Abstract
The study of different flow scenarios in the subsurface relies on the repeated resolution of the same system of partial differential equations, in particular to analyze the variability of model responses to uncertainties associated with the geological input data. This type of parametric analysis can lead to high computational costs. In this lecture, we will show how the method of reduced bases, combined with hyper-reduction techniques, can be applied to several models used in this field. This approach significantly reduces computational complexity, while providing an a posteriori estimate of the error between the solution of the reduced model and that of the discrete reference model.
