This paper proposes a framework based on proxies and rejection sampling (filtering) to perform multiple history-matching runs with a manageable number of reservoir simulations. The proposed work flow enables qualitative and quantitative analysis of a surveillance plan. Qualitatively, heavy-hitter-alignment analysis for the objective function and the observed data provides actionable measures for screening different surveillance designs. Quantitatively, the evaluation of expected uncertainty reduction from different surveillance plans allows for optimal design and selection of surveillance plans.
Introduction
In this work flow, the authors perform a set of training simulations (determined by experimental design) and use the result to build proxies for the objective function and each of the surveillance data points.
