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Stress Drop Estimation Study Using Large Volume Data

Research Project

Project/Area Number 19K14812
Research Category

Grant-in-Aid for Early-Career Scientists

Allocation TypeMulti-year Fund
Review Section Basic Section 17040:Solid earth sciences-related
Research InstitutionKyoto University (2020-2021)
The University of Tokyo (2019)

Principal Investigator

Yoshimitsu Nana  京都大学, 工学研究科, 助教 (20724735)

Project Period (FY) 2019-04-01 – 2022-03-31
Project Status Completed (Fiscal Year 2021)
Budget Amount *help
¥4,290,000 (Direct Cost: ¥3,300,000、Indirect Cost: ¥990,000)
Fiscal Year 2021: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
Fiscal Year 2020: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
Fiscal Year 2019: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
Keywords応力降下量 / 地震パラメタ / MCMC / ベイズ統計 / 統計学的解析
Outline of Research at the Start

応力降下量は,内陸地殻の応力状態を反映するのではないかと期待されてきたが,推定手法やデータの不安定性により,これまではっきりとした断層や大地震との関係性はわかっていなかった.本研究では統計学的手法による解析や解析値の評価をおこなうことで,従来手法とは異なる観点から応力降下量の推定とデータの評価をおこない,時空間変化の有無,大きな地震や断層との時空間関係を調べ,媒質変化のモニタリングとその解釈を試みる.

Outline of Final Research Achievements

Source parameters, which represent the source characteristics of earthquakes, are estimated by comparing the spectral ratio of seismic waveforms with the theoretical spectral ratio. In this study, we introduced a Markov Chain Monte Carlo (MCMC) method instead of the grid search method which is the general method in the previous studies. The probability density function used in the MCMC estimation was examined, and the F-distribution was adopted instead of the commonly used normal distribution. We considered F-distribution is more suitable for data with a ratio form. The method was applied to simulated spectra and induced earthquakes in Oklahoma, United States. The probability distribution was visualized by calculating the likelihood from the sampling density.

Academic Significance and Societal Importance of the Research Achievements

地震の震源断層近傍でどのように応力変化が進行しているかを直接計測することは困難であるが,断層周辺で発生した小地震と地殻内の応力状態の関係が明らかになれば,間接的に地殻の状態を推定することが可能かもしれない.これまで応力降下量と呼ばれる小地震の震源特性の推定値には大きな誤差があったが,本研究では新しい推定手法を用いることで値の確からしさについて評価し,より正確な推定に向けて一歩前進した.本研究は実用的な目的のみならず,地震発生の物理の理解にとっても重要となる.

Report

(4 results)
  • 2021 Annual Research Report   Final Research Report ( PDF )
  • 2020 Research-status Report
  • 2019 Research-status Report
  • Research Products

    (7 results)

All 2020 2019

All Journal Article (1 results) (of which Int'l Joint Research: 1 results,  Peer Reviewed: 1 results) Presentation (6 results) (of which Int'l Joint Research: 2 results)

  • [Journal Article] Robust Stress Drop Estimates of Potentially Induced Earthquakes in Oklahoma: Evaluation of Empirical Green's Function2019

    • Author(s)
      Yoshimitsu, N., W. L. Ellsworth, G. C. Beroza
    • Journal Title

      Journal of Geophysical Research: Solid Earth

      Volume: 124 Issue: 6 Pages: 5854-5866

    • DOI

      10.1029/2019jb017483

    • Related Report
      2019 Research-status Report
    • Peer Reviewed / Int'l Joint Research
  • [Presentation] マルコフ連鎖モンテカルロ法を用いた地震の震源パラメタ推定と確率密度関数の選択2020

    • Author(s)
      吉光奈奈,前田拓人,清智也
    • Organizer
      2020年度統計関連学会連合大会
    • Related Report
      2020 Research-status Report
  • [Presentation] 室内岩石実験から自然地震までの架け橋を目指した地震発生環境に関する研究2020

    • Author(s)
      吉光奈奈
    • Organizer
      日本地震学会2020年秋季大会
    • Related Report
      2020 Research-status Report
  • [Presentation] Estimation of source parameters in the Bayesian framework by Markov Chain Monte Carlo method2019

    • Author(s)
      Yoshimitsu, N., T. Maeda, T. Sei
    • Organizer
      American Geophysical Union 2019 Fall Meeting
    • Related Report
      2019 Research-status Report
    • Int'l Joint Research
  • [Presentation] Uncertainty Evaluation of Source Parameter Estimates by MCMC in Oklahoma2019

    • Author(s)
      Yoshimitsu, N., T. Maeda, T. Sei, W. L. Ellsworth
    • Organizer
      StatSei11
    • Related Report
      2019 Research-status Report
    • Int'l Joint Research
  • [Presentation] Evaluation of source parameters in the Bayesian framework by Markov Chain Monte Carlo method2019

    • Author(s)
      Yoshimitsu, N., T. Maeda, T. Sei
    • Organizer
      日本地震学会秋季大会
    • Related Report
      2019 Research-status Report
  • [Presentation] Uncertainty evaluation of source parameter estimates by MCMC in Oklahoma2019

    • Author(s)
      Yoshimitsu, N., T. Maeda, W. Ellsworth
    • Organizer
      日本地球惑星科学連合2019年大会
    • Related Report
      2019 Research-status Report

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Published: 2019-04-18   Modified: 2023-01-30  

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