Fracturing

Fracturing - © Dimitri Lague

For example, in terms of the fracturing process itself, and within the context of industrial and academic collaborations, we will discuss the question of growth and fracture arrest using pseudo-mechanical models and the relationships between fracture density and macroscopic elastic properties of the environment. These aspects are fundamental for understanding the mechanical strength of fractured massifs as well as energy storage issues. One of the inter-disciplinary components that we are launching is topography-induced fracturing in connection with the stress differentials generated by the relief. These spatial variations in fractures have an impact on the transfer of fluids and matter on hillslopes as well as on the erosion rates of the basement by rivers. Thus, dynamic couplings between fractures and topography still need to be explored.
 
(A final component concerns the coupling between the seismic cycle and erosion addressed under the ANR’s Young Researcher EROQUAKE project by P. Steer

Fracturing - © Dimitri Lague

By combining its expertise, and within the context of imagery  and interface dynamics, our team implements a very wide range of methods involving different spatial scales and numerous disciplines. New methods are being introduced and others are being stepped up. This is the case for the work on subsurface geophysical imaging with muon tomography,hydrogeodesy or complex electrical impedance techniques. New topo-bathymetric airborne LiDAR data will be used to characterize aquatic environments in connection with acoustic and optical fiber methods. Numerous innovative laboratory methods in microfluidics will benefit from the CPER Buffon experimental hall. There are two key challenges
in imagery : the first concerns the processing of massive data generated by certain sensors for which collaborations with IRISA are being developed. The second concerns the coupling between data and models, whether on aspects of inversion, assimilation and propagation of uncertainty in the context of prediction.