude. Determine the first target time window for the first microseismic event; Based on the data segment corresponding to the first target time window, the data of the first microseismic event is obtained.

[0008] In one embodiment of the present invention, the step of identifying microseismic events based on the third vibration data to obtain second microseismic event data includes: The third vibration data is denoised to obtain the processed fourth vibration data; The fourth vibration data is input into the target event recognition model to identify the second micro-vibration event; Determine the second target time window for the second microseismic event; Based on the data segment corresponding to the second target time window, the data of the second microseismic event is obtained.

[0009] In one embodiment of the present invention, the at least one data feature value includes: maximum value, minimum value, mean, mode, median, skewness, kurtosis, starting value, ending value, data volume within the error range of the maximum value, and data volume within the error range of the mode.

[0010] In one embodiment of the present invention, the step of determining the source coordinates by calculating and locating using an equivalent gradient velocity model based on the first microseismic event data and the second microseismic event data includes: The target microseismic event data is obtained by aligning the first microseismic event data and the second microseismic event data. Based on the target microseismic event data and the preset wave velocity, the source is located first, and the coordinates of the first source are obtained. The first source distance of each sensor is calculated based on the first source coordinates, and the second source coordinates are obtained by performing a second location of the source based on the first source distance. The first source-detection distance of each sensor is corrected based on the second source coordinates to obtain the second source-detection distance, and the preset wave velocity is corrected by the second source-detection distance through the equivalent gradient wave velocity model to obtain the corrected wave velocity. Repeat the above positioning and correction steps until the preset number of iterations is reached, and then determine the second source coordinates as the target source coordinates.

[0011] In one embodiment of the present invention, the equivalent gradient wave velocity model includes: V= K0+ K1x + K2x² + K3x³ + K4x 4 Where V is the corrected wave velocity, x is the average value of the second source-detection distance, and K0~K4 are the polynomial coefficients determined by fitting measured data.

[0012] In one embodiment of the present invention, the step of correcting the preset wave velocity using the second source-detector distance through an equivalent gradient wave velocity model to obtain the corrected wave velocity includes: Obtain the correspondence table between source-detection distance and beam velocity; Determine the two adjacent source detection distances of the second source detection distance in the relation table; Linear interpolation is performed between the wave velocities corresponding to the two adjacent source-detector distances in the relation table to determine the corresponding wave velocities, and the average value of the obtained wave velocities is determined as the corrected wave velocities.

[0013] In one embodiment of the present invention, the downhole monitoring network includes: Underground vibration sensors are deployed in the mine based on a preset spacing. The underground vibration sensors are velocity sensors or acceleration sensors, which are installed on the roof, floor or sidewalls of the mine roadway.

[0014] To achieve the above objectives, another aspect of the present invention provides a well-to-surface combined microseismic monitoring device, the device comprising: The building module is used to construct downhole monitoring networks and surface monitoring networks; The acquisition module is used to acquire the first vibration data monitored by the downhole monitoring network, and to obtain the second vibration data by synchronizing the first vibration data with GPS. The first identification module is used to identify micro-vibration events based on the second vibration data to obtain first micro-vibration event data; The second identification module is used to acquire the third vibration data monitored by the ground monitoring network, and to identify micro-vibration events based on the third vibration data to obtain the second micro-vibration event data. The determination module is used to calculate and locate the source coordinates based on the first microseismic event data and the second microseismic event data using an equivalent gradient velocity model.

[0015] The well-to-surface combined microseismic monitoring method and apparatus of this invention constructs a downhole monitoring network and a surface monitoring network; acquires first vibration data monitored by the downhole monitoring network, and obtains second vibration data by time synchronization of the first vibration data with GPS; identifies microseismic events based on the second vibration data, obtaining first microseismic event data; acquires third vibration data monitored by the surface monitoring network, and identifies microseismic events based on the third vibration data, obtaining second microseismic event data; and calculates and locates the source coordinates using an equivalent gradient velocity model based on the first and second microseismic event data. Therefore, this invention can determine the source coordinates by calculating and locating the source based on the first microseismic event data obtained from the downhole monitoring network and the second microseismic event data obtained from the surface monitoring network using an equivalent gradient velocity model, thereby effectively improving the accuracy of microseismic location and playing a positive role in promoting the development of rockburst prediction, forecasting, and prevention technologies.

[0016] Additional aspects and advantages of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description

[0017] The above and / or additional aspects and advantages of the present invention will become apparent and readily understood from the following description of the embodiments taken in conjunction with the accompanying drawings, wherein: Figure 1 This is a schematic flowchart of a well-ground combined microseismic monitoring method according to an embodiment of the present invention; Figure 2 This is a schematic diagram of source-detection distance and beam velocity according to an embodiment of the present invention; Figure 3 This is a schematic diagram of the structure of a well-ground combined microseismic monitoring device according to an embodiment of the present invention. Detailed Implementation

[0018] It should be noted that, unless otherwise specified, the embodiments and features described in the present invention can be combined with each other. The present invention will now be described in detail with reference to the accompanying drawings and embodiments.

[0019] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0020] The following description, with reference to the accompanying drawings, illustrates a well-to-surface combined microseismic monitoring method and apparatus according to embodiments of the present invention.

[0021] Figure 1 This is a schematic flowchart of the well-ground combined microseismic monitoring method according to an embodiment of the present invention.

[0022] like Figure 1 As shown, the method may include the following steps: Step 101: Construct downhole monitoring networks and surface monitoring networks.

[0023] In one embodiment of the present invention, the underground monitoring network may include: arranging underground vibration sensors in the mine based on a preset spacing, wherein the underground vibration sensors are velocity sensors or acceleration sensors, and are installed on the roof, floor or sidewalls of the mine roadway.

[0024] In one embodiment of the present invention, the aforementioned preset arrangement spacing can be set as needed, such as 200m. Also, in one embodiment of the present invention, the number of underground vibration sensors deployed throughout the mine can be 16 to 48.

[0025] In one embodiment of the present invention, multiple ground microseismic monitoring stations can be installed on the surface above the mining area, and a ground monitoring network can be constructed based on these stations. Each ground microseismic monitoring station may include: a microseismic sensor, a data acquisition device, a GPS timing device, and a wireless transmission device. Furthermore, the horizontal monitoring radius of a single ground microseismic monitoring station is greater than 1000m.

[0026] Step 102: Obtain the first vibration data monitored by the downhole monitoring network, and obtain the second vibration data by synchronizing the first vibration data with GPS.

[0027] In one embodiment of the present invention, after obtaining the first vibration data monitored by the downhole monitoring network through the downhole monitoring network in the above steps, the second vibration data can be obtained by time synchronization of the first vibration data through GPS.

[0028] In one embodiment of the present invention, the first vibration data may include P-wave arrival data and amplitude.

[0029] In one embodiment of the present invention, the GPS can provide a high-precision UTC timestamp and precisely align the high-precision UTC timestamp provided by the GPS with the data points in the first vibration data.

[0030] Step 103: Identify micro-seismic events based on the second vibration data to obtain the first micro-seismic event data.

[0031] In one embodiment of the present invention, after obtaining the second vibration data through the above steps, micro-vibration events can be identified based on the second vibration data to obtain the first micro-vibration event data.

[0032] In one embodiment of the present invention, the method for identifying microseismic events based on second vibration data and obtaining first microseismic event data may include the following steps: Step 1031: Based on the first average amplitude of the second vibration data within the first time window and the second average amplitude of the second vibration data within the second time window, wherein the time of the second time window is longer than that of the first time window.

[0033] Step 1032: Identify the first micro-seismic event based on the ratio of the first average amplitude to the second average amplitude.

[0034] In one embodiment of the present invention, the method for identifying a first micro-vibration event based on the ratio of a first average amplitude to a second average amplitude may include: if the ratio of the first average amplitude to the second average amplitude is greater than a preset threshold, then the first micro-vibration event is identified.

[0035] Step 1033: Determine the first target time window for the first microseismic event.

[0036] In one embodiment of the present invention, after the first microseismic event is identified through the above steps, the first target time window corresponding to the first microseismic event can be determined.

[0037] Step 1034: Obtain the data of the first microseismic event based on the data segment corresponding to the first target time window.

[0038] In one embodiment of the present invention, after determining the first target time window through the above steps, the data segment corresponding to the first target time window is determined as the first microseismic event data.

[0039] Step 104: Obtain the third vibration data monitored by the ground monitoring network, and identify microseismic events based on the third vibration data to obtain the second microseismic event data.

[0040] In one embodiment of the present invention, vibration data is monitored by microseismic sensors and acquisition devices in ground microseismic monitoring stations in a ground monitoring network, and the monitored vibration data is synchronized with time by a GPS timing device, and the time-synchronized vibration data is determined as the third vibration data.

[0041] Furthermore, in one embodiment of the present invention, the method for identifying microseismic events based on third vibration data and obtaining second microseismic event data may include the following steps: Step 1041: Denoise the third vibration data to obtain the processed fourth vibration data.

[0042] Step 1042: Input the fourth vibration data into the target event recognition model to identify the second micro-seismic event.

[0043] Step 1043: Determine the second target time window for the second microseismic event.

[0044] Step 1044: Obtain the second microseismic event data based on the data segment corresponding to the second target time window.

[0045] In one embodiment of the present invention, the third vibration data can be denoised using a denoising algorithm (such as frequency-wavenumber filtering FK) to obtain the processed fourth vibration data.

[0046] Furthermore, in one embodiment of the present invention, the aforementioned target time recognition model can be trained using historical data. In another embodiment, the input to the target time recognition model is fourth vibration data, and the output is the probability that the fourth vibration data is a "micro-vibration event" or "noise," with the type corresponding to the higher probability being determined as the type corresponding to the fourth vibration data. In another embodiment, the aforementioned target event recognition model can be a convolutional neural network (CNN).

[0047] Furthermore, in one embodiment of the present invention, after determining the second microseismic event through the above steps, a second target time window of the second microseismic event can be determined, and the second microseismic event data can be obtained based on the data segment corresponding to the second target time window.

[0048] Step 105: Based on the data from the first and second microseismic events, the equivalent gradient velocity model is used to calculate and locate the source coordinates.

[0049] In one embodiment of the present invention, after determining the first microseismic event data and the second microseismic event data through the above steps, the source coordinates can be determined by using the equivalent gradient velocity model based on the first microseismic event data and the second microseismic event data.

[0050] In one embodiment of the present invention, the method for determining the source coordinates based on first and second microseismic event data and using an equivalent gradient velocity model for calculation and location may include the following steps: Step 1051: Align the first microseismic event data and the second microseismic event data to obtain the target microseismic event data.

[0051] In one embodiment of the present invention, the method for obtaining target microseismic event data by aligning first microseismic event data and second microseismic event data may include: determining whether the first microseismic event data and the second microseismic event data are the same physical event, and determining the first microseismic event data and the second microseismic event data corresponding to the same physical event as the target microseismic event data.

[0052] Step 1052: Based on the target microseismic event data and the preset wave velocity, the source is located for the first time, and the coordinates of the first source are obtained.

[0053] In one embodiment of the present invention, the aforementioned target microseismic event data can be obtained by each sensor recording the arrival time T of the P-wave of the microseismic event. i .

[0054] Furthermore, in one embodiment of the present invention, the coordinates of each sensor in the downhole monitoring network and the surface monitoring network are obtained.

[0055] Furthermore, a preset wave velocity (e.g., 4000 m / s) can be determined based on the density of the downhole rock.

[0056] Furthermore, in one embodiment of the present invention, a mathematical model can be established using the relative travel time difference method, and the coordinates of the first seismic source can be obtained by solving the model using the least squares method. For details regarding the relative travel time difference method and the least squares method, please refer to existing technologies; these will not be elaborated upon here.

[0057] Step 1053: Calculate the first source distance to each sensor based on the first source coordinates, and perform a second source positioning based on the first source distance to obtain the second source coordinates.

[0058] In one embodiment of the present invention, the distance from the source to the coordinates of each sensor (including downhole and surface) can be calculated based on the coordinates of the first source, i.e., the first source-sensor distance.

[0059] Furthermore, in one embodiment of the present invention, the method for performing a second location of the seismic source based on the first source distance to obtain the second source coordinates may include: constructing an objective function based on the first source distance and calculating it using the Gauss-Newton method to obtain the second source coordinates.

[0060] In one embodiment of the present invention, the objective function can be: F(S) = Σ [ T i - t i (S) ]² Among them, t i (S) represents the theoretical travel time of the i-th sensor, and T represents the theoretical travel time of the i-th sensor. i Let be the measured travel time of the i-th sensor, where t i (S) = D i / V0,D i Let V0 be the first source-detection distance of the i-th sensor, V0 be the preset wave velocity, and S be the coordinates of the first seismic source.

[0061] Step 1054: Based on the coordinates of the second source, the first source distance of each sensor is corrected to obtain the second source distance, and the preset wave velocity is corrected by the second source distance through the equivalent gradient wave velocity model to obtain the corrected wave velocity.

[0062] In one embodiment of the present invention, after obtaining the second source coordinates through the above steps, the first source distance of each sensor can be corrected based on the second source coordinates to obtain the second source distance.

[0063] In one embodiment of the present invention, the above-mentioned equivalent gradient wave velocity model can be: V= K0+ K1x + K2x² + K3x³ + K4x 4 Where V is the corrected wave velocity, x is the average value of the second source-detection distance, and K0~K4 are the polynomial coefficients determined by fitting measured data.

[0064] In another embodiment of the present invention, the method described above for correcting a preset wave velocity using a second source-detector distance through an equivalent gradient wave velocity model to obtain a corrected wave velocity may include the following steps: Step 1: Obtain the correspondence table between source-detector distance and beam velocity; Step 2: Determine the two adjacent source distances of the second source distance in the relation table; Step 3: Perform linear interpolation between the wave velocities corresponding to the two adjacent source-receiver distances in the relationship table to determine the corresponding wave velocity, and determine the average value of the obtained wave velocity as the corrected wave velocity.

[0065] In one embodiment of the present invention, a correspondence table between source-receiver distance and wave velocity can be obtained based on different source-receiver distances and wave velocities obtained from field measurements. Table 1 shows the correspondence table between source-receiver distance and wave velocity.

[0066] Table 1

[0067] Example, Figure 2This is a schematic diagram illustrating the source-detection distance and beam velocity proposed in an embodiment of the present invention. Figure 2 As shown, assume the second source-detection distance d n If the distance is between 500m and 1000m, then the second source-detection distance d n Corresponding wave speed .

[0068] Furthermore, in one embodiment of the present invention, the average value of the wave velocity obtained from each second source ranging is determined as the corrected wave velocity.

[0069] Step 1055: Repeat the above positioning and correction steps until the preset number of iterations is reached, and determine the obtained second source coordinates as the target source coordinates.

[0070] In one embodiment of the present invention, after determining the corrected velocity through the above steps, the above positioning and correction steps 1052 to 1054 can be repeated until a preset number of iterations is reached, and the obtained second source coordinates are determined as the target source coordinates. In one embodiment of the present invention, the above preset number of iterations can be set as needed, such as 100.

[0071] The well-to-surface combined microseismic monitoring method of this invention constructs a downhole monitoring network and a surface monitoring network; acquires first vibration data monitored by the downhole monitoring network, and obtains second vibration data by time synchronization of the first vibration data with GPS; identifies microseismic events based on the second vibration data, obtaining first microseismic event data; acquires third vibration data monitored by the surface monitoring network, and identifies microseismic events based on the third vibration data, obtaining second microseismic event data; and calculates and locates the source coordinates using an equivalent gradient velocity model based on the first and second microseismic event data. Therefore, this invention can determine the source coordinates by calculating and locating the source based on the first microseismic event data obtained from the downhole monitoring network and the second microseismic event data obtained from the surface monitoring network using an equivalent gradient velocity model, thereby effectively improving the accuracy of microseismic location and playing a positive role in promoting the development of rockburst prediction, forecasting, and prevention technologies.

[0072] Figure 3 This is a schematic diagram of the structure of the well-ground combined microseismic monitoring device according to an embodiment of the present invention.

[0073] like Figure 3 As shown, the device may include: Module 301 is used to build downhole monitoring networks and surface monitoring networks; The acquisition module 302 is used to acquire the first vibration data monitored by the downhole monitoring network, and to obtain the second vibration data by synchronizing the first vibration data with GPS in time. The first identification module 303 is used to identify micro-vibration events based on the second vibration data and obtain the first micro-vibration event data. The second identification module 304 is used to acquire the third vibration data monitored by the ground monitoring network, and identify micro-vibration events based on the third vibration data to obtain the second micro-vibration event data. The determination module 305 is used to calculate and locate the source coordinates based on the first microseismic event data and the second microseismic event data using an equivalent gradient velocity model.

[0074] In one embodiment of the present invention, the first identification module 303 is specifically used for: The second vibration data is based on the first average amplitude within the first time window and the second average amplitude within the second time window, wherein the second time window is longer than the first time window. The first microseismic event is identified based on the ratio of the first average amplitude to the second average amplitude. Determine the first target time window for the first microseismic event; The data for the first microseismic event is obtained based on the data segment corresponding to the first target time window.

[0075] In one embodiment of the present invention, the second identification module 304 is specifically used for: The third vibration data is denoised to obtain the processed fourth vibration data. The fourth vibration data is input into the target event identification model to identify the second micro-seismic event; Determine the second target time window for the second microseismic event; The data for the second microseismic event are obtained based on the data segment corresponding to the second target time window.

[0076] In one embodiment of the present invention, the determining module 305 is specifically used for: The target microseismic event data is obtained by aligning the data from the first and second microseismic events. Based on the target microseismic event data and the preset wave velocity, the source is located first, and the coordinates of the first source are obtained. The first source distance of each sensor is calculated based on the first source coordinates, and the second source coordinates are obtained by performing a second location of the source based on the first source distance. The second source distance is obtained by correcting the first source distance of each sensor based on the second source coordinates, and the preset wave velocity is corrected by the second source distance through the equivalent gradient wave velocity model to obtain the corrected wave velocity. Repeat the above positioning and correction steps until the preset number of iterations is reached, and then determine the second source coordinates as the target source coordinates.

[0077] In one embodiment of the present invention, the above-mentioned equivalent gradient wave velocity model includes: V= K0+ K1x + K2x² + K3x³ + K4x 4 Where V is the corrected wave velocity, x is the average value of the second source-detection distance, and K0~K4 are the polynomial coefficients determined by fitting measured data.

[0078] In one embodiment of the present invention, the determining module 305 is specifically used for: Obtain the correspondence table between source-detection distance and beam velocity; Determine the two adjacent source distances in the relation table for the second source distance; Linear interpolation is performed between the wave velocities corresponding to the two adjacent source-detector distances in the relation table to determine the corresponding wave velocity, and the average value of the obtained wave velocity is determined as the corrected wave velocity.

[0079] In one embodiment of the present invention, the downhole monitoring network includes: Underground vibration sensors are deployed in the mine based on a preset spacing. The underground vibration sensors are velocity sensors or acceleration sensors, which are installed on the roof, floor or sidewalls of the mine roadway.

[0080] The well-to-surface combined microseismic monitoring device of this invention constructs a downhole monitoring network and a surface monitoring network; acquires first vibration data monitored by the downhole monitoring network, and obtains second vibration data by time synchronization of the first vibration data with GPS; identifies microseismic events based on the second vibration data, obtaining first microseismic event data; acquires third vibration data monitored by the surface monitoring network, and identifies microseismic events based on the third vibration data, obtaining second microseismic event data; and calculates and locates the source coordinates using an equivalent gradient velocity model based on the first and second microseismic event data. Therefore, this invention can determine the source coordinates by calculating and locating the source based on the first microseismic event data obtained from the downhole monitoring network and the second microseismic event data obtained from the surface monitoring network using an equivalent gradient velocity model, thereby effectively improving the accuracy of microseismic location and playing a positive role in promoting the development of rockburst prediction, forecasting, and prevention technologies.

[0081] In this specification, the use of terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., refers to a specific feature, structure, material, or characteristic described in connection with that embodiment or example, which is included in at least one embodiment or example of the invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0082] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this invention, "a plurality of" means at least two, such as two, three, etc., unless otherwise explicitly specified.

Claims

1. A method for well-to-surface microseismic monitoring, characterized in that, The method comprises the following steps: constructing a downhole monitoring network and a ground monitoring network; acquiring first vibration data monitored by the downhole monitoring network, and performing time synchronization on the first vibration data through GPS to obtain second vibration data; identifying microseismic events based on the second vibration data to obtain first microseismic event data; acquiring third vibration data monitored by the ground monitoring network, and identifying microseismic events based on the third vibration data to obtain second microseismic event data; based on the first microseismic event data and the second microseismic event data, performing calculation and positioning by using an equivalent gradient velocity model to determine a source coordinate.

2. The method of claim 1, wherein, The step of identifying microseismic events based on the second vibration data to obtain first microseismic event data comprises the following steps: based on a first average amplitude of the second vibration data within a first time window and a second average amplitude of the second vibration data within a second time window, wherein the time of the second time window is greater than that of the first time window; based on a ratio of the first average amplitude to the second average amplitude, identifying a first microseismic event; determining a first target time window of the first microseismic event; based on a data segment corresponding to the first target time window, obtaining first microseismic event data.

3. The method of claim 1, wherein, The step of identifying microseismic events based on the third vibration data to obtain second microseismic event data comprises the following steps: performing denoising processing on the third vibration data to obtain fourth vibration data; inputting the fourth vibration data into a target event identification model to identify a second microseismic event; determining a second target time window of the second microseismic event; based on a data segment corresponding to the second target time window, obtaining second microseismic event data.

4. The method of claim 1, wherein, The step of based on the first microseismic event data and the second microseismic event data, performing calculation and positioning by using an equivalent gradient velocity model to determine a source coordinate comprises the following steps: aligning the first microseismic event data and the second microseismic event data to obtain target microseismic event data; performing first positioning on a source based on the target microseismic event data and a preset wave velocity to obtain first source coordinates; based on the first source coordinates, calculating first source-geophone distances to each sensor and performing second positioning on the source based on the first source-geophone distances to obtain second source coordinates; based on the second source coordinates, modifying the first source-geophone distances to obtain second source-geophone distances, and modifying the preset wave velocity by using the second source-geophone distances through an equivalent gradient wave velocity model to obtain a modified wave velocity; repeating the positioning and modification steps until a preset iteration number is reached, and determining the obtained second source coordinates as target source coordinates.

5. The method of claim 4, wherein, The equivalent gradient wave velocity model comprises: V = K0+ K1x + K2x² + K3x³ + K4x 4 wherein V is the modified wave velocity, x is an average value of the second source-geophone distances, and K0-K4 are polynomial coefficients determined through fitting of measured data.

6. The method of claim 4, wherein, The step of modifying the preset wave velocity by using the second source-geophone distances through an equivalent gradient wave velocity model to obtain a modified wave velocity comprises the following steps: acquiring a corresponding relationship table of source-geophone distances and wave velocities; determining two adjacent source-geophone distances of the second source-geophone distances in the relationship table; Linear interpolation is performed between the corresponding wave velocities of the two adjacent source-receiver distances in the relationship table to determine the corresponding wave velocity, and an average of the obtained wave velocities is determined as the corrected wave velocity.

7. The method of claim 1, wherein, The downhole monitoring network comprises: The downhole vibration sensors are velocity sensors or acceleration sensors, and are installed on the roof, floor or side of the roadway of the mine.

8. A borehole-to-surface microseismic monitoring device, characterized in that, Comprise: The construction module is configured to construct the downhole monitoring network and the ground monitoring network; The acquisition module is configured to acquire first vibration data monitored by the downhole monitoring network, and perform time synchronization on the first vibration data to obtain second vibration data by using GPS; The first identification module is configured to identify microseismic events based on the second vibration data to obtain first microseismic event data; The second identification module is configured to acquire third vibration data monitored by the ground monitoring network, and identify microseismic events based on the third vibration data to obtain second microseismic event data; The determination module is configured to calculate and position by using an equivalent gradient velocity model based on the first microseismic event data and the second microseismic event data, and determine a source coordinate. 9.An electronic device comprising: at least one processor; and a memory connected with the at least one processor in communication; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-7.

10. A computer storage medium, wherein, The computer storage medium stores computer executable instructions; the computer executable instructions are executed by the processor to realize the method in any one of claims 1-7. The computer storage medium stores computer executable instructions; the computer executable instructions are executed by the processor to realize the method in any one of claims 1-7.

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