Process Safety in the oil and gas industry is managed through a robust Process Safety Management (PSM) system that involves the assessment of the risks associated with a facility in all steps of its life cycle. Risk levels tend to fluctuate throughout the life cycle of many processes due to several time varying risk factors (performances of the safety barriers, equipment conditions, staff competence, incidents history, etc.). While current practices for quantitative risk assessments (e.g. Bow-tie analysis, LOPA, etc.) have brought significant improvements in the management of major hazards, they are static in nature and do not fully take into account the dynamic nature of risk and how it improves risk-based decision making In an attempt to continually enhance the risk management in process facilities, the oil and gas industry has put in very significant efforts over the last decade toward the development of process safety key performance indicators (KPI or parameters to be observed) to continuously measure or gauge the efficiency of safety management systems and reduce the risks of major incidents. This has increased the sources of information that are used to assess risks in real-time. The use of such KPIs has proved to be a major step forward in the improvement of process safety in major hazards facilities. Looking toward the future, there appears to be an opportunity to use the multiple KPIs measured at a process plant to assess the quantitative measure of risk levels at the facility on a time-variant basis.ExxonMobil Research Qatar (EMRQ) has partnered with the Mary Kay O'Connor Process Safety Center -Qatar (MKOPSC-Q) to develop a methodology that establishes a framework for a tool that monitors in real time the potential increases in risk levels as a result of pre-identified risk factors that would include the use of KPIs (leading or lagging) as observations or evidence using Bayesian Belief Networks (BN).In this context, the paper presents a case study of quantitative risk assessment of a process unit using BN. The different steps of the development of the BN are detailed, including: translation of a Bowtie into a skeletal BBN, modification of the skeletal BN to incorporate KPIs (loss of primary containment (LOPC), equipment, management and human related), and testing of the BBN with forward and backward inferences. The outcomes of the dynamic modeling of the BN with real time insertion of evidence are discussed and recommendation for the framework for a dynamic risk assessment tool are made.

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Bow-ties are increasingly used in multiple industries to effectively manage risks during operation. Benefits of bow-ties include clear communication, operator ownership, relationship between safeguards for various threats and consequences, and the visibility of safeguard health during operations. In oil and gas, the main application of bow-ties has been to manage high consequence risks pertaining to process safety, i.e. loss of primary containment of hazardous substances. Unlike onshore facilities, escape from hazards can be inhibited by limited egress and evacuation options can be compromised as part of the events themselves, which heightens the potential number of fatalities in an offshore process safety event. Additionally, while the root cause of a good proportion of incidents originates from process safety hazards, many significant events have originated from offshore and marine structure hazards as well. Since offshore structural and marine failures are not always driven by loss of primary containment, the use of bow-ties in offshore structures and marine is less established. This paper introduces the use of bow-ties and associated principles as tools to manage all offshore risks, both process-safety and structural or marine related. It evaluates the application of bow-ties for a range of high consequence risk scenarios specific to fixed and floating offshore platforms, and provides simplified bow-ties for a range of different types of assets. Though it represents a less conventional approach than those commonly employed for offshore failure scenarios, use of bow-ties can support effective management of these risks, especially those requiring proactive management of safeguards, particularly ice feature overload, offshore collisions, multi-line mooring failures, and loss of floating stability.

The risk of operating and managing major hazard facilities is not a new one.