Testing Hubbert
Section snippets
Introduction and context
Since the beginning of commercial exploitation of oil, there has been great interest in two related questions: how much oil exists in the world, and when will we run out of oil? This very old discussion has recently resurfaced, as interest in oil depletion has increased along with increasing oil prices. Recent projections of global oil production have been made using a set of methods commonly referred to as the “Hubbert theory” of oil depletion, but these projections have been rejected by those
Methods of analysis
In this paper we test three assumptions of the Hubbert theory. We first ask if bell-shaped models fit historical production data better than other simple models. We then ask if regional oil production curves have been historically symmetric. Lastly, we test a commonly made assertion about oil depletion: that the Hubbert model fits larger regions better than smaller regions, due to a “smoothing” behavior resulting from summing smaller production curves. We emphasize that we do not test the
Best-fitting model results
One important general result is that 16 regions were disqualified from comparison due to extremely poor fit, and six more were classified as borderline nonconforming. The disqualified regions are not a significant portion of global production (about 3% of 2004 production), but the borderline-nonconforming regions represent 36% of global production. Thus, fully a third of global production is not well characterized by models with a single up–down cycle.
Discussion and conclusion
It is clear from the results of this analysis that no simple, single cycle model fits all historical production curves from oil producing regions. We illustrated that when comparing the three symmetrical models, the Hubbert model is the most widely useful model, but that somewhat less than half of the regions are well-described by the linear and exponential models. We also showed that when asymmetry is allowed in our oil production curves, that the asymmetrical exponential model becomes the
Acknowledgments
I would like to gratefully acknowledge the assistance of Anand Patil, Alex Farrell, Andrew Mills, and Jim Kirchner in the preparation and revision of this paper.
References (34)
The mineral economy: a model for the shape of oil production curves
Energy Policy
(2005)- et al.
Forecasting the limits to the availability and diversity of global conventional oil supply
Energy
(2004) Dynamics of energy technologies and global change
Energy Policy
(1999)The mineral economy: how prices and costs can falsely signal decreasing scarcity
Ecological Economics
(1999)- Ahlbrandt, T.S., 2005. Global overview of petroleum resources. In: Workshop on Trends in Oil Supply and Demand and...
- et al.
Oil prophets: looking at world oil studies over time
Petroleum Facts and Figures
(1959)- (1971)
Basic Petroleum Data Book: Petroleum Industry Statistics
(2004)- Babusiaux, D., Barreau, S., Bauquis, P., et al., 2004. Oil and Gas Production: Reserves, Costs, and Contracts. Editons...
The Coming Oil Crisis
Oil Crisis
The end of cheap oil
Scientific American
Hubbert's Peak: The Impending World Oil Shortage
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