RANDOM FORESTS-BASED SENSITIVITY ANALYSIS FOR RESERVOIR HISTORY MATCHING

Sensitivity analysis is typically required to screen unwanted history matching parameters so that computational cost can be reduced. Random Forests (RF) is a well-known statistical learning tool that maps a list of input parameters onto a predicted response.