The purpose of this paper is to present the innovative reliability modeling of Petrobras 2010 integrated gas supply chain. The model represents a challenge in terms of complexity and software robustness. It was jointly developed by PETROBRAS Gas & Power Department and Det Norske Veritas. It was carried out with the objective of evaluating security of supply of 2010 gas network design that was conceived to connect Brazilian Northeast and Southeast regions. To provide best in class analysis, state of the art software was used to quantify the availability and the efficiency of the overall network and its individual components (such as gas processing units, city-gates, compressor stations, pipelines). The study requests, as input, a lot of information, that should be provided from different sectors of Petrobras, since it is supposed to depict reliability performance of all gas supply chain players. Information such as 2010 design configurations, gas offer and demand profiles, shedding priority, pressure delivery conditions, supply contract and associated penalties, commodity prices, etc., should be raised and addressed. More than twelve processing plants were modeled, in a detailed manner, and have their performance indicators compared. Different gas sources were considered in the study, such as offshore platforms, onshore fields, Bolivia pipeline and LNG ships. Detailed failure probability and repair data were addressed. Contingency plans, for each identified scenario, were made, in order to evaluate probable losses that constitute an input for the reliability modeling. Therefore, two additional software’s were used for their validation: - Pipeline studio – TGNET (from Energy Solutions), to check pressure conditions; and an in-house Petrobras software (PLANAGE), used for best gas allocation purposes. Experienced operational team opinion was incorporated on that contingency plans elaboration. This work constitutes a powerful tool for Petrobras planning and optimization of gas supply chain future configurations. The simulation provides propositions for investments prioritization, based on cost benefit analysis, and as a by-product, contingency plans, that were developed, considering different failure scenarios.

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