JpGU-AGU Joint Meeting 2020

Presentation information

[E] Poster

S (Solid Earth Sciences ) » S-TT Technology & Techniques

[S-TT52] Seismic Big Data Analysis Based on the State-of-the-Art of Bayesian Statistics

convener:Hiromichi Nagao(Earthquake Research Institute, The University of Tokyo), Aitaro Kato(Earthquake Research Institute, the University of Tokyo), Keisuke Yano(The University of Tokyo, Graduate School of Information Science and Technology), Takahiro Shiina(Earthquake Research Institute, The University of Tokyo)

[STT52-P03] An application of reversible-jump MCMC method for simultaneous determinations of 1-D velocity structures and hypocenters around a fault (II): Synthetic analyses

*Takahiro Shiina1, Masayuki Kano2 (1.Earthquake Research Institute, The University of Tokyo, 2.Graduate School of Science, Tohoku University)

Keywords:Hypocenter, 1-D velocity structure, rj-MCMC

Our series of presentation (this study and Kano and Shiina [this meeting]) proposes an approach that can simultaneously estimate one-dimensional (1-D) velocity models and hypocenters based on a reversible-jump Markov chain Monte Carlo (rj-MCMC) method. A location of earthquake is routinely determined by using locally optimized 1-D velocity model, such as the JMA2001 1-D velocity model [Ueno et al., 2002]. Meanwhile, two or more 1-D velocity model can improve estimation accuracy of hypocenters of which earthquakes occur at around structural boundary [e.g., Sakai et al., 2004].
As described in Kano and Shiina [this meeting], we developed the rj-MCMC method for determining hypocenters and structures when a number of 1-D velocity models is given. In this presentation, therefore, we evaluate the developed method by using synthesized data sets that derived from two 1-D velocity models. Since the rj-MCMC requires only travel times between an earthquake and a receiver, we employ fast-marching method [e.g., Sethian and Popovici, 1999; Rawlinson and Sambridge, 2004] for travel time calculations. Note that a rj-MCMC-based estimations of 1-D velocity model and hypocenters had been suggested [e.g., Ryberg and Haberland, 2019]. However, the previous studies for the 1-D case mainly handled earthquakes which widely distributed in the targeted area. We thus discuss advantages and shortenings of the rj-MCMC method to simultaneous determinations of hypocenter and single 1-D velocity model for concentrated hypocenters, i.e., seismic swarms and aftershocks of a large earthquake.