Conventional oil and gas price forecasts typically include pessimistic, most-likely, and optimistic cases in an attempt to quantify economic uncertainty. An analysis of forecasts presented by industry and governmental organizations illustrates that conventional forecasting methods typically underestimate significantly the full range of uncertainty in oil and gas price forecasts. Economic indicators calculated using such forecasts will not reliably quantify investment risk. In this investigation we compared and contrasted several recently developed methods for quantifying upstream petroleum investment risk due to uncertainty in future prices. We analyzed five forecasting techniques - conventional, bootstrap, Inverted Hockey Stick (IHS), historical, and Sequential Gaussian Simulation (SGS). These techniques were applied to three synthetic projects and 23 industry projects to examine the uncertainty associated with economic indicators such as net present value, investment efficiency, and internal rate of return. Across all 26 projects, the conventional forecasts predicted a narrower range of economic indicator values than the four alternative methods, indicating that conventional methods routinely underestimate uncertainty.

All four alternative forecasting techniques can provide operators with more reliable quantification of the uncertainty inherent in their investment decisions than provided by conventional methods currently in widespread use. The four alternative methods have unique strengths and weaknesses that may affect their applicability in particular situations. The SGS methods is the most rigorous and accurate method; however, it is also the most difficult to apply. The IHS method serves as a reasonable approximation, and can be easily incorporated into existing procedures and software.

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