| dc.description.abstract | Accurately estimating hydrocarbon reserves is important, because it affects every phase
of the oil and gas business. Unfortunately, reserves estimation is always uncertain, since
perfect information is seldom available from the reservoir, and uncertainty can
complicate the decision-making process. Many important decisions have to be made
without knowing exactly what the ultimate outcome will be from a decision made today.
Thus, quantifying the uncertainty is extremely important.
Two methods for estimating original hydrocarbons in place (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 performance data, such as pressure and production data, are available.
In this work, I propose a methodology for using a Bayesian approach to quantify the
uncertainty of original gas in place (G), aquifer productivity index (J), and the volume of
the aquifer (Wi) as a result of combining volumetric and material balance analysis in a
water-driven gas reservoir.
The results show that we potentially have significant non-uniqueness (i.e., large
uncertainty) when we consider only volumetric analyses or material balance analyses. By combining the results from both analyses, the non-uniqueness can be reduced,
resulting in OGIP and aquifer parameter estimates with lower uncertainty. By
understanding the uncertainty, we can expect better management decision making. | en |
