An Effective Screening Design for Global Sensitivity Analysis of Reservoir Models with a Large Number of Parameters
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Supervisor: Dr. Zhangxing(John) Chen
This is an effective approach in identifying the important factors in a model that contains many factors, with a relatively small number of model evaluations. The method is convenient when the number of factors is large and/or the model execution time is such that the computational cost of more sophisticated techniques is excessive. It is a powerful method for complex cases with interactions and nonlinear effects. It can determine if the effect of the input factor (Xi) on the output (Y) is negligible, linear and additive, nonlinear OR involved in interactions with other input factors (X~i). There is a need to think about the choice of the p levels among which each input factor is varied. The variation size (delta) should also be carefully calculated accordingly. The number of Trajectories (r) directly depends on the previous choices. One drawback is that Morris only gives an overall measure of the interactions, indicating whether interactions exist, but it does not say which ones are the strongest.