Pipeline risk analysis is a common step carried out by operators in their overall Pipeline Integrity Management Process. There is a growing realization among operators of the need to adopt more proactive risk management approaches. This has brought about increased demand for more quantitative models to support risk reduction decision-making. Consequences of failure are a key component of these models where enhanced quantitative approaches can be deployed.

Impacts to the environment and upon populations are key issues which both operators and regulatory bodies seek to minimize. Pipeline risk models and High Consequence Area (HCA) analyses play an increasingly important role in this context by allowing operators to identify a range of potential scenarios and the relative impact to receptors based upon the best available data sources.

This paper presents the process and results of an HCA analysis project carried out by ROSEN for a major South American state-owned pipeline operator (hereafter referred to as ‘the Client’). This analysis was implemented using automated GIS processing methods and includes HCA analyses for approximately 2354 km of pipeline. The analysis was based on industry standards for both liquid and gas pipelines (i.e. American Petroleum Institute (API) and American Society of mechanical Engineers (ASME)), but customized for the specific needs of the Client and the South American geographical context.

A key use for the results of this analysis is to serve as input for the pipeline risk assessment model jointly developed by ROSEN Integrity Solutions, MACAW Engineering and the Client. The methodology for development of this model is briefly discussed, and operational uses of HCA results are illustrated. The benefits of this project include, but are not limited to, identifying areas that could be severely impacted should a pipeline failure occur, being able to assess the risk profile of credible threats in HCAs, but also being able to prioritize preventative and mitigation measures at HCAs to either reduce the likelihood of failure or the impact of failure upon various receptors.

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