Development of nonstationary point process model of swarm activity for monitoring of volcanic activity and aseismic slip
| Project/Area Number |
16K00065
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Multi-year Fund |
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| Section | 一般 |
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| Research Field |
Statistical science
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| Research Institution | The University of Tokyo (2018)
The Institute of Statistical Mathematics (2016-2017) |
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Principal Investigator |
KUMAZAWA Takao 東京大学, 地震研究所, 特任助教 (60649482)
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| Project Period (FY) |
2016-04-01 – 2019-03-31
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| Project Status |
Completed (Fiscal Year 2018)
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| Budget Amount *help |
¥4,550,000 (Direct Cost: ¥3,500,000、Indirect Cost: ¥1,050,000)
Fiscal Year 2018: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
Fiscal Year 2017: ¥1,690,000 (Direct Cost: ¥1,300,000、Indirect Cost: ¥390,000)
Fiscal Year 2016: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
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| Keywords | 地震活動 / 点過程 / ETASモデル / 統計 / 余震 / 常時地震活動 / 点過程モデル / 非定常ETASモデル / ベイズ統計 / 熊本地震 / ベイズ的逆解析 / 異常地震活動 / 確率予測 / 群発地震 |
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| Outline of Final Research Achievements |
In this study, we have developed a nonstationary ETAS model (a point process model) that analyzes seismic swarm data driven by some external forces such as fault pore fluid pressure due to magma and water intrusions. In particular, we proposed a method to predict the activity scale and the end time (duration) of volcanic swarm earthquakes caused by magma intrusion in Izu region, applying the relationship between crustal strain time series data and seismic activity.
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| Academic Significance and Societal Importance of the Research Achievements |
地殻内の現象は内陸部の稠密なGPS観測点による膨大な観測データに関わらず、それらの解析法の困難さと発展途上性から解っていないことが多い。地震発生時系列をETASモデルを基調とした非定常点過程モデルを用いてパラメータの時空間変動を推定し、判明している地球物理モデルと対応させていくことでプレート運動と地震発生メカニズムの関係理解をより一層深めることができると考えられる。
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Report
(4 results)
Research Products
(22 results)
