Effective asset integrity management is supported through the understanding of the condition of the asset, and the quantification of the safety and uncertainty of its properties. Risk based and risk informed decision making can help operators prioritize inspections and repairs on mainline pipe, as well as within operator facilities. Setting operator system specific targets for reliability and risk can help operators better understand the condition of their system, and provide one means of determining whether integrity action or other risk treatment is required on a specific asset, either on the mainline pipe system or on a facility asset system.
While mainline pipe condition is better understood through the use of inline inspection technology and non-destructive examination in the field, facility piping and storage condition is more difficult to understand due to the complexity and number of segments of assets within an operator’s facility, as well as the unpiggable nature of the majority of facility piping.
To help resolve this issue, a risk quantification can be done for each segmented asset within a facility. A relative ranking of asset risks can help prioritize facility integrity activities and drive the planning and execution optimization. However, simply looking at a relative ranking of asset risks may not be enough to maximize risk reduction and achieve safety and reliability targets.
This paper looks to expand on the implementation of Risk Based Inspection (RBI) standard in API 581 and explore more broadly how facility asset risk results can be used in integrity planning and decision making. The paper also examines the application of using finance principals to better quantify risk and carry out a meaningful cost benefit analysis to optimize integrity programs.
Interpreting a quantified risk dollar amount is an industry challenge, and shedding light onto the value of applying reliability and risk models beyond the safety of an operator’s system can be extremely beneficial for operators to enhance cost efficiency. The quantification of risk helps support the optimization of spend and resource allocation to bring efficiencies into integrity management systems while maintaining focus on the right risk mitigation across an operator’s system.