This study proposes two methods, (1) a probabilistic method based on historical oil prices and (2) a method based on Gaussian simulation, to model future prices of oil. With these methods to model future oil prices, we can calculate the ranges of uncertainty in traditional probability indicators based on cash flow analysis, such as net present values, net present value to investment ratio and internal rate of return. We found that conventional methods used to quantify uncertainty which use high, low and base prices produce uncertainty ranges far narrower than those observed historically. These methods fail because they do not capture the "shocks" in oil prices that arise from geopolitical events or supply-demand imbalances. Quantifying uncertainty is becoming increasingly important in the petroleum industry as many current investment opportunities in reservoir development require large investments, many in harsh exploration environments, with intensive technology requirements. Insight into the range of uncertainty, particularly for downside, may influence our investment decision in these difficult areas.
| Identifer | oai:union.ndltd.org:TEXASAandM/oai:repository.tamu.edu:1969.1/201 |
| Date | 30 September 2004 |
| Creators | Mendjoge, Ashish V |
| Contributors | Lee, W. J., Gaspar, Julian, McVay, Duane A., Datta-Gupta, Akhil |
| Publisher | Texas A&M University |
| Source Sets | Texas A and M University |
| Language | en_US |
| Detected Language | English |
| Type | Electronic Thesis, text |
| Format | 502302 bytes, 90024 bytes, electronic, application/pdf, text/plain, born digital |
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