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Decision Making Under Uncertainty in Pipeline Projects Using Monte Carlo Simulation

[+] Author Affiliations
Claudio de Brito Garcia, Leandro Bastos Machado

PETROBRAS, Rio de Janeiro, RJ, Brazil

Paper No. IPC2004-0241, pp. 749-755; 7 pages
  • 2004 International Pipeline Conference
  • 2004 International Pipeline Conference, Volumes 1, 2, and 3
  • Calgary, Alberta, Canada, October 4–8, 2004
  • Conference Sponsors: International Petroleum Technology Institute
  • ISBN: 0-7918-4176-6 | eISBN: 0-7918-3737-8
  • Copyright © 2004 by ASME


Uncertainty about a situation can often indicate risk, which is the possibility of loss, damage, or any other undesirable event. Most people and organization desire low or minimized risk, which would translate to stand to a scenario of high probability of success, profit, or some form of gain. This work shows the importance of risk analysis when it comes to compare two capital investment projects in the natural gas transmission business. A transmission company needs to choose between two alternatives for capacity expansion of a pipeline, with a maximum value for the transmission tariff previously agreed to the shipper. At first, the transmission tariff is calculated by the conventional method that comprises iterative calculation from an arbitrary value, until the project Net Present Value (NPV) reaches zero. Once calculated, the lower of the transmission tariffs associated to the two expansion projects indicates the best choice. That’s the way the majority of companies perform their economical analysis of the proposed problem. Monte Carlo Simulation risk analysis technique is a powerful tool to asses the risk associated to a capital investment project, which can be summarized as the probability of undesired results. The risk calculation is based on the uncertainties associated to the input data used to build the project free cash flow, and the simulation produces a frequency distribution, or histogram, for, the NPV of a project. As will be seen in the work, the investment with the largest expected NPV may not always be the best investment alternative.

Copyright © 2004 by ASME



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