PHA based on first principles qualitative and quantitative models and empirical knowledge

Industrial processes contain inherent risks and to assess such risks the use of Process Hazard Analysis (PHA) are commonly applied. The benefits of first principles qualitative and quantitative models and empirical knowledge support for PHA are explored. The use of qualitative hazard analysis based on functional modelling to guide hazard analysis is emphasized. The study proposes a framework for investigating potential hazard scenarios based on functional modeling, e.g. Multilevel Flow Modeling of process system. Subsequently quantitative hazard analysis is used to prioritize the hazard scenarios with highest potential. MFM represents the process on several levels of abstraction and supports logical inference. The potential hazard scenarios are ranked by likelihood and severity. Judgment about likelihood, severity and the tolerability of the resulting risk is made on a subjective basis using the empirical knowledge of the PHA team members. The potential hazard scenario generation procedure can be computer-aided. The proposed framework is applied for a water injection system to increase oil recovery from existing reservoir with better safety performance. Qualitative functional models are efficient for detailed description of possible accident scenarios. Domino effects can be visualized in an MFM model. The possible major accident scenarios are selected by likelihood and severity of their effects. The major accident scenarios can be examined in detail through further quantitative analysis. The hazard analysis of a water injection system demonstrates the feasibility and applicability of the proposed framework. In industrial practice, formulation of the major accident scenario is usually based on historical incidents and the outcome of HAZOP/HAZID type hazard identification studies. Such studies are dependent on the team and their collective knowledge rather than being systematic and objective in nature. The proposed framework performs systematic and comprehensive plant failure and consequence path generation by a computer-aided tool.