Dynamic evaluation method and system of earthquake impact field based on multi-source information

Abstract

This application belongs to the field of earthquake assessment technology, and in particular relates to a method and system for dynamic assessment of earthquake impact fields based on multi-source information. This method utilizes real-time observation data from various specialized seismic sensors to dynamically assess the earthquake impact field over time periods. It also integrates multi-source information, such as basic earthquake parameters, focal mechanism solutions, focal rupture processes, station ground motion parameters, and aftershock information, to comprehensively assess and correct the earthquake impact field.

Description

Technical Field

[0001] The present application belongs to the field of earthquake assessment technology, and in particular relates to a method and system for dynamic assessment of earthquake impact fields based on multi-source information. Background Art

[0002] The earthquake impact field refers to the spatial distribution range of the impact of seismic motion on the surface, buildings, infrastructure, etc. after an earthquake occurs. Its core is to describe the spatial distribution characteristics of seismic motion intensity (such as intensity, peak acceleration, etc.).

[0003] During the "black box period" after an earthquake when information is extremely scarce, quickly and accurately determining the earthquake impact field is of vital importance and is directly related to the efficiency of emergency rescue decisions and the reliability of rapid disaster assessment.

[0004] Currently, the determination of the impact field during earthquake emergency response relies primarily on basic source parameters (such as magnitude, location, and depth) obtained from earthquake rapid reports, combined with empirical models of earthquake motion attenuation for calculation. However, this determination method has significant limitations: its information source is relatively single and it relies too heavily on theoretical models, resulting in frequent large deviations between the assessment results and the actual observed damage. Especially when assessing highly destructive large earthquakes, it is difficult to accurately capture and determine the key factors that determine the impact field morphology, such as the specific direction of the rupture, the actual rupture scale, and the exact location of the macroscopic epicenter, relying solely on basic source parameters and static empirical models. This greatly limits the accuracy of earthquake impact field determination.

[0005] In view of this, there is an urgent need for a dynamic assessment method and system for earthquake impact fields based on multi-source information. Summary of the Invention

[0006] Based on this, it is necessary to provide a dynamic assessment method and system for earthquake impact fields based on multi-source information to solve the above technical problems.

[0007] In a first aspect, the present application provides a method for dynamic assessment of earthquake impact fields based on multi-source information, comprising:

[0008] Based on the initial P-wave and S-wave data from the seismic network, the time difference and amplitude are measured to obtain basic earthquake information, wherein the basic earthquake information includes epicenter location information and magnitude information;

[0009] Calculating the earthquake rupture direction based on the initial P wave, and obtaining a preliminary earthquake impact range based on the epicenter location information and the magnitude information and in combination with an empirical earthquake intensity attenuation relationship model;

[0010] Based on the epicenter location information and the magnitude information, as well as an active fault database, searching for the direction of the active fault closest to the epicenter as the long axis direction of the earthquake impact field, and combining the empirical attenuation relationship model of earthquake motion constructed with historical earthquake motion data to obtain a preliminary earthquake motion intensity distribution, wherein the preliminary earthquake motion intensity distribution represents the spatial distribution of peak ground acceleration;

[0011] The peak ground acceleration, peak ground velocity, and earthquake intensity at the strong motion stations were calculated using the waveforms of the strong motion network observation data. The preliminary spatial distribution of the intensity was then obtained based on regression fitting of the measured attenuation relationship and the Kriging interpolation algorithm.

[0012] Based on the waveform data obtained by the seismic network, the CAP method is used to perform phase separation processing and time domain waveform fitting inversion calculation to obtain a focal mechanism solution, wherein the focal mechanism solution includes two orthogonal fault planes;

[0013] Based on the waveform data obtained by the seismic network and the focal mechanism solution, an inversion calculation is performed using a near-field full waveform iterative deconvolution method to obtain the spatiotemporal evolution results of the fault rupture, wherein the spatiotemporal evolution results of the fault rupture include two sets of maximum displacements of earthquake motions and macroscopic epicenter positions;

[0014] According to each set of the spatiotemporal evolution results of the fault rupture, the distance parameters involved in the preliminary earthquake intensity distribution and the preliminary intensity spatial distribution are adjusted respectively, so as to obtain two sets of target earthquake impact ranges and target earthquake intensity distributions;

[0015] Using the current measured data obtained by the strong motion network, deviation correction and adjustment are performed on the two sets of target earthquake impact ranges and the target ground motion intensity distributions, thereby obtaining two sets of final earthquake impact ranges and final ground motion intensity distributions;

[0016] The aftershock distribution direction and scale of the aftershock data recorded by the seismic network within a preset time period are analyzed for true rupture direction, and one of the two groups of fault rupture spatiotemporal evolution results is selected as the optimal group as the final result.

[0017] In some practicable embodiments, the step of performing time difference and amplitude measurement processing based on the initial P-wave and S-wave observed data from the seismic network to obtain basic earthquake information includes:

[0018] Obtaining the initial P wave and the S wave based on observation data from the seismic network;

[0019] Using the first arrival time difference between the initial P wave and the S wave, an arrival time difference calculation is performed to obtain epicenter position information;

[0020] The magnitude information is obtained using the maximum displacement amplitude of the first complete cycle of the initial P wave.

[0021] In some practicable embodiments, the steps of calculating the earthquake rupture direction based on the initial P wave, and obtaining a preliminary earthquake impact range based on the epicenter location information and the magnitude information and in combination with an empirical earthquake intensity attenuation relationship model, include:

[0022] Calculating the earthquake rupture direction based on the trend surface interpolation of the initial P wave to determine the long axis direction of the impact field;

[0023] A preliminary earthquake impact range is obtained based on the epicenter location information, the magnitude information, and an empirical earthquake intensity attenuation relationship model, wherein the empirical earthquake intensity attenuation relationship model is:

[0024] ;

[0025] in, represents the predicted intensity value, Indicates the magnitude information, It represents the straight-line distance from the predicted calculation point to the epicenter. 、 、 and They represent the coefficients of the empirical earthquake intensity attenuation relationship model.

[0026] In some practicable embodiments, the step of searching for the direction of the active fault closest to the epicenter as the long axis direction of the earthquake impact field based on the epicenter location information and the magnitude information, and an active fault database, and combining the empirical attenuation relationship model of earthquake motion constructed with historical earthquake motion data to obtain a preliminary earthquake motion intensity distribution includes:

[0027] According to the epicenter location information, query the active fault database and extract the fault strike closest to the epicenter as the long axis direction of the earthquake impact field;

[0028] The magnitude information and the long axis direction of the earthquake impact field are input into the earthquake motion empirical attenuation relationship model constructed based on historical earthquake motion data. The attenuation gradient along the long axis and in the vertical direction is calculated to obtain a preliminary earthquake motion intensity distribution. The calculation formula of the earthquake motion empirical attenuation relationship model is:

[0029] ;

[0030] in, represents the peak ground acceleration, Indicates the magnitude of the earthquake, represents the straight-line distance from the calculation point to the epicenter, 、 、 They represent the coefficients of the empirical attenuation relationship model of earthquake motion, represents a natural constant, represents the magnitude-related correction coefficient.

[0031] In some practicable methods, the steps of using the waveform of the strong motion network observation data to calculate the peak ground acceleration, peak ground velocity, and earthquake intensity of the strong motion station, and then obtaining a preliminary intensity spatial distribution based on regression fitting of the measured attenuation relationship and the Kriging interpolation algorithm include:

[0032] Performing time domain analysis on the waveform of the strong motion network observation data to obtain the peak ground acceleration and the peak ground velocity;

[0033] Obtaining the earthquake intensity of the strong motion station according to the absolute maximum value of the peak ground acceleration and the peak ground velocity;

[0034] The earthquake intensity, focal depth and distance from the strong vibration station to the epicenter of the strong vibration station , input the regression fitting measured attenuation relationship model, perform nonlinear regression calculation, and obtain the regression fitting parameters 、 and , wherein the formula of the regression fitting measured attenuation relationship model is:

[0035] ;

[0036] in, Indicates the earthquake intensity at the strong motion station. represents the focal depth, 、 and They represent the parameters of the regression fitting measured attenuation relationship model;

[0037] Using Kriging interpolation, the earthquake intensity at strong motion stations was spatially interpolated to obtain the preliminary spatial distribution of intensity.

[0038] In some practicable embodiments, the step of performing phase separation processing and time domain waveform fitting inversion calculation using the CAP method based on the waveform data obtained by the seismic network to obtain a focal mechanism solution includes:

[0039] Separating key seismic phase windows such as P-waves and S-waves based on the waveform data obtained by the seismic network to obtain a phase-separated waveform data set;

[0040] According to the waveform data set after phase separation, the waveform fitting residual matrix and preliminary source parameters are formed, and the focal mechanism solution is obtained by inversion calculation based on the CAP method.

[0041] In some practicable methods, the step of performing inversion calculation based on the waveform data obtained by the seismic network and the focal mechanism solution by using the near-field full waveform iterative deconvolution method to obtain the spatiotemporal evolution results of the fault rupture includes:

[0042] Based on the waveforms of the seismic network and the focal mechanism solution, two sets of fault rupture spatiotemporal evolution results were obtained through iterative full waveform deconvolution.

[0043] Based on the spatiotemporal evolution of the two sets of fault ruptures, the maximum displacement of the earthquake motion is calculated by convolution of the medium response based on the slip distribution, and the macroscopic epicenter position is located based on the energy release rate curve, thereby obtaining two sets of maximum displacement and macroscopic epicenter positions.

[0044] According to the two groups of maximum displacements and macroscopic epicenter positions of the earthquake motions, the rupture evolution sequences of the two groups of orthogonal fault planes are modified to obtain optimized spatiotemporal evolution results of the fault ruptures.

[0045] In some practicable embodiments, the step of adjusting the distance parameters involved in the preliminary earthquake intensity distribution and the preliminary intensity spatial distribution based on each set of the fault rupture spatiotemporal evolution results, and correspondingly obtaining two sets of target earthquake impact ranges and target earthquake intensity distributions, includes:

[0046] Using the data of each set of the spatiotemporal evolution results of the fault rupture, the model parameters corresponding to the preliminary seismic motion intensity distribution and the preliminary intensity spatial distribution, as well as the distance parameters in the model are adjusted respectively, and the adjusted model is used for calculation to obtain two sets of target earthquake impact ranges and target seismic motion intensity distributions.

[0047] In some practicable embodiments, the step of using the current measured data obtained from the strong motion network to perform deviation correction adjustment on the two sets of target earthquake impact ranges and the target ground motion intensity distributions, and correspondingly obtaining two sets of final earthquake impact ranges and final ground motion intensity distributions, includes:

[0048] Using the current measured data obtained from the strong motion network, the current earthquake impact range and current ground motion intensity distribution are obtained;

[0049] Deviation correction is performed based on the current earthquake impact range and the current seismic motion intensity distribution and the target earthquake impact range and the target seismic motion intensity distribution to obtain two sets of final earthquake impact ranges and final seismic motion intensity distributions.

[0050] In a second aspect, the present application provides a dynamic assessment system for earthquake impact fields based on multi-source information, the system comprising:

[0051] The real-time collection module of earthquake sensor information is used to collect earthquake waveform data from sensors such as the seismic network, strong motion network, and intensity meters in real time;

[0052] The basic earthquake parameter determination module is used to perform time difference and amplitude measurement processing based on the initial P wave and S wave observed by the seismic network to obtain basic earthquake information, where the basic earthquake information includes epicenter location information and magnitude information;

[0053] The module for judging the earthquake rupture direction and impact range based on the initial P wave is used to calculate the earthquake rupture direction based on the initial P wave, epicenter location information, and magnitude information, and to obtain the preliminary earthquake impact range by combining the empirical earthquake intensity attenuation relationship model;

[0054] The earthquake motion intensity prediction module is used to search for the direction of the active fault closest to the epicenter based on the epicenter location and magnitude information, as well as the active fault database. This direction is used as the long axis direction of the earthquake impact field. The module then uses the empirical earthquake motion attenuation relationship model constructed using historical earthquake motion data to obtain a preliminary earthquake motion intensity distribution. The preliminary earthquake motion intensity distribution represents the spatial distribution of peak ground acceleration.

[0055] The focal mechanism solution calculation module is used to perform phase separation processing and time domain waveform fitting inversion calculation based on the waveform data obtained from the seismic network using the CAP method to obtain the focal mechanism solution, where the focal mechanism solution contains two orthogonal fault planes;

[0056] The source rupture process inversion module is used to perform inversion calculations based on the waveform data and focal mechanism solutions obtained from the seismic network using the near-field full waveform iterative deconvolution method to obtain the spatiotemporal evolution results of the fault rupture. The spatiotemporal evolution results of the fault rupture include two sets of maximum ground motion displacements and macroscopic epicenter locations.

[0057] The seismic parameter calculation module and the earthquake intensity distribution assessment module are used to calculate the peak ground acceleration, peak ground velocity and earthquake intensity of the strong motion station using the waveform of the strong motion network observation data. Then, based on the regression fitting of the measured attenuation relationship and the Kriging interpolation algorithm, the preliminary intensity spatial distribution is obtained.

[0058] Deviation correction module based on seismic parameters: This module uses the current measured data obtained from the strong motion network to perform deviation correction adjustments on two sets of target earthquake impact ranges and target seismic intensity distributions, thereby obtaining two sets of final earthquake impact ranges and final seismic intensity distributions.

[0059] The earthquake impact field correction module based on the earthquake source rupture process and the earthquake rupture direction determination module based on aftershock information are used to adjust the distance parameters involved in the preliminary earthquake motion intensity distribution and the preliminary intensity spatial distribution according to each set of fault rupture spatiotemporal evolution results, and obtain two sets of target earthquake impact ranges and target earthquake motion intensity distributions, and analyze the real rupture direction of the aftershock distribution direction and scale of the aftershock data recorded by the seismic network within a preset time period, and select one set of the two sets of fault rupture spatiotemporal evolution results as the optimal set as the final result. Beneficial effects: The present application provides a dynamic assessment method for earthquake impact fields based on multi-source information, which makes full use of the real-time observation data of professional earthquake sensors and is more in line with the characteristics of different earthquakes; uses station waveform data to assess the rupture direction, scale and macro-epicenter position of large earthquakes, and can more accurately assess the impact field of large earthquakes; and dynamically assesses the earthquake impact field in different time periods, taking into account both efficiency and quality. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the conventional technology, the following briefly introduces the drawings required for use in the embodiments or the conventional technology descriptions. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0061] Figure 1 is a flow chart of a method for dynamic evaluation of earthquake impact fields based on multi-source information in one embodiment;

[0062] Figure 2 The diagram is a schematic diagram of a method for dynamic evaluation of earthquake impact fields based on multi-source information in one embodiment. DETAILED DESCRIPTION

[0063] To facilitate understanding of the present application, the present application will be described more fully below with reference to the accompanying drawings. The accompanying drawings provide embodiments of the present application. However, the present application may be implemented in many different forms and is not limited to the embodiments described herein. Rather, these embodiments are provided to make the disclosure of the present application more thorough and comprehensive.

[0064] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which this application belongs. The terms used herein in the specification of this application are for the purpose of describing specific embodiments only and are not intended to limit this application. The term "and / or" as used herein includes any and all couplings of one or more of the associated listed items.

[0065] It will be understood that the terms "first," "second," etc. used herein may be used to describe various elements, but these elements are not limited by these terms. These terms are only used to distinguish a first element from another element.

[0066] The following are some explanations of some terms involved in this application to facilitate understanding of this application:

[0067] P waves (Primary Wave, longitudinal waves) and S waves (Secondary Wave, transverse waves) are the two basic types of seismic body waves (waves that propagate through the interior of the Earth).

[0068] Peak Ground Acceleration (PGA) refers to the maximum absolute value of ground acceleration during an earthquake. It represents the maximum instantaneous acceleration reached by the earthquake at a specific location.

[0069] PGV (Peak Ground Velocity) refers to the maximum absolute value of the ground velocity during an earthquake. It represents the maximum instantaneous ground velocity caused by seismic waves.

[0070] An active fault is a fault that has slipped recently (on a geological scale) and may slip again in the future, causing an earthquake.

[0071] The Strong Motion Network (SMN) is an observation network consisting of accelerometers (stations) specifically designed to record strong ground motions. Its core goal is to obtain a complete, undistorted record of strong ground motions (those with the potential to cause damage).

[0072] The Seismic Network (Earthquake Monitoring Network) is an observation network composed of highly sensitive seismometers. Its core objectives are to detect and locate earthquakes, determine their magnitude, and study source processes and the Earth's internal structure, with a particular focus on recording complete seismic wave sequences (including microseismic events).

[0073] The CAP (Cut and Paste) method is a core technology that uses regional broadband seismic waveforms (mainly extracting P-wave and S-wave windows) to perform time domain fitting and invert focal mechanism solutions (fault type, strike, dip, slip angle, depth, and moment magnitude).

[0074] Kriging interpolation is an earthquake intensity estimation technique based on the principle of spatial autocorrelation. Its core is to use the measured intensity values ​​of nearby strong motion stations to scientifically predict the intensity distribution in areas without stations, following the physical law of intensity similarity between geographically adjacent areas.

[0075] like Figure 1 and Figure 2 As shown, in the first aspect, the present application provides a method for dynamic evaluation of earthquake impact field based on multi-source information, the method includes

[0076] S100, based on the initial P wave and initial S wave observed by the seismic network, the time difference and amplitude are measured and processed to obtain basic earthquake information.

[0077] The basic earthquake information includes epicenter location information and magnitude information.

[0078] Specifically, obtaining basic earthquake information may include the following steps:

[0079] S101, obtaining the initial P wave and the initial S wave based on observation data from the seismic network.

[0080] Specifically, real-time observations are carried out using a seismic network. When an earthquake occurs, the observed raw waveform data is obtained. After conventional waveform noise reduction and baseline calibration processing, the processed observation data is obtained. For example, based on the physical characteristics of seismic wave propagation speed and vibration direction: the longitudinal wave (P wave) that arrives at the seismic network first causes the ground to vibrate up and down / forward and backward, and the transverse wave (S wave) that arrives later causes the ground to sway left and right, thereby distinguishing the two and forming initial P waves and initial S waves.

[0081] It should be noted that the number of seismic stations can be set as needed, for example, the number of seismic stations in the network can be 3-4.

[0082] S102: Calculate the arrival time difference using the initial arrival time difference between the initial P wave and the initial S wave to obtain epicenter position information.

[0083] Specifically, P waves propagate about 1.7 times faster than S waves, and the time difference between the arrival of seismic waves at different stations (PS arrival time difference) is proportional to the distance from the epicenter.

[0084] Exemplarily, the operation process is to measure the time difference between the first arrival of the P wave and the first arrival of the S wave recorded by each seismic station; next, the time difference is converted into the straight-line distance from the seismic station to the epicenter (epicenter distance); the epicenter distance data of at least three seismic stations are combined, and a circle is drawn with the position of each seismic station as the center and the epicenter distance as the radius. The intersection of multiple circles is the epicenter position.

[0085] S103: Obtain magnitude information using the maximum displacement amplitude of the first complete cycle of the initial P wave.

[0086] Specifically, the amount of energy released by an earthquake is positively correlated with the amplitude of the initial vibration of the seismic wave. The larger the amplitude of the first wave, the higher the magnitude. Therefore, the maximum vibration amplitude (displacement or velocity) of the first complete cycle after the initial P wave is extracted. Next, the amplitude attenuation effect (larger amplitude nearer, smaller amplitude farther away) is corrected based on the distance from the epicenter. Finally, the corrected amplitudes from multiple seismic stations are combined and the average magnitude is calculated using the principle of energy conservation to obtain the magnitude information.

[0087] S200, calculating the earthquake rupture direction based on the initial P wave, and obtaining a preliminary earthquake impact range based on the epicenter location information and the magnitude information and in combination with an empirical earthquake intensity attenuation relationship model.

[0088] Specifically, obtaining a preliminary earthquake impact range may include the following steps:

[0089] S201 , calculating the earthquake rupture direction based on the trend surface interpolation of the initial P wave to determine the long axis direction of the impact field.

[0090] Specifically, earthquake rupture propagation causes the initial P-wave dominant period to exhibit a spatially directional gradient. Stations in the direction of the rupture's advance will record shorter dominant periods and higher amplitude gradients. This spatial variation can be captured using trend surface interpolation.

[0091] For example, the specific implementation process is as follows:

[0092] During the data preparation phase, observation data from at least three seismic stations near the epicenter were obtained, including the geographic coordinates (longitude and latitude) of each station and the initial P-wave dominant period (the maximum period of the initial 3-4 second P wave) recorded by each station.

[0093] The locations of seismic stations are considered discrete points on a two-dimensional plane, and their initial P-wave dominant periods form a spatial distribution field. A continuous period distribution model is constructed through quadratic surface fitting (implemented using a standard mathematical tool library). This continuous period distribution model aims to represent the spatially uneven distribution of dominant periods. Its physical basis is the propagation law of seismic waves along the rupture fault.

[0094] Next, the spatial gradient of the periodic distribution model is calculated, where the gradient direction points to the direction of fastest wavefront propagation, which is physically equivalent to the rupture propagation direction. The gradient direction is quantized into an azimuth angle through standard vector operations (such as the inverse tangent function), and the output is the rupture direction.

[0095] The rupture direction is taken as the dominant extension direction (long axis direction) of the earthquake impact field, that is, the initial earthquake impact range. This is because the earthquake energy is most fully released along the rupture direction, causing the surface movement to propagate farther in this direction and the range of damage to be larger.

[0096] For example, a two-dimensional plane coordinate system is established (x, y corresponds to the longitude and latitude of the station); next, a trend surface function is constructed:

[0097] S202: Obtain a preliminary earthquake impact range based on the epicenter location information, the magnitude information, and an empirical earthquake intensity attenuation relationship model, wherein the empirical earthquake intensity attenuation relationship model is (Formula 1):

[0098] (1)

[0099] in, represents the predicted intensity value, Indicates the magnitude information, represents the straight-line distance from the calculation point to the epicenter, 、 、 and They represent the coefficients of the empirical earthquake intensity attenuation relationship model.

[0100] Specifically, represents the regional attenuation constant; represents the magnitude sensitivity coefficient; represents the distance attenuation coefficient; Indicates the near-field saturation adjustment item. 、 、 and They are all obtained through regression fitting. In other words, empirical earthquake intensities can be obtained by combining data from historical ground motion data with magnitude, and then regression fitting is performed on the empirical earthquake intensities. As can be seen, the coefficients vary depending on the tectonic region, and there may be significant differences. For example, the North China Plain in China (2.1, 1.5, 1.8, 20) and the Sichuan-Yunnan Fault Zone in China (1.8, 1.7, 2.2, 15).

[0101] In formula 1, Indicates the magnitude dominant term: when the magnitude M increases by 1, the intensity Increase Spend; Represents the distance attenuation term. Logarithmic attenuation reflects the characteristic that seismic wave energy decays exponentially with distance. Can be avoided When it is 0, Diverge.

[0102] in addition, Ability to make dynamic adjustments in subsequent steps, that is, Replace epicentral distance with fault distance, which here means the major or minor axis distance. The epicentral distance is used in the initial assessment, but it will be dynamically replaced with the fault distance in subsequent steps based on the inversion results of the source rupture process.

[0103] S300 , based on the epicenter location information and the magnitude information, as well as an active fault database, searching for the direction of the active fault closest to the epicenter as the long axis direction of the earthquake impact field, and obtaining a preliminary seismic motion intensity distribution.

[0104] The preliminary seismic intensity distribution represents the spatial distribution of peak ground acceleration.

[0105] Specifically, obtaining a preliminary ground motion intensity distribution may include the following steps:

[0106] S301 : According to the epicenter location information, query the active fault database and extract the fault strike closest to the epicenter as the long axis direction of the earthquake impact field.

[0107] Specifically, the active fault database is the geological constraint basis for earthquake impact field assessment and can be obtained through the accumulation of data formed by geological and geophysical exploration.

[0108] After obtaining the epicenter location information in the above steps, the geological and geophysical detection data in the active fault database are queried with the epicenter as the center and the preset distance as the radius to obtain the fault direction closest to the epicenter, and use it as the long axis direction of the earthquake impact field.

[0109] S302: Input the magnitude information and the long axis direction of the earthquake impact field into an empirical earthquake motion attenuation relationship model constructed using historical earthquake motion data, calculate the attenuation gradient along the long axis and in the vertical direction, and obtain a preliminary earthquake motion intensity distribution. The calculation of the empirical earthquake motion attenuation relationship model is (Formula 2):

[0110] (2)

[0111] in, represents the peak ground acceleration, Indicates the magnitude of the earthquake, represents the straight-line distance from the calculation point to the epicenter, 、 、 They represent the coefficients of the empirical attenuation relationship model of earthquake motion, represents a natural constant, represents the magnitude-related correction coefficient.

[0112] in, Corrected near field , and the attenuation nonlinearity at high magnitude M, when Approaching 0, , to avoid the divergence of logarithmic terms. When M increases, Enhances near-field saturation effects (e.g., the PGA of a large earthquake slows down near the epicenter). By inputting the major or minor axis distance, the PGA can be calculated separately along the fault strike and perpendicular to the fault, reflecting the elliptical distribution of ground motion intensity (e.g., slower decay along the major axis). Indicates the base PGA logarithmic constant, Indicates the amplification factor of magnitude to the logarithm of PGA, Indicates the influence coefficient of distance attenuation on the PGA logarithm, represents the near-field saturation effect adjustment coefficient, and Combined use, for The coefficient of .

[0113] It should be noted that when calculating along the long axis, The major axis distance of the elliptical coordinate system is used; when calculating along the minor axis direction, The short axis distance is used.

[0114] S400 uses the waveform of the strong motion network observation data to calculate the peak ground acceleration, peak ground velocity and earthquake intensity of the strong motion station. Then, based on the regression fitting of the measured attenuation relationship and the Kriging interpolation algorithm, the preliminary spatial distribution of intensity is obtained.

[0115] Specifically, obtaining the preliminary spatial distribution of intensity may include the following steps:

[0116] S401, performing time domain analysis on the waveform of the strong motion network observation data to obtain the peak ground acceleration and the peak ground velocity.

[0117] Specifically, a seismic waveform is a time-domain record of ground vibrations. PGA and PGV represent the maximum impact force (peak acceleration) and maximum velocity (peak velocity) exerted by the seismic wave on the surface during propagation, respectively. Extracting these values ​​essentially involves finding the extreme points in the waveform—the peak ground acceleration and peak ground velocity.

[0118] S402: Obtain the earthquake intensity of the strong motion station according to the absolute maximum value of the peak ground acceleration and the peak ground velocity.

[0119] Specifically, the earthquake intensity at the strong motion station is positively correlated with the peak ground acceleration and the peak ground velocity. Conventional conversion methods, such as the national standard conversion method, can be used to convert the peak ground acceleration and the peak ground velocity to obtain the earthquake intensity at the strong motion station.

[0120] S403: The earthquake intensity, focal depth and distance from the strong vibration station to the epicenter are recorded. , input the regression fitting measured attenuation relationship model, perform nonlinear regression calculation, and obtain the regression fitting parameters 、 and , wherein the regression fitting measured attenuation relationship model formula 3 is:

[0121] ;

[0122] in, Indicates the earthquake intensity at the strong motion station. represents the focal depth, 、 and are the parameters of the regression fitting model of the measured attenuation relationship.

[0123] Specifically, the energy of earthquake waves decays with distance, and the decay rate is related to depth. Therefore, the focal depth and the intensity of each strong earthquake station are combined. (The straight-line distance from the strong motion station to the epicenter (epicenter distance)) is input into the regression fitting measured attenuation relationship model to optimize 、 and Optimized 、 and , which can be used in subsequent steps.

[0124] It should be noted that the focal depth is obtained from the observation data of the seismic network in step S100, that is, the basic information of the earthquake also includes the focal depth.

[0125] S404: Using Kriging interpolation, perform spatial interpolation calculations on the earthquake intensities at the strong motion stations to obtain a preliminary spatial distribution of the intensity.

[0126] Specifically, the instrument intensity values ​​of strong motion stations at geographically adjacent locations are similar. Therefore, the Kriging interpolation method can be used to perform spatial interpolation calculations, thereby achieving the deduction from discrete point observations to continuous spatial distribution.

[0127] Kriging interpolation is a technique that uses the principle of spatial autocorrelation to dynamically calculate weight coefficients (the closer the distance, the higher the weight) based on the measured intensity values ​​of nearby strong motion stations, and scientifically deduce the intensity distribution in areas without stations. In fault zones, the weights of stations along the fault direction are additionally enhanced to ensure that the intensity distribution conforms to the geological structural characteristics. Ultimately, a continuous spatial isointensity line map is generated, which is the preliminary spatial distribution of intensity. The Kriging interpolation method used in this application is a conventional application of the Kriging interpolation method, as shown in the following example:

[0128] For example, the instrumental intensity values ​​recorded by strong motion stations exhibit a continuous pattern in their spatial distribution: geographically adjacent stations have similar intensities, while the greater the distance, the greater the difference. Based on this physical property, we first calculate the actual surface distance between any two strong motion stations and then calculate the intensity difference between them.

[0129] For example, strong motion stations that are geographically closer have a greater influence on the intensity prediction of the target area. This influence gradually weakens with increasing distance, and its attenuation characteristics are determined by the law of spatial autocorrelation. In the fault zone area, the intensity propagation along the fault strike has a continuous characteristic, while the vertical strike shows a rapid attenuation characteristic. During the interpolation process, the spatial correlation along the fault strike is significantly higher than that in the vertical direction. The weight coefficient of each prediction point is dynamically generated based on its spatial relationship with all strong motion stations. The weight follows: distance attenuation relationship: the weight of close stations is higher than that of distant stations; geological structure adaptation: stations along the strike of the fault zone area receive higher weights; spatial correlation constraint: the weight distribution is consistent with the spatial distribution pattern of the measured intensity.

[0130] Based on this pattern, a dynamic weighting coefficient is generated for each predicted location, with strong motion stations closer to the location receiving higher weights and those farther away receiving decreasing weights (the degree of decrease is determined by spatial correlation and does not pre-set a fixed ratio). In fault zones, the directional characteristics of the geological structure are additionally considered: strong motion stations along the fault strike have significantly stronger spatial correlation due to the persistence of intensity propagation, while those perpendicular to the fault strike have correspondingly weaker correlation due to the rapid energy decay. Ultimately, a continuous spatial intensity distribution is obtained by weightedly combining the measured intensity values ​​of all valid strong motion stations.

[0131] S500: Based on the waveform data acquired by the seismic network, the CAP method is used to perform seismic phase processing and time domain waveform fitting inversion calculation to obtain a focal mechanism solution.

[0132] The focal mechanism solution includes two orthogonal fault planes.

[0133] Specifically, obtaining the focal mechanism solution may include the following steps:

[0134] S501, separating key seismic phase windows such as P waves and S waves based on the waveform data obtained by the seismic network to obtain a waveform data set after phase separation.

[0135] Specifically, after the seismic station network obtains the original waveform data, it first separates the key seismic phases, detects the first arrival time of the P wave (dominated by the vertical component) and the S wave (dominated by the horizontal component) in the waveform of each seismic station, and locates the starting point of the waveform analysis; with the first arrival time as the starting point, intercepts the P wave window (vertical component) and the S wave window (horizontal component) containing the complete physical vibration process; decomposes the horizontal component into the radial component (energy propagation direction) and the tangential component (vertical propagation direction) according to the propagation direction of the seismic wave; finally, the radial component and the tangential component are combined to obtain a structured phase-seismic waveform data set, which contains the waveforms of the vertical segment of the P wave, the radial segment of the S wave, and the tangential segment of the surface wave at each station.

[0136] S502: Based on the waveform data set after phase separation, a waveform fitting residual matrix and preliminary source parameters are formed, and an inversion calculation is performed based on the CAP method to obtain a focal mechanism solution.

[0137] Specifically, the inversion of the phase-specific waveform data set is completed. First, a theoretical waveform is constructed to generate a theoretical seismic waveform for the preset source parameter space (strike / dip / slip angle); next, the theoretical seismic waveform is aligned with the observed waveform on the time axis.

[0138] Residual matrix construction:

[0139] The residuals of the three components are calculated separately to construct a three-dimensional residual matrix, including the residual of the vertical component of the P wave, the residual of the radial component of the S wave, and the residual of the tangential component of the S wave.

[0140] Extract preliminary source parameters, mark the minimum position in the residual matrix, and record the corresponding parameter combination as preliminary source parameters, such as strike angle, dip angle and slip angle.

[0141] Finally, the waveform fitting residual matrix and preliminary source parameters are obtained.

[0142] Next, the focal mechanism solution was inverted using the CAP method. Initial focal parameters were used as input. New parameter combinations within a smaller range were generated, centered around these initial focal parameters. The theoretical waveform and residuals were recalculated. The parameter with the smallest residual was selected as the final optimal solution.

[0143] Finally, based on the physical characteristics of the double-couple source, the orthogonal solution is calculated and two sets of mathematically equivalent orthogonal fault plane parameters (strike angle / dip angle / slip angle) are output.

[0144] S600: Based on the waveform data acquired by the seismic network and the focal mechanism solution, an inversion calculation is performed by using a near-field full waveform iterative deconvolution method to obtain a spatiotemporal evolution result of the fault rupture.

[0145] The spatiotemporal evolution results of the fault rupture include two sets of maximum earthquake displacements and macroscopic epicenter positions.

[0146] Specifically, obtaining the spatiotemporal evolution results of fault rupture may include the following steps:

[0147] S601, based on the waveforms of the seismic network and the focal mechanism solution, two sets of fault rupture spatiotemporal evolution results are obtained through iterative full waveform deconvolution.

[0148] Specifically, the original waveforms recorded by the seismic network and the two sets of fault plane parameters given by the focal mechanism solution are used to infer the stratigraphic rupture process by directly comparing the morphological differences between the actual waveforms and the theoretical synthetic waveforms.

[0149] First, a theoretical seismic waveform is generated based on the fault plane parameters. Then, the theoretical waveform is aligned with the actual recorded waveform on the time axis, and the differences in amplitude fluctuations and phase delays between the two are analyzed. If the actual waveform amplitude is greater than the theoretical value, the slip amount of the fault plane in that direction is increased; if the actual waveform phase lags, the rupture start time of the corresponding area is delayed. This comparison and adjustment process is repeated until the actual waveform and the theoretical waveform basically coincide in shape in the preset main frequency band, and finally two sets of physical processes describing the rupture propagation direction, speed and slip amount are output.

[0150] S602, based on the two sets of spatiotemporal evolution results of the fault rupture, the maximum displacement value of the earthquake motion is calculated through medium response convolution based on the slip distribution, and the macro-epicenter position is located based on the energy release rate curve, thereby obtaining two sets of maximum earthquake motion displacements and macro-epicenter positions.

[0151] Specifically, the rupture inversion results and actual observation data are used to determine the earthquake displacement and epicenter position. For earthquake displacement, the maximum positive / negative offset value is read from the displacement waveform recorded by the strong vibration station. This value represents the maximum amplitude of the surface shaking. For the macroscopic epicenter position, the density of the spatial distribution of aftershocks is statistically analyzed, and the coordinates of the geometric center point of the area with the most concentrated aftershocks are used as the actual energy release center. This position is usually closer to the core area of ​​destruction than the microscopic epicenter. In other words, the displacement extreme value is read from the instrument record, and the dense center of aftershocks is used as the focus of destruction. The setting of the dense center can set a density threshold to determine whether it is the center and the focus of destruction.

[0152] It should be noted that the fault slip distribution is used as the source excitation function and is convolved in the time domain with the velocity structure transfer function of the crustal medium to simulate the energy transfer process of seismic waves propagating from the source to the surface. The absolute value of the maximum positive / negative offset of the convolution output surface displacement time history curve is read as the maximum displacement value of the seismic motion at that location. The slip distribution is integrated along the time axis to generate an energy release rate curve, which characterizes the instantaneous energy release intensity of the fault rupture process. The peak moment of the curve is identified, and the spatial slip distribution at the peak moment is extracted. The location of the maximum slip is defined as the macro-epicenter.

[0153] The slip distribution represents the dislocation intensity at each point on the fault plane, equivalent to the propagation response of seismic waves from the fault plane to the surface. The maximum displacement is the extreme value of this response. The principle of epicenter location refers to the moment of peak energy release, which corresponds to the moment of the main rupture of the fault. The point of maximum slip at this time is the center of energy release and better reflects the actual core of damage than the microscopic epicenter.

[0154] S603: According to the two groups of maximum displacements and macroscopic epicenter positions of the earthquake motions, the rupture evolution sequences of the two groups of orthogonal fault planes are modified to obtain optimized spatiotemporal evolution results of the fault ruptures.

[0155] Specifically, the two sets of rupture results were cross-validated and corrected using measured displacement data and aftershock distributions. The theoretically expected displacements for each rupture evolution sequence were spatially compared with the actual displacement values, and the locations of strong motion stations with deviations exceeding a preset value were marked. Secondly, the rationality of the epicenter location was verified. If the deviation between the macroepicenter and the mainshock location was greater than a set value, such as 20 kilometers, the coordinates of the dense aftershock center were used instead. If the epicentral distance between the two sets of results was greater than a set value, such as 15 kilometers, the option with the larger displacement value was preferred. Finally, for the marked areas of displacement anomalies, the actual waveforms at those locations were re-compared with the theoretical waveforms. Only the slip and rupture timing in the anomaly areas were adjusted, while the original results for other areas were maintained. The corrected rupture process better matched the observed wave characteristics and energy release patterns. The rupture parameters of the unmarked areas were completely inherited from the initial results, namely the two sets of fault rupture spatiotemporal evolution results output by S601.

[0156] S700, adjusting the distance parameters involved in the preliminary earthquake impact range and the preliminary seismic intensity distribution according to each set of spatiotemporal evolution results of the fault rupture, and obtaining two sets of target earthquake impact ranges and target seismic intensity distributions accordingly.

[0157] Specifically, obtaining two sets of target earthquake impact ranges and target ground motion intensity distributions may include the following steps:

[0158] Using the data of each set of the spatiotemporal evolution results of the fault rupture, the model parameters corresponding to the preliminary seismic motion intensity distribution and the preliminary intensity spatial distribution, as well as the distance parameters in the model are adjusted respectively, and the adjusted model is used for calculation to obtain two sets of target earthquake impact ranges and target seismic motion intensity distributions.

[0159] Specifically, using the data of each set of the spatiotemporal evolution of the fault rupture, the following operations are performed on the attenuation models corresponding to the preliminary ground motion intensity distribution and the preliminary intensity spatial distribution: the epicenter distance in the model is replaced by the fault distance. The original attenuation coefficient remains unchanged, and the attenuation coefficient in Formula 3 is 、 and , and in Formula 2 、 、 and Etc., use the replaced model to recalculate the target intensity spatial distribution (corrected earthquake impact range) and target ground motion intensity distribution (corrected PGA spatial distribution).

[0160] It should be noted that based on the fault geometric parameters (strike / dip / slip angle) and the spatial coordinates of the rupture surface in the spatiotemporal evolution results of the fault rupture, the shortest distance from the predicted point to the fault (fault distance R) is calculated through the spatial projection relationship.

[0161] S800: Using the current measured data obtained by the strong motion network, deviation correction adjustment is performed on the two sets of target earthquake impact ranges and the target seismic intensity distributions, thereby obtaining two sets of final earthquake impact ranges and final seismic intensity distributions.

[0162] Specifically, obtaining two sets of final earthquake impact ranges and final ground motion intensity distributions may include the following steps:

[0163] S801, using the current measured data obtained by the strong motion network, obtain the current earthquake impact range and the current ground motion intensity distribution.

[0164] S802 , performing deviation correction based on the current earthquake impact range and the current seismic motion intensity distribution and the target earthquake impact range and the target seismic motion intensity distribution to obtain two sets of final earthquake impact ranges and final seismic motion intensity distributions.

[0165] It should be noted that the current measured data obtained from the strong motion network is used, and conventional algorithms are used to calculate the current earthquake impact range and current ground motion intensity distribution. Next, the current earthquake impact range and current ground motion intensity distribution are compared with the target earthquake impact range and target ground motion intensity distribution, and a deviation correction is performed. The correction method can use the least squares method to more closely match the measured earthquake data, thereby further correcting the ground motion intensity distribution. The least squares method is used to quantify and correct the difference between the target impact field (theoretical prediction) and the current impact field (measured), so that the final result is more consistent with the actual damage distribution.

[0166] S900, performing a true rupture direction analysis on the aftershock distribution direction and scale of the aftershock data recorded by the seismic network within a preset time period, selecting one group as the optimal group from the two groups of spatiotemporal evolution results of the fault rupture, and obtaining a final result.

[0167] Specifically, within the preset time period, the true rupture direction is analyzed based on the aftershock distribution direction and scale of the aftershock data recorded by the seismic network. The true rupture direction is compared with the two groups of final earthquake impact ranges and final seismic intensity distributions, and the closest one is selected as the optimal group.

[0168] Example

[0169] A dynamic assessment method for earthquake impact fields based on multi-source information mainly includes the following steps:

[0170] 1. Use the P-wave and S-wave observation data from the seismic network to preliminarily determine the basic parameters of the earthquake.

[0171] 2. Using the initial P-wave data from the seismic network, the trend surface interpolation method is used to preliminarily assess the direction of the earthquake rupture, thereby determining the direction of the long axis of the impact field. Then, the earthquake impact range is preliminarily assessed based on the epicenter location, magnitude, and the empirical earthquake intensity attenuation relationship model (Formula 1).

[0172] (1)

[0173] I: intensity, R: major axis or minor axis distance, a, b, c, d: model coefficients

[0174] 3. The epicenter location and magnitude information are obtained based on the basic earthquake parameters. The direction of the fault closest to the epicenter is searched based on the active fault data as the long axis direction of the earthquake impact field. The earthquake motion intensity distribution is preliminarily predicted using the empirical attenuation relationship model (Formula 2) constructed based on historical earthquake motion data.

[0175] + eR (2)

[0176] PGA: Peak ground acceleration, R: Major axis or minor axis distance, a, b, c, d, e, i: Model coefficients

[0177] 4. Use the strong motion network observation data to calculate the station PGA, PGV and instrumental seismic intensity. According to the earthquake intensity attenuation model (Formula 3), the measured attenuation relationship of this earthquake is fitted based on the regression analysis method. Combined with the station instrumental seismic intensity, the Kriging interpolation method is used to preliminarily estimate the earthquake intensity distribution.

[0178] (3)

[0179] I: intensity, R: epicenter distance, D: focal depth, a, b, c: model coefficients

[0180] 5. Using station waveform data, based on the CAP method, through phase processing and time domain waveform fitting, the focal mechanism solution is inverted and calculated to determine the type of seismic fault and rupture direction, generally obtaining two orthogonal fault planes.

[0181] 6. Based on the station waveform data and focal mechanism solution, the near-field full waveform iterative deconvolution method is used to invert the focal rupture process and infer the maximum ground motion displacement and macroscopic epicenter location. Since the input is the focal mechanism of two fault planes, this step will produce two focal rupture process results.

[0182] 7. Based on the rupture surface data calculated from the source rupture process, adjust the source parameters such as rupture direction and rupture scale, thereby improving R in Equations 2 and 3 to the fault distance, and correcting the ground motion intensity distribution and earthquake intensity distribution. This step also produces two rupture surface results.

[0183] 8. Based on the measured data such as PGA from the strong motion network, the least squares method is used to correct the deviation of the empirical seismic attenuation relationship, so that the model is closer to the measured earthquake data, thereby further correcting the seismic intensity distribution.

[0184] 9. Based on the aftershock information obtained within 2 hours after the earthquake, the direction and scale of the earthquake rupture are determined according to the distribution direction and area of ​​the aftershocks.

[0185] 10. Combined with aftershock information, the above steps are finally determined to produce the correct results in the earthquake impact field of the two rupture surfaces.

[0186] like Figure 2 As shown, the workflow involved in the dynamic assessment method of earthquake impact field based on multi-source information of the present invention includes:

[0187] 1. After an earthquake occurs, real-time waveform data from sensors such as the seismic network, strong motion network, and intensity meters are collected in real time.

[0188] 2. Within 5 minutes after the earthquake, the basic parameters of the earthquake are preliminarily calculated using the P-wave and S-wave observation data from the seismic monitoring network.

[0189] 3. Within 5 minutes after the earthquake, the initial P wave of the seismic network observation data is used to preliminarily assess the earthquake rupture direction and impact range based on the trend surface interpolation method, that is, the initial earthquake impact range.

[0190] 4. Within 15 minutes after the earthquake, the first version of the earthquake motion intensity distribution, i.e., the preliminary prediction of the earthquake motion intensity distribution, is evaluated using the basic earthquake parameters, geological structure information near the epicenter, and the empirical seismic attenuation relationship model.

[0191] 5. Within 15 minutes after the earthquake, the station PGA, PGV and instrumental earthquake intensity are calculated using strong motion network observation data.

[0192] 6. Within 15 minutes after the earthquake, the focal mechanism solution is calculated based on the station waveform data using the CAP method through phase processing and time domain waveform fitting.

[0193] 7. Within 20 minutes after the earthquake, based on the station waveform data, the focal mechanism solution is used as input and the near-field full waveform iterative deconvolution method is used to calculate the spatiotemporal variation process of the source rupture, that is, the macroscopic epicenter of the rupture radius.

[0194] 8. The first edition of earthquake intensity distribution based on instrumental earthquake intensity assessment within 20 minutes after the earthquake.

[0195] 9. Within 25 minutes after the earthquake, based on the rupture surface data calculated from the earthquake source rupture process, the seismic motion distribution prediction with correction of the rupture direction and magnitude, and the earthquake intensity distribution with correction of the rupture direction and magnitude.

[0196] 10. Within 30 minutes after the earthquake, the third edition of the earthquake intensity distribution forecast was quickly calculated using the bias correction method based on the strong motion network ground motion parameter data PGA and PGV.

[0197] 11. Within 120 minutes after the earthquake, continuously collect spatiotemporal aftershock information and spatiotemporal geographic information, use the distribution direction of the aftershocks to determine the final rupture direction, and obtain the final version of the earthquake impact field, that is, the dynamic fusion of earthquake disaster information at different time periods and the dynamic determination of the earthquake impact field.

[0198] In a second aspect, the present application provides a dynamic assessment system for earthquake impact fields based on multi-source information, the system comprising:

[0199] The real-time collection module of earthquake sensor information is used to collect earthquake waveform data from sensors such as the seismic network, strong motion network, and intensity meters in real time;

[0200] The basic earthquake parameter determination module is used to perform time difference and amplitude measurement processing based on the initial P wave and S wave observed by the seismic network to obtain basic earthquake information, where the basic earthquake information includes epicenter location information and magnitude information;

[0201] The module for judging the earthquake rupture direction and impact range based on the initial P wave is used to calculate the earthquake rupture direction based on the initial P wave, epicenter location information, and magnitude information, and to obtain the preliminary earthquake impact range by combining the empirical earthquake intensity attenuation relationship model;

[0202] The earthquake motion intensity prediction module is used to search for the direction of the active fault closest to the epicenter based on the epicenter location and magnitude information, as well as the active fault database. This direction is used as the long axis direction of the earthquake impact field. The module then uses the empirical earthquake motion attenuation relationship model constructed using historical earthquake motion data to obtain a preliminary earthquake motion intensity distribution. The preliminary earthquake motion intensity distribution represents the spatial distribution of peak ground acceleration.

[0203] The focal mechanism solution calculation module is used to perform phase separation processing and time domain waveform fitting inversion calculation based on the waveform data obtained from the seismic network using the CAP method to obtain the focal mechanism solution, where the focal mechanism solution contains two orthogonal fault planes;

[0204] The source rupture process inversion module is used to perform inversion calculations based on the waveform data and focal mechanism solutions obtained from the seismic network using the near-field full waveform iterative deconvolution method to obtain the spatiotemporal evolution results of the fault rupture. The spatiotemporal evolution results of the fault rupture include two sets of maximum ground motion displacements and macroscopic epicenter locations.

[0205] The seismic parameter calculation module and the earthquake intensity distribution assessment module are used to calculate the peak ground acceleration, peak ground velocity and earthquake intensity of the strong motion station using the waveform of the strong motion network observation data. Then, based on the regression fitting of the measured attenuation relationship and the Kriging interpolation algorithm, the preliminary intensity spatial distribution is obtained.

[0206] Deviation correction module based on seismic parameters: This module uses the current measured data obtained from the strong motion network to perform deviation correction adjustments on two sets of target earthquake impact ranges and target seismic intensity distributions, thereby obtaining two sets of final earthquake impact ranges and final seismic intensity distributions.

[0207] The earthquake impact field correction module based on the source rupture process and the earthquake rupture direction determination module based on aftershock information are used to adjust the preliminary seismic motion intensity distribution and preliminary intensity spatial distribution, and the distance parameters involved, according to each set of fault rupture spatiotemporal evolution results, to obtain two sets of target earthquake impact ranges and target seismic motion intensity distributions, and to analyze the true rupture direction of the aftershock distribution direction and scale of the aftershock data recorded by the seismic network within a preset time period, and select one set of the two sets of fault rupture spatiotemporal evolution results as the optimal set as the final result.

[0208] Those skilled in the art will appreciate that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0209] The various embodiments in the present disclosure are described in a progressive manner, and the same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on the differences from other embodiments.

[0210] The scope of protection of the present disclosure is not limited to the above-described embodiments. Obviously, those skilled in the art may make various modifications and variations to the present disclosure without departing from the scope and spirit of the present disclosure. If such modifications and variations fall within the scope of the claims of the present disclosure and their equivalents, the present disclosure is intended to include such modifications and variations.

Claims

1. A method for dynamic assessment of earthquake impact field based on multi-source information, characterized in that the method include: Based on the initial P-wave and S-wave data from the seismic network, the time difference and amplitude are measured to obtain basic earthquake information, wherein the basic earthquake information includes epicenter location information and magnitude information; Calculating the earthquake rupture direction based on the initial P wave, and obtaining a preliminary earthquake impact range based on the epicenter location information and the magnitude information and in combination with an empirical earthquake intensity attenuation relationship model; Based on the epicenter location information and the magnitude information, as well as an active fault database, searching for the direction of the active fault closest to the epicenter as the long axis direction of the earthquake impact field, and combining the empirical attenuation relationship model of earthquake motion constructed with historical earthquake motion data to obtain a preliminary earthquake motion intensity distribution, wherein the preliminary earthquake motion intensity distribution represents the spatial distribution of peak ground acceleration; The peak ground acceleration, peak ground velocity, and earthquake intensity at the strong motion stations were calculated using the waveforms of the strong motion network observation data. The preliminary spatial distribution of the intensity was then obtained based on regression fitting of the measured attenuation relationship and the Kriging interpolation algorithm. Based on the waveform data obtained by the seismic network, the CAP method is used to perform phase separation processing and time domain waveform fitting inversion calculation to obtain a focal mechanism solution, wherein the focal mechanism solution includes two orthogonal fault planes; Based on the waveform data obtained by the seismic network and the focal mechanism solution, an inversion calculation is performed using a near-field full waveform iterative deconvolution method to obtain the spatiotemporal evolution results of the fault rupture, wherein the spatiotemporal evolution results of the fault rupture include two sets of maximum displacements of earthquake motions and macroscopic epicenter positions; According to each set of the spatiotemporal evolution results of the fault rupture, the distance parameters involved in the preliminary earthquake intensity distribution and the preliminary intensity spatial distribution are adjusted respectively, so as to obtain two sets of target earthquake impact ranges and target earthquake intensity distributions; Using the current measured data obtained by the strong motion network, deviation correction and adjustment are performed on the two sets of target earthquake impact ranges and the target ground motion intensity distributions, thereby obtaining two sets of final earthquake impact ranges and final ground motion intensity distributions; The aftershock distribution direction and scale of the aftershock data recorded by the seismic network within a preset time period are analyzed for true rupture direction, and one of the two groups of fault rupture spatiotemporal evolution results is selected as the optimal group as the final result.

2. The method for dynamic assessment of earthquake impact field based on multi-source information according to claim 1, characterized in that: The step of performing time difference and amplitude measurement processing based on the initial P wave and S wave observed by the seismic network to obtain basic earthquake information includes: Obtaining the initial P wave and the S wave based on observation data from the seismic network; Using the first arrival time difference between the P wave and the S wave, an arrival time difference calculation is performed to obtain epicenter position information; The magnitude information is obtained using the maximum displacement amplitude of the first complete cycle of the initial P wave.

3. The method for dynamic assessment of earthquake impact field based on multi-source information according to claim 1, characterized in that: The step of calculating the earthquake rupture direction based on the initial P wave, and obtaining the preliminary earthquake impact range based on the epicenter location information and the magnitude information and in combination with an empirical earthquake intensity attenuation relationship model, includes: Calculating the earthquake rupture direction based on the trend surface interpolation of the initial P wave to determine the long axis direction of the impact field; A preliminary earthquake impact range is obtained based on the epicenter location information, the magnitude information, and an empirical earthquake intensity attenuation relationship model, wherein the empirical earthquake intensity attenuation relationship model is: ； in, represents the predicted intensity value, Indicates the magnitude information, It represents the straight-line distance from the predicted calculation point to the epicenter. 、 、 and They represent the coefficients of the empirical earthquake intensity attenuation relationship model.

4. The method for dynamic assessment of earthquake impact field based on multi-source information according to claim 1, characterized in that: The step of searching for the direction of the active fault closest to the epicenter as the long axis direction of the earthquake impact field based on the epicenter location information and the magnitude information, and an active fault database, and obtaining a preliminary earthquake motion intensity distribution in combination with an empirical earthquake motion attenuation relationship model constructed using historical earthquake motion data, includes: According to the epicenter location information, query the active fault database and extract the fault strike closest to the epicenter as the long axis direction of the earthquake impact field; The magnitude information and the long axis direction of the earthquake impact field are input into the earthquake motion empirical attenuation relationship model constructed based on historical earthquake motion data. The attenuation gradient along the long axis and in the vertical direction is calculated to obtain a preliminary earthquake motion intensity distribution. The calculation formula of the earthquake motion empirical attenuation relationship model is: ； in, represents the peak ground acceleration, Indicates the magnitude of the earthquake, represents the straight-line distance from the calculation point to the epicenter, 、 、 、 and They represent the coefficients of the empirical attenuation relationship model of earthquake motion, represents a natural constant, represents the magnitude-related correction coefficient.

5. The method for dynamic assessment of earthquake impact field based on multi-source information according to claim 4, characterized in that: The steps of calculating the peak ground acceleration, peak ground velocity, and earthquake intensity of the strong motion station using the waveform of the strong motion network observation data, and then obtaining the preliminary intensity spatial distribution based on the regression fitting of the measured attenuation relationship and the Kriging interpolation algorithm include: Performing time domain analysis on the waveform of the strong motion network observation data to obtain the peak ground acceleration and the peak ground velocity; Obtaining the earthquake intensity of the strong motion station according to the absolute maximum value of the peak ground acceleration and the peak ground velocity; The earthquake intensity, focal depth and distance from the strong vibration station to the epicenter of the strong vibration station , input the regression fitting measured attenuation relationship model, perform nonlinear regression calculation, and obtain the regression fitting parameters 、 and , wherein the formula of the regression fitting measured attenuation relationship model is: ； in, Indicates the earthquake intensity at the strong motion station. represents the focal depth, 、 and They represent the parameters of the regression fitting measured attenuation relationship model; Using Kriging interpolation, the earthquake intensity at strong motion stations was spatially interpolated to obtain the preliminary spatial distribution of intensity.

6. The method for dynamic assessment of earthquake impact field based on multi-source information according to claim 1, characterized in that: The step of performing phase separation processing and time domain waveform fitting inversion calculation using the CAP method based on the waveform data obtained from the seismic network to obtain a focal mechanism solution includes: Separating the P-wave and S-wave key phase windows based on the waveform data acquired by the seismic network to obtain a phase-separated waveform data set; According to the waveform data set after phase separation, the waveform fitting residual matrix and preliminary source parameters are formed, and the focal mechanism solution is obtained by inversion calculation based on the CAP method.

7. The method for dynamic assessment of earthquake impact field based on multi-source information according to claim 1, characterized in that: The step of performing inversion calculation based on the waveform data obtained from the seismic network and the focal mechanism solution by using the near-field full waveform iterative deconvolution method to obtain the spatiotemporal evolution results of the fault rupture includes: Based on the waveforms of the seismic network and the focal mechanism solution, two sets of fault rupture spatiotemporal evolution results were obtained through iterative full waveform deconvolution. Based on the spatiotemporal evolution of the two sets of fault ruptures, the maximum displacement of the earthquake motion is calculated by convolution of the medium response based on the slip distribution, and the macroscopic epicenter position is located based on the energy release rate curve, thereby obtaining two sets of maximum displacement and macroscopic epicenter positions. According to the two groups of maximum displacements and macroscopic epicenter positions of the earthquake motions, the rupture evolution sequences of the two groups of orthogonal fault planes are modified to obtain optimized spatiotemporal evolution results of the fault ruptures.

8. The method for dynamic assessment of earthquake impact field based on multi-source information according to claim 1, characterized in that: The step of adjusting the distance parameters involved in the preliminary earthquake intensity distribution and the preliminary intensity spatial distribution according to each set of the spatiotemporal evolution results of the fault rupture, and correspondingly obtaining two sets of target earthquake impact ranges and target earthquake intensity distributions, comprises: Using the data of each set of the spatiotemporal evolution results of the fault rupture, the model parameters corresponding to the preliminary seismic motion intensity distribution and the preliminary intensity spatial distribution, as well as the distance parameters in the model are adjusted respectively, and the adjusted model is used for calculation to obtain two sets of target earthquake impact ranges and target seismic motion intensity distributions.

9. The method for dynamic assessment of earthquake impact field based on multi-source information according to claim 1, characterized in that: The step of using the current measured data obtained from the strong motion network to perform deviation correction adjustment on the two sets of target earthquake impact ranges and the target ground motion intensity distributions to obtain two sets of final earthquake impact ranges and final ground motion intensity distributions includes: Using the current measured data obtained from the strong motion network, the current earthquake impact range and current ground motion intensity distribution are obtained; Deviation correction is performed based on the current earthquake impact range and the current seismic motion intensity distribution and the target earthquake impact range and the target seismic motion intensity distribution to obtain two sets of final earthquake impact ranges and final seismic motion intensity distributions.

10. A dynamic assessment system for earthquake impact fields based on multi-source information, characterized in that: The system includes: The real-time collection module of earthquake sensor information is used to collect earthquake waveform data from the seismic network, strong motion network and intensity meter in real time; The basic earthquake parameter determination module is used to perform time difference and amplitude measurement processing based on the initial P wave and S wave observed by the seismic network to obtain basic earthquake information, where the basic earthquake information includes epicenter location information and magnitude information; The module for judging the earthquake rupture direction and impact range based on the initial P wave is used to calculate the earthquake rupture direction based on the initial P wave, epicenter location information, and magnitude information, and to obtain the preliminary earthquake impact range by combining the empirical earthquake intensity attenuation relationship model; The earthquake motion intensity prediction module is used to search for the direction of the active fault closest to the epicenter based on the epicenter location and magnitude information, as well as the active fault database. This direction is used as the long axis direction of the earthquake impact field. The module then uses the empirical earthquake motion attenuation relationship model constructed using historical earthquake motion data to obtain a preliminary earthquake motion intensity distribution. The preliminary earthquake motion intensity distribution represents the spatial distribution of peak ground acceleration. The focal mechanism solution calculation module is used to perform phase separation processing and time domain waveform fitting inversion calculation based on the waveform data obtained from the seismic network using the CAP method to obtain the focal mechanism solution, where the focal mechanism solution contains two orthogonal fault planes; The source rupture process inversion module is used to perform inversion calculations based on the waveform data and focal mechanism solutions obtained from the seismic network using the near-field full waveform iterative deconvolution method to obtain the spatiotemporal evolution results of the fault rupture. The spatiotemporal evolution results of the fault rupture include two sets of maximum ground motion displacements and macroscopic epicenter locations. The seismic parameter calculation module and the earthquake intensity distribution assessment module are used to calculate the peak ground acceleration, peak ground velocity and earthquake intensity of the strong motion station using the waveform of the strong motion network observation data. Then, based on the regression fitting of the measured attenuation relationship and the Kriging interpolation algorithm, the preliminary intensity spatial distribution is obtained. Deviation correction module based on seismic parameters: This module uses the current measured data obtained from the strong motion network to perform deviation correction adjustments on two sets of target earthquake impact ranges and target seismic intensity distributions, thereby obtaining two sets of final earthquake impact ranges and final seismic intensity distributions. The earthquake impact field correction module based on the source rupture process and the earthquake rupture direction determination module based on aftershock information are used to adjust the preliminary seismic motion intensity distribution and preliminary intensity spatial distribution, and the distance parameters involved, according to each set of fault rupture spatiotemporal evolution results, to obtain two sets of target earthquake impact ranges and target seismic motion intensity distributions, and to analyze the true rupture direction of the aftershock distribution direction and scale of the aftershock data recorded by the seismic network within a preset time period, and select one set of the two sets of fault rupture spatiotemporal evolution results as the optimal set as the final result.

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