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dc.contributor.advisorMcVay, Duane A.
dc.creatorFariyibi, Festus Lekan
dc.date.accessioned2006-10-30T23:25:41Z
dc.date.available2006-10-30T23:25:41Z
dc.date.created2006-08
dc.date.issued2006-10-30
dc.identifier.urihttps://hdl.handle.net/1969.1/4224
dc.description.abstractThis study presents an analysis of several recently published methods for quantifying the uncertainty in economic evaluations due to uncertainty in future oil prices. Conventional price forecasting methods used in the industry typically underestimate the range of uncertainty in oil and gas price forecasts. These forecasts traditionally consider pessimistic, most-likely, and optimistic cases in an attempt to quantify economic uncertainty. The recently developed alternative methods have their unique strengths as well as weaknesses that may affect their applicability in particular situations. While stochastic methods can improve the assessment of price uncertainty they can also be tedious to implement. The inverted hockey stick method is found to be an easily applied alternative to the stochastic methods. However, the primary basis for validating this method has been found to be unreliable. In this study, a consistent and reliable validation of uncertainty estimates predicted by the inverted hockey stick method is presented. Verifying the reliability of this model will ensure reliable quantification of economic uncertainty. Although we cannot eliminate uncertainty from investment evaluations, we can better quantify the uncertainty by accurately predicting the volatility in future oil and gas prices. Reliably quantifying economic uncertainty will enable operators to make better decisions and allocate their capital with increased efficiency.en
dc.format.extent1488046 bytesen
dc.format.mediumelectronicen
dc.format.mimetypeapplication/pdf
dc.language.isoen_US
dc.publisherTexas A&M University
dc.subjectUncertaintyen
dc.subjectoil pricesen
dc.subjectProject evaluationsen
dc.subjectforecastsen
dc.titleApplication of price uncertainty quantification models and their impacts on project evaluationsen
dc.typeBooken
dc.typeThesisen
thesis.degree.departmentPetroleum Engineeringen
thesis.degree.disciplinePetroleum Engineeringen
thesis.degree.grantorTexas A&M Universityen
thesis.degree.nameMaster of Scienceen
thesis.degree.levelMastersen
dc.contributor.committeeMemberAhr, Wayne M.
dc.contributor.committeeMemberLee, William J.
dc.type.genreElectronic Thesisen
dc.type.materialtexten
dc.format.digitalOriginborn digitalen


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