Summary
Earthquakes are spectacular natural disasters, as exemplified by the 2004 Sumatra and 2011 Tohoku-Oki earthquakes. Predicting earthquakes remains one of the biggest societal challenges in natural science. This research project will attempt answering the following question: How predictable are earthquakes? We propose a multidisciplinary approach articulated around three main axes: (i) the deterministic predictability of earthquakes in simple, homogeneous faults, studied by reproducing and understanding earthquake phenomena in the laboratory, (ii) the deterministic predictability of earthquakes in complex, heterogeneous faults, studied by laboratory experiments producing multiple earthquake cycles on faults with controlled heterogeneities and (iii) the statistical predictability of earthquakes, studied by forecasting the spatial distribution of experimental seismicity using machine learning. At the core of this project lies the development of a new dedicated experimental setup to generate multiple earthquake cycles along a fault with prescribed complex geometry and rheology. With this new capability, we will conduct a threefold experimental program to: (i) compute the complete energy budget of laboratory earthquakes, (ii) study the sensitivity of rupture nucleation, propagation and arrest to heterogeneities, and (iii) study the effect of heterogeneities on the relation between fault seismic coupling and seismicity. Our work will provide insights for earthquake hazard mitigation, constrain the physics underlying ubiquitously observed seismological statistical laws (Omori, Gutenberg-Richter) and test seismic slip inversion and dynamic rupture modelling techniques in unprecedented data sets on rock fracture dynamics in experiments that mimic field conditions. The new infrastructure we plan to install will reproduce earthquake rupture processes with a spatio-temporal imaging resolution never achieved before.
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| Web resources: | https://cordis.europa.eu/project/id/101041966 |
| Start date: | 01-01-2023 |
| End date: | 31-12-2027 |
| Total budget - Public funding: | 2 498 856,00 Euro - 2 498 856,00 Euro |
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Original description
Earthquakes are spectacular natural disasters, as exemplified by the 2004 Sumatra and 2011 Tohoku-Oki earthquakes. Predicting earthquakes remains one of the biggest societal challenges in natural science. This research project will attempt answering the following question: How predictable are earthquakes? We propose a multidisciplinary approach articulated around three main axes: (i) the deterministic predictability of earthquakes in simple, homogeneous faults, studied by reproducing and understanding earthquake phenomena in the laboratory, (ii) the deterministic predictability of earthquakes in complex, heterogeneous faults, studied by laboratory experiments producing multiple earthquake cycles on faults with controlled heterogeneities and (iii) the statistical predictability of earthquakes, studied by forecasting the spatial distribution of experimental seismicity using machine learning. At the core of this project lies the development of a new dedicated experimental setup to generate multiple earthquake cycles along a fault with prescribed complex geometry and rheology. With this new capability, we will conduct a threefold experimental program to: (i) compute the complete energy budget of laboratory earthquakes, (ii) study the sensitivity of rupture nucleation, propagation and arrest to heterogeneities, and (iii) study the effect of heterogeneities on the relation between fault seismic coupling and seismicity. Our work will provide insights for earthquake hazard mitigation, constrain the physics underlying ubiquitously observed seismological statistical laws (Omori, Gutenberg-Richter) and test seismic slip inversion and dynamic rupture modelling techniques in unprecedented data sets on rock fracture dynamics in experiments that mimic field conditions. The new infrastructure we plan to install will reproduce earthquake rupture processes with a spatio-temporal imaging resolution never achieved before.Status
SIGNEDCall topic
ERC-2021-STGUpdate Date
09-02-2023
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