Abstract
Assessing the potential impacts associated with CO2 storage operations implies using large-scale models characterized by a very large number of grid cells (>500,000) and high computation time cost (> several hours). Yet, investigating the influence of the input parameters on the model results requires multiple simulations (>1,000), which might become impracticable due to the computation burden. A meta-modelling strategy is then proposed, basically consisting in approximating the long running model by a costless-to-evaluate model, for instance a Gaussian Process, based on a very limited number of simulations (e.g., 50). This strategy is tested to investigate the sensitivity of the overpressure induced by an industrial-scale CO2 injection into a fluvial heterogeneous reservoir, to the properties of the shale formation using a 3-dimensional long running multiphase flow model (with CPU time > 5 days).
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