Japan Geoscience Union Meeting 2024

Presentation information

[E] Oral

S (Solid Earth Sciences ) » S-CG Complex & General

[S-CG40] Science of slow-to-fast earthquakes

Wed. May 29, 2024 3:30 PM - 4:45 PM Convention Hall (CH-B) (International Conference Hall, Makuhari Messe)

convener:Aitaro Kato(Earthquake Research Institute, the University of Tokyo), Asuka Yamaguchi(Atomosphere and Ocean Research Institute, The University of Tokyo), Yohei Hamada(Japan Agency for Marine-Earth Science and Technology), Akemi Noda(Meteorological Research Institute, Japan Meteorological Agency), Chairperson:Satoshi Ide(Department of Earth an Planetary Science, University of Tokyo), Saeko Kita(International Institute of Seismology and Earthquake Engineering, BRI)

4:30 PM - 4:45 PM

[SCG40-40] Rapid slip modeling of large earthquakes by joint inversion of W-phase and back-projected images

*Yuyang Peng1, Dun Wang1, Nozomu Takeuchi2 (1.China Univ. of Geosciences, 2.Univ. of Tokyo)

Keywords:Rapid slip model, Large earthquake, Joint inversion

We present an innovative finite fault inversion algorithm that combines W-phase finite fault inversion with Image Deconvolution Back-Projection (IDBP) for the rapid determination of coseismic slip models following significant earthquakes. This integrated algorithm synergistically leverages the strengths of both methods, enabling precise determination of moment tensor, slip distribution, and centroid location. The application of this integrated algorithm to the analysis of the 2015 Mw 7.8 Nepal and the 2013 Mw 7.5 Alaska earthquakes yielded results closely aligned with detailed post-earthquake studies, highlighting the algorithm's accuracy and reliability. By overcoming inherent limitations of individual methods, it provides a comprehensive understanding of the earthquake source process. The algorithm's automated implementation potential, requiring minimal parameters, enhances its suitability for near real-time earthquake analysis, with promising applications in disaster mitigation and tsunami hazard assessment.