Method and device for locating microseismic events

Abstract

The application provides a microseismic event positioning method and device, and relates to the technical field of intelligent mine safety. The method comprises the following steps: grouping receivers associated with a target monitoring area according to a set geometric constraint condition to obtain a plurality of receiver groups; for each receiver group, determining a time domain focusing function of the receiver group based on time domain signals collected by receivers in the group; determining an energy normalization coefficient of the receiver group according to the time domain focusing function of the receiver group; determining a spatial attenuation factor of the receiver group according to position information of the receiver group and the target monitoring area; performing cross-group weighted fusion on the plurality of receiver groups according to the energy normalization coefficient and the spatial attenuation factor of the receiver group to obtain an initial source imaging result of the target monitoring area; and positioning a microseismic event of the target monitoring area according to the initial source imaging result to determine the spatial position of the microseismic event. The application can improve imaging accuracy and the monitoring accuracy of the microseismic event.

Description

Technical Field

[0001] This application relates to the field of intelligent mining technology, and in particular to a method and apparatus for locating microseismic events. Background Technology

[0002] In the coal industry, it is necessary to locate microseismic events, predict potential geological disasters such as collapses, and avoid safety accidents. Summary of the Invention

[0003] The purpose of this application is to at least partially solve one of the technical problems in the related art.

[0004] Therefore, the first objective of this application is to propose a method for locating microseismic events, which can enable real-time monitoring of large-scale microseismic events, thereby significantly shortening imaging time and improving monitoring efficiency.

[0005] The second objective of this application is to propose a device for locating microseismic events.

[0006] The third objective of this application is to propose an electronic device.

[0007] The fourth objective of this application is to provide a computer-readable storage medium.

[0008] The fifth objective of this application is to provide a computer program product.

[0009] To achieve the above objectives, the first aspect of this application proposes a method for locating microseismic events, comprising:

[0010] The receivers associated with the target monitoring area are grouped according to the set geometric constraints to obtain multiple receiver groups;

[0011] For each receiver group, the time-domain focusing function of the receiver group is determined based on the time-domain signals acquired by the receivers within the group;

[0012] The energy normalization coefficient of the receiver group is determined based on the time-domain focusing function of the receiver group;

[0013] Based on the location information of the receiver group and the target monitoring area, the spatial attenuation factor of the receiver group is determined;

[0014] Based on the energy normalization coefficient and spatial attenuation factor of the receiver group, cross-group weighted fusion is performed on the multiple receiver groups to obtain the initial source imaging results of the target monitoring area.

[0015] Based on the initial source imaging results, microseismic events are located in the target monitoring area to determine their spatial location.

[0016] To achieve the above objectives, a third aspect of this application provides a microseismic event location device, comprising:

[0017] The grouping module is used to group the receivers associated with the target monitoring area according to the set geometric constraints to obtain multiple receiver groups;

[0018] The first determining module is used to determine the time-domain focusing function of each receiver group based on the time-domain signals collected by the receivers within the group.

[0019] The second determining module is used to determine the energy normalization coefficient of the receiver group based on the time-domain focusing function of the receiver group;

[0020] The third determining module is used to determine the spatial attenuation factor of the receiver group based on the location information of the receiver group and the target monitoring area;

[0021] The fusion module is used to perform cross-group weighted fusion of the multiple receiver groups based on the energy normalization coefficient and spatial attenuation factor of the receiver groups to obtain the initial source imaging results of the target monitoring area.

[0022] The positioning module is used to locate microseismic events in the target monitoring area based on the initial source imaging results, so as to determine the spatial location of the microseismic events.

[0023] To achieve the above objectives, a third aspect of this application provides an electronic device, including: a processor; and a memory communicatively connected to the processor; the memory stores computer-executable instructions; the processor executes the computer-executable instructions stored in the memory to enable the processor to perform the method described in the above aspect of the embodiment.

[0024] To achieve the above objectives, a fourth aspect of this application provides a computer-readable storage medium having a computer program stored thereon, the computer instructions being configured to cause the computer to perform the method described in the above aspect of the embodiment.

[0025] To achieve the above objectives, a fifth aspect of this application provides a computer program product, including a computer program that, when executed by a processor, implements the method described in the above aspect of the embodiment.

[0026] The microseismic event localization method and apparatus provided in this application group receivers through geometric constraints to achieve sparse aperture grouping, thereby reducing the computational complexity of data processing, significantly shortening imaging time, and enabling real-time monitoring of large-scale microseismic events, thus improving monitoring efficiency. Through conjugate wavefield inversion and dual-weighted fusion techniques, not only can peak energy be focused, but artifacts can also be effectively suppressed, thereby significantly improving imaging resolution and facilitating more accurate determination of the spatial location and characteristics of microseismic events.

[0027] Additional aspects and advantages of this application 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 this application. Attached Figure Description

[0028] The above and / or additional aspects and advantages of this application will become apparent and readily understood from the following description of the embodiments taken in conjunction with the accompanying drawings, wherein:

[0029] Figure 1 A flowchart illustrating a method for locating microseismic events provided in an embodiment of this application;

[0030] Figure 1a This is a schematic diagram of a receiver group provided in an embodiment of this application;

[0031] Figure 2 A flowchart illustrating another method for locating microseismic events provided in an embodiment of this application;

[0032] Figure 3 A flowchart illustrating another method for locating microseismic events provided in an embodiment of this application;

[0033] Figure 4 A flowchart illustrating another method for locating microseismic events provided in an embodiment of this application;

[0034] Figure 5 This is a schematic diagram of the structure of a microseismic event location device provided in an embodiment of this application. Detailed Implementation

[0035] The embodiments of this application are described in detail below. Examples of these embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain this application, and should not be construed as limiting this application.

[0036] The following explanations, in conjunction with the accompanying drawings, cover the methods and devices for locating microseismic events and the methods and devices for classifying foreign objects on coal conveyor belts.

[0037] Figure 1 This is a flowchart illustrating a method for locating microseismic events provided in an embodiment of this application. The entity executing the method for locating microseismic events can be an electronic device or a server; this is not limited to either.

[0038] like Figure 1 As shown, the method for locating this microseismic event may include, but is not limited to, the following steps:

[0039] S101, the receivers associated with the target monitoring area are grouped according to the set geometric constraints to obtain multiple receiver groups.

[0040] In some embodiments, multiple receivers may be deployed within the target monitoring area to monitor the target monitoring area. These receivers deployed within the target monitoring area are the receivers associated with the target monitoring area.

[0041] In some embodiments, the number of receivers associated with the target monitoring area is determined, and based on the number of receivers, the number of groups is determined. Further, the receivers associated with the target monitoring area are grouped according to the number of groups and the number of receivers, in conjunction with geometric constraints.

[0042] In some embodiments, the defined geometric constraints may include, but are not limited to, at least one of the following conditions:

[0043] The monitoring range of all receiver groups forms a closed spatial coverage of the target monitoring area;

[0044] The minimum spacing between adjacent receivers within a group is greater than or equal to the set spacing;

[0045] The number of receivers in each receiver group is the same.

[0046] In some embodiments, receivers associated with the target monitoring area can be grouped according to set geometric constraints to obtain multiple receiver groups.

[0047] For example, according to the set geometric constraints, multiple receivers associated with the target monitoring area can be grouped into K subgroups, where each group needs to meet the following conditions:

[0048] (1) The azimuth coverage of each receiver group is ≥180°, which ensures that all receiver groups can fully cover the target monitoring area. In other words, the monitoring range of all receiver groups can form a closed spatial coverage of the target monitoring area. Optionally, the receivers are divided using the Delaunay triangulation algorithm, so that the monitoring range of all receiver groups can form a closed spatial coverage of the target monitoring area.

[0049] (2) The minimum spacing between adjacent receivers within a group is ≥ λ / 2, where the spacing is set to λ / 2; it can be understood that λ is an empirical value or determined through calibration. By constraining the minimum spacing between adjacent receivers within a group to ≥ λ / 2, coherence loss between near-field wavefields can be avoided. For example, when λ = 100m, the spacing is set to ≥ 50m.

[0050] (3) The size of each receiver group is balanced, meaning that the number of receivers in each receiver group is the same. For example, if the number of receivers deployed in the target monitoring area is N, the number of groups is determined based on N, for example... Furthermore, the number of receivers in each group is M, where M≈N / K, thereby achieving group balance of receivers within the target monitoring area.

[0051] like Figure 1a As shown, multiple receivers are deployed within the target monitoring area. According to the geometric constraints of this application, four groups can be obtained: Group 1, Group 2, Group 3 and Group 4, where the same color belongs to the same group.

[0052] In this embodiment, the receivers are grouped based on geometric constraints to achieve sparse aperture grouping, thereby enabling an exponential increase in computational complexity from full aperture reverse time migration (O(N)). 3 The growth rate decreases to linear (O(K×M)). 2 In this model, N represents the number of receivers associated with the target monitoring area, K represents the number of receiver groups, and M represents the number of receivers within each receiver group. This optimization enables real-time processing of large-scale microseismic monitoring, significantly reducing imaging time and improving monitoring efficiency.

[0053] S102, for each receiver group, determine the time-domain focusing function of the receiver group based on the time-domain signals acquired by the receivers within the group.

[0054] In some embodiments, the target monitoring area can transmit signals, and each receiver deployed in the target monitoring area can collect the signals transmitted by the target monitoring area, and can collect the time-domain signals transmitted by the target monitoring area.

[0055] In some embodiments, for each receiver group, the time-domain signals acquired by the receivers within the group can be frequency-domain converted, and a frequency-domain inverse-time wave field of the receiver can be constructed based on the frequency-domain signals. Furthermore, the time-domain focusing function of the receiver group can be determined based on the frequency-domain inverse-time wave field of the receiver. The time-domain focusing function is the wave field image formed by the signal from the target monitoring area x acquired by the receiver group at different times t, which can reflect the energy distribution of the signal acquired by the receiver group in space and time, that is, the energy intensity of the target monitoring area at different times. For example, in a seismic wave field image, a strong wave area may correspond to the vicinity of the earthquake source.

[0056] S103, determine the energy normalization coefficient of the receiver group based on the time-domain focusing function of the receiver group.

[0057] The energy conditions within different receiver groups may differ. If the signal energy is too high or too low, it may cause instability in numerical calculations. In order to eliminate the differences in signal energy among different receiver groups, the energy normalization coefficient of the receiver group can be determined based on the time-domain focusing function of the receiver group.

[0058] In some embodiments, after obtaining the time-domain focusing function of the receiver group, the focusing peak energy of the receiver group can be determined based on the time-domain focusing function of the receiver group, and further, the energy normalization coefficient of the receiver group can be determined based on the focusing peak energy of each receiver group.

[0059] S104. Determine the spatial attenuation factor of the receiver group based on the location information of the receiver group and the target monitoring area.

[0060] The farther the receiver is from the target monitoring area, the greater the energy attenuation of the signal collected by the receiver in space. In this embodiment, the positional relationship between the receiver group and the target monitoring area can be determined, and further, the spatial attenuation factor of the receiver group can be determined based on the positional relationship.

[0061] S105. Based on the energy normalization coefficient and spatial attenuation factor of the receiver group, cross-group weighted fusion is performed on multiple receiver groups to obtain the initial source imaging results of the target monitoring area.

[0062] In some embodiments, after obtaining the energy normalization coefficient and spatial attenuation factor of the receiver group, cross-group weighted fusion can be performed on multiple receiver groups based on the energy normalization coefficient and spatial attenuation factor of the receiver group to obtain the initial source imaging results of the target monitoring area.

[0063] In this embodiment, by using conjugate wavefield inversion and a dual-weighted fusion strategy of energy normalization coefficient and spatial attenuation factor, not only can peak energy be focused, but artifacts can also be effectively suppressed, thereby effectively improving imaging resolution and enabling a clearer determination of the spatial location and characteristics of microseismic events.

[0064] S106. Based on the initial source imaging results, the microseismic events in the target monitoring area are located to determine their spatial location.

[0065] In some embodiments, the initial source imaging results can be input into a pre-trained microseismic location model, which then locates microseismic events in the target monitoring area based on the initial source imaging results, accurately determining the spatial location of the microseismic events.

[0066] In some embodiments, the initial source imaging results can be enhanced in resolution, and the enhanced initial source imaging results can be input into a pre-trained microseismic location model to locate microseismic events in the target monitoring area and accurately determine the spatial location of microseismic events.

[0067] In some embodiments, the positioning results output by the microseismic positioning model may include, but are not limited to, edge and normal locations such as fault locations and crack locations within the target monitoring area, as well as the features corresponding to different locations.

[0068] In some embodiments, based on the location results, it is determined whether a microseismic event has occurred in the target monitoring area. Further, in response to the location results indicating the presence of a microseismic event in the target monitoring area, alarm information can be generated based on the location of the microseismic event.

[0069] Optionally, when the location results indicate the presence of fault locations and / or crack locations in the target monitoring area, it can be determined that a microseismic event has occurred in the target monitoring area. Furthermore, the edge locations such as fault locations and / or crack locations can be used as the spatial locations of microseismic events. It can be understood that the spatial location of a microseismic event is also the location of the seismic source.

[0070] The microseismic event localization method provided in this application grouped the receivers by geometric constraints to achieve sparse aperture grouping, thereby reducing the computational complexity of data processing, significantly shortening the imaging time, and enabling real-time monitoring of large-scale microseismic events, thus improving monitoring efficiency.

[0071] By employing conjugate wavefield inversion and dual-weighted fusion strategies, not only can peak energy be focused, but artifacts can also be effectively suppressed, thereby significantly improving imaging resolution and facilitating a more accurate determination of the spatial location and characteristics of microseismic events.

[0072] Furthermore, by optimizing receiver layout and wavefield processing, microseismic events can be located more accurately, reducing false alarms and missed alarms, and improving the reliability and practicality of monitoring.

[0073] Figure 2 This is a flowchart illustrating a method for locating microseismic events provided in an embodiment of this application. The entity executing the method for locating microseismic events can be an electronic device or a server; this is not limited to either.

[0074] like Figure 2 As shown, the method for locating this microseismic event may include, but is not limited to, the following steps:

[0075] S201, the receivers associated with the target monitoring area are grouped according to the set geometric constraints to obtain multiple receiver groups.

[0076] The implementation method of step S201 can be any of the implementation methods in the embodiments of this application, and will not be described in detail here.

[0077] S202 performs frequency domain conversion on the time domain signal acquired by the receiver to obtain the frequency domain signal of the receiver.

[0078] In some embodiments, the time-domain signal of the i-th receiver Perform a Fourier transform to obtain the frequency domain signal from the receiver.

[0079] Alternatively, the following formula (1) can be used for the time-domain signal of the i-th receiver. Perform a Fourier transform to obtain the frequency domain signal of the receiver:

[0080]

[0081] in, This represents the result of converting the signal from the i-th receiver from the time domain to the frequency domain, i.e., the time-domain signal. The corresponding frequency domain signal.

[0082] Furthermore, by converting the time-domain signal to a frequency-domain signal using Fourier transform, the effective frequency band of 0-50Hz can be extracted, preserving the amplitude and phase information of the wave field, thus providing a foundation for subsequent frequency-domain inverse-time wave field calculations. In this embodiment, by extracting the effective frequency band, high-frequency noise can be suppressed, reducing noise interference with the signal, thereby enabling the construction of a more accurate frequency-domain inverse-time wave field.

[0083] S203, based on the receiver's frequency domain signal, constructs the receiver's frequency domain inverse time wave field.

[0084] In some embodiments, the conjugate Green's function can be obtained by solving the wave equation. Furthermore, based on the frequency domain signal and the conjugate Green's function... Construct a frequency-domain inverse time wave field.

[0085] Alternatively, the frequency domain inverse time wave field of the receiver can be constructed using the following formula (2):

[0086]

[0087] Where x represents the target monitoring area; ω represents different frequencies; It is a frequency-domain inverse-time wave field, which can accurately describe the inverse-time propagation process of the wave field from the receiver to the target monitoring area.

[0088] S204. For each receiver group, determine the time-domain focusing function of the receiver group based on the frequency-domain inverse time wave field of the receivers in the receiver group.

[0089] In some embodiments, for each receiver group, the frequency domain energy of the receiver is determined based on the frequency domain inverse time wave field of the receiver in the receiver group, and the normalized wave field corresponding to the receiver group is determined based on the frequency domain energy of the receiver in the receiver group. Further, an inverse Fourier transform is performed on the normalized wave field to obtain the time domain focusing function of the receiver group.

[0090] In some embodiments, the frequency domain energy of the receiver can be squared to obtain the squared value of the frequency domain energy of the receiver. Further, the squared values ​​of the frequency domain energy of the receivers within the group are summed to obtain the sum of squared frequency domain energy corresponding to the receiver group. Further, the sums of squared frequency domain energy corresponding to the receiver group are compared to determine the largest sum of squared frequency domain energy. Based on the largest sum of squared frequency domain energy, the sum of squared frequency domain energy corresponding to the receiver group is normalized to obtain the normalized wavefield of the receiver group.

[0091] Optionally, taking the k-th receiver group as an example, the normalized wave field of the k-th receiver group can be determined using the following formula (3):

[0092]

[0093] Among them, W k (x,ω) represents the normalized wave field of the k-th receiver group, which can be obtained by energy normalization of the frequency-domain inverse-time wave field of the k-th receiver group; W k It is dimensionless and its corresponding value range is [0,1].

[0094] G k This represents the set of receivers within the k-th receiver group;

[0095] x represents the target monitoring area, and ω represents different frequencies;

[0096] Indicates receiver group G k The sum of squares of the energy of the frequency-domain reverse-time wave field of all receivers can reflect the receiver group G. k The total energy contribution to the target monitoring area x.

[0097] In this embodiment, by normalizing the frequency domain energy of the receiver group, the dominance effect of the high-energy receiver group can be suppressed, thereby preventing the signal of the low-energy receiver group from being masked, and thus enabling the time-domain aggregation function to accurately reflect the overall energy distribution of the target monitoring area.

[0098] Alternatively, the following formula (4) can be used to perform an inverse Fourier transform on the normalized wave field of the receiver group to determine the time-domain focusing function of the receiver group:

[0099]

[0100] Where x represents the target monitoring area; t represents different times; I k (x,t) represents the focusing energy of the k-th receiver group at different times t in the target monitoring area x.

[0101] S205, determine the energy normalization coefficient of the receiver group based on the time-domain focusing function of the receiver group.

[0102] In some embodiments, the peak focusing energy of the receiver group is determined based on the time-domain focusing function of the receiver group, and the peak focusing energy of each receiver group is summed to obtain the total peak focusing energy. Further, the energy normalization coefficient of the receiver group is obtained based on the peak focusing energy of the receiver group and the total peak focusing energy.

[0103] Alternatively, the energy normalization coefficient of the receiver group can be determined using the following formula (5):

[0104]

[0105] Where, max t |I k (x,t)| represents the peak focusing energy of the k-th receiver group at different times t in the target monitoring area x. That is, the maximum energy value is determined from the focusing energy at different times of the location point x, and is used as the peak focusing energy of the k-th receiver group. This indicates the total focused peak energy.

[0106] S206. Determine the spatial attenuation factor of the receiver group based on the location information of the receiver group and the target monitoring area.

[0107] In some embodiments, first location information of the receiver group can be determined. Optionally, the first location information of the receiver group can be determined based on the installation positions of the receivers within the group; for example, the center position can be selected as the first location information of the receiver group. As another example, the first location information of the receiver group can be determined by weighting the installation positions of the receivers within the group.

[0108] In some embodiments, a second location information of the target monitoring area can be determined. Optionally, the center location of the target monitoring area can be used as the second location information of the target monitoring area.

[0109] Furthermore, based on the first location information and the second location information of the target monitoring area, the distance between the receiver group and the target monitoring area is determined, and based on the distance between the receiver group and the target monitoring area, the spatial attenuation factor of the receiver group is determined.

[0110] Alternatively, the spatial attenuation factor of the receiver group can be determined using the following formula (6):

[0111]

[0112] Where, α k (x) represents the spatial decay factor; c k G represents the k-th receiver group. k First location information (e.g., G) k (geometric center position); ||xc k || 2 This represents the distance between the k-th receiver group and the target monitoring area x; σ represents the set attenuation coefficient, which can be determined based on the grid spacing, for example, it can be 1.5 times the grid spacing. It is understood that the target monitoring area can be divided into multiple grids, with the grid spacing being the distance between adjacent grids.

[0113] In this embodiment of the application, the spatial attenuation factor α is used. k (x) can dynamically adjust the contribution weights of different receiver groups, thereby suppressing the influence of far-field noise.

[0114] S207. Based on the energy normalization coefficient and spatial attenuation factor of the receiver group, cross-group weighted fusion is performed on multiple receiver groups to obtain the initial source imaging results of the target monitoring area.

[0115] In some embodiments, the time-domain focusing functions of the receiver group at different times within the target monitoring area are summed to obtain the focusing function of the receiver group. Based on the energy normalization coefficient and spatial attenuation factor of the receiver group, the focusing functions of the receiver group are weighted and fused across groups to obtain the weighted focusing function of the receiver group. Furthermore, the weighted focusing functions of the receiver group are summed to obtain the initial source imaging result.

[0116] Alternatively, the initial source imaging results of the target monitoring area can be determined using the following formula (7):

[0117]

[0118] Among them, I final (x) represents the initial source imaging result.

[0119] S208. Based on the initial source imaging results, microseismic events are located in the target monitoring area to determine their spatial location.

[0120] The implementation method of step S208 can be any of the implementation methods in the embodiments of this application, and will not be described in detail here.

[0121] The microseismic event localization method provided in this application grouped the receivers by geometric constraints to achieve sparse aperture grouping, thereby reducing the computational complexity of data processing, significantly shortening the imaging time, and enabling real-time monitoring of large-scale microseismic events, thus improving monitoring efficiency.

[0122] By using conjugate wavefield inversion and dual-weighted fusion techniques, not only can peak energy be focused, but artifacts can also be effectively suppressed, thereby effectively improving imaging resolution and facilitating a more accurate determination of the spatial location and characteristics of microseismic events.

[0123] Furthermore, by employing geometrically constrained grouping and dual-weighted fusion techniques, the monitoring needs of microseismic events under complex geological conditions can be effectively addressed. Optimizing receiver layout and wavefield processing enables more accurate localization of microseismic events, reducing false positives and false negatives, and improving the reliability and practicality of monitoring.

[0124] Figure 3 This is a flowchart illustrating a method for locating microseismic events provided in an embodiment of this application. The entity executing the method for locating microseismic events can be an electronic device or a server; this is not limited to either.

[0125] like Figure 3 As shown, the method for locating this microseismic event may include, but is not limited to, the following steps:

[0126] S301, the receivers associated with the target monitoring area are grouped according to the set geometric constraints to obtain multiple receiver groups.

[0127] S302, for each receiver group, determine the time-domain focusing function of the receiver group based on the time-domain signals acquired by the receivers within the group.

[0128] S303, determine the energy normalization coefficient of the receiver group based on the time-domain focusing function of the receiver group.

[0129] S304. Determine the spatial attenuation factor of the receiver group based on the location information of the receiver group and the target monitoring area.

[0130] S305, based on the energy normalization coefficient and spatial attenuation factor of the receiver group, performs cross-group weighted fusion of multiple receiver groups to obtain the initial source imaging results of the target monitoring area.

[0131] The implementation methods of steps S301 to S305 can be any of the implementation methods in the embodiments of this application, and will not be described in detail here.

[0132] S306 sharpens and enhances the initial source imaging results to obtain the target source imaging results.

[0133] In some embodiments, the three-dimensional gradient amplitude of the initial source imaging result is determined, and a sharpening enhancement operation is performed on the initial source imaging result based on the three-dimensional gradient amplitude to obtain the target source imaging result.

[0134] In some embodiments, the three-dimensional gradient magnitude of the initial source imaging result can be determined using the following formula (8):

[0135]

[0136] Furthermore, the gradient amplitude is enhanced by a sharpening factor γ, and the initial source imaging results and the sharpened gradient amplitudes are fused to obtain the target source imaging results.

[0137] In some embodiments, the following formula (9) can be used to obtain the target source imaging results:

[0138]

[0139] Here, γ is an empirical coefficient, with a default value of 0.8. Through sharpening enhancement operations, the width of the blurred area in the image can be significantly compressed, thereby improving the resolution.

[0140] S307. Based on the target seismic source imaging results, microseismic events are located in the target monitoring area to determine the spatial location of the microseismic events.

[0141] In some embodiments, the target seismic source imaging results can be input into a pre-trained microseismic location model. This pre-trained model then locates microseismic events in the target monitoring area based on the target seismic source imaging results, accurately outputting the spatial location of the microseismic events. For a detailed description of step S307, please refer to the relevant descriptions in the above embodiments; they will not be repeated here.

[0142] In this embodiment of the application, in order to reduce the width of the blurred area in the initial source imaging result, the initial source imaging result can be sharpened and enhanced to effectively compress the blurred area at the group boundary, improve the imaging resolution, and further improve the localization accuracy of microseismic events.

[0143] Figure 4 This is a flowchart illustrating a method for locating microseismic events provided in an embodiment of this application. The entity executing the method for locating microseismic events can be an electronic device or a server; this is not limited to either.

[0144] like Figure 4 As shown, the method for locating this microseismic event may include, but is not limited to, the following steps:

[0145] S401, Identify the receiver associated with the target monitoring area.

[0146] S402, Determine the geometric constraints.

[0147] Optionally, geometric constraints include:

[0148] Azimuth coverage ≥180°;

[0149] Minimum spacing within a group ≥ λ / 2;

[0150] Balanced Scale

[0151] S403 groups the receivers based on geometric constraints.

[0152] S404, determine the spatial attenuation factor of the receiver group.

[0153] S405 performs a Fourier transform on the time-domain signal acquired by the receiver.

[0154] S406 constructs a frequency-domain inverse time wave field based on the receiver's frequency-domain signal.

[0155] S407, frequency domain energy normalization of the receiver group, determines the normalized wave field of the receiver group.

[0156] S408 determines the time-domain aggregation function of the receiver group based on the normalized wave field.

[0157] S409, based on the time-domain aggregation function, determines the energy normalization coefficients of the receiver group.

[0158] S410, based on spatial attenuation factor and energy normalization coefficient, performs cross-group weighted fusion of multiple receiver groups to determine the initial source imaging results of the target monitoring area.

[0159] S411, calculate the three-dimensional gradient magnitude of the initial source imaging results.

[0160] S412, based on the three-dimensional gradient amplitude, sharpens the initial source imaging results to obtain the target source imaging results.

[0161] S413 outputs the spatial location of microseismic events based on the target source imaging results.

[0162] The microseismic event localization method provided in this application grouped the receivers by geometric constraints to achieve sparse aperture grouping, thereby reducing the computational complexity of data processing, significantly shortening the imaging time, and enabling real-time monitoring of large-scale microseismic events, thus improving monitoring efficiency.

[0163] By using conjugate wavefield inversion and dual-weighted fusion techniques, not only can peak energy be focused, but artifacts can also be effectively suppressed, thereby effectively improving imaging resolution and facilitating a more accurate determination of the spatial location and characteristics of microseismic events.

[0164] Furthermore, by employing geometrically constrained grouping and dual-weighted fusion techniques, the monitoring needs of microseismic events under complex geological conditions can be effectively addressed. By optimizing receiver layout and wavefield processing, microseismic events can be located more accurately, reducing false positives and false negatives, and improving the reliability and practicality of monitoring.

[0165] Furthermore, the initial source imaging results can be sharpened and enhanced to effectively compress the blurred areas at group boundaries, improve imaging resolution, and further improve the accuracy of microseismic event localization.

[0166] To implement the aforementioned method for locating microseismic events, this application provides a device for locating microseismic events. For example... Figure 5 As shown, the microseismic event location device 500 includes: a grouping module 501, a first determination module 502, a second determination module 503, a third determination module 504, a fusion module 505, and a location module 506.

[0167] Grouping module 501 is used to group receivers associated with the target monitoring area according to set geometric constraints to obtain multiple receiver groups;

[0168] The first determining module 502 is used to determine the time-domain focusing function of each receiver group based on the time-domain signals collected by the receivers within the group.

[0169] The second determining module 503 is used to determine the energy normalization coefficient of the receiver group based on the time-domain focusing function of the receiver group;

[0170] The third determining module 504 is used to determine the spatial attenuation factor of the receiver group based on the location information of the receiver group and the target monitoring area;

[0171] The fusion module 505 is used to perform cross-group weighted fusion of the multiple receiver groups according to the energy normalization coefficient and spatial attenuation factor of the receiver group to obtain the initial source imaging result of the target monitoring area.

[0172] The positioning module 506 is used to locate microseismic events in the target monitoring area based on the initial source imaging results, so as to determine the spatial location of the microseismic events.

[0173] In some embodiments, the defined geometric constraints include:

[0174] The monitoring range of all receiver groups forms a closed spatial coverage over the target monitoring area;

[0175] The minimum spacing between adjacent receivers is greater than or equal to the set spacing;

[0176] The number of receivers in each receiver group is the same.

[0177] In some embodiments, the first determining module 502 is further configured to:

[0178] The time-domain signal acquired by the receiver is subjected to Fourier transform to obtain the frequency-domain signal of the receiver;

[0179] Based on the frequency domain signal of the receiver, the frequency domain inverse time wave field of the receiver is constructed;

[0180] For each receiver group, the time-domain focusing function of the receiver group is determined based on the frequency-domain inverse time wave field of the receivers in the receiver group.

[0181] In some embodiments, the first determining module 502 is further configured to:

[0182] The frequency domain energy of the receiver is determined based on the frequency domain inverse time wave field of the receiver.

[0183] The normalized wave field of the receiver group is determined based on the frequency domain energy of the receivers in the receiver group;

[0184] The inverse Fourier transform of the normalized wave field is used to obtain the time-domain focusing function of the receiver group.

[0185] In some embodiments, the second determining module 503 is further configured to:

[0186] The peak focusing energy of the receiver group is determined based on the time-domain focusing function of the receiver group;

[0187] The total focused peak energy is obtained by summing the focused peak energies of each receiver group.

[0188] The energy normalization coefficient of the receiver group is obtained based on the focused peak energy of the receiver group and the total focused peak energy.

[0189] In some embodiments, the third determining module 504 is further configured to:

[0190] Determine the first location information of the receiver group;

[0191] Based on the first location information and the second location information of the target monitoring area, the distance between the receiver group and the target monitoring area is determined;

[0192] The spatial attenuation factor of the receiver group is determined based on the distance between the receiver group and the target monitoring area.

[0193] In some embodiments, the fusion module 505 is further configured to:

[0194] The focusing function of the receiver group is obtained by summing the time-domain focusing functions of the receiver group at different times within the target monitoring area;

[0195] Based on the energy normalization coefficient and spatial attenuation factor of the receiver group, the focusing function of the receiver group is weighted and fused across groups to obtain the weighted focusing function of the receiver group.

[0196] The weighted focusing function of the receiver group is summed to obtain the initial source imaging result.

[0197] In some embodiments, the positioning module 506 is further configured to:

[0198] Determine the three-dimensional gradient amplitude of the initial source imaging results;

[0199] Based on the three-dimensional gradient amplitude, a sharpening and enhancement operation is performed on the initial source imaging result to obtain the target source imaging result.

[0200] Based on the imaging results of the target seismic source, microseismic events are located in the target monitoring area to determine the spatial location of the microseismic events.

[0201] In some embodiments, the positioning module 506 is further configured to:

[0202] The second image is input into a pre-trained microseismic location model, which then locates microseismic events in the target monitoring area based on the second image and outputs the spatial location of the microseismic events.

[0203] Since the apparatus provided in this application corresponds to the methods provided in the above-mentioned embodiments, the implementation of the methods is also applicable to the apparatus provided in this embodiment, and will not be described in detail in this embodiment.

[0204] The methods and apparatus provided in the embodiments of this application have been described above. To implement the functions of the methods provided in the embodiments of this application, the electronic device may include a hardware structure and software modules, and may implement the above functions in the form of a hardware structure, software modules, or a hardware structure plus software modules. One of the above functions may be executed in the form of a hardware structure, software modules, or a hardware structure plus software modules.

[0205] To implement the above embodiments, this application also proposes an electronic device, including: a processor and a memory communicatively connected to the processor; the memory stores computer execution instructions; the processor executes the computer execution instructions stored in the memory to implement the method provided in the foregoing embodiments.

[0206] To implement the above embodiments, this application also proposes a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the methods provided in the foregoing embodiments.

[0207] To implement the above embodiments, this application also proposes a computer program product, including a computer program that, when executed by a processor, implements the methods provided in the foregoing embodiments.

[0208] The collection, storage, use, processing, transmission, provision, and application of user personal information involved in this application all comply with the provisions of relevant laws and regulations and do not violate public order and good morals.

[0209] It should be noted that personal information collected from users should be used for legitimate and reasonable purposes and should not be shared or sold outside of these legitimate uses. Furthermore, such collection / sharing should only be conducted after receiving the user's informed consent, including but not limited to notifying the user to read the user agreement / user notice and sign an agreement / authorization that includes authorization of relevant user information before the user uses the function. In addition, any necessary steps must be taken to protect and safeguard access to such personal information data and ensure that others with access to personal information data comply with their privacy policies and procedures.

[0210] This application is intended to provide an implementation scheme for users to selectively prevent the use or access to their personal information data. Specifically, this application is intended to provide hardware and / or software to prevent or block access to such personal information data. Once personal information data is no longer needed, risks can be minimized by restricting data collection and deleting data. Furthermore, where applicable, such personal information is de-identified to protect user privacy.

[0211] In the foregoing descriptions of the embodiments, the terms "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in any number or more embodiments or examples. Furthermore, 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.

[0212] 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 application, "multiple" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0213] Any process or method description in the flowchart or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or more executable instructions for implementing custom logic functions or processes, and the scope of the preferred embodiments of this application includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order depending on the functions involved, as should be understood by those skilled in the art to which embodiments of this application pertain.

[0214] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-included system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of computer-readable media include: an electrical connection having one or more wires (electronic device), a portable computer disk drive (magnetic device), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Alternatively, the computer-readable medium may be paper or other suitable media on which the program can be printed, since the program can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in a computer memory.

[0215] It should be understood that various parts of this application can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented using software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0216] Those skilled in the art will understand that all or part of the steps of the methods in the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, the program includes one or a combination of the steps of the method embodiments.

[0217] Furthermore, the functional units in the various embodiments of this application can be integrated into a processing module, or each unit can exist physically separately, or two or more units can be integrated into a module. The integrated module can be implemented in hardware or as a software functional module. If the integrated module is implemented as a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium.

[0218] The storage medium mentioned above can be a read-only memory, a disk, or an optical disk, etc. Although embodiments of this application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting this application. Those skilled in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of this application.

Claims

1. A method for locating microseismic events, characterized in that, The method includes: The receivers associated with the target monitoring area are grouped by sparse aperture according to the set geometric constraints to obtain multiple receiver groups; For each receiver group, the frequency domain energy of the receiver is determined based on the frequency domain inverse time wave field of the receivers within the group. Based on the frequency domain energy of the receivers in the receiver group, the normalized wave field of the receiver group is determined. The inverse Fourier transform of the normalized wave field is then performed to determine the time domain focusing function of the receiver group. Based on the time-domain focusing function of the receiver group, the focusing peak energy of the receiver group is determined. The focusing peak energy of each receiver group is summed to obtain the total focusing peak energy. Based on the focusing peak energy of the receiver group and the total focusing peak energy, the energy normalization coefficient of the receiver group is determined. Based on the location information of the receiver group and the target monitoring area, the distance between the receiver group and the target monitoring area is determined, and based on the distance between the receiver group and the target monitoring area, the spatial attenuation factor of the receiver group is determined; Based on the energy normalization coefficient and spatial attenuation factor of the receiver group, cross-group weighted fusion is performed on the multiple receiver groups to obtain the initial source imaging results of the target monitoring area. Based on the initial source imaging results, microseismic events are located in the target monitoring area to determine their spatial location.

2. The method according to claim 1, characterized in that, The defined geometric constraints include: The monitoring range of all receiver groups forms a closed spatial coverage over the target monitoring area; The minimum spacing between adjacent receivers is greater than or equal to the set spacing; The number of receivers in each receiver group is the same.

3. The method according to claim 1, characterized in that, The process of determining the frequency domain reverse time wave field of the receiver includes: The time-domain signal acquired by the receiver is subjected to Fourier transform to obtain the frequency-domain signal of the receiver; Based on the frequency domain signal of the receiver, the frequency domain inverse time wave field of the receiver is constructed.

4. The method according to any one of claims 1-3, characterized in that, The step of determining the distance between the receiver group and the target monitoring area based on the location information of the receiver group and the target monitoring area includes: Determine the first location information of the receiver group; The distance between the receiver group and the target monitoring area is determined based on the first location information and the second location information of the target monitoring area.

5. The method according to any one of claims 1-3, characterized in that, The step of performing cross-group weighted fusion of the multiple receiver groups based on the energy normalization coefficient and spatial attenuation factor of the receiver groups to obtain the initial source imaging results includes: The focusing function of the receiver group is obtained by summing the time-domain focusing functions of the receiver group at different times within the target monitoring area; Based on the energy normalization coefficient and spatial attenuation factor, the focusing function of the receiver group is weighted and fused across groups to obtain the weighted focusing function of the receiver group. The weighted focusing function of the receiver group is summed to obtain the initial source imaging result.

6. The method according to claim 1, characterized in that, The step of locating microseismic events in the target monitoring area based on the initial source imaging results to determine the spatial location of the microseismic events includes: Determine the three-dimensional gradient amplitude of the initial source imaging results; Based on the three-dimensional gradient amplitude, a sharpening and enhancement operation is performed on the initial source imaging result to obtain the target source imaging result. Based on the imaging results of the target seismic source, microseismic events are located in the target monitoring area to determine the spatial location of the microseismic events.

7. The method according to claim 1 or 6, characterized in that, The method further includes: The initial source imaging result or the target source imaging result is input into the pre-trained microseismic location model. The pre-trained microseismic location model locates microseismic events in the target monitoring area based on the initial source imaging result or the target source imaging result, and outputs the spatial location of the microseismic event.

8. A device for locating microseismic events, characterized in that, The device includes: The grouping module is used to group the receivers associated with the target monitoring area according to the set geometric constraints, resulting in multiple receiver groups; The first determining module is used to determine the frequency domain energy of each receiver group based on the frequency domain inverse time wave field of the receivers in the group, determine the normalized wave field of the receiver group based on the frequency domain energy of the receivers in the receiver group, and perform an inverse Fourier transform on the normalized wave field to determine the time domain focusing function of the receiver group. The second determining module is used to determine the peak focusing energy of the receiver group based on the time-domain focusing function of the receiver group, sum the peak focusing energy of each receiver group to obtain the total peak focusing energy, and determine the energy normalization coefficient of the receiver group based on the peak focusing energy of the receiver group and the total peak focusing energy. The third determining module is used to determine the distance between the receiver group and the target monitoring area based on the location information of the receiver group and the target monitoring area, and to determine the spatial attenuation factor of the receiver group based on the distance between the receiver group and the target monitoring area; The fusion module is used to perform cross-group weighted fusion of the multiple receiver groups based on the energy normalization coefficient and spatial attenuation factor of the receiver groups to obtain the initial source imaging results of the target monitoring area. The positioning module is used to locate microseismic events in the target monitoring area based on the initial source imaging results, so as to obtain the spatial location of the microseismic events.

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