5:15 PM - 7:15 PM
[SCG49-P02] Dynamic source inversion of small-to-moderate earthquakes: A novel method and its application

Keywords:source inversion, rupture dynamics, 2023 Jishishan earthquake, rupture velocity, seismic hazard assessment
Inverting pre-stress and frictional parameters on faults from observations is a challenging task, particularly due to its high computational burden. However, recent advances in high-performance computing have enabled seismologists to invert the physical parameters that control the rupture dynamics. Here, we introduce a novel method to search the optimal model that fits near-fault data. The model assumes rupture evolution on elliptical patches governed by a linear slip-weakening friction law. The forward solver combines the GPU-accelerated curved grid finite difference method (CGFDM) (Zhang Z. al., 2014; Zhang W. al., 2020) capable of modeling the 3D spontaneous rupture of faults with geometric complexity such as oblique and non-planar faults, and precalculated Green's functions to synthetic observed waveforms. The inverse problem is solved using a non-linear global search algorithm, called parameter-shifted grey wolf optimizer (psGWO) (Zhang Z. & Zhang Y., 2021). Additionally, we attempt to explore the parameter space using a Monte Carlo method. Synthetic tests investigating the performance of the proposed method demonstrate that we can recover the main characteristics of dynamic and kinematic parameters. We also conduct a fully dynamic inversion for the 2023 Mw 6.0 Jishishan, Gansu earthquake, with constraints from seismic and geodetic observations. The result reveals a weak nucleation followed by a predominantly northwestward rupture propagation with a slow rupture velocity of 1.65 km/s and mean stress drop of 5.89 MPa. The radiation efficiency is as low as 10%, suggesting that the event may have occurred on an immature fault. The inferred physical parameters (i.e., stress drop, fracture energy) are consistent with the scaling relations from previous studies (Cocco et al., 2023). We anticipate that such method can improve our understanding of the physics of small-to-moderate earthquakes and aid in physics-based seismic hazard assessment.
References
Zhang, W., Zhang, Z., Li, M., & Chen, X. (2020). GPU implementation of curved-grid finite-difference modelling for non-planar rupture dynamics. Geophysical Journal International, 222(3), 2121-2135.
Zhang, Z., Zhang, W., & Chen, X. (2014). Three-dimensional curved grid finite-difference modelling for non-planar rupture dynamics. Geophysical Journal International, 199(2), 860-879.
Zhang, Z., & Zhang, Y. (2021). Application of a parameter-shifted grey wolf optimizer for earthquake dynamic rupture inversion. Earthquake Science, 34(6), 507-521.
Cocco, M., Aretusini, S., Cornelio, C., Nielsen, S. B., Spagnuolo, E., Tinti, E., & Di Toro, G. (2023). Fracture energy and breakdown work during earthquakes. Annual Review of Earth and Planetary Sciences, 51(1), 217-252.
References
Zhang, W., Zhang, Z., Li, M., & Chen, X. (2020). GPU implementation of curved-grid finite-difference modelling for non-planar rupture dynamics. Geophysical Journal International, 222(3), 2121-2135.
Zhang, Z., Zhang, W., & Chen, X. (2014). Three-dimensional curved grid finite-difference modelling for non-planar rupture dynamics. Geophysical Journal International, 199(2), 860-879.
Zhang, Z., & Zhang, Y. (2021). Application of a parameter-shifted grey wolf optimizer for earthquake dynamic rupture inversion. Earthquake Science, 34(6), 507-521.
Cocco, M., Aretusini, S., Cornelio, C., Nielsen, S. B., Spagnuolo, E., Tinti, E., & Di Toro, G. (2023). Fracture energy and breakdown work during earthquakes. Annual Review of Earth and Planetary Sciences, 51(1), 217-252.