Similarity of fast and slow earthquakes illuminated by machine learning

Claudia Hulbert, Bertrand Rouet-Leduc, Paul A. Johnson, Christopher X. Ren, Jacques Riviere, David C. Bolton, Chris J. Marone

Research output: Contribution to journalArticle

5 Citations (Scopus)

Abstract

Tectonic faults fail in a spectrum of modes, ranging from earthquakes to slow slip events. The physics of fast earthquakes are well described by stick–slip friction and elastodynamic rupture; however, slow earthquakes are poorly understood. Key questions remain about how ruptures propagate quasi-dynamically, whether they obey different scaling laws from ordinary earthquakes and whether a single fault can host multiple slip modes. We report on laboratory earthquakes and show that both slow and fast slip modes are preceded by a cascade of micro-failure events that radiate elastic energy in a manner that foretells catastrophic failure. Using machine learning, we find that acoustic emissions generated during shear of quartz fault gouge under normal stress of 1–10 MPa predict the timing and duration of laboratory earthquakes. Laboratory slow earthquakes reach peak slip velocities of the order of 1 × 10−4 m s−1 and do not radiate high-frequency elastic energy, consistent with tectonic slow slip. Acoustic signals generated in the early stages of impending fast laboratory earthquakes are systematically larger than those for slow slip events. Here, we show that a broad range of stick–slip and creep–slip modes of failure can be predicted and share common mechanisms, which suggests that catastrophic earthquake failure may be preceded by an organized, potentially forecastable, set of processes.

Original languageEnglish (US)
Pages (from-to)69-74
Number of pages6
JournalNature Geoscience
Volume12
Issue number1
DOIs
StatePublished - Jan 1 2019

Fingerprint

earthquake
rupture
elastodynamics
machine learning
fault gouge
tectonics
acoustic emission
energy
physics
friction
acoustics
quartz
laboratory

All Science Journal Classification (ASJC) codes

  • Earth and Planetary Sciences(all)

Cite this

Hulbert, Claudia ; Rouet-Leduc, Bertrand ; Johnson, Paul A. ; Ren, Christopher X. ; Riviere, Jacques ; Bolton, David C. ; Marone, Chris J. / Similarity of fast and slow earthquakes illuminated by machine learning. In: Nature Geoscience. 2019 ; Vol. 12, No. 1. pp. 69-74.
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Similarity of fast and slow earthquakes illuminated by machine learning. / Hulbert, Claudia; Rouet-Leduc, Bertrand; Johnson, Paul A.; Ren, Christopher X.; Riviere, Jacques; Bolton, David C.; Marone, Chris J.

In: Nature Geoscience, Vol. 12, No. 1, 01.01.2019, p. 69-74.

Research output: Contribution to journalArticle

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