Quantifying Uncertainty in Original-Gas-in-Place Estimates With Bayesian Integration of Volumetric and Material Balance Analyses

Abstract

ABSTRACT Accuracy in hydrocarbon reserves estimates affects virtually every phase of the oil and gas business. Unfortunately, reserves estimates are uncertain, since perfect information is seldom available from the reservoir, and uncertainty can complicate the decision-making process. Managers have to make many important decisions early (e.g., facilities expansions, development drilling, etc.) without reliable knowledge of reserves. Thus, it is probably more important to quantify reserves uncertainty early than any other time in the life of a reservoir. Reserves are closely related to original hydrocarbons in place (OHIP). Two methods for estimating OHIP are volumetric and material balance methods. The volumetric method is convenient to calculate OHIP during the early development period, while the material balance method can be used later, after some performance data, particularly pressure and production information, are available. Both methods may have substantial uncertainty. In this paper, we present a methodology that uses a Bayesian approach to quantify the uncertainty of original gas in place (G), aquifer productivity index (J), and the volume of the aquifer (Wi) by combining volumetric and material balance analyses in a water-driven gas reservoir. The results show that we potentially have large uncertainty in OGIP estimates when we consider only volumetric analyses or only material balance analyses. However, by combining the results from both analyses, the uncertainty can be reduced. This reduction in uncertainty should lead to better management decisions in many cases.