Managing Process Safety Risk at the Dynamic Frontline

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Abstract Process safety approaches developed and implemented over the past 20-30 years have enabled us to improve the design basis of our facilities. Yet we still see major incidents occurring at a steady rate. Traditional approaches to risk management may be appropriate as a basis for design, but they are not helpful in operations management where decisions continuously take place that impacts exposure to Major Accident Hazard (MAH) risk. A 2017 international survey1 looked into the state of process safety and risk management in the hazardous industries. 70% of survey respondents reported a gap between how process safety management is intended and the reality of operations. Only six percent of respondents indicated their companies were up-to-date on safety critical maintenance. The survey results highlighted that the real world of operations is neither simple nor static and highlighted a gap in organizations’ abilities to develop a single, shared view of the operational reality of risk. The current trend towards digitalization of the industry offers companies an opportunity for a clearer understanding of risk to reduce incidents and enhance the journey towards sustainable production and Operational Excellence. So-called "big data" and "edge data" techniques applied to the streams of data arising from modern facilities holds out the promise of a process safety early warning system that looks at potential signals and trends in facility operations data to make MAH risk exposure visible, prominent and available in real-time. A new category of Operational Risk Management (ORM) software tools is emerging which seek to deliver on this promise. This paper shares the approaches adopted by two major international oil industry operators who are leveraging a new approach to process safety and operational risk management to achieve safer, more sustainable operations.