Safety analysis of offshore decommissioning operation through Bayesian network

Abstract

Decommissioning of offshore platforms is becoming increasingly popular. The removal of these heavy steel structures is characterised by high risks that may compromise personnel safety and loss of assets. The removal operation relies on dedicated barges and heavy lift vessels that may descent or capsize because of mechanical or structural failure. The knowledge of associated hazards is driven by experience and failure data are often obtained empirically through analogous operations, which further introduces uncertainty to the risk analysis. This paper proposes an integrated safety analysis approach for conducting decommissioning risk analysis of offshore installations. The approach incorporates hierarchical Bayesian analysis (HBA) with Bayesian network (BN) to assess the accident causations leading to futile decommissioning operation. First, the overall system failure of a lifting vessel was reviewed with emphasis on where safety issues arise. In addition, the failure data obtained from expert judgements were aggregated through statistical distribution based on HBA. The aggregated failure data are then used to conduct dynamic safety analysis using BN, to assess and evaluate the risks of offshore jacket removal operations. The accident model is illustrated with a case study from Brent Alpha decommissioning technical document to demonstrate the capability of incorporating HBA with BN to conduct risk analysis.

A Bayesian network model for the probabilistic safety assessment of offshore wind decommissioning

“…Kim et al (2020) developed a dynamic probabilistic method based on BN and clustering analysis to quantify the risks associated with offshore wind turbines. Babaleye and Kurt (2020) proposed a framework for the application of hierarchical Bayesian analysis (HBA) for data collection and the BNs to perform probabilistic risk assessment of offshore decommissioning projects. For logistics risk assessment, Rahman et al (2020) proposed the application of advanced BNs to logistics operations of supply vessel emergency response in offshore marine locations because of the limited knowledge about the hazards and risks involved.…”

A novel comprehensive framework for analyzing and assessing water quality and failure consequences based on Bayesian networks

“…The Bayesian network (BN) is a probabilistic directed acyclic graphical model (DAG; Zhu & Deshmukh., 2003). It is a powerful model for probabilistic uncertain knowledge representation and inference and is progressively used in the field of safety and risk analysis (Babaleye & Kurt, 2020), reliability evaluation (Kumar, Bose, Srivardhan, & Rao, 2020), diagnosis (Cheng, Zhu, Fu, Wang, & Sun, 2019) and other.…”