今週のうなぎセミナーについてお知らせいたします。

Here is information of the Unagi-seminar(Jan 7).

************** うなぎセミナーのご案内 (Unagi-seminar) **************

科目：地震学ゼミナールIV B, D / Seminar on Seismology IV B, D（修士・博士）
日時：2021年1月7日（木）14:00～
場所：オンライン(Zoom)

Date and time：Jan 7 (Thursday), 14:00～
Site：Online by Zoom

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[発表者 1 (Presenter 1)]
Chintan TIMSINA

[題目 (title)]
Three-Dimensional Upper Crustal Velocity Model of Central Nepal

[要旨 (Abstract)]
We investigate the 3D Upper crustal seismic velocity model of central Nepal in the source region of the 2015 (Mw 7.8) Gorkha earthquake. We use 39,306 P-wave arrivals and 27,218 S-P times from 1741 local events to carry out simultaneous inversion for Vp, Vp/Vs, and hypocenters. These data were recorded by 42 stations of a temporary aftershock monitoring network from June 2015 to April 2016. First, we calculate a 1D velocity model of the area following the approach of Kissling et al. (1994) and relocate all the events in the database. With this 1D velocity model, we then use SIMUL2000 (Thurber and Eberhart-Phillips, 1999) to determine a coarse 3D velocity model. Finally, the grid spacing is made smaller to determine a detailed 3D velocity model.
This study contributes to our knowledge of seismo-tectonics by providing a detailed velocity structure within the source region of the Gorkha earthquake.

[発表者 2 (Presenter 2)]
Shukei OHYANAGI

[題目 (title)]
Attempt to detect offshore seismicity near the Japen Trench using a deep learning technique

[要旨 (Abstract)]
The Japan Trench subduction zone is a cradle for various types of seismic activities, such as Mw 9.0 Tohoku-Oki megathrust event, VLFE, or SSE. In past few years, ocean bottom seismic observations by S-Net (cable network of OBSs) and dense networks of free-fall type OBS reveal tectonic tremor in shallow portion of the subduction zone [e.g. Nishikawa et al., 2019; Tanaka et al., 2019; Ohta et al. 2019]. In contrast to tectonic tremor activity, acquired OBS data have not fully utilized to understand microseismicity of the same region. They are often used to relocate earthquakes cataloged in the JMA unified catalog which developed with recordings of onshore seismic network [e.g. Shinohara et al., 2012], but attempt to detect microseismicity solely visible from offshore seismic network is uncommon.
Here, we employed Earthquake Transformer (EQT) [Mousavi et al., 2020], the newly developed deep learning module which performs detection and phase picking of microearthquake. EQT is applied to a OBS network deployed in offshore Fukushima near the trench, which observation was performed from Sep.2016 to Oct.2017. As a result, EQT detects more than 5000 microearthquakes, which is six times more events than the earthquakes located by the JMA in the same region during the observation period. The detected events are located using hypomh [Hirata and Matsu’ura, 1993]. The developed catalog reveals microseismicity collocated to shallow tectonic tremors [Nishikawa et al., 2019; Ohta et al., 2019], and change in seismicity rate following the tremor burst activities.

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