Abstract

The vast proportion of yearly oil and gas reserve additions are accounted for by reserve changes in known oil and gas fields. For example, in 2008 approximately 96% of the dry natural gas reserve additions in the United States were accounted for by reserve changes in known fields. The increase in proved ultimate recovery that results from these reserve changes is known as reserve appreciation or reserve growth. Ideally, reserve growth should be measured by comparing the current known petroleum volumes equal to cumulative production plus remaining reserves of fields discovered in say, 1950, with their initial discovery sizes. Unfortunately, implementing the ideal is often not possible since the initial discovery sizes of fields discovered before 1975, or thereabouts, are many times unknown. Up to now, the standard solution to the problem has been based largely on the work of Arrington (1960) who developed a method to estimate reserve growth when initial discovery sizes are unknown and the number of time series observations is small. While the contribution of the economic environment to the growth process has been acknowledged by geologists, the application of the Arrington method presumes that growth is independent of the economic environment. In our view, this creates a bias. For example, if, as we suspect, the economic environment affects reserve growth, then an Arrington-based supply analysis will underestimate the response of supplies to higher prices. In this paper, we employ a rich database from the former United States Minerals Management Service (MMS) to evaluate the contribution of the economic environment to the reserve growth process. In contrast to Forbes and Zampelli (2009) which examined reserve growth at the individual field level, the analysis in this paper aggregates the field level data based on the year of first production. One advantage of this approach is that it has the potential to yield insights about the resource potential of a particular geologic province. The results strongly suggest that age is not the sole factor in explaining a field’s annual reserve growth. In particular, we find that the annual growth rate in the known petroleum volumes of a field is affected by the economic environment as proxied by price. Incorporation of this effect into the modeling process has the potential to improve the accuracy of resource assessments.