Abstract

Integrated and automated integrity management is essential for Arctic and cold region pipeline failure prevention, predictive maintenance, and life extension because the consequence of a failure will be disastrous both environmentally and economically. Without managing integrity, the condition of pipeline would continue to deteriorate until found unfit for service or premature failure. Real-time Condition Monitoring (CM) is a sensor- based monitoring technique aimed at enhancing the productivity of pipeline operation. The main intent of condition monitoring is to assess operating conditions and performance, improve performance, aid maintenance, extend life, and inform operator if the integrity is compromised. Other purpose of monitoring is to provide warning when something is starting to go wrong, and provide instantaneous information when things have gone wrong. This paper presents a recently developed concept and methodology for Arctic pipeline integrity management using Inspection, Maintenance and Repair (IMR) strategy using real-time CM data by probabilistic risk assessment. The probabilistic risk assessment is performed by combining advanced probabilistic analysis with computation. In this paper, the joint probability of failure arising from potential pipeline defects (e.g. corrosion, cracking, and strain) and likely operational deviations (e.g. pressure, temperature, and vibration) is computed real-time using the CM data to predict a condition-based IMR strategy. Having such a model would enable rapid decision-making regarding pipeline failure prevention, predictive maintenance and life extension.

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