As pipeline operators progressively adopt operating strategies of continual risk management with a view to minimizing total expenditures within safety, environmental, and reliability constraints, the need for quantitative assessments of risk levels and setting risk tolerability criteria becomes evident. The advantages of quantitative risk assessment are that it’s measurable and helps to identify specific segments in a pipeline where mitigation measures should be applied, thereby reducing the risk of the entire system.
This paper is a case study of a large LNG producer, how they manage their pipelines and the role of risk assessment within their multiple pipeline integrity management system. It describes how PII’s risk software (PVi) assisted data driven, quantitative risk assessment to identify and prioritize specific segments of the pipelines for risk mitigation.
The paper explains the importance of gathering accurate data to conduct quantitative risk assessments and how the risk model is developed in such a way that any anecdotal understanding of pipeline risks are avoided so that risk results are data driven.
It explains organizational challenges faced by the operator when such a process is implemented, including the importance of stakeholder engagement in the data gathering, risk assessment and decision making process and methods adopted to overcome those challenges and obtain engagement.
An overview of the risk model used is described including various threat and consequence models. The criteria established for pipeline segmentation are also described.
Scenarios are provided where the quantified risk of just one short segment increases the entire pipeline risk and how an appropriate change in attribute and/or operating procedure can reduce the risk to an acceptable level.
A discussion is also included on how the risk engine supplies ‘what if’ scenarios to demonstrate reduction in risk that the agreed mitigation activities will achieve prior to asset integrity expenditure.