Proceedings of the 2018 2nd International Conference on Advances in Energy, Environment and Chemical Science (AEECS 2018)

Failure Reason Analysis of Subsea BOP in Deepwater on Bayesian network

Authors
Gang Liu, Hongfei Lu, Boyao Li
Corresponding Author
Gang Liu
Available Online March 2018.
DOI
10.2991/aeecs-18.2018.27How to use a DOI?
Keywords
deepwater BOP system; Bayesian network; risk identification; common cause failure.
Abstract

Deepwater drilling is the key of offshore oil and gas exploration and development. Deepwater BOP system is the key equipment which ensure safety in drilling operation. In order to prevent deepwater well control accidents and guarantee deepwater drilling undersafe and efficient conditions Bayesian network and FTA methods were comprehensive used to analyze risk of subsea BOP. During the analysis, both of human error and component failure were considered to make the calculation more objective. 6 main failure reasons such as wellhead connector failure, power system failure and accumulator failure are obtained. According to the calculation some improvement measures or suggestions have been proposed for the optimization of deepwater BOP system.

Copyright
© 2018, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Download article (PDF)

Volume Title
Proceedings of the 2018 2nd International Conference on Advances in Energy, Environment and Chemical Science (AEECS 2018)
Series
Advances in Engineering Research
Publication Date
March 2018
ISBN
978-94-6252-479-8
ISSN
2352-5401
DOI
10.2991/aeecs-18.2018.27How to use a DOI?
Copyright
© 2018, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Gang Liu
AU  - Hongfei Lu
AU  - Boyao Li
PY  - 2018/03
DA  - 2018/03
TI  - Failure Reason Analysis of Subsea BOP in Deepwater on Bayesian network
BT  - Proceedings of the 2018 2nd International Conference on Advances in Energy, Environment and Chemical Science (AEECS 2018)
PB  - Atlantis Press
SP  - 144
EP  - 155
SN  - 2352-5401
UR  - https://doi.org/10.2991/aeecs-18.2018.27
DO  - 10.2991/aeecs-18.2018.27
ID  - Liu2018/03
ER  -