Risk-based selection of subsea leak detection technologies
As traditional oil and gas deposits dwindle, non-traditional marginal reserves are being exploited to further economical and industrial needs worldwide. These reserves are often far from civilization, deep in the sea or in regions such as the Arctic. Now, more than ever, risks related to transportin...
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ftmemorialuniv:oai:research.library.mun.ca:10655 2023-10-01T03:53:46+02:00 Risk-based selection of subsea leak detection technologies Hillier, Alan 2013 application/pdf https://research.library.mun.ca/10655/ https://research.library.mun.ca/10655/1/Hillier_Alan.pdf en eng Memorial University of Newfoundland https://research.library.mun.ca/10655/1/Hillier_Alan.pdf Hillier, Alan <https://research.library.mun.ca/view/creator_az/Hillier=3AAlan=3A=3A.html> (2013) Risk-based selection of subsea leak detection technologies. Masters thesis, Memorial University of Newfoundland. thesis_license Thesis NonPeerReviewed 2013 ftmemorialuniv 2023-09-03T06:47:58Z As traditional oil and gas deposits dwindle, non-traditional marginal reserves are being exploited to further economical and industrial needs worldwide. These reserves are often far from civilization, deep in the sea or in regions such as the Arctic. Now, more than ever, risks related to transporting oil and gas products need to be determined in these remote and sensitive ecological areas. Continuous monitoring of subsea pipelines is the best way to detect leaks quickly and prevent/minimize damage. A number of systems and technologies exist for this purpose. The present work describes two analytical approaches to making decisions related to best technology selection. The first is selecting the best available technology through researching desired parameters and conducting objective analysis. The second approach uses a risk-based methodology for identifying the best technology. The key focus of the present work is to develop a method to quantify uncertainties involved with leak detection technologies on subsea arctic pipelines applicable to harsh environments and use the quantified uncertainty in decision making. This thesis presents both approaches in detail and discusses their application to a real-life case study. Thesis Arctic Memorial University of Newfoundland: Research Repository Arctic |
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Memorial University of Newfoundland: Research Repository |
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As traditional oil and gas deposits dwindle, non-traditional marginal reserves are being exploited to further economical and industrial needs worldwide. These reserves are often far from civilization, deep in the sea or in regions such as the Arctic. Now, more than ever, risks related to transporting oil and gas products need to be determined in these remote and sensitive ecological areas. Continuous monitoring of subsea pipelines is the best way to detect leaks quickly and prevent/minimize damage. A number of systems and technologies exist for this purpose. The present work describes two analytical approaches to making decisions related to best technology selection. The first is selecting the best available technology through researching desired parameters and conducting objective analysis. The second approach uses a risk-based methodology for identifying the best technology. The key focus of the present work is to develop a method to quantify uncertainties involved with leak detection technologies on subsea arctic pipelines applicable to harsh environments and use the quantified uncertainty in decision making. This thesis presents both approaches in detail and discusses their application to a real-life case study. |
format |
Thesis |
author |
Hillier, Alan |
spellingShingle |
Hillier, Alan Risk-based selection of subsea leak detection technologies |
author_facet |
Hillier, Alan |
author_sort |
Hillier, Alan |
title |
Risk-based selection of subsea leak detection technologies |
title_short |
Risk-based selection of subsea leak detection technologies |
title_full |
Risk-based selection of subsea leak detection technologies |
title_fullStr |
Risk-based selection of subsea leak detection technologies |
title_full_unstemmed |
Risk-based selection of subsea leak detection technologies |
title_sort |
risk-based selection of subsea leak detection technologies |
publisher |
Memorial University of Newfoundland |
publishDate |
2013 |
url |
https://research.library.mun.ca/10655/ https://research.library.mun.ca/10655/1/Hillier_Alan.pdf |
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Arctic |
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Arctic |
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Arctic |
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Arctic |
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https://research.library.mun.ca/10655/1/Hillier_Alan.pdf Hillier, Alan <https://research.library.mun.ca/view/creator_az/Hillier=3AAlan=3A=3A.html> (2013) Risk-based selection of subsea leak detection technologies. Masters thesis, Memorial University of Newfoundland. |
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