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Articles

Safety analysis of offshore decommissioning operation through Bayesian network

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Pages 99-109 | Published online: 21 Mar 2019
 

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 a 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 an 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 a risk analysis.

SUBJECT CLASSIFICATION CODES:

Acknowledgements

The authors thankfully acknowledge all the experts for their valuable inputs on the accident analysis description.

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes on contributors

Ahmed O. Babaleye holds a Bachelor of Engineering degree (2011) in Mechanical Engineering and Production Technology from the Saimaa University of Applied Sciences in Finland, a Master of Science (Technology) in Mechanical Engineering from Aalto University, 2013 (Formerly, Helsinki University of Technology). He also holds a Master of Science degree in Subsea and Pipeline Engineering from the University of Strathclyde, United Kingdom. He is presently a PhD Candidate at the department of Naval Architecture, Ocean and Marine Engineering in the University of Strathclyde. With over 4 years of active research, design and development activities within the domain of subsea and offshore technologies, he has been involved in the design and management of complex engineering projects. His PhD research is focused on the failure analysis of decommissioning and abandonment operations using advanced probabilistic and statistical tools. In the past 2 years, he has developed tools and techniques to aid in the safety risk analysis of plugging and abandonment activities including time-dependence and model formulation under uncertain reservoir condition and limited failure data.

Rafet E. Kurt is a recognised expert in the field of ship recycling. For more than 10 years, Dr Kurt has been working in this area and contributed to the development of tools, models, and training tailored for the unique needs of the ship recycling sector. Besides actively conducting research in this field, Dr Kurt also contributed to the development of international regulations (i.e. International Maritime Organisation's, Hong Kong Convention and European Union's Ship Recycling Regulation). Additionally, Dr Kurt is an expert in the field of maritime safety and risk with a specific focus to maritime human factors which includes design, optimisation, and operation of ships by considering the human factors, safety, and risk at the core of the subject.

Additional information

Funding

The financial support was provided by the John Blackburn Main IMarEST Fellowship; Engineering the future body; and the Department of Naval, Ocean and Marine Engineering, of the University of Strathclyde.

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