  Numerical simulations are a highly valuable tool to evaluate the impact of
the uncertainties of various modelparameters, and to optimize e.g.
injection-production scenarios in the context of underground storage (of
CO2typically). Finite volume approximations of Darcy's parabolic model for
flows in porous media are typically runmany times, for many values of
parameters like permeability and porosity, at costly computational efforts.We
study the relevance of reduced basis methods as a way to lower the overall
simulation cost of finite volumeapproximations to Darcy's parabolic model for
flows in porous media for different values of the parameters suchas
permeability. In the context of underground gas storage (of CO2 typically) in
saline aquifers, our aim isto evaluate quickly, for many parameter values, the
flux along some interior boundaries near the well injectionarea-regarded as a
quantity of interest-. To this end, we construct reduced bases by a standard
POD-Greedyalgorithm. Our POD-Greedy algorithm uses a new goal-oriented error
estimator designed from a discrete space-time energy norm independent of the
parameter. We provide some numerical experiments that validate theefficiency of
the proposed estimator.
