scholarly journals Teleseismic inversion of the 2004 Sumatra-Andaman earthquake rupture process using complete Green’s functions

2014 ◽  
Vol 66 (1) ◽  
Author(s):  
Masahiro Yoshimoto ◽  
Yoshiko Yamanaka
Keyword(s):  
Green's Functions ◽  
Green’S Functions ◽  
Rupture Process ◽  
Earthquake Rupture ◽  
Earthquake Rupture Process ◽  
Andaman Earthquake

Fast Inversion of the Earthquake Rupture Processes with Complicated Velocity Structure: An Application to the Earthquake of 2017 Mw 6.5 Jiuzhaigou, China

2021 ◽  
pp. 2150030
Author(s):  
Jiemin Wang ◽  
Haitao Yin ◽  
Zhijun Feng ◽  
Pifeng Ma ◽  
Liang Wang
Keyword(s):  
Green’S Function ◽  
Green's Function ◽  
Green's Functions ◽  
Velocity Structure ◽  
Green’S Functions ◽  
Velocity Model ◽  
Rupture Process ◽  
Earthquake Rupture ◽  
Earthquake Rupture Process ◽  
Complex Structural

Due to the limitation of seismic station coverage or the network transport interrupted when the earthquake occurred, an accurate seismic shakemap may not be released to the public quickly. When the near-source observed waveforms for the intensity prediction technology used are incomplete, we synthesize the seismic waveform into observation waveforms. An accurate seismic rupture process is necessary to synthesize virtual station observations. So, we should release the rupture process as soon as possible after a large earthquake. Most large earthquakes occur at the junction of two or three tectonic terranes. With violent tectonic movements, fault basins and uplift zones are distributed on the edge of the plateau. With complex structural conditions, the 1D layered half-space velocity structure model could not meet the requirement of earthquake rupture process inversion. It takes much time to calculate 3D Green’s function with a 3D velocity model for the complete waveform inversion of the earthquake rupture process. To rapidly invert the rupture process as accurately as possible, according to the geological conditions of the station, we calculated several Green’s function libraries in advance. We extracted Green’s functions from these libraries for each site based on the sites’ coordinates once an earthquake occurs. The time we spend in extracting Green’s functions from several Green libraries equals that we spend in extracting Green’s functions from one single library. The applicability of this method was tested in the 2017 Jiuzhaigou M6.5 earthquake with complex structural conditions in the mountain uplift zone. With our model, the time we spent in calculating the rupture process was almost the same as that we spent with the 1D velocity structure model, which was far less than that we could have spent in calculating 3D Green’s function. The degree of fitting between the synthetic data and the observation data of our model was much higher than the fitting of the 1D velocity model, which means that the earthquake rupture process we determined was more reliable.

Rupture Process of the Mainshock of the 2019 Ridgecrest Earthquake Sequence from Waveform Inversion with Empirical Green’s Functions

2021 ◽  
Author(s):  
Shuang-Lan Wu ◽  
Atsushi Nozu ◽  
Yosuke Nagasaka
Keyword(s):  
Green's Functions ◽  
Green’S Functions ◽  
Ground Motions ◽  
Strong Motion ◽  
Rupture Process ◽  
Earthquake Sequence ◽  
Slip Model ◽  
Near Fault ◽  
Empirical Green’S Functions ◽  
Empirical Green's Functions

ABSTRACT The 2019 Mw 7.1 mainshock of the Ridgecrest earthquake sequence, which was the first event exceeding Mw 7.0 in California since the 1999 Hector Mine earthquake, caused near-fault ground motions exceeding 0.5g and 70  cm/s. In this study, the rupture process and the generation mechanism of strong ground motions of the mainshock were investigated through waveform inversions of strong-motion data in the frequency range of 0.2–2.0 Hz using empirical Green’s functions (EGFs). The results suggest that the mainshock involved two large slip regions: the primary one with a maximum slip of approximately 4.4 m was centered ∼3  km northwest of the hypocenter, which was slightly shallower than the hypocenter, and the secondary one was centered ∼25  km southeast of the hypocenter. Outside these regions, the slip was rather small and restricted to deeper parts of the fault. A relatively small rupture velocity of 2.1  km/s was identified. The robustness of the slip model was examined by conducting additional inversion analyses with different combinations of EGF events and near-fault stations. In addition, using the preferred slip model, we synthesized strong motions at stations that were not used in the inversion analyses. The synthetic waveforms captured the timing of the main phases of observed waveforms, indicating the validity of the major spatiotemporal characteristics of the slip model. Our large slip regions are also generally visible in the models proposed by other researchers based on different datasets and focusing on lower frequency ranges (generally lower than 0.5 Hz). In particular, two large slip regions in our model are very consistent with two of the four subevents identified by Ross et al. (2019), which may indicate that part of the large slip regions that generated low-frequency ground motions also generated high-frequency ground motions up to 2.0 Hz during the Ridgecrest mainshock.

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