Gas pipeline projects are capital intensive and are exposed to many risks related to uncertainties of their main components such as capital investment (material and services) - Capex, operation and maintenance costs - Opex, construction and assembly - C&A schedule, C&A Costs and others. Such items need to be properly addressed to mitigate project risk otherwise they may impact negatively the project sustainability normally measured by the project net present value - NPV. The availability of the compression system, if not properly addressed, may expose a gas pipeline project to undesirable risks. This paper will present a case study demonstrating how useful is Monte Carlo Simulation in association with Thermo-hydraulic simulation and economic evaluation in identifying and quantifying risks and in helping defining the optimum level of availability for the gas pipeline compression system. The installation of standby compressor station units helps achieving the necessary availability level to face contractual obligations related to transmission capacity. Technical and economical evaluation are of fundamental importance to support the decision making process in the design phase of a pipeline project. Monte Carlo Simulation is also used in the economical evaluation to provide accurate and reliable results. The aforementioned approach impacts project positively while supporting transportation rate design and also defining pipeline capacity that Transporter will negotiate with the Local Distribution Companies (LDC's) on a firm contractual basis.
Credit for inventing the Monte Carlo method often goes to Stanislaw Ulam, a Polish born mathematician who worked for John von Neumann on the United States' Manhattan Project during World War II. The Monte Carlo method, as it is understood today, encompasses any technique of statistical sampling employed to approximate solutions to quantitative problems. According to Evans and Olson (1998) Simulation is the process of building a mathematical or logical model of a system or a decision problem, and experimenting with the model to obtain insight into the system's behavior or to assist in solving the decision problem. The authors define Monte Carlo simulation, basically, as a sampling experiment whose purpose is to estimate the distribution of an outcome variable that depends on several probabilistic input variables. Monte Carlo simulation is often used to evaluate the expected impact of policy changes and risk involved in decision making. Risk is often defined as the probability of occurrence of an undesirable outcome. As a reference for applying Monte Carlo simulation in compressor station project selection Santos (2003) has evaluated the impact of Capex, Opex, and Construction and Assembly schedule on the economic sustainability of a project while comparing two different alternatives for implementing compressor stations in Petrobras gas pipeline network as described below:
Compressor station as a Transporter asset: in this alternative Capex, Opex are Transporter responsibility. Transporter will keep the ownership of the compressor station asset.
Compression service contract: in this alternative Capex and Opex are the responsibilities of a Service Provider Company that will be responsible for the installation, operation and maintenance of the compressor station and