Quantitative methods in the risk analysis on the example of the oil sector

• Autorzy: Byrska-Rąpała A.
• Języki publikacji: EN

Abstrakty

EN

The geological object (deposit) is a specific type of asset of mining enterprise which cannot be quantitatively or qualitatively interchangeably measured. In spite of rapid development of geological and economic sciences, still none of universal method of evaluation of value of resources has been settled yet. In the article, on the example of the oil sector, author described chosen methods of the mathematical statistics and the financial mathematics tools, which are used in the risk assessment related to estimating the fair market value of hydrocarbons. In the article the following subjects are presented: - the hyperbolic lognormal distribution in the exploration risk assessment, - the exponential utility function and the evaluation of the real option in the economic risk assessment. For each area of risk assessment is to recommend software. Statistical methods and the financial engineering used in estimating the fair value of the properties, are from many years the topic of numerous scientific publications and research. Many of the studies has indicated the importance of mathematical methods in solving problems in the area, where not long ago intuition and experience of evaluator of deposit were mainstream.

Słowa kluczowe

EN

fair market value; hyperbolic lognormal distribution; exponential utility function; risk tolerance level; equivalent of certainty; real option

PL

godziwa wartość rynkowa; opcja realna; ekwiwalent pewności; poziom tolerancji ryzyka

• Wydawca: Wydawnictwo Szkoły Głównej Gospodarstwa Wiejskiego w Warszawie
• Czasopismo: Information Systems in Management
• Rocznik: 2012
• Tom: Vol. 1, No. 3
• Strony: 171--183
• Opis fizyczny: Bibliogr. 9 poz., rys., tab., wykr.

Twórcy

autor

Byrska-Rąpała A.

• Faculty of Management, AGH University of Science of Technology Krakow

Bibliografia

• [1] Byrska-Rąpała A., Metodyka szacowania wartości godziwej złoża węglowodorów, Wydawnictwa AGH, Kraków 2011. (in Polish).
• [2] Crovelli R.A., Schmoker J.W., Balay R.H., U.S. Department of Interior U.S. Geological Survey: fractal lognormal percentage analysis of the U.S. Geological Survey’s 1995 National Assessment of Conventional Oil and Gas Resources, Nonrenewable Resources 1997, vol. 6, no. 1, p. 43─53.
• [3] Divi R.S., Probabilistic methods in petroleum resource assessment, with some examples using data from the Arabian region, Journal of Petroleum Science and Engineering 2004, vol. 42, p. 95─106.
• [4] Hickman T.S., The evolution of economic forecasts and risk adjustments in property evaluation in the U.S, Journal of Petroleum Technology 1991, vol. 43, no. 2, p. 220─225.
• [5] Lerche I., MacKay A.J., Economic Risk in Hydrocarbon Exploration, Academic Press, San Diego 1999.
• [6] Lerche I., Noeth S., Value Change in Oil and Gas Production: I. Additional Information at Fixed Cost but Variable Resolution Probability, Energy Exploration and Exploitation 2002, vol. 20, no. 1, p. 463─478.
• [7] Nepomuceno F., Suslick S.B., Walls M., Managing technological and financial uncertainty: a decision science approach for strategic drilling decisions, Natural Resources Research 1999, vol. 8, no. 3, p. 193─203.
• [8] Nikravesh M., Soft computing-based computational intelligent for reservoir characterization, Expert System with Application 2004, vol. 26, no. 1, p. 19─38.
• [9] Suslick S.B., Schiozer D.J., Risk analysis applied to petroleum exploration and production: an overview, Journal of Petroleum Science and Engineering 2004, vol. 44, p. 1─9.