METHOD AND SYSTEM FOR RAPID MODEL EVALUATION USING MULTILEVEL SURROGATES

摘要

The present techniques disclose methods and systems for rapidly evaluating multiple models using multilevel surrogates (for example, in two or more levels). These surrogates form a hierarchy in which surrogate accuracy increases with its level. At the highest level, the surrogate becomes an accurate model, which may be referred to as a full-physics model (FPM). The higher level surrogates may be used to efficiently train the low level surrogates (more specifically, the lowest level surrogate in most applications), reducing the amount of computing resources used. The low level surrogates are then used to evaluate the entire parameter space for various purposes, such as history matching, evaluating the performance of a hydrocarbon reservoir, and the like.