Missions

Fault networks are hierarchical in nature. We have already shown that two faults (in 2D), of same lengths, when allowed to interact over multiple seismic cycles produce a spectra of transient energy release without appealing to heterogeneities in stress and/or friction properties. It is not a leap of imagination to now say that when fault networks over multiple length scales, and realistic 3D geometries, are accounted for, the continuous, spatiotemporally complex, energy release can be captured by appealing to geometrical, rather than mechanical, heterogeneities. This framework would use tectonically, and seismologically inferred fault geometries and would cross-validate with decadal scale continuous geodetic data. We would also like to reproduce characteristic scaling laws and statistical properties like Gutenberg-Richter and Omori decay laws.

Activités

Develop, improve, and extend, the H-Matrix algorithm to 3D fault networks; Obtain synthetic GPS and INSAR like time-series to cross-validate with observations in well studied fault networks; Constrain model parameters to capture large paleo-earthquakes in those fault networks; Capture statistical, and spectral, properties of energy release on them; Provide training data set to the Machine learning algorithms

Compétences

Fracture Mechanics, Seismology, Computational Earthquake Source Mechanics

Contexte de travail

The post doctoral candidate would be based at the Laboratoire de Géologie (UMR 8538) at Ecole Normale Supérieure. Founded in 1880, the LG ENS is a joint research unit between the CNRS and ENS-PSL. Built on a long tradition in Earth and Environmental Sciences, it houses research that covers a wide field - Geology, Geodesy, Geomorphology, Geodynamics, Marine Geophysics, Geomechanics, Hydrogeology, Mineralogy, Seismology and Tectonics - which makes it a privileged place for exchanges at thematic borders.

Contraintes et risques

None