Hostname: page-component-cd9895bd7-p9bg8 Total loading time: 0 Render date: 2024-12-23T06:12:35.540Z Has data issue: false hasContentIssue false

Collision Risk Modelling of Supply Vessels and Offshore Platforms Under Uncertainty

Published online by Cambridge University Press:  27 March 2017

Andrew John*
Affiliation:
(Offshore Technology Centre, Petroleum Training Institute Effurun, Delta State, Nigeria)
Umukoro Johnson Osue
Affiliation:
(Welding Engineering Department, Petroleum Training Institute Effurun, Delta State, Nigeria)
*

Abstract

Serious accidents in the marine and offshore industry have underscored the need for safety evaluation of maritime operations using risk and safety analysis methods which have become a powerful tool in identifying technical solutions and operational management procedures. Given that Fault Tree Analysis (FTA) is a known methodology used for analysing engineering systems, the approach is usually conducted using known failure data. But most offshore operations are conducted in a challenging and uncertain environment and the failure data of some of these systems are usually unavailable requiring a flexible and yet robust algorithm for their analysis. This paper therefore seeks to analyse the complex structure of Offshore Supply Vessel (OSV) collision with platforms by incorporating a Fuzzy Fault Tree Analysis (FFTA) method. Fuzzy set theory provides the flexibility to represent vague information from the analysis process. The methodology is structured in such a manner that diverse sets of data are integrated and synthesized for analysing the system. It is envisaged that the proposed method could provide the analyst with a framework to evaluate the risks of collision enabling informed decisions regarding the deployments of resources for system improvement.

Type
Research Article
Copyright
Copyright © The Royal Institute of Navigation 2017 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

Ali, M. and Haugen, S. (2012). Collision between offshore supply vessels and offshore installations. 11th International Probabilistic Safety Assessment and Management Conference and the Annual European Safety and Reliability Conference, PSAM11 ESREL 2012, 7:5643–5652.Google Scholar
Andrews, J.D. and Moses, T.R. (2002). Reliability and risk assessment. 2nd ed. London; Bury St Edmonds: Professional Engineering Publication Limited.Google Scholar
Bai, Y. and Jin, W.L. (2016). Risk Assessment Applied to Offshore Structures. Marine structural design, Second edition, 735763.Google Scholar
Chen, S.J. and Hwang, C.L. (1999). Fuzzy multiple attribute decision making. 1st ed. Berlin, Heidelberg: Springer-Verlag.Google Scholar
ConocoPhillips. (2013). Notes from a workshop with SINTEF and marine representatives from ConocoPhillips, 06.12.2013.Google Scholar
Coupe, V.M.H., van der Gaag, L.C. (2002). Properties of sensitivity analysis of Bayesian Belief networks. Annals of Mathematics and Artificial Intelligence, 36, 323356.Google Scholar
Flage, R., Baraldi, P., Zio, E. and Aven, T. (2013). Probability and possibility-based representations of uncertainty in fault tree analysis. Risk Analysis, 33, 121133.Google Scholar
Forrester, J.W. and Senge, P.M. (1980). Tests for building confidence in system dynamics models. TIMS Study Management Science. 14, 209228.Google Scholar
Hsu, H.M. and Chen, T.C. (1994). Aggregation of fuzzy opinion under group decision making. Fuzzy Set Systems, 79, 279285.Google Scholar
John, A. (2010). Risk assessment of deep water flexible riser collapse, focusing on offshore mobile drilling units. MSc Thesis, Liverpool John Moores University, UK.Google Scholar
John, A. (2013). Proactive risk management of maritime infrastructure systems: resilience engineering perspectives. PhD Thesis, Liverpool John Moores University, Liverpool.Google Scholar
John, A., Paraskevadakis, D., Bury, A., Yang, Z. and Wang, J. (2015). A new approach for evaluating the disruption risks of a seaport system. In: Nowakowski, T, Mlynczak, M, Jodejko-Pietruczuk, A, et al. (eds) Safety and reliability: methodology and applications. London: Taylor & Francis Group, 591598.Google Scholar
John, A., Nwaoha, T. C. and Kpangbala, T. M. (2016). A collaborative modelling of ship and port interface operations under uncertainty, Proceedings of IMechE Part M: Journal of Engineering for the Maritime Environment, DOI: 10.1177/1475090216629704 Google Scholar
Kongsvik, T., Bye, R., Fenstad, J., Gjøsund, G., Haavik, T., Schei Olsen, M., and Vedal Størkensen, K. (2011). Barrierer mellom fartøy og innretninger. identifisering, vurderinger og mulige forbedringstiltak. Technical report, NTNU Samfunnsforskning AS.Google Scholar
Kvitrud, A. (2011). Collisions between platforms and ships in Norway in the period 2001-2010. International Conference on Ocean, Offshore and Artic Engineering, Vol. 2, 637641.Google Scholar
Lavasani, M.R.M., Wang, J., Yang, Z. and Finlay, J. (2012). Application of MADM in a fuzzy environment for selecting the best barrier for offshore wells. Expert Systems with Applications, 39, 2466-2478.Google Scholar
Mentes, A. and Helvacioglu, I. (2011). An application of fuzzy fault tree analysis for spread mooring systems. Ocean Engineering, 38, 285294.Google Scholar
Nouri, S., Gharabaghi, A.R.M. and Mazaheri, S. (2008). Analysis of Ship Collision with a Semi-submersible Platform Proceedings of the Eighth ISOPE Pacific/Asia Offshore Mechanics Symposium Bangkok, Thailand, November 10-14, 2008.Google Scholar
NPD. (1992). Regulations Relating to Implementation and Use of Risk Analysis in the Petroleum Activities. Norwegian Petroleum Directorate, Stavanger, Norway.Google Scholar
Oltedal, H. (2012). Ship-platform collisions in the north sea. 11th International Probabilistic Safety Assessment and Management Conference and the Annual European Safety and Reliability Conference 2012, PSAM11 ESREL 2012, 8:6470–6479.Google Scholar
Pillay, A. and Wang, J. (2003). Technology and safety of marine systems. 1st ed. Amsterdam: Elsevier Science.Google Scholar
Serco Assurance. (2003). Ship/Platform Collision Incident Database (2001). Health and Safety Executive, Research Report 053.Google Scholar
Ship Owners. (2015). Security for small and specialist vessels, a case study for offshore supply vessel collision in offshore Brazil. Case number 58479.Google Scholar
Sugeno, M. (1999). Fuzzy modelling and control. Florida, USA: CRC Press.Google Scholar
Tvedt, E. (2013). Review of ship-platform collision risk models. Department of Production and Quality Engineering, Norwegian University of Science and Technology.Google Scholar
Trbojevic, M.V and Carr, J.B. (2000). Risk based methodology for safety improvements in ports. Journal of Hazardous Material, 71, 467480.Google Scholar
UK HSE. (1992). Safety Case Regulation. United Kingdom, Health and Safety Executive.Google Scholar
UK HSE. (1995). Prevention of Fire and Explosion, and Emergency Response Regulation. United Kingdom, Health and Safety Executive.Google Scholar
Uğurlu, O., Kose, E., Yildirim, U. and Yüksekyildiz, E. (2015). Marine accident analysis for collision and grounding in oil tanker using FTA method. Maritime Policy and Management, 42, 163185.Google Scholar
Yuhua, D. and Datao, Y. (2005). Estimation of failure probability of oil and gas transmission pipelines by fuzzy fault tree analysis. Journal of Loss Prevention in the Process industries, 18, 8388.Google Scholar