Subsea Oil Spill Risk Management Based on Sensor Networks
The use of Wireless Sensor Networks (WSNs) in support of Dynamic Risk Assessment regarding oil spills still lacks a proper integration. WSNs enable prompt responses to such emergencies through an appropriate inspection, thus avoiding possible larger disasters. This work proposes a methodology for th...
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The Italian Association of Chemical Engineering (AIDIC)
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ftntnutrondheimi:oai:ntnuopen.ntnu.no:11250/2684450 2023-05-15T15:38:54+02:00 Subsea Oil Spill Risk Management Based on Sensor Networks Tabella, Gianluca Salvo Rossi, Pierluigi Paltrinieri, Nicola Cozzani, Valerio 2020 application/pdf https://hdl.handle.net/11250/2684450 https://doi.org/10.3303/CET2082034 eng eng The Italian Association of Chemical Engineering (AIDIC) Chemical Engineering Transactions. 2020, 82 199-204. urn:issn:1974-9791 https://hdl.handle.net/11250/2684450 https://doi.org/10.3303/CET2082034 cristin:1838246 199-204 82 Chemical Engineering Transactions Peer reviewed Journal article 2020 ftntnutrondheimi https://doi.org/10.3303/CET2082034 2020-10-28T23:33:58Z The use of Wireless Sensor Networks (WSNs) in support of Dynamic Risk Assessment regarding oil spills still lacks a proper integration. WSNs enable prompt responses to such emergencies through an appropriate inspection, thus avoiding possible larger disasters. This work proposes a methodology for the setup of a WSN as a Leak Detection System in which a Fusion Center collects sensors’ binary decisions and provides a more reliable decision about the presence/absence of a leak. The detection rules are based on statistical signal processing techniques, and the choice of the optimal thresholds is made through the optimization of three objective functions tailored to the Oil&Gas industry. Detection performances are assessed in terms of the Receiver Operating Characteristic (ROC) curve. The case study is the Goliat FPSO, a production platform located in the Barents Sea, and related requirements dictated by Norwegian authorities to prevent oil spills. The considered WSN monitors the subsea manifolds through passive acoustic sensors. publishedVersion Copyright © 2020, AIDIC Servizi S.r.l. Article in Journal/Newspaper Barents Sea Goliat NTNU Open Archive (Norwegian University of Science and Technology) Barents Sea |
institution |
Open Polar |
collection |
NTNU Open Archive (Norwegian University of Science and Technology) |
op_collection_id |
ftntnutrondheimi |
language |
English |
description |
The use of Wireless Sensor Networks (WSNs) in support of Dynamic Risk Assessment regarding oil spills still lacks a proper integration. WSNs enable prompt responses to such emergencies through an appropriate inspection, thus avoiding possible larger disasters. This work proposes a methodology for the setup of a WSN as a Leak Detection System in which a Fusion Center collects sensors’ binary decisions and provides a more reliable decision about the presence/absence of a leak. The detection rules are based on statistical signal processing techniques, and the choice of the optimal thresholds is made through the optimization of three objective functions tailored to the Oil&Gas industry. Detection performances are assessed in terms of the Receiver Operating Characteristic (ROC) curve. The case study is the Goliat FPSO, a production platform located in the Barents Sea, and related requirements dictated by Norwegian authorities to prevent oil spills. The considered WSN monitors the subsea manifolds through passive acoustic sensors. publishedVersion Copyright © 2020, AIDIC Servizi S.r.l. |
format |
Article in Journal/Newspaper |
author |
Tabella, Gianluca Salvo Rossi, Pierluigi Paltrinieri, Nicola Cozzani, Valerio |
spellingShingle |
Tabella, Gianluca Salvo Rossi, Pierluigi Paltrinieri, Nicola Cozzani, Valerio Subsea Oil Spill Risk Management Based on Sensor Networks |
author_facet |
Tabella, Gianluca Salvo Rossi, Pierluigi Paltrinieri, Nicola Cozzani, Valerio |
author_sort |
Tabella, Gianluca |
title |
Subsea Oil Spill Risk Management Based on Sensor Networks |
title_short |
Subsea Oil Spill Risk Management Based on Sensor Networks |
title_full |
Subsea Oil Spill Risk Management Based on Sensor Networks |
title_fullStr |
Subsea Oil Spill Risk Management Based on Sensor Networks |
title_full_unstemmed |
Subsea Oil Spill Risk Management Based on Sensor Networks |
title_sort |
subsea oil spill risk management based on sensor networks |
publisher |
The Italian Association of Chemical Engineering (AIDIC) |
publishDate |
2020 |
url |
https://hdl.handle.net/11250/2684450 https://doi.org/10.3303/CET2082034 |
geographic |
Barents Sea |
geographic_facet |
Barents Sea |
genre |
Barents Sea Goliat |
genre_facet |
Barents Sea Goliat |
op_source |
199-204 82 Chemical Engineering Transactions |
op_relation |
Chemical Engineering Transactions. 2020, 82 199-204. urn:issn:1974-9791 https://hdl.handle.net/11250/2684450 https://doi.org/10.3303/CET2082034 cristin:1838246 |
op_doi |
https://doi.org/10.3303/CET2082034 |
_version_ |
1766370312425832448 |