Screening method using the derivative-based global sensitivity indices with application to reservoir simulator

Screening method using the derivative-based global sensitivity indices with application to reservoir simulator — Reservoir simulator can involve a large number of uncertain input parameters. Sensitivity analysis can help reservoir engineers focusing on the inputs whose uncertainties have an impact on the model output, which allows reducing the complexity of the model. There are several ways to define the sensitivity indices. One of the quantitative definition is the variance based sensitivity indices which can quantify the amount of output uncertainty due to the uncertainty of inputs. However, the classical methods to estimate such sensitivity indices in a high dimensional problem can require a huge number of reservoir model evaluation. Recently, new sensitivity indices based on averaging local derivatives of the model output over the inputs domain have been introduced. These so-called derivative-based global sensitivity measures (DGSM) have been proposed to overcome the problem of dimensionality and are linked to total effect indices which are variance based sensitivity indices. In this work we propose a screening method based on a revised DGSM indices which increase the interpretability in some complex case and have a lower computational cost, as demonstrated by numerical test cases and by an application on a synthetic reservoir test model. ha l-0 07 89 80 7, v er si on 1 18 F eb 2 01 3