Boxing Earthquakes and Faults in ACtive Tectonics
This project aims to enhance understanding of earthquake ruptures and fault geometry by generating experimental earthquakes and using neural networks to analyze real seismic data for improved hazard mitigation.
Projectdetails
Introduction
Large-magnitude earthquakes accommodate most of the tectonic deformations of the Earth along active fault systems. However, despite the occurrence of numerous earthquakes every year, our knowledge of the physical processes governing earthquake ruptures, the relation between rupture propagation, slip distribution, and fault geometry, and the evolution of the fault geometry through successive earthquake cycles is still extremely limited. This limitation hinders significant progress in earthquake hazard mitigation.
Challenges in Understanding Earthquake Processes
Although an increasing number of observations points to a key role of the fault geometry and its evolution on the way rupture propagates and ends through successive earthquake cycles, understanding the 3D geometry of fault systems and its dynamics during earthquakes from natural data alone remains difficult and fraught with problems.
Proposed Approach
In this project, I propose a new approach to address those pending questions by generating my own earthquakes from a combination of lab experiments and numerical simulations. This method aims to make a major step forward in the understanding of natural observations of earthquake ruptures and fault systems.
Objectives
- Generate experimental earthquakes to provide original data.
- Study simultaneously rupture processes and fault geometry.
- Analyze the evolution of fault geometry in 3D.
Data Utilization
The new dataset will be used to train neural networks designed to solve for earthquake source parameters, including:
- 3D rupture geometry
- Finite slip distribution
Eventually, the neural networks will analyze real earthquake ruptures, incorporating remote sensing, field, and seismological data, to produce 3D earthquake rupture models.
Conclusion
The project BE_FACT will thus produce an integrated view of the earthquake fault systems that will answer these long-lasting questions about the intimate relations between earthquake ruptures and fault system geometry. This research will provide a new stepping-stone toward a more earthquake-resilient society.
Financiële details & Tijdlijn
Financiële details
Subsidiebedrag | € 2.489.125 |
Totale projectbegroting | € 2.489.125 |
Tijdlijn
Startdatum | 1-11-2024 |
Einddatum | 31-10-2029 |
Subsidiejaar | 2024 |
Partners & Locaties
Projectpartners
- CENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE CNRSpenvoerder
Land(en)
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HOw Predictable are Earthquakes
This project aims to enhance earthquake predictability through a multidisciplinary approach combining laboratory experiments and machine learning to improve hazard mitigation and understand seismic behavior.
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This project aims to enhance earthquake prediction and early warning systems in Chile by using Distributed Acoustic Sensing to monitor fault activity through a dense ocean-bottom seismic observatory.
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This project aims to understand and predict rare earthquakes in Stable Continental Regions by leveraging AI to create a comprehensive earthquake catalog and modeling static fatigue effects on crustal stress.
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HYQUAKE aims to develop a predictive framework for fluid-induced fault slip by integrating laboratory experiments, numerical models, and machine learning to enhance earthquake forecasting.
FrOm RupturE procesS to Earthquake Early warnING
FORESEEING aims to understand earthquake nucleation processes through interdisciplinary research to enhance Earthquake Early Warning systems, ultimately saving lives and reducing damage.
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