Seismic activity degree factor extraction method and system based on seismic data

Abstract

This application provides a method and system for extracting seismic activity factors based on seismic data, relating to the field of earthquake engineering technology. The method obtains effective seismic event sets by acquiring seismic data of a target area and performing magnitude screening and aftershock removal. It then acquires a hierarchical source region model and extracts three-level polygon boundary data: statistical region, tectonic region, and tectonic source. Based on the epicenter location and magnitude parameters of each earthquake in the effective seismic event set, spatial fusion is performed within the spatial range defined by the polygon boundary data to generate an activity horizontal distribution layer. The activity horizontal distribution layer is spatially overlaid with the polygon boundary data to extract the cumulative activity within each level of polygon boundary. Finally, the cumulative activity is amortized according to the actual area of ​​each level of polygon to obtain and output the seismic activity factor, thus improving the accuracy and spatial resolution of quantitative seismic activity assessment.

Description

Technical Field

[0001] This application relates to the field of earthquake engineering technology, and in particular to a method and system for extracting seismic activity factors based on seismic data. Background Technology

[0002] In seismic hazard analysis and engineering site safety assessment, quantitatively assessing the level of seismic activity in a specific area is an important prerequisite for determining site ground motion parameters, and obtaining quantitative indicators that reflect the intensity of regional seismic activity is one of the core contents of the above assessment work.

[0003] Currently, when quantitatively describing the level of regional seismic activity, the commonly used technical approach is to statistically analyze earthquake events according to magnitude ranges based on historical earthquake catalogs, combine the spatial division of source areas, and use the statistical relationship between earthquake frequency and magnitude to estimate the annual average occurrence rate parameter of each potential source area, and then use this occurrence rate parameter to characterize the level of seismic activity in each region.

[0004] However, this method has several shortcomings in practical engineering applications: First, in terms of spatial resolution, since the entire potential source area is used as the statistical unit, it cannot reflect the non-uniform spatial distribution characteristics of seismic activity within the source area; second, in terms of multi-scale fusion, existing methods only perform statistics at a single spatial scale, making it difficult to take into account the assessment needs of multiple levels from macro to micro; and third, in terms of time factor consideration, traditional methods lack the memory of historical strong earthquake time characteristics and the fusion mechanism of seismic event spatial clustering characteristics, resulting in insufficient sensitivity of the evaluation results to active segments. Summary of the Invention

[0005] This application provides a method and system for extracting seismic activity factors based on seismic data, in order to solve the problems of insufficient spatial resolution, difficulty in multi-level fusion, and lack of temporal memory in the existing technology for quantitative evaluation of seismic activity levels.

[0006] To address the aforementioned technical problems, in a first aspect, this application provides a method for extracting seismic activity factors based on seismic data, comprising: Seismic data for the target area is acquired, and the data is filtered by magnitude and aftershocks are removed to obtain a set of effective seismic events. Obtain a hierarchical source region model of the target area, and extract the polygonal boundaries of the statistical region, the polygonal boundaries of the tectonic region, and the polygonal boundaries of the tectonic source from the hierarchical source region model as polygonal boundary data. The statistical region, the tectonic region, and the tectonic source are superimposed in the hierarchical source region model. Based on the epicenter location and magnitude parameters of each earthquake in the effective earthquake event set, spatial fusion is performed within the spatial range defined by polygon boundary data to generate an active horizontal distribution layer that covers the target area. Spatially overlay the activity horizontal distribution layer with the polygon boundary data to extract the cumulative activity falling within the polygon boundaries of each statistical area, each polygon boundary of each construction area, and each polygon boundary of the construction source. Based on the actual area of ​​each polygon, the cumulative activity is calculated and distributed to obtain the seismic activity factor, which is then output.

[0007] Optionally, based on the epicenter location and magnitude parameters of each earthquake in the effective seismic event set, spatial fusion is performed within the spatial range defined by the polygonal boundary data to generate an active horizontal distribution layer, including: The target area is divided into multiple equally spaced spatial grids; Using the geometric center of each spatial grid as the computation node, the energy contribution of each earthquake event to each computation node is calculated based on the spatial distance between each computation node and the epicenter of each earthquake in the effective earthquake event set. The number of earthquakes, the cumulative amount of energy contribution, and the maximum magnitude of each calculation node within the preset time limit are statistically analyzed to obtain the frequency statistics, energy statistics, and maximum magnitude statistics for each calculation node. Spatial interpolation is performed on the frequency statistics, energy statistics, and maximum magnitude statistics of each calculation node to generate an active horizontal distribution layer.

[0008] Optionally, after generating the active horizontal distribution layer, the following is also included: Extract the seismic clustering intensity of each computing node within a preset neighborhood; Obtain the historical earthquake occurrence time intervals for each computing node's corresponding location, and determine the memory correlation degree of the current time period with the historical strong earthquake magnitudes based on the historical earthquake occurrence time intervals and the current time period; Based on the earthquake concentration intensity and memory correlation, the energy statistics of each calculation node are corrected by nonlinear weights to obtain the corrected energy statistics. Replace the energy statistics with the corrected energy statistics to update the activity level distribution layer.

[0009] Optionally, the activity level distribution layer is spatially overlaid with the polygon boundary data to extract the cumulative activity falling within the polygon boundaries of each statistical region, each construction region, and each construction source polygon boundary, including: Perform a topological intersection operation between the active horizontal distribution layer and the polygon boundary data in the geographic information system to obtain the intersecting geometric objects. In intersecting geometric objects, the proportion of the area occupied by the part of each spatial grid located inside the polygon boundary after being cut by the polygon boundary data is calculated to obtain the geometric intersection ratio. Based on the geometric intersection ratio of each spatial grid and the corresponding grid value of each spatial grid in the active horizontal distribution layer, calculate the grid value contribution component of each spatial grid falling inside the polygon boundary. The cumulative activity of the polygon boundary is obtained by summing the grid numerical contribution components of all spatial grids within the same polygon boundary.

[0010] Optionally, the cumulative activity is calculated by amortizing the actual area of ​​each polygon level to obtain and output the seismic activity factor, including: Transform the polygon boundary data to the Mercator projection coordinate system, and extract the geometric vertex coordinates of each level of polygon in the Mercator projection coordinate system; Calculate the horizontal projected physical area of ​​the region enclosed by polygons of all levels based on the coordinates of the geometric vertices. Divide the cumulative activity level by the corresponding horizontal projected physical area to obtain the activity level value per unit physical area, and output the activity level value as the seismic activity factor.

[0011] Optionally, before acquiring seismic data for the target area, filtering the seismic data by magnitude and removing aftershocks to obtain a valid set of seismic events, the following steps are also included: Receive the target area selection instruction and determine the geographic spatial range to be analyzed. The target area selection instruction can be a selection instruction for a preset fixed area or a custom area division instruction based on the latitude and longitude coordinates of the four vertices input by the user. Based on the geographic spatial scope, the system reads the basic files of the geographic information system and the directory of historical seismic networks from the preset storage path as earthquake data.

[0012] Optionally, the earthquake data can be filtered by magnitude and aftershocks removed to obtain a set of effective earthquake events, including: Using a preset year as a boundary, historical earthquake data is filtered using the first lower limit of magnitude, while data recorded by modern instruments is filtered using the second lower limit of magnitude, thus obtaining a preliminary earthquake sequence. Set up spatial and temporal search windows to identify the mainshock and associated cluster earthquake events from the preliminary earthquake sequence; Clustered earthquake events are removed, and the earthquake events retained after removing clustered earthquake events from the preliminary earthquake sequence are determined as the effective earthquake event set.

[0013] Optionally, in the process of obtaining the hierarchical source region model of the target area and extracting the polygonal boundaries of the statistical region, the polygonal boundaries of the tectonic region, and the polygonal boundaries of the tectonic source from the hierarchical source region model as polygonal boundary data, the following further steps are included: The software's graphical interface displays a hierarchical drop-down menu, which includes options for the statistics area, construction area, and construction source. These options correspond to three levels of division. In response to the toggle operation of any option in the hierarchical drop-down selection menu, the polygon boundary data corresponding to the selected option is read and rendered in the chart area; In response to the completion of the seismic activity factor calculation, the seismic activity factor value corresponding to the selected option is mapped to the area enclosed by the polygon boundary data in the chart area and updated synchronously.

[0014] Optionally, after mapping the seismic activity factor value corresponding to the selected option to the area enclosed by the polygon boundary data in the chart area, the method also includes: Based on the preset paper layout size of the engineering report, adjust the display ratio of the chart area in the software's graphical interface to obtain the adjusted chart area display content; The polygonal boundary graphic with seismic activity factor overlaid in the adjusted chart area is rendered as a vector graphic file. Vector graphic files have lossless scaling characteristics. Save the vector graphics file to the preset output directory.

[0015] Secondly, this application provides a seismic activity factor extraction system based on seismic data, comprising: The acquisition module is used to acquire seismic data of the target area, filter the seismic data by magnitude and remove aftershocks to obtain a set of effective seismic events; The extraction module is used to obtain the hierarchical source area model of the target area and extract the polygonal boundaries of the statistical area, the polygonal boundaries of the tectonic area, and the polygonal boundaries of the tectonic source from the hierarchical source area model as polygonal boundary data. The statistical area, the tectonic area, and the tectonic source are superimposed in the hierarchical source area model. The fusion module is used to perform spatial fusion within the spatial range defined by polygon boundary data based on the epicenter location and magnitude parameters of each earthquake in the effective seismic event set, and generate an active horizontal distribution layer that covers the target area. The overlay module is used to spatially overlay the activity horizontal distribution layer with the polygon boundary data and extract the cumulative activity falling within the polygon boundaries of each statistical area, each construction area, and each construction source polygon boundary. The calculation module is used to calculate the cumulative activity based on the actual area of ​​each level of polygon, obtain the seismic activity factor, and output it.

[0016] This application provides a method for extracting seismic activity factors based on seismic data. The method includes: acquiring seismic data for a target area; filtering the seismic data by magnitude and removing aftershocks to obtain a valid set of seismic events; acquiring a hierarchical source region model for the target area; extracting the polygonal boundaries of statistical zones, tectonic zones, and tectonic sources from the hierarchical source region model as polygonal boundary data, wherein the statistical zones, tectonic zones, and tectonic sources are overlaid in the hierarchical source region model; spatially fusing the polygonal boundary data within the spatial range defined by the polygonal boundary data based on the epicenter location and magnitude parameters of each earthquake in the valid seismic event set to generate a horizontal activity distribution layer covering the target area; spatially overlaying the horizontal activity distribution layer with the polygonal boundary data to extract the cumulative activity falling within the polygonal boundaries of each statistical zone, each tectonic zone, and each tectonic source; and calculating the cumulative activity based on the actual area of ​​each polygonal level to obtain and output the seismic activity factor.

[0017] Compared with existing technologies, this application has the following advantages: By spatially fusing within the multi-level spatial range defined by the hierarchical source area model, discrete seismic events are transformed into a continuous horizontal distribution layer of activity, overcoming the problem of insufficient spatial resolution of traditional methods; through spatial overlay and area amortization calculation, activity factor extraction from three levels—statistical zone, tectonic zone, and tectonic source—is realized, ensuring spatial consistency of assessment results between different levels; by introducing seismic clustering intensity and memory correlation to perform nonlinear weight correction on energy statistics, the sensitivity of the evaluation results to recent active segments and historical strong earthquake recurrence segments is enhanced, improving the accuracy and reliability of quantitative seismic activity assessment. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 This is a schematic diagram of the overall process of a seismic activity factor extraction method based on seismic data, provided in an embodiment of this application.

[0020] Figure 2 This is a schematic diagram of the spatial overlay relationship of a hierarchical source region model provided in an embodiment of this application.

[0021] Figure 3 This is a schematic diagram of a process for generating an active horizontal distribution layer through spatial fusion, as provided in an embodiment of this application.

[0022] Figure 4 This is a schematic diagram illustrating the normalization and fusion of a frequency statistics raster layer, an energy statistics raster layer, and a maximum magnitude statistics raster layer to generate an active horizontal distribution layer, as provided in an embodiment of this application.

[0023] Figure 5 This is a schematic diagram illustrating a process for spatially overlaying an active horizontal distribution layer and polygon boundary data, as provided in an embodiment of this application.

[0024] Figure 6 This is a schematic diagram illustrating the topological intersection operation and geometric intersection ratio calculation of a spatial grid and a polygon boundary, provided as an embodiment of this application.

[0025] Figure 7 This is a schematic diagram of a seismic activity factor extraction system based on seismic data, provided as an embodiment of this application. Detailed Implementation

[0026] To enable those skilled in the art to better understand the present application, the present application will be further described in detail below with reference to the accompanying drawings and specific embodiments. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present application.

[0027] In engineering practice of seismic hazard analysis, when quantitatively assessing the level of regional seismic activity, existing technologies typically use the entire potential seismic source area as a statistical unit to estimate the annual average occurrence rate parameter. This approach has shortcomings in terms of spatial resolution, multi-level fusion, and temporal memory.

[0028] To address the aforementioned issues, the research and development approach of this application is as follows: First, by screening the magnitude and removing aftershocks from the original earthquake catalog, a high-quality set of independent earthquake events is obtained, eliminating the interference of aftershocks on the statistical results; then, a hierarchical source region model is introduced as a multi-level spatial constraint framework, from the macroscopic statistical region to the mesoscale tectonic region and then to the microscopic tectonic source, providing a coarse-to-fine spatial division system for activity assessment. Based on this, discrete seismic events are transformed into a continuous horizontal distribution layer covering the target area through spatial gridding and energy contribution value calculation. Seismic clustering intensity and memory correlation are introduced for nonlinear weight correction to enhance the response sensitivity to recent active segments and historical strong earthquake recurrence segments. Finally, the horizontal distribution layer is accurately overlaid with multi-level polygon boundaries through topological intersection operation, and the seismic activity factor corresponding to each level of polygon is obtained through area amortization calculation, so that the activity assessment results between regions of different levels and different area scales are comparable.

[0029] The core of this application is to provide a method for extracting seismic activity factors based on seismic data, and a flowchart of one specific implementation is shown below. Figure 1 As shown, the method includes: S1: Obtain seismic data for the target area, filter the seismic data by magnitude and remove aftershocks to obtain a set of effective seismic events.

[0030] The purpose of this step is to extract a set of independent earthquake events from the original earthquake catalog that meet the integrity requirements and have been free from aftershock interference, so as to provide reliable basic data for subsequent spatial fusion.

[0031] In this step, the effective earthquake event set refers to the set of earthquake events retained after the magnitude lower limit filtering and aftershock removal process. Each earthquake record in this set is an independent mainshock event and does not include secondary aftershock events triggered by the mainshock.

[0032] An effective earthquake event set includes the epicenter location, time of occurrence, and magnitude parameters of each earthquake. The epicenter location refers to the vertical projection of the earthquake source onto the Earth's surface, usually expressed as a coordinate pair of longitude and latitude values. The time of occurrence refers to the specific time when the earthquake occurred, accurate to the year, month, day, hour, minute, and second. The magnitude parameter is a quantitative indicator used to characterize the amount of energy released by the earthquake.

[0033] The specific implementation process for this step is as follows: First, using a predetermined year as a boundary, earthquake data is divided into two parts: historical recorded data and modern instrument recorded data. Historical recorded data refers to earthquake event records collected and organized before the predetermined year through manual observation, documentary records, and other methods. Due to the lack of sophisticated instruments at the time, the completeness of historical recorded data is usually high, meaning that only earthquake events of a certain magnitude or higher can be fully recorded. Modern instrument recorded data refers to earthquake event data automatically collected and recorded by sophisticated observation instruments such as seismographs on and after the predetermined year. Due to the improved sensitivity of instruments, modern instrument recorded data can record earthquake events of lower magnitude.

[0034] Then, the historical data is filtered using a first lower magnitude limit, and the modern instrument-recorded data is filtered using a second lower magnitude limit to obtain a preliminary earthquake sequence. The first lower magnitude limit refers to the minimum magnitude threshold set for the historical data; historical earthquake events with magnitudes below this threshold will be filtered out. This threshold is set based on the results of the historical earthquake catalog integrity analysis of the target area. The second lower magnitude limit refers to the minimum magnitude threshold set for the modern instrument-recorded data; modern instrument-recorded earthquake events with magnitudes below this threshold will be filtered out. Since the catalog integrity magnitude of the historical data is higher than that of the modern instrument-recorded data, the value of the first lower magnitude limit is greater than the value of the second lower magnitude limit.

[0035] Next, spatial and temporal search windows are set to identify the mainshock and associated cluster earthquake events from the preliminary earthquake sequence. The spatial search window is a circular spatial area centered on the epicenter of an earthquake event and with a radius related to the magnitude of the earthquake event as the search range. The temporal search window is a time interval before and after an earthquake event, with the time of occurrence of the earthquake event as the reference and a time width related to the magnitude of the earthquake event as the search range.

[0036] Cluster earthquake events refer to a series of subordinate earthquake events triggered by a mainshock that occur densely near the epicenter of the mainshock and within a short period before and after the mainshock's occurrence, including foreshocks and aftershocks. In this application, the Gardner-Nobof method is used to identify cluster earthquake events. The principle of this method is that for each earthquake event in the preliminary earthquake sequence, a spatial search window radius and a temporal search window width positively correlated with the magnitude of the earthquake event are determined based on the magnitude of the earthquake event. Other earthquake events associated with the earthquake event are searched within the spatiotemporal range defined by the spatial search window radius and the temporal search window width. If the magnitude of the searched earthquake event is smaller than that of the earthquake event, the searched earthquake event is marked as a cluster earthquake event.

[0037] Finally, clustered earthquake events are removed, and the earthquake events remaining after removing clustered earthquake events from the preliminary earthquake sequence are determined as the effective earthquake event set.

[0038] In practical engineering applications, assuming the target area is region A, and using 1900 as the preset year limit, historical data recorded before 1900 are filtered using a surface wave magnitude of 4.7 as the first lower limit, and modern instrument data recorded from 1900 onwards are filtered using a surface wave magnitude of 3.0 as the second lower limit.

[0039] After magnitude screening, a preliminary earthquake sequence containing 1,500 earthquake records was obtained. Then, the Gardner-Nobov method was used to remove aftershocks. Taking a surface wave magnitude 5.0 earthquake event as an example, the spatial search window radius determined by the Gardner-Nobov method was 40 kilometers, and the temporal search window width was 155 days.

[0040] Earthquake events with a magnitude less than 5.0 were searched within a 155-day period before and after the earthquake, centered on the epicenter and within a radius of 40 kilometers. These events were marked as clustered earthquake events and removed. After removing aftershocks, the final set of valid earthquake events contained 1,200 independent earthquake records.

[0041] The above example is only one implementation of this application. Under different target areas and earthquake catalog conditions, the specific values ​​of the preset year, the lower limit of the first magnitude and the lower limit of the second magnitude can be adjusted according to the actual situation.

[0042] This application ensures the independence and integrity of each record in the effective seismic event set by screening earthquake magnitudes and removing aftershocks from the earthquake data, and avoids the biased impact of aftershock events on subsequent activity level statistics.

[0043] It should be noted that before executing step S1, the target area needs to be determined, specifically: receiving the target area selection instruction and determining the geographic spatial range to be analyzed.

[0044] Among them, the target area selection instruction refers to the operation instruction issued by the user to the processing program to delineate the analysis range. This instruction includes two forms: one is the selection instruction for a preset fixed area, that is, to select one of several standard areas pre-configured in the program as the target area; the other is the custom area division instruction based on the latitude and longitude coordinates of the four vertices input by the user, that is, the user inputs four geographical coordinate points to form a closed quadrilateral area as the target area.

[0045] When a user uses a custom region division command, the four vertices are arranged in a counterclockwise or clockwise order to form a closed quadrilateral region. When the target region involves crossing the 180° East meridian, the region needs to be split into two sub-regions, processed separately, and then merged.

[0046] After determining the geospatial scope, the system reads the basic files of the geographic information system and the directory of historical seismic networks under the preset storage path as earthquake data. The preset storage path refers to the disk directory address where the data files are located in advance in the program. This path points to the folder where the basic geospatial data and earthquake record data are stored.

[0047] Geographic Information System (GIS) basic files refer to vector data files used to describe the geometric shape and attribute information of geospatial features. Specific types include vector spatial data exchange format files or geographic database files. These files contain spatial information such as administrative boundaries, fault zone distribution, and geological structural zoning of the target area, as well as corresponding attribute fields.

[0048] The historical earthquake network catalog refers to a database file of earthquake events formed by the long-term recording and collation of earthquake networks. Each record in the file corresponds to an earthquake event. The fields of information contained in each record include epicentral longitude, epicentral latitude, focal depth, time of occurrence, and magnitude scale type, among which the magnitude scale type is used to identify the magnitude measurement method used for that record.

[0049] S2: Obtain the hierarchical source area model of the target region, and extract the polygonal boundaries of the statistical area, the polygonal boundaries of the tectonic area, and the polygonal boundaries of the tectonic source from the hierarchical source area model as polygonal boundary data. The statistical area, the tectonic area, and the tectonic source are superimposed in the hierarchical source area model.

[0050] In step S1, a set of preprocessed valid seismic events has been obtained. In order to spatially associate the discrete seismic events in the set of valid seismic events with areas of geological significance, a hierarchical source region model needs to be introduced to provide a spatial constraint framework. Therefore, this step obtains the hierarchical source region model of the target area.

[0051] In this step, the hierarchical source region model refers to a spatial model that divides the target area into three levels—statistical zone, tectonic zone, and tectonic source—from macroscopic to microscopic according to the geological tectonic background and seismic activity characteristics. The construction process of this model is as follows: First, based on the geotectonic zoning and regional plate boundary characteristics, the target area is divided into several statistical zones, each corresponding to a macroscopic geological unit with a relatively independent seismic tectonic background. Then, within each statistical zone, based on similar seismic tectonic environments and seismogenic mechanisms, it is further subdivided into several tectonic zones. Finally, within each tectonic zone, based on the identified active fault zone orientation, densely distributed historical earthquake segments, and deep geophysical exploration results, several tectonic sources are delineated, each corresponding to one or a group of active structures with independent seismogenic capabilities.

[0052] During the model construction process, the boundaries of polygons at all levels are determined based on the following criteria: the boundaries of statistical areas mainly refer to the boundaries of first-order tectonic units, such as plate suture zones and large deep fault zones; the boundaries of tectonic areas mainly refer to the boundaries of second-order geological tectonic units and the spatial clustering characteristics of regional seismic activity; the boundaries of tectonic sources are mainly delineated by referring to the spatial distribution range of active fault zones, the difference in seismic activity density on both sides of the fault zone, and the distribution characteristics of focal depth.

[0053] The statistical region is the most macroscopic level of spatial division unit, with an area ranging from tens of thousands to hundreds of thousands of square kilometers; the tectonic region is the intermediate level of spatial division unit, with an area ranging from thousands to tens of thousands of square kilometers; and the tectonic source is the most microscopic level of spatial division unit, with an area ranging from hundreds to thousands of square kilometers.

[0054] In the hierarchical source region model, the three levels of statistical region, tectonic region and tectonic source are superimposed. This superposition relationship means that the upper-level polygon completely covers the scope of the lower-level polygon in space. That is, a statistical region can contain multiple tectonic regions, a tectonic region can contain multiple tectonic sources, and the spatial scope of the lower-level polygon does not exceed the boundary of the upper-level polygon.

[0055] See Figure 2 As shown, Figure 2 A schematic diagram of the spatial overlay relationship of a hierarchical source region model is shown. In this diagram, the first statistical region 31 is the outermost polygon, which contains two intermediate-level polygons: the first structural region 311 and the second structural region 312. The first structural region 311 contains two innermost polygons: the first structural source 3111 and the second structural source 3112. The second structural region 312 contains three innermost polygons: the third structural source 3121, the fourth structural source 3122, and the fifth structural source 3123. The three levels of polygons form a hierarchical spatial structure of nested layers.

[0056] In the specific implementation process, the polygonal boundaries of the statistical area, the polygonal boundaries of the tectonic area, and the polygonal boundaries of the tectonic source are extracted from the hierarchical source area model, and the three-level polygonal boundaries are unified as polygonal boundary data.

[0057] Among them, polygon boundary data refers to the set of boundary coordinates of all tertiary polygons extracted from the hierarchical source area model. The boundary of each polygon consists of a set of latitude and longitude coordinate points arranged in sequence, with the first and last coordinate points coinciding to form a closed polygonal region.

[0058] During the process of acquiring hierarchical source area models and extracting polygon boundary data, interactive operation functions can also be provided through the software's graphical interface.

[0059] The interface is divided into two parts: the chart area on the left and the control panel area on the right.

[0060] Above the right-hand control panel area is a level drop-down menu containing the following five level options: Level 3 - Potential Source Area - Tectonic Source, Level 3 - Potential Source Area - Background Source, Level 2 - Seismic Tectonic Area, Level 1 - Seismic Statistics Area - Seismic Zone, and a seismic activity model data option. When the user selects different level options, the program reads the polygon boundary coordinate data of the corresponding level from the data file of the level source area model and renders and displays it in the chart area on the left.

[0061] In the center of the right-hand control panel area is a target area selection panel. This panel contains multiple radio buttons, including options for All Regions, Region A, Region B, Region C, Region D, Region E, Region F, and a custom option. Users can determine the target area to be analyzed by selecting different region options. When selecting the custom option, users can manually input the latitude and longitude coordinates of the four vertices to define the target area. For example, the All Region option can be the entire country, Region A can be North China, Region B can be Northeast China, Region C can be Northwest China, Region D can be Southwest China, Region E can be South China, and Region F can be Shandong Province.

[0062] At the bottom of the right-hand control panel area is a copyright information area, which displays version information and release date, among other things.

[0063] The left-hand chart area displays a geographic base map of the target region using a latitude and longitude coordinate system. The horizontal axis represents longitude, and the vertical axis represents latitude. The polygon boundaries corresponding to the selected level option are overlaid and rendered on the geographic base map. When the user selects a region option, the range of the user-defined target analysis region is marked with a dashed rectangle.

[0064] The filtering principle of each level option in the hierarchical drop-down menu is as follows: When the user selects the Level 1 - Seismic Statistical Zone - Seismic Zone option, the program reads all polygon records marked as statistical zone level from the data file of the hierarchical source area model. The polygons at this level are delineated based on the spatial range of tectonic zones and regional seismic zones. Each statistical zone polygon corresponds to a macroscopic seismic statistical unit. When the user selects the Level 2 - Seismic Tectonic Zone option, the program reads all polygon records marked as tectonic zone level from the data file of the hierarchical source area model. The polygons at this level are delineated within the statistical zone based on the similarity of the seismic tectonic environment. Each tectonic zone polygon corresponds to a mesoscale geological tectonic unit. When the user selects the Level 3 - Potential Source Area - Tectonic Source option, the program reads all polygon records marked as tectonic source level from the data file of the hierarchical source area model. The polygons at this level are delineated based on active fault zones and densely seismically active segments. Each tectonic source polygon corresponds to one or a group of active structures with independent seismic generation capabilities.

[0065] The hierarchical drop-down selection menu refers to a drop-down selection control set in the software's graphical interface. This control contains three toggleable option items: statistical area option, structural area option, and structural source option, which correspond to the three-level division in the hierarchical source area model.

[0066] The chart area refers to the visualization area in the software's graphical interface used to display map and graphic content. When the user performs a switching operation in the hierarchy drop-down selection menu, the polygon boundary data corresponding to the selected option is read and rendered in the chart area.

[0067] Once all calculation steps for the seismic activity factor are completed, the program automatically generates a calculation completion command. In response to this command, the seismic activity factor value corresponding to the selected option is mapped to the area enclosed by the polygon boundary data in the chart area using a color gradient, thus achieving synchronous updating and display of numerical and spatial values.

[0068] This application introduces a hierarchical source region model, providing a multi-scale spatial constraint framework from macro to micro for subsequent spatial fusion and activity factor extraction.

[0069] S3: Based on the epicenter location and magnitude parameters of each earthquake in the effective earthquake event set, spatial fusion is performed within the spatial range defined by the polygon boundary data to generate an active horizontal distribution layer that covers the target area.

[0070] In step S2, polygonal boundary data has been acquired. In order to transform the spatial distribution characteristics of discrete earthquake events obtained in step S1 into continuous planar distribution information, spatial fusion processing of the epicenter location and magnitude parameters of each earthquake event is required within the spatial range defined by the polygonal boundary data. Therefore, this step performs spatial fusion to generate an active horizontal distribution layer.

[0071] Spatial fusion refers to the process of converting the spatial location information and magnitude parameter information of each earthquake event in the effective earthquake event set into a continuous raster layer covering the target area through processing steps such as spatial gridding, energy contribution value calculation, and spatial interpolation.

[0072] The activity level distribution layer refers to the raster data layer covering the target area obtained after spatial fusion. Each grid cell in this layer has a scalar value that reflects the level of seismic activity at that location.

[0073] See Figure 3 As shown, Figure 3 A schematic diagram of a spatial fusion process for generating an active horizontally distributed layer is shown. The specific implementation process of this process is as follows: S31: Divide the target area into multiple equally spaced spatial grids. A spatial grid refers to dividing the geographical range of the target area into several rectangular cells according to fixed longitude and latitude intervals. Each cell is a spatial grid. The selection of the spatial grid interval needs to take into account the geographical scale of the target area and the seismic positioning accuracy. When the target area is at the provincial level, the longitude and latitude interval can be set to 0.1 degrees. When the target area is at the city level, the interval can be reduced accordingly to obtain higher spatial resolution.

[0074] S32: Using the geometric center of each spatial grid as the computation node, calculate the energy contribution of each earthquake event to each computation node based on the spatial distance between each computation node and the epicenter of each earthquake in the effective earthquake event set.

[0075] The computation node refers to the geometric center point of each spatial grid, which serves as the spatial reference point for subsequent statistical and interpolation operations.

[0076] The energy contribution value refers to the amount of activity level impact of a single earthquake event on a certain computing node. The magnitude of this impact is positively correlated with the earthquake magnitude and negatively correlated with the distance from the earthquake epicenter to the computing node. Its physical meaning is similar to the gravitational potential of a mass on a point in space in a gravitational potential field.

[0077] The energy contribution value is calculated using a gravitational field decay model. The distance decay law of this model follows a negative power law decay form of energy with distance. The specific mathematical expression (1) is as follows:

[0078] In the mathematical expression (1): G is the energy contribution value, which is dimensionless; M is the magnitude parameter of the earthquake event, in magnitude. denoted as , representing the spatial distance from the epicenter of the earthquake event to the calculation node, in kilometers; 'a' is the magnitude amplification factor, used to control the influence of magnitude on the energy contribution value, dimensionless; 'b' is the distance attenuation index, used to control the rate attenuation of the energy contribution value as distance increases, dimensionless; 'c' is the distance smoothing constant, used to avoid numerical divergence when the distance between the earthquake epicenter and the calculation node approaches zero, in kilometers.

[0079] S33: Statistically analyze the number of earthquakes, the cumulative amount of energy contribution, and the maximum magnitude of each calculation node within the preset time limit to obtain the frequency statistics, energy statistics, and maximum magnitude statistics for each calculation node.

[0080] The preset time limit refers to the time interval range used for statistical analysis of earthquake events. The start and end times of this range can be determined based on the time span covered by the effective set of earthquake events and the needs of engineering analysis. The frequency statistics value refers to the number of earthquakes that occur within the preset time limit, where the epicenter falls within the statistical radius centered on the calculation node.

[0081] The energy statistics value refers to the sum of the energy contributions of all valid seismic events to the calculation node within a preset time limit; the maximum magnitude statistics value refers to the maximum magnitude of seismic events whose epicenter falls within the statistical radius centered on the calculation node within a preset time limit.

[0082] S34: Spatial interpolation is performed on the frequency statistics, energy statistics, and maximum magnitude statistics of each computing node to generate an activity level distribution map.

[0083] Specifically, spatial interpolation is performed on the frequency statistics, energy statistics, and maximum magnitude statistics of each calculation node to generate three independent raster layers: a frequency statistics raster layer, an energy statistics raster layer, and a maximum magnitude statistics raster layer. The reason for generating three independent raster layers first, rather than directly generating a single layer, is that these three indicators, frequency statistics, energy statistics, and maximum magnitude statistics, characterize the level of seismic activity from different dimensions. Frequency statistics reflect the density of seismic events, energy statistics reflect the comprehensive energy impact of seismic events, and maximum magnitude statistics reflect the strongest earthquake level that the region may experience. Interpolating these three independently can preserve their respective spatial distribution characteristics and avoid mutual interference between indicators with different dimensions and numerical ranges during the statistical stage.

[0084] See Figure 4 As shown, Figure 4 This diagram illustrates a method for generating an activity horizontal distribution layer by normalizing and fusing a frequency statistics raster layer, an energy statistics raster layer, and a maximum magnitude statistics raster layer; Figure 4 In the process, three independent raster layers represent the numerical values ​​at each calculation node with different gray levels. The darker the color, the larger the value. The fusion process is as follows: First, all grid values ​​in each raster layer are subjected to minimum-maximum normalization, and the values ​​in each layer are uniformly mapped to the range of 0 to 1 to eliminate the differences in the dimensions and numerical ranges between the three types of indicators. Then, the three normalized raster layers are fused by weighted summation. The fusion formula is shown in mathematical expression (2).

[0085]

[0086] In mathematical expression (2): V is the comprehensive activity level value of a certain grid in the merged activity level distribution layer, which is dimensionless; This is the normalized value of the grid in the frequency statistics raster layer, and it is dimensionless. This is the normalized value of the grid in the energy statistics raster layer, and is dimensionless. This is the normalized value of the grid in the maximum magnitude statistics raster layer, and is dimensionless. , , The fusion weighting coefficients are the frequency statistics, energy statistics, and maximum magnitude statistics, respectively. The sum of the three is equal to 1. The specific weighting values ​​can be set according to the focus of the engineering analysis. After calculating all grids one by one according to the above formula, the fused activity horizontal distribution layer is obtained.

[0087] Spatial interpolation algorithms can employ inverse distance weighted interpolation. The principle of inverse distance weighted interpolation is to perform a weighted average based on the inverse power of the distance between the point to be estimated and the known data points. The closer the known points are, the greater their contribution to the estimated value. This algorithm is suitable for spatial interpolation in this context because seismic activity levels exhibit a strong correlation in space as distance increases. Inverse distance weighted interpolation can precisely reflect this spatial autocorrelation characteristic.

[0088] In practical engineering applications, based on the effective seismic event set of region A obtained in step S1, region A is divided into equally spaced spatial grids with a spacing of 0.1 degrees, resulting in a total of 5000 spatial grids, with the geometric center of each grid serving as the calculation node.

[0089] For the first calculation node, all 1200 earthquake records in the effective earthquake event set are traversed, and the energy contribution value of each earthquake record to the calculation node is calculated one by one. It is assumed that the magnitude amplification factor a is 1.0, the distance attenuation index b is 2.0, and the distance smoothing constant c is 10 kilometers.

[0090] When the magnitude parameter M of a certain earthquake record in the effective earthquake event set is 5.5, and the spatial distance d from the epicenter of the earthquake event to the first calculation node is 30 kilometers, substituting into the mathematical expression (1) yields: Therefore, the energy contribution value of this seismic record to the first calculation node is... .

[0091] After traversing all 1200 records in this manner, the energy contribution values ​​of all records are summed to obtain the energy statistics value of the first calculation node. At the same time, the total number of earthquakes whose epicenters fall within the statistical radius within the preset time limit is counted as the frequency statistics value, and the maximum magnitude within the range is recorded as the maximum magnitude statistics value.

[0092] After completing the statistics of all 5000 computing nodes, inverse distance weighted spatial interpolation was performed on the frequency statistics, energy statistics and maximum magnitude statistics, and the three interpolation results were normalized and weighted and fused to finally generate an activity horizontal distribution layer covering region A.

[0093] The above example is only one implementation of this application. Under different target area conditions, the specific values ​​of parameters such as spatial grid spacing, magnitude amplification factor, distance attenuation index and distance smoothing constant can be adjusted according to actual needs.

[0094] After generating the activity horizontal distribution layer, since this activity horizontal distribution layer is only based on the fusion of the spatial distribution and magnitude information of earthquake events, and has not yet considered the spatial clustering characteristics of earthquake events and the time memory effect of historical strong earthquakes on the current period activity assessment, it is necessary to further introduce earthquake clustering intensity and memory correlation to correct the energy statistics.

[0095] The specific correction process is as follows: First, the seismic clustering intensity of each computing node within a preset neighborhood is extracted. The preset neighborhood refers to a circular spatial area centered on the computing node and with a set radius value as the search range, which is used to statistically analyze the spatial distribution characteristics of seismic events within this area.

[0096] Earthquake clustering intensity refers to the degree of spatial concentration of earthquake events within a preset neighborhood, used to measure whether there is a clustering of earthquake events in the area. Earthquake clustering intensity can be quantitatively calculated using the nearest neighbor index. The nearest neighbor index is calculated by dividing the actual average distance from each earthquake event to its neighboring earthquake events within the preset neighborhood by the expected average distance under the random distribution assumption (set according to needs). When the ratio is less than 1, it indicates that the earthquake events are clustered, and the smaller the ratio, the higher the degree of clustering.

[0097] Then, the historical earthquake occurrence time intervals for each computing node are obtained, and the memory correlation degree of the current time period with the historical strong earthquake magnitudes is determined based on the historical earthquake occurrence time intervals and the current time period. The historical earthquake occurrence time interval refers to the time span between the most recent strong earthquake occurrence time within the neighborhood of the computing node and the current time period, in years.

[0098] Memory correlation refers to the weight of the impact of historical strong earthquakes on the assessment of the activity level in the current period. This weight decreases as the time interval increases. The calculation of memory correlation adopts the form of an exponential decay function, and the specific mathematical expression (3) is as follows:

[0099] In mathematical expression (3): R is the memory association degree, which is dimensionless; denoted as magnitude parameter for historical strong earthquakes, in magnitude; t represents the historical earthquake time interval, in years; T is the decay time constant, used to control the rate at which the memory effect fades over time, in years; e is the base of the natural logarithm; when the time interval t is smaller, the exponential decay term is closer to 1, and the memory correlation is greater; when the time interval t is much larger than the decay time constant T, the memory correlation approaches zero.

[0100] Finally, the energy statistics of each calculation node are nonlinearly weighted and corrected based on the seismic clustering intensity and memory correlation, resulting in corrected energy statistics. The nonlinear weight correction involves normalizing the seismic clustering intensity and memory correlation to the interval between 0 and 1, and then fusing them with the original energy statistics in the form of a power function. This results in regions with high clustering intensity and high memory correlation receiving higher correction weights, while regions with low clustering intensity and low memory correlation receive lower correction weights. The corrected energy statistics replace the original energy statistics to update the activity level distribution layer.

[0101] The reason for using earthquake clustering intensity and memory correlation for correction is that seismic activity is not uniformly distributed in space but often exhibits clustering phenomena. At the same time, sections that have experienced strong earthquakes in the past still have a high potential for seismic activity in the future. By incorporating these two factors into the activity level assessment, the sensitivity of the assessment results to recent active sections and sections with recurrence of historical strong earthquakes can be enhanced.

[0102] This application improves the assessment accuracy of the activity level distribution layer by introducing seismic clustering intensity and memory correlation to perform nonlinear weight correction on energy statistics.

[0103] S4: Spatially overlay the activity horizontal distribution layer with the polygon boundary data to extract the cumulative activity falling within the polygon boundaries of each statistical area, each construction area, and each construction source polygon boundary.

[0104] In step S3, an activity level distribution layer covering the target area has been generated. In order to perform zonal statistics on the continuously distributed activity level information according to the spatial division of the hierarchical source area model, it is necessary to perform spatial overlay operation on the activity level distribution layer and the polygon boundary data. Therefore, this step performs spatial overlay and extracts the cumulative activity within the polygon boundaries of each level.

[0105] In this step, the cumulative activity level refers to the weighted sum of all spatial grids in the activity level distribution layer within the boundary of a specific polygon. This value reflects the total level of seismic activity in the area covered by the polygon, and its dimension is consistent with that of the grid values ​​in the activity level distribution layer. It is a dimensionless comprehensive activity level index value.

[0106] See Figure 5 As shown, Figure 5 A schematic diagram of a process for spatially overlaying an active horizontal distribution layer with polygon boundary data is shown. The specific implementation process of this process is as follows: S51: Perform a topological intersection operation between the active horizontal distribution layer and the polygon boundary data in the geographic information system to obtain the intersecting geometric objects.

[0107] Topological intersection is a standard spatial analysis operator in geographic information systems. The input of this operator is two sets of spatial geometric features, and the output is the geometric object and its attribute information corresponding to the spatial intersection of the two sets of features. In this application, the inputs are the spatial grid in the active horizontal distribution layer and the polygons at all levels in the polygon boundary data.

[0108] See Figure 6 As shown, Figure 6 A schematic diagram is shown illustrating the topological intersection operation and geometric intersection ratio calculation of a spatial mesh and a polygon boundary; in Figure 6In the middle, the left side shows multiple equally spaced spatial grids, represented by solid-line rectangles; the middle part is the polygon boundary, represented by a thick solid-line irregular polygon, which intersects with some spatial grids; the right side shows the result of the topological intersection operation, where spatial grids completely inside the polygons are represented by dark fill, and spatial grids cut by the polygon boundaries are divided into internal and external parts, with the internal parts represented by medium-depth fill and the external parts represented by light fill.

[0109] The specific implementation of topological intersection operation can be achieved using a polygon clipping algorithm. The calculation process of this algorithm is as follows: For each spatial grid, the four boundary line segments of the spatial grid and all line segments of the polygon boundary are traversed in turn, and the coordinates of the intersection points between each line segment are calculated; all intersection points are arranged in order of their positions on the spatial grid boundary, and combined with the inner and outer determination results of the polygon boundary, the spatial grid is cut into two geometric fragments located inside and outside the polygon.

[0110] S52: In intersecting geometric objects, calculate the proportion of the area occupied by the part of each spatial grid located inside the polygon boundary after being cut by the polygon boundary data, and obtain the geometric intersection ratio.

[0111] The geometric intersection ratio is calculated using the shoelace formula to calculate the area of ​​the geometric fragments located inside the polygon after cutting and the original area of ​​the spatial mesh, respectively. The mathematical expression of the shoelace formula (4) is:

[0112] In mathematical expression (4): S is the area of ​​the polygon, in square kilometers; and These are the x and y coordinates of the i-th vertex of the polygon, respectively; the summation operation iterates from the first vertex to the last vertex, and the next vertex after the last vertex loops back to the first vertex; || represents the absolute value operation.

[0113] Calculate the area of ​​the geometric fragment located inside the polygon after cutting. and the original area of ​​the spatial grid Then, the mathematical expression (5) for the geometric intersection ratio P is:

[0114] In the mathematical expression (5): P is the geometric intersection ratio, which ranges from 0 to 1 and is dimensionless; The area of ​​the geometric fragment located inside the polygon after the spatial grid is cut is expressed in square kilometers. This represents the original area of ​​the spatial grid, expressed in square kilometers; this applies when the spatial grid is entirely within the polygon. = The geometric intersection ratio P = 1.0; when the spatial mesh is completely outside the polygon, =0, geometric intersection ratio P=0.

[0115] S53: Based on the geometric intersection ratio of each spatial grid and the corresponding grid value of each spatial grid in the active horizontal distribution layer, calculate the grid value contribution component of each spatial grid falling inside the polygon boundary.

[0116] The grid values ​​are scalar values, that is, each spatial grid corresponds to a scalar value in the active horizontal distribution layer; the grid value contribution component is equal to the geometric intersection ratio multiplied by the grid value.

[0117] S54: Accumulate the mesh numerical contribution components of all spatial meshes within the same polygon boundary to obtain the cumulative activity of the polygon boundary.

[0118] Perform the above accumulation operation on the polygon boundaries of the statistical region, the polygon boundaries of the structural region, and the polygon boundaries of the structural source, respectively, to obtain the cumulative activity of each statistical region, the cumulative activity of each structural region, and the cumulative activity of each structural source.

[0119] In practical engineering applications, taking the third structural source 3121 in region A as an example, the polygon boundary of the third structural source 3121 involves a total of 120 spatial grids. Among them, 100 spatial grids are completely located inside the polygon of the third structural source 3121, and are represented by dark fill. The geometric intersection ratio of these 100 spatial grids is 1.0. The other 20 spatial grids are cut by the polygon boundary of the third structural source 3121, and are represented by medium-depth fill inside and light-colored fill outside.

[0120] Taking one of the cut spatial grids as an example, assuming that the grid value of the spatial grid in the active horizontal distribution layer is 0.75 and the geometric intersection ratio is 0.6, then the grid value contribution component of the spatial grid is 0.6 × 0.75 = 0.45.

[0121] After summing up all the grid numerical contribution components of the 120 spatial grids, the cumulative activity of the third structural source 3121 is obtained.

[0122] This application uses topological intersection operations and area ratio weighting to perform spatial overlay, which can accurately handle irregular cutting of spatial grids by polygon boundaries and ensure the accuracy of the activity accumulation extraction results.

[0123] S5: Based on the actual area of ​​each polygon, the cumulative activity is calculated and the seismic activity factor is obtained and output.

[0124] In step S4, the cumulative activity level within the boundaries of each level of polygon has been extracted. Since the polygon areas of different levels and regions are different, direct comparison using the cumulative activity level is not comparable. Therefore, it is necessary to calculate the cumulative activity level based on the actual area of ​​each level of polygon.

[0125] In this step, the seismic activity factor refers to the activity level value per unit physical area. This value eliminates the influence of different polygon area sizes on the activity comparison, allowing for direct comparison of seismic activity levels at different levels and in different regions. The unit of the seismic activity factor is the comprehensive activity level index value per square kilometer.

[0126] The specific implementation process for this step is as follows: First, the polygon boundary data is converted to the Mercator projection coordinate system, and the geometric vertex coordinates of each level of polygon are extracted in the Mercator projection coordinate system. The Mercator projection coordinate system is an conformal cylindrical projection coordinate system that can convert latitude and longitude coordinates on the Earth's ellipsoid into plane rectangular coordinates, which facilitates planar geometric calculations of area and distance. When the latitudinal span of the target area is large, the Mercator projection will introduce area distortion. In this case, a partitioned projection method can be used to divide the target area into several strips with smaller latitudinal spans. Within each strip, the area is calculated using the projection parameters corresponding to the central latitude, and then the results are summed to reduce the impact of area distortion.

[0127] Then, based on the geometric vertex coordinates, the horizontal projected physical area of ​​the region enclosed by each level of polygon is calculated using the polygon area calculation formula, with the unit being square kilometers. The horizontal projected physical area refers to the planar geometric area occupied by the polygon on the horizontal projection plane of the Mercator projection coordinate system. After projection distortion correction, this area value is approximately equal to the actual area of ​​the corresponding region on the Earth's ellipsoid.

[0128] Finally, the cumulative activity is divided by the corresponding horizontal projected physical area to obtain the activity level value per unit physical area, and this activity level value is output as the seismic activity factor.

[0129] In practical engineering applications, assuming that the cumulative activity of the third structural source 3121 in region A is 85.6 after step S4, after converting the polygonal boundary data of the third structural source 3121 to the Mercator projection coordinate system, the coordinates of each geometric vertex are extracted and the horizontal projected physical area is calculated to be 1280 square kilometers.

[0130] The seismic activity factor of the third tectonic source 3121 is 85.6 / 1280 = 0.0669 per square kilometer. Similarly, the seismic activity factors of each tectonic zone and each statistical zone can be calculated separately.

[0131] This application normalizes the cumulative activity level to a unit area by using area-averaging calculation, making the activity assessment results of polygons with different area scales comparable.

[0132] After obtaining the seismic activity factor and completing the visualization mapping, the display ratio of the chart area can be adjusted according to the preset paper layout size of the engineering report.

[0133] The preset paper layout size refers to the output paper specifications agreed upon in the engineering report. The process of adjusting the display scale is as follows: obtain the preset paper layout size parameters, map the spatial range of the geographic elements in the chart area to the page coordinate system corresponding to the paper layout size, and use affine transformation to realize the conversion from geographic coordinates to page coordinates during the mapping process, while maintaining the consistency of the scale of geographic elements on the page.

[0134] Then, the polygonal boundary graphic with seismic activity factor superimposed on the adjusted chart area is rendered into a vector graphic file. The vector graphic file can be in scalable vector graphic format or portable document format. This vector graphic file has lossless scaling characteristics and will not have pixelation distortion after being enlarged or reduced. Finally, the vector graphic file is saved to the preset output directory.

[0135] In summary, the seismic activity factor extraction method based on seismic data provided in this application obtains a high-quality effective set of seismic events by screening seismic data by magnitude and removing aftershocks. Combined with the multi-level spatial constraint framework provided by the hierarchical source area model, spatial fusion of discrete seismic events into a continuous horizontal distribution layer is achieved through spatial gridding and energy contribution value calculation within the spatial range defined by polygon boundary data. Then, the accurate overlay of the horizontal distribution layer of activity with the multi-level polygon boundary is achieved through topological intersection operation and area ratio weighting. Finally, the seismic activity factor corresponding to each level of polygon is obtained through area amortization calculation. This method improves the spatial resolution of quantitative seismic activity assessment, enhances the spatial consistency among multi-level assessment results, and increases the sensitivity of assessment results to recent active zones and historical strong earthquake recurrence zones.

[0136] See Figure 7 As shown, Figure 7 A schematic diagram of a seismic activity factor extraction system based on seismic data is shown. The seismic activity factor extraction system includes a processor 71, a memory 72, and a bus 73. The processor 71 and the memory 72 are connected by the bus 73.

[0137] The memory 72 stores a computer program, which, when executed by the processor 71, causes the seismic activity factor extraction system to perform the methods described in the above embodiments.

[0138] This application also provides a seismic activity factor extraction system based on seismic data, including: The acquisition module is used to acquire seismic data of the target area, filter the seismic data by magnitude and remove aftershocks to obtain a set of effective seismic events; The extraction module is used to obtain the hierarchical source area model of the target area and extract the polygonal boundaries of the statistical area, the polygonal boundaries of the tectonic area, and the polygonal boundaries of the tectonic source from the hierarchical source area model as polygonal boundary data. The statistical area, the tectonic area, and the tectonic source are superimposed in the hierarchical source area model. The fusion module is used to perform spatial fusion within the spatial range defined by polygon boundary data based on the epicenter location and magnitude parameters of each earthquake in the effective seismic event set, and generate an active horizontal distribution layer that covers the target area. The overlay module is used to spatially overlay the activity horizontal distribution layer with the polygon boundary data and extract the cumulative activity falling within the polygon boundaries of each statistical area, each construction area, and each construction source polygon boundary. The calculation module is used to calculate the cumulative activity based on the actual area of ​​each level of polygon, obtain the seismic activity factor, and output it.

[0139] The seismic activity factor extraction system based on seismic data in this application embodiment is used to implement the aforementioned seismic activity factor extraction method based on seismic data. Therefore, the specific implementation of the seismic activity factor extraction system based on seismic data can be found in the embodiment section of the seismic activity factor extraction method based on seismic data above. The specific implementation can be referred to the description of the corresponding embodiments, which will not be repeated here.

[0140] This application also provides an electronic device, including: a memory for storing a computer program; and a processor for executing the computer program to implement the steps of the seismic activity factor extraction method based on seismic data as described above.

[0141] This application also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of any of the above-described methods for extracting seismic activity factors based on seismic data.

[0142] In one exemplary embodiment, the aforementioned computer-readable storage medium may include, but is not limited to, various media capable of storing computer programs, such as USB flash drives, read-only memory, random access memory, portable hard drives, magnetic disks, or optical disks.

[0143] The embodiments of this application also provide a computer program product, which includes a computer program that, when executed by a processor, implements the steps in any of the embodiments of the seismic activity factor extraction method based on seismic data.

[0144] Those skilled in the art will further recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0145] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in one or more embodiments of this specification are all information and data authorized by the user or fully authorized by all parties. Furthermore, the collection, use and processing of related data must comply with relevant laws, regulations and standards, and corresponding operation entry points are provided for users to choose to authorize or refuse.

[0146] The foregoing has provided a detailed description of a method and system for extracting seismic activity factors based on seismic data, as provided in this application. Specific examples have been used to illustrate the principles and implementation methods of this application. The descriptions of the embodiments above are merely for the purpose of helping to understand the method and its core ideas. It should be noted that those skilled in the art can make various improvements and modifications to this application without departing from its principles, and these improvements and modifications also fall within the protection scope of this application.

Claims

1. A method for extracting seismic activity factors based on seismic data, characterized in that, include: Seismic data for the target area is acquired, and the seismic data is filtered by magnitude and aftershocks are removed to obtain a set of effective seismic events. Obtain a hierarchical source region model of the target area, and extract the polygonal boundaries of the statistical region, the polygonal boundaries of the tectonic region, and the polygonal boundaries of the tectonic source from the hierarchical source region model as polygonal boundary data, wherein the statistical region, the tectonic region, and the tectonic source are superimposed in the hierarchical source region model; Based on the epicenter location and magnitude parameters of each earthquake in the effective earthquake event set, spatial fusion is performed within the spatial range defined by the polygon boundary data to generate an active horizontal distribution layer, which covers the target area. The activity level distribution layer is spatially overlaid with the polygon boundary data to extract the cumulative activity level that falls within the polygon boundaries of each statistical area, each polygon boundary of each construction area, and each polygon boundary of the construction source. Based on the actual area of ​​each polygon, the cumulative activity is calculated by amortization to obtain the seismic activity factor, which is then output.

2. The method according to claim 1, characterized in that, The process involves spatially fusing the epicenter locations and magnitude parameters of each earthquake within the effective seismic event set, within the spatial range defined by the polygonal boundary data, to generate an active horizontal distribution layer, including: The target area is divided into multiple equally spaced spatial grids; Using the geometric center of each spatial grid as a computation node, the energy contribution value of each earthquake event to each computation node is calculated based on the spatial distance between each computation node and the epicenter of each earthquake in the effective earthquake event set. The frequency, energy, and maximum magnitude of each computing node within a preset time limit are statistically analyzed to obtain the frequency statistics, energy statistics, and maximum magnitude statistics of each computing node. Spatial interpolation is performed on the frequency statistics, energy statistics, and maximum magnitude statistics of each computing node to generate an active horizontal distribution layer.

3. The method according to claim 2, characterized in that, After generating the active horizontal distribution layer, the following is also included: Extract the seismic clustering intensity of each computing node within a preset neighborhood range; Obtain the historical earthquake occurrence time intervals corresponding to the locations of each computing node, and determine the memory correlation degree of the current time period with the historical strong earthquake magnitudes based on the historical earthquake occurrence time intervals and the current time period; Based on the earthquake clustering intensity and the memory correlation degree, the energy statistics of each computing node are corrected by nonlinear weights to obtain the corrected energy statistics. Replace the energy statistics with the corrected energy statistics to update the activity level distribution layer.

4. The method according to claim 1, characterized in that, The step of spatially overlaying the activity horizontal distribution layer with the polygon boundary data and extracting the cumulative activity falling within the polygon boundaries of each statistical region, each construction region, and each construction source polygon boundary includes: The active horizontal distribution layer and the polygon boundary data are subjected to a topological intersection operation in the geographic information system to obtain the intersecting geometric objects. In the intersecting geometric objects, the proportion of the area occupied by the portion of each spatial grid located inside the polygon boundary after being cut by the polygon boundary data is calculated to obtain the geometric intersection ratio; Based on the geometric intersection ratio of each spatial grid and the corresponding grid value of each spatial grid in the active horizontal distribution layer, calculate the grid value contribution component of each spatial grid falling inside the polygon boundary; The cumulative activity of the polygon boundary is obtained by summing the grid numerical contribution components of all the spatial grids within the same polygon boundary.

5. The method according to claim 1, characterized in that, The process of amortizing the cumulative activity based on the actual area of ​​polygons at each level to obtain and output the seismic activity factor includes: The polygon boundary data is converted to the Mercator projection coordinate system, and the geometric vertex coordinates of each level of polygon are extracted in the Mercator projection coordinate system. Calculate the horizontal projected physical area of ​​the region enclosed by polygons of all levels based on the coordinates of the geometric vertices. Divide the cumulative activity level by the corresponding horizontal projected physical area to obtain the activity level value per unit physical area, and output the activity level value as the seismic activity factor.

6. The method according to claim 1, characterized in that, Before acquiring seismic data for the target area, performing magnitude screening and aftershock removal on the seismic data, and obtaining a valid set of seismic events, the process also includes: Receive a target area selection instruction and determine the geographic spatial range to be analyzed. The target area selection instruction is either a selection instruction for a preset fixed area or a custom area division instruction based on the latitude and longitude coordinates of the four vertices input by the user. Based on the geographic spatial range, the basic files of the geographic information system and the directory of historical seismic networks under the preset storage path are read as earthquake data.

7. The method according to claim 1, characterized in that, The process of filtering earthquake data by magnitude and removing aftershocks yields a set of effective earthquake events, including: Using a preset year as a boundary, the historical data recorded in the earthquake data is filtered using the first lower limit of magnitude, and the data recorded by modern instruments is filtered using the second lower limit of magnitude to obtain a preliminary earthquake sequence. Set up spatial and temporal search windows to identify the mainshock and associated cluster earthquake events from the preliminary earthquake sequence; The clustered earthquake events are removed, and the earthquake events remaining after removing the clustered earthquake events from the preliminary earthquake sequence are determined as the effective earthquake event set.

8. The method according to claim 1, characterized in that, In the process of obtaining the hierarchical source region model of the target area, and extracting the polygonal boundaries of the statistical region, the polygonal boundaries of the tectonic region, and the polygonal boundaries of the tectonic source region from the hierarchical source region model as polygonal boundary data, the following further steps are included: The software's graphical interface displays a hierarchical drop-down selection menu, which includes a statistics area option, a construction area option, and a construction source option. The statistics area option, construction area option, and construction source option correspond to three levels of division, respectively. In response to a toggle operation on any option in the hierarchical drop-down selection menu, the polygon boundary data corresponding to the selected option is read, and the polygon boundary data is rendered in the chart area; In response to the completion command of the calculation of the seismic activity factor, the seismic activity factor value corresponding to the selected option is mapped to the area enclosed by the polygon boundary data in the chart area and the display is updated synchronously.

9. The method according to claim 8, characterized in that, After mapping the seismic activity factor value corresponding to the selected option to the area enclosed by the polygon boundary data in the chart area, the process further includes: Based on the preset paper layout size of the engineering report, adjust the display ratio of the chart area in the software's graphical interface to obtain the adjusted chart area display content; The polygonal boundary graphic with the seismic activity factor superimposed on the content of the adjusted chart area is rendered as a vector graphic file, and the vector graphic file has the characteristic of lossless scaling. Save the vector graphics file to the preset output directory.

10. A seismic activity degree factor extraction system based on seismic data, characterized in that, include: The acquisition module is used to acquire seismic data of the target area, perform magnitude screening and aftershock removal on the seismic data, and obtain a set of effective seismic events; The extraction module is used to obtain the hierarchical source area model of the target area, and extract the polygonal boundaries of the statistical area, the polygonal boundaries of the tectonic area, and the polygonal boundaries of the tectonic source from the hierarchical source area model as polygonal boundary data, wherein the statistical area, the tectonic area, and the tectonic source are superimposed in the hierarchical source area model. The fusion module is used to perform spatial fusion within the spatial range defined by the polygon boundary data based on the epicenter location and magnitude parameters of each earthquake in the effective earthquake event set, and to generate an active horizontal distribution layer that covers the target area. The overlay module is used to spatially overlay the activity horizontal distribution layer with the polygon boundary data and extract the cumulative activity falling within the polygon boundaries of each statistical area, each polygon boundary of each construction area, and each polygon boundary of the construction source. The calculation module is used to perform amortization calculation on the cumulative activity based on the actual area of ​​each level of polygon, obtain the seismic activity factor, and output it.

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