DOI: 10.1111/risa.70401 ISSN: 0272-4332

Hybrid Semi‐Quantitative Risk Assessment for Aging Offshore Platforms: A HAZOP–FMEA–Bow‐Tie Framework With Sensitivity Analysis and KRI‐Based Governance

Muhammad Fawad Saleem, Majid Baseer, Qasim Tariq, Ahmad Khan

ABSTRACT

Aging offshore installations increasingly operate beyond their original design life, yet conventional periodic risk assessments capture barrier degradation only intermittently. This study presents a barrier‐conditioned semi‐quantitative risk‐assessment workflow that integrates Hazard and Operability Study (HAZOP), Failure Mode and Effects Analysis (FMEA), and bow‐tie barrier analysis. The workflow combines decomposed residual likelihood and consequence scoring with threshold‐stability testing and a Key Risk Indicator (KRI)‐based update rule. Its principal contribution is the governance linkage: an explicit rule set that maps barrier condition and KRI threshold breaches to changes in residual likelihood, residual consequence, and risk band between formal safety‐case reviews. To ensure transparency and reproducibility, the workflow is demonstrated through a fully synthetic scenario representing a life‐extended semi‐submersible installation; all inputs are constructed and explicitly identified throughout as scenario assumptions. Under the illustrative scoring assumptions, a 19‐hazard register spanning seven hazard categories yields two high, nine medium, and eight low residual risks, with blowout/well‐control failure and hydrogen sulfide release remaining the highest residual risks. Per‐perturbation threshold‐stability analysis and distribution‐based Monte Carlo propagation indicate that 16 of the 19 residual risk ratings are sensitive to classification boundaries, suggesting that the reported scores should be interpreted as central estimates subject to uncertainty. The proposed workflow provides a transparent tool for risk screening and governance support, complementing full quantitative risk assessment (QRA) while preserving its essential analytical role.

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