Modelling the costs of non-conventional oil: A case study of Canadian bitumen
High crude oil prices, uncertainties about the consequences of climate change and the eventual decline of conventional oil production raise the issue of alternative fuels, such as non-conventional oil and biofuels. This paper describes a simple probabilistic model of the costs of non-conventional oil, including the role of learning-by-doing in driving down costs. This forward-looking analysis quantifies the effects of both learning and production constraints on the costs of supplying bitumen, which can then be upgraded into synthetic crude oil, a substitute to conventional oil. The results show large uncertainties in the future costs of supplying bitumen from Canadian oil sands deposits, with a 90% confidence interval of $7-12 in 2030, and $6-15 in 2060 (2005 US$). The influence of each parameter on the supply costs is examined, with the minimum supply cost, the learning rate (LR), and the depletion curve exponent having the largest influence. Over time, the influence of the LR on the supply costs decreases, while the influence of the depletion curve exponent increases.
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