Dynamic Risk Assessment of Decommissioning Offshore Jacket Structures

Abstract

The need to develop an integrated dynamic safety and risk analysis model for decommissioning offshore jacket structures is driven by the risky, expensive and complex nature of the operation. Many of the existing risk analysis techniques applicable to offshore assets failed to recognise and capture evolving risks during different stages of the decommissioning operation. This paper describes risk-based safety model to conduct quantitative risk analysis for offshore jacket decommissioning failure. First, a bow-tie technique is developed to model the accident cause-consequence relationship. Subsequently, a Bayesian belief network is used to update the failure probabilities of the contributing elements and thus, provides a more case-specific and realistic safety analysis when compared to the static nature of a bow-tie. This paper also presents the application of experiential learning in the dynamic safety analysis. The proposed technique is tested using a real-life case study from the Shell Brent Alpha platform. An algorithm to limit the effect of generic failure data was also developed. It is observed that the proposed technique helps to identify hazards shortly before they occur and sensitivity analysis revealed the most critical elements of the operation that must be managed to prevent catastrophe and consequently, reduce associated costs of remediation