Rapid Estimates of the Source Time Function and Mw using Empirical Green's Function Deconvolution

2014 ◽  
Vol 104 (4) ◽  
pp. 1812-1819 ◽  
Author(s):  
H. M. Benz ◽  
R. B. Herrmann
Keyword(s):  
Green’S Function ◽  
Green's Function ◽  
Time Function ◽  
Source Time Function ◽  
Empirical Green’S Function ◽  
Empirical Green's Function

THE EMPIRICAL GREEN’S FUNCTION TECHNIQUE MODIFICATION FOR ACCELEROGRAM SYNTHESIS IN LOWSEISMICITY REGIONS

2018 ◽  
Vol 12 (5-6) ◽  
pp. 72-80
Author(s):  
A. A. Krylov
Keyword(s):  
Green’S Function ◽  
Green's Function ◽  
Main Shock ◽  
Amplitude Spectrum ◽  
Strong Motion ◽  
Function Technique ◽  
Focal Region ◽  
Empirical Green’S Function ◽  
Epicentral Zone ◽  
Empirical Green's Function

In the absence of strong motion records at the future construction sites, different theoretical and semi-empirical approaches are used to estimate the initial seismic vibrations of the soil. If there are records of weak earthquakes on the site and the parameters of the fault that generates the calculated earthquake are known, then the empirical Green’s function can be used. Initially, the empirical Green’s function method in the formulation of Irikura was applied for main shock record modelling using its aftershocks under the following conditions: the magnitude of the weak event is only 1–2 units smaller than the magnitude of the main shock; the focus of the weak event is localized in the focal region of a strong event, hearth, and it should be the same for both events. However, short-termed local instrumental seismological investigation, especially on seafloor, results usually with weak microearthquakes recordings. The magnitude of the observed micro-earthquakes is much lower than of the modeling event (more than 2). To test whether the method of the empirical Green’s function can be applied under these conditions, the accelerograms of the main shock of the earthquake in L'Aquila (6.04.09) with a magnitude Mw = 6.3 were modelled. The microearthquake with ML = 3,3 (21.05.2011) and unknown origin mechanism located in mainshock’s epicentral zone was used as the empirical Green’s function. It was concluded that the empirical Green’s function is to be preprocessed. The complex Fourier spectrum smoothing by moving average was suggested. After the smoothing the inverses Fourier transform results with new Green’s function. Thus, not only the amplitude spectrum is smoothed out, but also the phase spectrum. After such preliminary processing, the spectra of the calculated accelerograms and recorded correspond to each other much better. The modelling demonstrate good results within frequency range 0,1–10 Hz, considered usually for engineering seismological studies.

The corner frequencies and stress drops of intraplate earthquakes in the northeastern United States

1998 ◽  
Vol 88 (2) ◽  
pp. 531-542 ◽  
Author(s):  
Jinghua Shi ◽  
Won-Young Kim ◽  
Paul G. Richards
Keyword(s):  
Green’S Function ◽  
Green's Function ◽  
Vertical Component ◽  
Corner Frequency ◽  
Northeastern United States ◽  
Empirical Green’S Function ◽  
Intraplate Earthquakes ◽  
Short Period ◽  
Empirical Green's Function ◽  
Stress Drops

Abstract This article presents the estimation of stress drops for small to middle-sized intraplate earthquakes in the northeastern United States. The vertical-component Sg and Lg waves of 49 earthquakes were analyzed, and their seismic corner frequencies and seismic moments were determined. For these events, both short-period and broadband records were obtained from stations in the region. There are eight events each of which has an aftershock good enough to be treated as its empirical Green's function, and their corner frequencies were estimated from empirical Green's function methods. For the other events, the corner frequencies were directly estimated by the spectral fitting of the vertical component of the Sg- or Lg-wave displacement spectrum with the ω-square source spectral model, using the available broadband and high-frequency short-period data and a frequency-dependent Q correction. The static stress drops, Δσ, were then calculated from the corner frequency and seismic moment. From our study, the source corner frequencies estimated by fitting the Lg displacement spectrum with the assumed ω-square source model are more consistent with the corner frequencies measured from empirical Green's function deconvolution method than those estimated from the intersection of horizontal low-frequency spectral asymptote and a line indicating the ω−2 decay above the corner frequency. The source corner frequencies we estimated proved to be most appropriate for the small to middle-sized earthquakes. The static stress drops calculated from these corner-frequency estimates tend to be independent of seismic moment for events above a certain size. For earthquakes with size less than about 2 × 1020 dyne-cm, the stress drop tends to decrease with decreasing moment, suggesting a breakdown in self-similarity below a threshold magnitude. A characteristic rupture size of about 100 m is implied for these smaller earthquakes.

Reproducing the Spatial Characteristics of High-Frequency Ground Motions for the 1850 M 7.5 Xichang Earthquake

2021 ◽  
Author(s):  
Zongchao Li ◽  
Jize Sun ◽  
Lihua Fang ◽  
Xueliang Chen ◽  
Mengtan Gao ◽  
...  
Keyword(s):  
Green’S Function ◽  
Ground Motion ◽  
Green's Function ◽  
Function Method ◽  
Ground Motions ◽  
Empirical Green’S Function ◽  
Green’S Function Method ◽  
Spatial Characteristics ◽  
Meizoseismal Area ◽  
Empirical Green's Function

Abstract Reproducing the spatial characteristics of large historical earthquakes and predicting the strong ground motions of future destructive large earthquakes through actual small earthquakes have high-practical value. The empirical Green’s function method is a numerical simulation method that can impart real seismic information in synthetic ground motions. In this article, we use data from the 2018 M 5.1 Xichang earthquake to reproduce the ground-motion characteristics of the 1850 M 7.5 Xichang earthquake using the empirical Green’s function method. The uncertainties of the parameters, such as the number, area, and locations of asperities, are considered. The synthetic time histories, peak ground accelerations (PGAs), and response spectra are obtained through simulation. The main results are as follows. (1) The synthetic Xichang earthquake (such as the ground-motion intensity and attenuation characteristic of the PGA) matches well with the M 8.0 Wenchuan earthquake and M 7.3 Jiji earthquake. When the number of asperities is 1 or 2, the PGA characteristics of the Xichang earthquake match well not only with the Next Generation Attenuation-West2 (2014) ground-motion model in the range of 100 km but also with the seismic ground-motion parameter zonation map of China in the range of 20–100 km. (2) The prediction results based on the asperity source model are relatively reliable in the range of 20–100 km. The one-asperity and two-asperity models of the Xichang earthquake match better than the three-asperity and four-asperity models. (3) We can speculate that when the M 7.5 earthquake struck the Xichang area, the damage was relatively strong. The PGA may have exceeded 1.0g in the meizoseismal area, and the seismic intensity in the meizoseismal area may have reached or exceeded a degree of X–XI. Therefore, the synthesized M 7.5 Xichang earthquake has the strength characteristics of a large destructive earthquake.

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