The Laboratory of Soil Mechanics (LMS) at the Swiss Federal Institute of Technology (EPFL) in Lausanne, is seeking a motivated phd candidate and a postdoctoral researcher to support the development of innovative tools for improving representative multi-physical modeling of geological CO2 storage (GCS).
LMS is a research lab directed by Prof. Lyesse Laloui that targets real-world challenges related to climate change, global energy demand, sustainable urban design and construction and safe and environmentally friendly waste disposal systems, through the development of unique analytical tools and innovative technologies.
The objective of this project is to develop a novel methodology through data-driven Machine Learning (ML) approaches for improving successful upscaling of subsurface engineering. A unique dataset from a metre-scale demonstrator of GCS in EPFL will enable fine training of the ML algorithms and the results will be compared to more conventional constitutive modeling approaches. Implementation of physical laws and multi-physics constrains may be considered for evaluating their impact on the accuracy of the results and computational cost. The methodology aims to significantly improve computational time and reliability of multi-scale modeling for the prediction of the macroscopic mechanical behavior of the involved geomaterials in GCS (caprock and reservoir).
The overall approach of the project aims to bridge lab- to field-scales in the context of a wider range of geotechnical/geomechanical subsurface applications (e.g. radioactive waste storage, hydrogen storage, hydrocarbon extraction etc.).
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