Post-Doctoral position: Assimilation de données géophysiques dans des modèles géologiques 3D
Assimilation of geophysical data in 3D geological models
Term: one-year, renewable
Description : Most inverse methods in geophysics tend to use parcimonious and simplified descriptions of the subsurface. Whereas such parameterization choices allow for fast and effective methods, it tends to reduce the space of uncertainty and may introduce estimation bias. From a geological standpoint, most models used in inversion are very smooth and seldom match the complexity of field observations. Therefore, designing inverse methods able to handle realistic descriptions of the geological medium is a real challenge. The goal of this project is to develop geophysical data assimilation methods using a description of subsurface models through geological objects and geostatistical parameters. This project will be based on a recent method which stochastically simulates 3D geological interfaces to sample structural uncertainty (Cherpeau et al, 2010). A goal of this project will be to refine this simulation model so that only models compatible with geophysical observations are retained. For this, the first stage will be to appropriately solve the forward problem (e.g., wave propagation) on the chosen parameterization. Then, a stochastic inverse method will be chosen chosen to reduce structural uncertainty by model updating. Ultimately, this work will clear the path for a better integration of sensor data for the monitoring of reservoirs, underground storage sites or seismically active regions.
Context: This postdoc project is connected to the Gocad Research Consortium, which aims at developing 3D subsurface modeling methods by multidisciplinary data integration. This consortium, currently supported by 18 companies and 130 universities, is part of the OTELO observatory, the second largest geosciences research organization in France with over 450 personnel, and of the Nancy School of Geology. The methods developed by the consortium are generally applied to the prospection of natural resources, the management of underground storage sites and the understanding of natural objects.
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