Reservoir Simulation and Reserves Classifications—Guidelines for Reviewing Model History Matches To Help Bridge the Gap Between Evaluators and Simulation Specialists

Abstract

Abstract As the scrutiny on oil and gas reserves continues to increase, the subject of evaluating reservoir simulation models has come to the forefront. Regulatory bodies, such as the U.S. Securities and Exchange Commission, do not provide detailed criteria on the use of reservoir simulation models in the reserves estimation process, other than their stated position that the model must have a "good history match". A great deal of high quality, highly technical research has been conducted in the field of history matching and of late in "automatic" history matching, and the paper reviews some of this research. While much of this research is useful, it is not clear that any particular quantitative assessment can be made of history match quality, or if such a method really helps to understand the applicability of the history matched model. It is easy to understand why reservoir simulation specialists and reserves estimators may be at odds as to the use and utility of a particular model. It is well recognized that, in general, only a limited amount of time is available to review models; thus, only a fraction of the time devoted to the original model construction can usually be devoted to the review process. The authors have been on both sides of this dilemma, and this paper is intended to provide some suggestions for a systematic review of models (for whatever ultimate use) and start a dialogue to discuss how history matches should be evaluated with respect to reserves. It is noted that, for the most part, model reviews do not need to address whether a model is "perfect" overall, rather a review should address whether a model is fit for a particular purpose. The authors propose that the applicability of the model, and the quality of the history match can always be qualitatively assessed if one views the model as an analogy for a particular property. Therefore, the "analogy" approach suggested by the authors provides a specific methodology for incorporating simulation model results in the reserves estimation process.