Earthquake rupture imaging

Detailed and high-resolution imaging of earthquake rupture processes is critical to understanding the initiation, propagation, and termination of earthquakes, and hence their fundamental physics and the seismic hazard. As a long-term effort in my group, we have been working extensively in earthquake rupture process imaging. To make the best possible scientific findings we have been developing new tools to push the waveform inversion and modelling to as high a frequency as possible. The higher the frequency we can conduct such analysis the higher the resolution we can image the rupture process of the earthquake as well as the earth velocity structure. High frequency (i.e. 1-10Hz) seismic waves are also most relevant to the seismic hazard evaluation and assessment, as most of the buildings have resonance frequency in this frequency range.

My group has been continuously tracing large and significant earthquakes on a global scale. With the new tools my group has developed in recent years, we have been making unique scientific findings for a series of significant earthquakes. Here are a few representative cases: by jointly analysing multidisciplinary observations, we found that the 2016 Mw7.8 New Zealand earthquake has simultaneously ruptured the crustal faults and the plate boundary fault on more than 12 fault segments (Wang et al., 2018). The rupture model nicely reconciles the geodetic, seismic, and tsunami observations to provide a robust solution (Wang et al., 2018). Through a holistic application of finite fault modelling, back-projection, and multiple point source inversions, we found that the 2019 Mw8.0 Peru earthquake occurred at the depth of 120km was facilitated by the thermal pressurization of pore fluid that dehydrated from the hydrous serpentines (Luo et al., 2021), which was made for the first time for deep-focus earthquakes to improve our understanding of their mechanism. Using our newly developed multiple-point source inversion algorithm (Shi et al., 2018), we showed that the highly heterogeneous pore fluid pressure had enabled the rupture on the orthogonal faults during the Mw7.0 Ridgecrest earthquake (Shi and Wei, 2020). 

We have developed a new multiple-point source inversion tool (Shi et al., 2018), that takes advantage of the Cut-And-Paste (Zhu and Helmberger, 1996) method and a path calibration strategy. The application of the technique to the 2016 Mw6.4 Kumamoto earthquake has revealed an anti-dipping fault geometry that was well supported by the high-resolution seismicity and first P-wave motion focal mechanism. The method was later generalized to incorporate both regional and teleseismic datasets (Luo et al., 2021). We have also systematically analysed the sources of uncertainties in the back-projection method, which is an array data processing technique that traces the high-frequency radiation and rupture front (hence rupture speed) of large earthquakes. The back-projection method is of great complementary to the traditional deterministic rupture process imaging technique, it has led to a series of great findings in recent years, yet a comprehensive uncertainty analysis has been missing. Our study (Zeng et al., 2020) has merged this knowledge gap and provide a more quantitative framework for future back-projection earthquake rupture imaging. We also innovatively combine high-frequency teleseismic depth phases modelling with surface wave relative relocation method to refine the earthquake catalogue to a higher resolution that allows much clearer delineation of fault geometry (Wang et al., 2017; 2018). Note that many of these methods do not rely on nearfield dataset, thus can be easily generalized to global seismological studies. 

Funding Sources: 

  • Earth Observatory of Singapore

Project Years: 

2015
2016
2017
2018
2019
2020
2021
2022

EOS Team: 

Principal Investigator
Co-Investigator
Co-Investigator

Collaborators: 

Co-Investigator(s):

Wang Xin, Institute of Geology and Geophysics, Chinese Academy of Sciences

Chen Meng, University of Electronic Science and Technology of China

Collaborator(s):

Wenbo Wu, Department of Geoscience, Princeton University

Wang Teng, Peking University

Publications: