JpGU-AGU Joint Meeting 2020

講演情報

[E] ポスター発表

セッション記号 S (固体地球科学) » S-TT 計測技術・研究手法

[S-TT52] 最先端ベイズ統計学が拓く地震ビッグデータ解析

コンビーナ:長尾 大道(東京大学地震研究所)、加藤 愛太郎(東京大学地震研究所)、矢野 恵佑(東京大学大学院情報理工学系研究科)、椎名 高裕(東京大学地震研究所)

[STT52-P04] A Bayesian seismic tomography adapted to discontinuities

*倉田 澄人1高倉 直哉1矢野 恵佑1駒木 文保1 (1.東京大学 大学院情報理工学系研究科)

キーワード:地震学、地震波トモグラフィ、ベイズ統計学

Seismic tomography is an analysis method to estimate subsurface structures of the Earth using arrival times of earthquakes. In this study, we introduce two procedures to estimate velocity structures under western North America on the basis of arrival times of P-waves.
We divide subsurfaces into meshes with different seismic velocities. We consider associations among the meshes in the estimation of velocity parameters. Velocity structures are broadly continuous but change drastically along the discontinuity such as Moho and Conrad. In addition, they change largely along the boundary between land and sea. Therefore, we first adopt Bayesian estimation with the prior distribution accommodating such information.
We second introduce a regularization to estimate behavior of velocity structures around discontinuities more sharply. We apply a network Lasso-type regularization to estimate velocity parameters. We use the regularization term which penalizes difference of velocity parameters among adjacent meshes. With this effect, similar velocities will be smoothed, on the other hand, sharp changes of velocity will be emphasized.
The resulting velocity structure can capture change points of velocities more clearly. We compare our procedure with the existing tomography through numerical studies.