Offshore oil and gas exploitation is principally conducted using dry or wet tree
systems, otherwise called the subsea Xmas tree system. Due to the shift to
deeper waters, subsea production system (SPS) has come to be a preferred
technology with attendant economic benefits. At the centre of the SPS is the
subsea control module (SCM), responsible for the proper functioning and
monitoring of the entire system. With increasing search for hydrocarbons in
deep and ultra-deepwaters, the SCM system faces important environmental,
safety and reliability challenges and little research has been done in this area.
Analysis of the SCM reliability then becomes very fundamental due to the huge
cost associated with failure. Several tools are available for this analysis, but the
FMECA stands out due to its ability to not only provide failure data, but also
showcase the system’s failure modes and mechanisms associated with the
subsystems and components being evaluated. However, the technique has
been heavily challenged in various literatures for several reasons. To close this
gap, a novel multi-criteria approach is developed for the analysis and ranking of
the SCM failures modes.
This research specifically focusses on subsea tree-mounted electro-hydraulic
(E-H) SCM responsible for the underwater control of oil and gas production. A
risk identification of the subsea control module is conducted using industry
experts. This is followed by a comprehensive component based FMECA
analysis of the SCM conducted with the conventional RPN technique, which
reveals the most critical failure modes for the SCM. A novel framework is
developed using multi-criteria fuzzy TOPSIS methodology and applied to the
most critical failure modes obtained from the FMECA evaluation using
unconventional parameters. Finally, a validation of these results is performed
using a stochastic input evaluation and SCM failure data obtained from the
offshore industry standard reliability database, OREDA.
| Identifer | oai:union.ndltd.org:CRANFIELD1/oai:dspace.lib.cranfield.ac.uk:1826/9256 |
| Date | 09 1900 |
| Creators | Umofia, Anietie Nnana |
| Contributors | Kolios, Athanasios, Brennan, Feargal |
| Publisher | Cranfield University |
| Source Sets | CRANFIELD1 |
| Language | English |
| Detected Language | English |
| Type | Thesis or dissertation, Doctoral, PhD |
| Rights | © Cranfield University 2014. All rights reserved. No part of this publication may be reproduced without the written permission of the copyright owner. |
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