Applying the Disaggregation-Aggregation Paradigm for Crude Oil Pipeline Risk Management
Pipelines is the most efficient (and hence popular) mean to transport crude oil and natural gas. However, there exist several reasons that could trigger a failure of pipelines and the following consequences to people’s properties, human health, and the environment. To this end, pipeline risk management is a primary concern for Oil and Gas companies. Since multiple factors contribute to the risk level of a pipeline, in this work we apply the aggregation-disaggregation paradigm of MCDA to assess the risk of every part of a crude oil pipeline. The presented method considers multiple dimensions (criteria), it is able to deal with the uncertainties in the criteria measurements, and it aggregates the preferences of multiple experts. We focus on a crude oil pipeline owned by the Nigerian Petroleum Development Company, and we used experts’ opinion to get the evaluations of the alternatives on the criteria set. To deal with the inherent uncertainty, we applied stochastic UTA, a method that allows a probabilistic distribution to get used for alternatives evaluations. We were able to estimate the significance weight for every criterion, its marginal utility function, a final ranking of the segments, and valuable insights about how those ranks are achieved. In particular, it became apparent that for the specific location of the pipeline, the external interference criterion has greater importance than in other regions. In fact, it becomes a criterion of primary importance (in tandem with the corrosion criterion).
- American Institute of Chemical Engineers (Ed.) (2001). Layer of protection analysis: Simplified process risk assessment. New York: Center for Chemical Process Safety of the American Institute of Chemical Engineers.Google Scholar
- Bisdorff, R., Meyer, P., & Veneziano, T. (2009). XMCDA: A standard XML encoding of MCDA data (p. 53). EURO XXIII: European conference on Operational Research.Google Scholar
- Bolzon, G., & NATO (Eds.) (2011). Integrity of pipelines transporting hydrocarbons: Corrosion, mechanisms, control, and management. Proceedings of the NATO Advanced Research Workshop on Corrosion Protection of Pipelines Transporting Hydrocarbons, Biskra, Algeria, April 26–28, 2010. Dordrecht: Springer.Google Scholar
- Christodoulakis, N. (2015). Analytical methods and multicriteria decision support systems under uncertainty: The Talos system. Retrieved from http://phdtheses.ekt.gr/eadd/handle/10442/36427.
- Cobanoglu, M. M. (2014). Statistical modeling of corrosion failures in natural gas transmission pipelines. Retrieved from http://hdl.handle.net/1969.1/152566.
- Delias, P., & Matsatsinis, N. F. (2007). The multiple criteria paradigm as a background for agent methodologies (pp. 227–237). 8th Annual International Workshop “Engineering Societies in the Agents World”, Athens, Greece.Google Scholar
- Kiefner, J. F. (2007). Evaluating the stability of manufacturing and construction defects in natural gas pipelines. Worthington, OH: U.S. Department of Transportation Office of Pipeline Safety.Google Scholar
- Muhlbauer, W. K. (2004). Pipeline risk management manual: Ideas, techniques, and resources. Amsterdam: Elsevier.Google Scholar
- Petrova, E. (2011). Critical infrastructure in Russia: Geographical analysis of accidents triggered by natural hazards. Environmental Engineering and Management Journal, 10, 53–58.Google Scholar
- Siskos, Y. (1983). Analyse de systèmes de décision multicritère en univers aléatoire. Foundations of Control Engineering, 10, 193–212.Google Scholar
- Siskos, Y., Spyridakos, A., & Yannacopoulos, D. (1993). MINORA: A multicriteria decision aiding system for discrete alternatives. Journal of Information Science and Technology, 2, 136–149.Google Scholar
- Siskos, Y., & Yannacopoulos, D. (1985). UTASTAR: An ordinal regression method for building additive value functions. Investigação Operacional, 5, 39–53.Google Scholar