Industry Needs Re-Education in Uncertainty Assessment
| Autor: | Duane A. McVay |
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| Rok vydání: | 2015 |
| Předmět: | |
| Zdroj: | Journal of Petroleum Technology. 67:72-76 |
| ISSN: | 1944-978X 0149-2136 |
| Popis: | Management It is clear the oil and gas industry recognizes the large uncertainty in which it operates. A search in the OnePetro technical paper database using the keywords “uncertainty” or “risk” returns more than 53,000 conference and journal papers. Yet, it is also clear that the industry does not know how to reliably assess uncertainty and that this inability negatively affects industry performance. Capen (1976) described the difficulty of assessing uncertainty. He pointed to massive capital overruns and low industry returns due to an almost universal tendency to underestimate uncertainty. Brashear et al. (2001) and Rose (2004) later documented the dismal performance of the industry in the last 10 to 20 years of the 20th century due to chronic bias and evaluation methods that do not account for the full uncertainty. Although industry profitability may have improved in the past decade because of high oil prices, Neeraj Nandurdikar in an October 2014 JPT article, “Wanted: A New Type of Business Leader to Fix E&P Asset Developments,” showed that the oil and gas industry continues to perform significantly below estimations and expectations. He cited three ways that assets erode value, all of which relate to unreliable assessments of uncertainty: (1) production and reserves estimates are overestimated, (2) capital costs are underestimated, and (3) development times are underestimated. And these do not include price estimations; the surprising oil price slide at the time of this writing has the potential to move industry performance from below expectations to below profitability. While project evaluations can be affected by many different types of biases, these can be reduced fundamentally to two primary biases: overconfidence and directional bias. Overconfidence is underestimation of uncertainty; i.e., our estimated distributions of uncertain quantities, such as reserves, are too narrow. They are too narrow because we do not consider all the possible outcomes. There is considerable evidence in the literature, both inside and outside the petroleum industry, of our general human tendency for overconfidence. Directional bias results when the subset of possible outcomes considered is shifted in either the optimistic or pessimistic direction. There is also evidence that we are usually optimistic in our overconfidence; i.e., we fail to consider some possible negative outcomes, or we give greater weight to possible positive outcomes than possible negative outcomes. As a result of the two primary biases, we make decisions with incorrect estimated distributions rather than true distributions (Fig. 1). |
| Databáze: | OpenAIRE |
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