A method and system for realizing earthquake early warning simulation based on a seismic network and WEBGL

Abstract

A method for realizing earthquake early warning simulation based on a seismic network and WEBGL comprises the following steps: S100, acquiring seismic network data, monitoring station data and three-dimensional geological body modeling data; S200, constructing a three-dimensional geological body model according to the acquired three-dimensional geological body modeling data according to a preset rule; S300, acquiring seismic surface wave and body wave results according to the acquired seismic network data and monitoring station data; and S400, combining the acquired seismic surface wave and body wave results with the constructed three-dimensional geological body model to realize an earthquake wave propagation simulation effect. The present application is based on Chinese seismic network monitoring data combined with WEBGL, and is aimed at a region where geological data collection has been performed. According to the stratum structure and medium properties in the collection region, the detection data returned by the monitoring station terminal are analyzed through built-in calculation formulas to respectively calculate the diffusion rate and diffusion distance of the surface wave and body wave of the earthquake point, and finally the real-time earthquake position and diffusion range are displayed to provide early warning and reference for earthquake prevention and disaster relief work in the region.

Description

Technical Field

[0001] This invention relates to the field of earthquake early warning, and in particular to a method and system for earthquake early warning simulation based on seismic networks and WEBGL. Background Technology

[0002] Monitoring data is a crucial output of earthquake monitoring, providing fundamental data for earthquake early warning and scientific research. However, in reality, the processing of monitoring data faces several challenges, such as unstable data quality, long processing times, and high processing costs. These issues severely impact the reliability and real-time nature of monitoring data, thereby affecting the accuracy and reliability of earthquake early warning and scientific research. Earthquake early warning is a vital application of earthquake monitoring, capable of reducing loss of life and property caused by earthquakes. However, in practice, problems such as short warning times and unclear warning ranges affect the accuracy and reliability of earthquake early warning systems. Summary of the Invention

[0003] In view of the above problems, the present invention is proposed to provide a method and system for earthquake early warning simulation based on seismic networks and WEBGL to overcome or at least partially solve the above problems.

[0004] To address the aforementioned technical problems, the embodiments of this application disclose the following technical solutions:

[0005] A method for earthquake early warning simulation based on seismic networks and WEBGL includes:

[0006] S100. Acquire seismic network data, monitoring station data, and 3D geological body modeling data;

[0007] S200. Based on the acquired three-dimensional geological body modeling data, construct a three-dimensional geological body model according to preset rules;

[0008] S300. Based on the acquired seismic network data and monitoring station data, obtain the seismic surface wave and body wave results;

[0009] S400 combines the acquired seismic surface wave and body wave results with the constructed three-dimensional geological model to achieve the effect of seismic wave propagation simulation.

[0010] Furthermore, in S100, the background Java program continuously accesses the China Earthquake Networks Center to obtain the latest data in real time and store it in the database; the monitoring station data includes at least the arrival time of P-waves and S-waves detected by the monitoring station and the earthquake azimuth, and the wave velocity and propagation distance are calculated by the time interval between the arrival of seismic waves between stations; the three-dimensional geological body modeling data includes at least the distribution of geological fault zones, the distribution of rock strata structure, and basic geological attribute data.

[0011] Furthermore, in S200, based on the acquired 3D geological body modeling data, a 3D geological body model is constructed according to preset rules, including:

[0012] S201. Obtain the basic data of geological body coordinates, elevation, range, and velocity, and organize them into an Excel file;

[0013] S202. Import the compiled Excel file into the modeling software;

[0014] S203. Set the Excel data columns associated with the horizontal and vertical axes, and confirm the range of the horizontal and vertical axes of the model, and set the number of rows and columns;

[0015] S204. Set the average value grading based on the range of rate values ​​in Excel;

[0016] S205. Construct and export the geological body model using the attribute preview.

[0017] Furthermore, in S300, seismic surface waves are obtained based on the acquired seismic network data and monitoring station data. Specific methods include: using a Java program to simulate a browser accessing the seismic station website, and then parsing the data in the Java program; using JSONP to request the target page, parsing the requested data to obtain the real-time earthquake location, earthquake magnitude, and focal depth.

[0018] Furthermore, in S300, seismic surface waves are obtained based on the acquired seismic network data and monitoring station data. The specific methods include: based on the monitoring data returned by the monitoring stations: the arrival time of P-wave and the arrival time of S-wave, the epicentral distance is calculated according to the system's built-in algorithm (arrival time of S-wave - arrival time of P-wave) / 2 * propagation velocity.

[0019] Furthermore, in S300, seismic surface waves are obtained based on the acquired seismic network data and monitoring station data. The specific methods also include: inputting the name of the three-dimensional geological body model and the location of the seismic point, calculating the incident angle of the seismic wave based on the ratio of the seismic point location to the refractive index of the rock layer, calculating the reflection angle and refraction angle based on the normal, and then obtaining the coordinates of the refraction point and the coordinates of the reflection point based on the input seismic point coordinates X and the distance and distance cos azimuth angle.

[0020] Furthermore, in S400, the acquired seismic surface wave and body wave results are combined with the construction of a three-dimensional geological model. The specific methods include: based on the surface wave and body wave results, obtaining the source point data for drawing surface waves, seismic wave velocity data, SVG information and feature location information of the stratigraphic profile for drawing body waves, as well as two-dimensional coordinate arrays of seismic waves and reflection lines.

[0021] Furthermore, in S400, the simulation effect of seismic wave propagation is achieved through specific methods including: the front end integrates and processes the returned data, and plots the simulation effect of body wave propagation in three-dimensional strata and the dynamic propagation effect of surface wave on the stratum surface based on the stratum data of the source point and the seismic wave velocity and propagation radius.

[0022] This invention also discloses a system for earthquake early warning simulation based on seismic networks and WEBGL, comprising: a data acquisition unit, a three-dimensional geological body model construction unit, a seismic surface wave and volume wave result acquisition unit, and a seismic wave propagation simulation effect realization unit; wherein:

[0023] The data acquisition unit is used to acquire seismic network data, monitoring station data, and three-dimensional geological body modeling data.

[0024] The three-dimensional geological body model construction unit is used to construct a three-dimensional geological body model according to preset rules based on the acquired three-dimensional geological body modeling data.

[0025] The seismic surface wave and body wave result acquisition unit is used to acquire seismic surface wave and body wave results based on the acquired seismic network data and monitoring station data.

[0026] The seismic wave propagation simulation effect realization unit is used to combine the acquired seismic surface wave and body wave results with the constructed three-dimensional geological model to realize the seismic wave propagation simulation effect.

[0027] Furthermore, a system for earthquake early warning simulation based on seismic networks and WEBGL includes: a three-dimensional geological body model construction unit, which constructs a three-dimensional geological body model according to preset rules based on acquired three-dimensional geological body modeling data. The preset rules include:

[0028] S201. Obtain the basic data of geological body coordinates, elevation, range, and velocity, and organize them into an Excel file;

[0029] S202. Import the compiled Excel file into the modeling software;

[0030] S203. Set the Excel data columns associated with the horizontal and vertical axes, and confirm the range of the horizontal and vertical axes of the model, and set the number of rows and columns;

[0031] S204. Set the average value grading based on the range of rate values ​​in Excel;

[0032] S205. Construct and export the geological body model using the attribute preview.

[0033] The beneficial effects of the above-described technical solutions provided in the embodiments of the present invention include at least the following:

[0034] This invention discloses a method for earthquake early warning simulation based on seismic networks and WEBGL, comprising: S100. acquiring seismic network data, monitoring station data, and three-dimensional geological body modeling data; S200. constructing a three-dimensional geological body model according to preset rules based on the acquired three-dimensional geological body modeling data; S300. acquiring seismic surface wave and body wave results based on the acquired seismic network data and monitoring station data; S400. combining the acquired seismic surface wave and body wave results with the constructed three-dimensional geological body model to achieve the effect of seismic wave propagation simulation.

[0035] This invention, based on monitoring data from the China Earthquake Networks Center and combined with WebGL, targets areas where geological data has been collected. Based on the stratigraphic structure and medium properties within the collected area, and according to the detection data returned by the monitoring station terminals, it uses built-in calculation formulas to perform comprehensive calculation and analysis, calculating the propagation rate and distance of surface waves and body waves at the earthquake point. Finally, it displays the real-time earthquake location and propagation range on a Cesium sphere through 3D animation, providing early warning and reference for earthquake prevention and disaster relief work in the region.

[0036] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0037] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used in conjunction with embodiments of the invention to explain the invention and do not constitute a limitation thereof. In the drawings:

[0038] Figure 1 This is a flowchart of a method for earthquake early warning simulation based on seismic networks and WEBGL, as described in Embodiment 1 of the present invention.

[0039] Figure 2 This is the simulation effect of seismic wave propagation in strata in Embodiment 1 of the present invention;

[0040] Figure 3 This is a simulation of seismic wave propagation on the Earth's surface in Embodiment 1 of the present invention. Detailed Implementation

[0041] Exemplary embodiments of the present disclosure will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.

[0042] To address the problems existing in the prior art, embodiments of the present invention provide a method and system for earthquake early warning simulation based on seismic networks and WEBGL.

[0043] Example 1

[0044] This embodiment discloses a method for earthquake early warning simulation based on seismic networks and WEBGL, such as... Figure 1 ,include:

[0045] S100. Acquire seismic network data, monitoring station data, and 3D geological body modeling data; specifically, in S100 of this embodiment, the background Java program continuously accesses the China Seismic Network to acquire the latest data in real time and store it in the database; monitoring station data includes at least the arrival time and earthquake azimuth of P-waves (vibration direction is the same as the propagation direction) and S-waves (vibration direction is perpendicular to the propagation direction) detected by the monitoring stations, and the wave velocity and propagation distance are calculated by the time interval between the arrival of seismic waves between stations; 3D geological body modeling data includes at least the distribution of geological fault zones, the distribution of rock strata structure, and basic geological attribute data.

[0046] S200. Based on the acquired three-dimensional geological body modeling data, construct a three-dimensional geological body model according to preset rules; specifically, in S200 of this embodiment, based on the acquired three-dimensional geological body modeling data, construct a three-dimensional geological body model according to preset rules, the preset rules including:

[0047] S201. Obtain the basic data of geological body coordinates, elevation, range, and velocity, and organize them into an Excel file;

[0048] S202. Import the compiled Excel file into the modeling software;

[0049] S203. Set the Excel data columns associated with the horizontal and vertical axes, and confirm the range of the horizontal and vertical axes of the model, and set the number of rows and columns;

[0050] S204. Set the average value grading based on the range of rate values ​​in Excel;

[0051] S205. Construct and export the geological body model using the attribute preview.

[0052] S300. Based on the acquired seismic network data and monitoring station data, obtain seismic surface wave and body wave results; In S300 of this embodiment, the method for obtaining seismic surface waves based on the acquired seismic network data and monitoring station data includes: simulating a browser access to a target website through a Java program, and then parsing the data in the Java program; requesting the target page using JSONP, and parsing the requested data to obtain real-time earthquake location, earthquake magnitude, and focal depth.

[0053] In some preferred embodiments, seismic surface waves are obtained based on the acquired seismic network data and monitoring station data. The specific method includes: based on the monitoring data returned by the monitoring stations: the arrival time of P-wave (the vibration direction is the same as the propagation direction, which is the seismic P-wave) and the arrival time of S-wave (the vibration direction is perpendicular to the propagation direction, which is the seismic S-wave), the epicentral distance is calculated according to the system's built-in algorithm (arrival time of S-wave - arrival time of P-wave) / 2 * propagation speed (calculated with the destructive S-wave speed of 4 km / s).

[0054] In some preferred embodiments, seismic surface waves are obtained based on the acquired seismic network data and monitoring station data. The specific method further includes: inputting the name of the three-dimensional geological body model and the location of the seismic point; calculating the incident angle of the seismic wave based on the ratio of the seismic point location to the refractive index of the rock layer; calculating the reflection angle and refraction angle based on the normal; and then obtaining the coordinates of the refraction point and the coordinates of the reflection point based on the input seismic point coordinates X and the distance and distance cos azimuth angle.

[0055] S400 combines the acquired seismic surface wave and body wave results with the constructed three-dimensional geological model to achieve the effect of seismic wave propagation simulation.

[0056] In S400 of this embodiment, the acquired seismic surface wave and body wave results are combined with the construction of a three-dimensional geological model. The specific method includes: based on the surface wave and body wave results, obtaining the source point data for drawing surface waves, seismic wave velocity data, SVG information and feature location information for drawing the stratigraphic profile of body waves, as well as two-dimensional coordinate arrays of seismic waves and reflection lines.

[0057] In S400 of this embodiment, the seismic wave propagation simulation effect is achieved. The specific method includes: the front end integrates and processes the returned data, and based on the seismic source point stratum data and the seismic wave velocity and propagation radius, plots the simulation effect of body wave propagation in the three-dimensional strata and the dynamic propagation effect of surface waves on the stratum surface. The seismic wave stratum propagation simulation effect and the seismic wave surface propagation simulation effect are as follows: Figure 2 and 3 As shown.

[0058] This embodiment discloses a method for earthquake early warning simulation based on seismic networks and WEBGL, including: S100. acquiring seismic network data, monitoring station data, and three-dimensional geological body modeling data; S200. constructing a three-dimensional geological body model according to preset rules based on the acquired three-dimensional geological body modeling data; S300. acquiring seismic surface wave and body wave results based on the acquired seismic network data and monitoring station data; S400. combining the acquired seismic surface wave and body wave results with the constructed three-dimensional geological body model to achieve the effect of seismic wave propagation simulation. This invention, based on monitoring data from the China Seismic Network and WEBGL, targets areas where geological data has been collected. Based on the stratigraphic structure and medium properties within the collected area, and according to the detection data returned by the monitoring station terminals, it performs comprehensive calculation and analysis using built-in calculation formulas to calculate the diffusion rate and diffusion distance of surface waves and body waves at the earthquake point, ultimately displaying the real-time earthquake location and diffusion range, providing early warning and reference for earthquake prevention and disaster relief work in the area.

[0059] Example 2

[0060] A system for earthquake early warning simulation based on a seismic network and WEBGL, as described in Example 1, includes: a data acquisition unit, a three-dimensional geological body model construction unit, a seismic surface wave and body wave result acquisition unit, and a seismic wave propagation simulation effect realization unit; wherein:

[0061] The data acquisition unit is used to acquire seismic network data, monitoring station data, and 3D geological body modeling data. Specifically, it continuously accesses the China Seismic Network through a background Java program to acquire the latest data in real time and store it in the database. The monitoring station data includes at least the arrival times of P-waves and S-waves and the azimuth of the earthquakes detected by the monitoring stations. The wave velocity and propagation distance are calculated from the time interval between the arrival of seismic waves between stations. The 3D geological body modeling data includes at least the distribution of geological fault zones, the distribution of rock strata, and basic geological attribute data.

[0062] A 3D geological body model construction unit is used to construct a 3D geological body model according to preset rules based on the acquired 3D geological body modeling data. The preset rules include:

[0063] S201. Obtain the basic data of geological body coordinates, elevation, range, and velocity, and organize them into an Excel file;

[0064] S202. Import the compiled Excel file into the modeling software;

[0065] S203. Set the Excel data columns associated with the horizontal and vertical axes, and confirm the range of the horizontal and vertical axes of the model, and set the number of rows and columns;

[0066] S204. Set the average value grading based on the range of rate values ​​in Excel;

[0067] S205. Construct and export the geological body model using the attribute preview.

[0068] The seismic surface wave and body wave result acquisition unit is used to obtain seismic surface wave and body wave results based on the acquired seismic network data and monitoring station data. Specifically, the method for acquiring seismic surface waves based on the acquired seismic network data and monitoring station data includes: simulating a browser access to the seismic station website using a Java program, and then parsing the data in the Java program; and using JSONP to request the target page, parsing the requested data to obtain real-time earthquake location, earthquake magnitude, and focal depth.

[0069] Based on the acquired seismic network and monitoring station data, seismic surface waves are obtained. Specific methods include: 1) Calculating the epicentral distance using the system's built-in algorithm ((S-wave arrival time - P-wave arrival time) / 2 * propagation velocity) based on the monitoring data returned by the monitoring stations (P-wave arrival time - S-wave arrival time) * propagation velocity. 2) 3) Obtaining seismic surface waves using the acquired seismic network and monitoring station data, specifically by: inputting the name of the 3D geological model and the location of the seismic point; calculating the seismic wave incident angle based on the ratio of the seismic point location to the refractive index of the rock strata; calculating the reflection angle and refraction angle based on the normal; and finally obtaining the coordinates of the refraction point and the reflection point based on the input seismic point coordinates (X-coordinate) and the distance and distance cos azimuth.

[0070] The seismic wave propagation simulation unit is used to combine the acquired seismic surface wave and body wave results with the constructed three-dimensional geological model to achieve the seismic wave propagation simulation effect. Specifically, combining the acquired seismic surface wave and body wave results with the constructed three-dimensional geological model involves: obtaining the source point data for plotting the surface waves, seismic wave velocity data, and SVG information and feature location information for plotting the stratigraphic profile of the body waves, as well as two-dimensional coordinate arrays of the seismic waves and reflection lines, based on the surface wave and body wave results. The specific methods for achieving the seismic wave propagation simulation effect include: the front-end integrates and processes the returned data, and plots the simulation effect of body wave propagation in the three-dimensional stratigraphy and the dynamic propagation effect of surface waves on the stratigraphic surface based on the source point stratigraphic data, seismic wave velocity, and propagation radius.

[0071] This embodiment, based on monitoring data from the China Earthquake Networks Center and combined with WEBGL, targets areas where geological data has been collected. Based on the stratigraphic structure and medium properties within the collected area, and according to the detection data returned by the monitoring station terminals, it uses built-in calculation formulas to perform comprehensive calculation and analysis, calculating the propagation rate and distance of surface waves and body waves at the earthquake point. Finally, it displays the real-time earthquake location and propagation range on the Cesium sphere through 3D animation, providing early warning and reference for earthquake prevention and disaster relief work in the region.

[0072] It should be understood that the specific order or hierarchy of steps in the disclosed process is an example of an exemplary method. Based on design preferences, it should be understood that the specific order or hierarchy of steps in the process may be rearranged without departing from the scope of this disclosure. The appended method claims provide elements of various steps in an exemplary order and are not intended to limit the scope to the specific order or hierarchy described.

[0073] In the detailed description above, various features are combined together in a single embodiment to simplify this disclosure. This approach to disclosure should not be construed as reflecting an intention that embodiments of the claimed subject matter require more features than are explicitly stated in each claim. Rather, as reflected in the appended claims, the invention is presented with fewer features than all of the features in a single disclosed embodiment. Therefore, the appended claims are hereby explicitly incorporated into the detailed description, with each claim representing a separate preferred embodiment of the invention.

[0074] Those skilled in the art will also understand that the various illustrative logic blocks, modules, circuits, and algorithm steps described in conjunction with the embodiments herein can be implemented as electronic hardware, computer software, or a combination thereof. To clearly illustrate the interchangeability between hardware and software, the various illustrative components, blocks, modules, circuits, and steps described above are generally described in terms of their functionality. Whether such functionality is implemented as hardware or software depends on the specific application and the design constraints imposed on the overall system. Those skilled in the art can implement the described functionality in alternative ways for each specific application; however, such implementation decisions should not be construed as departing from the scope of this disclosure.

[0075] The steps of the methods or algorithms described in conjunction with the embodiments herein can be directly embodied in hardware, software modules executed by a processor, or a combination thereof. The software modules can reside in RAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory, registers, hard disks, removable disks, CD-ROMs, or any other form of storage medium well known in the art. An exemplary storage medium is connected to the processor, enabling the processor to read information from and write information to the storage medium. Of course, the storage medium can also be a component of the processor. The processor and storage medium can reside in an ASIC. The ASIC can reside in a user terminal. Alternatively, the processor and storage medium can exist as discrete components in the user terminal.

[0076] For software implementation, the techniques described in this application can be implemented using modules (e.g., procedures, functions, etc.) that perform the functions described in this application. This software code can be stored in memory units and executed by a processor. The memory units can be implemented within the processor or outside the processor; in the latter case, they are communicatively coupled to the processor via various means, as is well known in the art.

[0077] The foregoing description includes examples of one or more embodiments. It is certainly impossible to describe all possible combinations of components or methods in order to describe the above embodiments, but those skilled in the art will recognize that further combinations and arrangements of the various embodiments are possible. Therefore, the embodiments described herein are intended to cover all such changes, modifications, and variations that fall within the scope of the appended claims. Furthermore, the term "comprising" as used in the specification or claims is interpreted in a manner similar to the term "including," as interpreted when used as a conjunction in the claims. Additionally, the use of any term "or" in the specification of the claims is intended to mean "non-exclusive or."

Claims

1. A method for earthquake early warning simulation based on seismic networks and WEBGL, characterized in that, include: S100. Acquire seismic network data, monitoring station data, and 3D geological body modeling data; S200. Based on the acquired three-dimensional geological body modeling data, construct a three-dimensional geological body model according to preset rules; S300. Based on the acquired seismic network data and monitoring station data, obtain seismic surface wave and body wave results; In S300, based on the acquired seismic network data and monitoring station data, obtain seismic surface waves. Specific methods include: simulating a browser access to the seismic station website using a Java program, and then parsing the data in the Java program; using JSONP to request the target page, parsing the requested data to obtain real-time earthquake location, earthquake magnitude, and focal depth; In S300, seismic surface waves are obtained based on the acquired seismic network data and monitoring station data. The specific methods include: based on the monitoring data returned by the monitoring stations: the arrival time of P-wave and the arrival time of S-wave, the epicentral distance is calculated according to the system's built-in algorithm (arrival time of S-wave - arrival time of P-wave) / 2 * propagation velocity; In S300, seismic surface waves are obtained based on the acquired seismic network data and monitoring station data. The specific method also includes: inputting the name of the three-dimensional geological body model and the location of the seismic point, calculating the incident angle of the seismic wave based on the ratio of the seismic point location and the refractive index of the rock layer, calculating the reflection angle and refraction angle based on the normal, and then obtaining the coordinates of the refraction point and the coordinates of the reflection point based on the input seismic point coordinates X and the distance and distance cos azimuth angle. S400 combines the acquired seismic surface wave and body wave results with the constructed three-dimensional geological model to achieve the effect of seismic wave propagation simulation.

2. The method for earthquake early warning simulation based on seismic networks and WEBGL as described in claim 1, characterized in that, In S100, a background Java program continuously accesses the China Earthquake Networks Center to obtain the latest data in real time and store it in the database; monitoring station data includes at least the arrival time of P-waves and S-waves and the azimuth of the earthquakes detected by the monitoring stations, and wave velocity and propagation distance are calculated by the time interval between the arrival of seismic waves between stations; three-dimensional geological body modeling data includes at least the distribution of geological fault zones, the distribution of rock strata, and basic geological attribute data.

3. The method for earthquake early warning simulation based on seismic networks and WEBGL as described in claim 1, characterized in that, In S200, based on the acquired 3D geological body modeling data, a 3D geological body model is constructed according to preset rules, including: S201. Obtain the basic data of geological body coordinates, elevation, range, and velocity, and organize them into an Excel file; S202. Import the compiled Excel file into the modeling software; S203. Set the Excel data columns to be linked to the horizontal and vertical axes, and confirm the range of the horizontal and vertical axes of the model, and set the number of rows and columns; S204. Set the average value grading based on the range of rate values ​​in Excel; S205. Construct and export the geological body model using the attribute preview.

4. The method for earthquake early warning simulation based on seismic networks and WEBGL as described in claim 1, characterized in that, In S400, the acquired seismic surface wave and body wave results are combined with the construction of a three-dimensional geological model. The specific methods include: based on the surface wave and body wave results, obtaining the source point data for drawing surface waves, seismic wave velocity data, SVG information and feature location information for drawing the stratigraphic profile of body waves, as well as two-dimensional coordinate arrays of seismic waves and reflection lines.

5. The method for earthquake early warning simulation based on seismic networks and WEBGL as described in claim 1, characterized in that, In S400, the simulation effect of seismic wave propagation is achieved by the following methods: the front end integrates and processes the returned data, and plots the simulation effect of body wave propagation in three-dimensional strata and the dynamic propagation effect of surface wave on the stratum surface based on the stratum data of the source point and the seismic wave velocity and propagation radius.

6. A system for earthquake early warning simulation based on seismic networks and WEBGL, employing any one of the methods described in claims 1-5, characterized in that, include: The system comprises a data acquisition unit, a 3D geological model construction unit, a seismic surface wave and body wave result acquisition unit, and a seismic wave propagation simulation effect realization unit; among which: The data acquisition unit is used to acquire seismic network data, monitoring station data, and three-dimensional geological body modeling data. The three-dimensional geological body model construction unit is used to construct a three-dimensional geological body model according to preset rules based on the acquired three-dimensional geological body modeling data. The seismic surface wave and body wave result acquisition unit is used to acquire seismic surface wave and body wave results based on the acquired seismic network data and monitoring station data. The seismic wave propagation simulation effect realization unit is used to combine the acquired seismic surface wave and body wave results with the constructed three-dimensional geological model to realize the seismic wave propagation simulation effect.

7. The system for earthquake early warning simulation based on seismic networks and WEBGL as described in claim 6, characterized in that, The 3D geological body model construction unit constructs a 3D geological body model according to the acquired 3D geological body modeling data and preset rules, including: S201. Obtain the basic data of geological body coordinates, elevation, range, and velocity, and organize them into an Excel file; S202. Import the compiled Excel file into the modeling software; S203. Set the Excel data columns to be linked to the horizontal and vertical axes, and confirm the range of the horizontal and vertical axes of the model, and set the number of rows and columns; S204. Set the average value grading based on the range of rate values ​​in Excel; S205. Construct and export the geological body model using the attribute preview.

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