This paper presents a comparison between the increasingly popular experimental design method and the simpler and quicker Monte-Carlo probabilistic technique used to manage subsurface uncertainty, and provide estimates of hydrocarbons in place and ultimate recovery. The experimental design method is based on simulated reservoir models which describe the key static and dynamic uncertainties.

Experimental design can be an expensive tool to adopt, especially when dealing with large numbers of static uncertainties, as it involves significant investment in time and human and computing resources to construct the required reservoir models. A case study is presented whereby Monte-Carlo probabilistic volume estimations were calculated prior to the experimental design method to obtain a quick estimate of the hydrocarbon in place and ultimate recovery. An experimental design was then undertaken and the results compared with the probabilistic outcomes.

The analysis provides interesting insights into the benefits and some of the limitations of the two methods when used for estimation of hydrocarbon in place and ultimate recovery. Fields examples are used to illustrate the different methodologies.

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