Probabilistic Methods for Uncertainty Quantification

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Author(s): N. Chugunov (Institute for Systems Analysis – Russian Academy of Sciences, Russia), G. Shepelyov (Institute for Systems Analysis – Russian Academy of Sciences, Russia)and M. Sternin (Institute for Systems Analysis – Russian Academy of Sciences, Russia)
Copyright: 2008
Pages: 11
Source title: Encyclopedia of Decision Making and Decision Support Technologies
Source Author(s)/Editor(s): Frederic Adam (University College Cork, Ireland)and Patrick Humphreys (London School of Economics, UK)
DOI: 10.4018/978-1-59904-843-7.ch082

Keywords: Accounting and Finance / Business & Management / Business Science Reference / Decision Support Systems

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Abstract

The complexity and interdisciplinary nature of modern problems are often coupled with uncertainty inherent to real-life situations. There is a wide class of real-world problems described by well-formulated quantitative models for which a decision maker (DM) has to deal with uncertainty in values of initial parameters for these models. A good example of such a problem is hydrocarbon reservoir assessment in the exploration stage, which requires the involvement and joint consideration of geological, petroleum engineering, and financial models of reservoir exploration. The consequences of some unreasonable decisions can lead to millions of dollars in loss to the companies as it happens in the oil business, where industry sources on investment decision analysis continue to report surprise values (outside the [P10;P90] range) far more than the 20% indicated by this interval (Welsh, Begg, Bratvold, & Lee, 2004).

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