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2017 | 17 | nr 1 | 37--51
Tytuł artykułu

Application of 2k Full Factorial Experiment for the Determination of Risk Factors Significance of Oil and Gas Production Enterprises' Activity

Autorzy
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The efficiency of risk management software depends on the quality of risk assessment at the stage of such system development. The number of potential variables (factors) in many risk management software applications is large. Another important aspect is that the scientists and engineers face to challenge which risk factors are significant or what the acceptable range of its values is at the initial stage of the risk controlling system development. The paper suggests a way to determine the significant specific risk factors of domestic oil and gas production enterprises' activity and to screen out the insignificant factors. In order to achieve these goals, the simulation analysis was conducted by the aid of 2-level full factorial experiment. Empirical data-processing operation was carried out through the instrumentality of mathematical statistics methods. It has been suggested to exclude (screen) at the stage of model construction eleven risk factors (of thirty-five ones identified), which impact on the financial and economical state of analyzed companies is insignificant (less than 5%). (original abstract)
Rocznik
Tom
17
Numer
Strony
37--51
Opis fizyczny
Twórcy
  • Ivano-Frankivsk National Technical University of Oil and Gas, Ukraine
Bibliografia
  • AlKazimi, M.A., & Grantham, K. (2015). Investigating new risk reduction and mitigation in the oil and gas industry. Journal of Loss Prevention in the Process Industries, 34(2015), 196-208.
  • Andersen, S., & Mostue, B.A. (2012). Risk analysis and risk management approaches applied to the petroleum industry and their applicability to IO concepts. Safety Science, 50(10), 2010-2019.
  • Doroshenko, V.M. (1993). Foundations of scientific research. Kyiv, Ukraine: ISDO.
  • Gryniuk, O.I. (2016). Theoretical and applied aspects of identification of activity risks of oil and gas enterprises. The Journal Economic Analysis, 25(2), 63-78. Retrieved from https://www.econa.org.ua/index.php/econa/index
  • Gryniuk, O.I. (2016). Scientific-methodological approaches to risks evaluation and prediction of oil and gas extraction enterprises activity. Herald of Khmelnytskyi national university. Economic sciences, 1(1), 10-23. Retrieved from http://journals.khnu.km.ua/vestnik/zmisthtme.htm
  • Johnsen, S.O., Aas, A., & Qian, Y. (2012). Sector-Specific Information Infrastructure Issues in the Oil, Gas, and Petrochemical Sector. In J. Lopez, R. Setola, & S.D. Wolthusen (Eds.), Critical Infrastructure Protection (Vol. 7130, pp. 235-279). Heidelberg, Springer.
  • Li, Wen (2015). Efficiency of Manufacturing Processes: Energy and Ecological Perspectives (1st ed.). Cham, Springer International Publishing AG.
  • Marhavilas, P.K., Koulouriotis, D., & Gemeni, V. (2011). Risk analysis and assessment methodologies in the work sites: On a review, classification and comparative study of the scientific literature of the period 2000-2009. Journal of Loss Prevention in the Process Industries, 24(2011), 477-523.
  • Phases of a designed experiment (n.d.). In Minitab 17 Support. Retrieved February 8, 2017, from http://support.minitab.com/en-us/minitab/17/topic-library/modeling-statistics/doe/basics/phases-of-a-designed-experiment/
  • Quinao, J.J., & Zarrouk, S.J. (2014). Applications of Experimental Design and Response Surface Method in probabilistic geothermal resource assessment - Preliminary results. Proceedings of Thirty-Ninth Workshop on Geothermal Reservoir Engineering, Stanford University, Stanford, California, 24-26 February 2014, 1, 71-83. Retrieved February 8, 2017, from https://pangea.stanford.edu/ERE/pdf/IGAstandard/SGW/2014/Quinao.pdf
  • Shahriar, A., Sadiq, R., & Tesfamariam, S. (2012). Risk analysis for oil & gas pipelines: A sustainability assessment approach using fuzzy based bow-tie analysis. Journal of Loss Prevention in the Process Industries, 25(3), 505-523.
  • Skogdalen, J.E., & Vinnem, J.E. (2011). Quantitative risk analysis offshore - Human and organizational factors. Reliability Engineering & System Safety, 96(4), 468-479.
  • Walpole, R.E., Myers, R.H., Myers, S.L., & Ye, K.E. (2012). Probability & Statistics for Engineers & Scientists (9th ed.). Boston, USA: Prentice Hall.
Typ dokumentu
Bibliografia
Identyfikatory
Identyfikator YADDA
bwmeta1.element.ekon-element-000171501224

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