Dynamic risk analysis of offloading process in floating liquefied natural gas (FLNG) platform using Bayesian Network. (May 2016)
- Record Type:
- Journal Article
- Title:
- Dynamic risk analysis of offloading process in floating liquefied natural gas (FLNG) platform using Bayesian Network. (May 2016)
- Main Title:
- Dynamic risk analysis of offloading process in floating liquefied natural gas (FLNG) platform using Bayesian Network
- Authors:
- Yeo, ChuiTing
Bhandari, Jyoti
Abbassi, Rouzbeh
Garaniya, Vikram
Chai, Shuhong
Shomali, Behzad - Abstract:
- Abstract: The growing demand for natural gas has pushed oil and gas exploration to more isolated and previously untapped regions around the world where construction of LNG processing plants is not always a viable option. The development of FLNG will allow floating plants to be positioned in remote offshore areas and subsequently produce, liquefy, store and offload LNG in the one position. The offloading process from an FLNG platform to a gas tanker can be a high risk operation. It consists of LNG being transferred, in hostile environments, through loading arms or flexible cryogenic hoses into a carrier which then transports the LNG to onshore facilities. During the carrier's offloading process at onshore terminals, it again involves risk that may result in an accident such as collision, leakage and/or grounding. It is therefore critical to assess and monitor all risks associated with the offloading operation. This study is aimed at developing a novel methodology using Bayesian Network (BN) to conduct the dynamic safety analysis for the offloading process of an LNG carrier. It investigates different risk factors associated with LNG offloading procedures in order to predict the probability of undesirable accidents. Dynamic failure assessment using Bayesian theory can estimate the likelihood of the occurrence of an event. It can also estimate the failure probability of the safety system and thereby develop a dynamic failure assessment tool for the offloading process at aAbstract: The growing demand for natural gas has pushed oil and gas exploration to more isolated and previously untapped regions around the world where construction of LNG processing plants is not always a viable option. The development of FLNG will allow floating plants to be positioned in remote offshore areas and subsequently produce, liquefy, store and offload LNG in the one position. The offloading process from an FLNG platform to a gas tanker can be a high risk operation. It consists of LNG being transferred, in hostile environments, through loading arms or flexible cryogenic hoses into a carrier which then transports the LNG to onshore facilities. During the carrier's offloading process at onshore terminals, it again involves risk that may result in an accident such as collision, leakage and/or grounding. It is therefore critical to assess and monitor all risks associated with the offloading operation. This study is aimed at developing a novel methodology using Bayesian Network (BN) to conduct the dynamic safety analysis for the offloading process of an LNG carrier. It investigates different risk factors associated with LNG offloading procedures in order to predict the probability of undesirable accidents. Dynamic failure assessment using Bayesian theory can estimate the likelihood of the occurrence of an event. It can also estimate the failure probability of the safety system and thereby develop a dynamic failure assessment tool for the offloading process at a particular FLNG plant. The main objectives of this paper are: to understand the LNG offloading process, to identify hazardous events during offloading operation, and to perform failure analysis (modelling) of critical accidents and/or events. Most importantly, it is to evaluate and compare risks. A sensitivity analysis has been performed to validate the risk models and to study the behaviour of the most influential factors. The results have indicated that collision is the most probable accident to occur during the offloading process of an LNG carrier at berth, which may have catastrophic consequences. Highlights: Conducted a detailed hazard assessment in FLNG offloading process. A novel methodology for dynamic risk analysis of offloading process in FLNG. Determined the most influencing factors on risk of offloading process in FLNG. … (more)
- Is Part Of:
- Journal of loss prevention in the process industries. Volume 41(2016:May)
- Journal:
- Journal of loss prevention in the process industries
- Issue:
- Volume 41(2016:May)
- Issue Display:
- Volume 41 (2016)
- Year:
- 2016
- Volume:
- 41
- Issue Sort Value:
- 2016-0041-0000-0000
- Page Start:
- 259
- Page End:
- 269
- Publication Date:
- 2016-05
- Subjects:
- FLNG -- Accident -- Dynamic risk analysis -- Bayesian network -- Safety barriers
Chemical industries -- Safety measures -- Periodicals
660.2804 - Journal URLs:
- http://www.sciencedirect.com/science/journal/09504230/ ↗
http://www.journals.elsevier.com/journal-of-loss-prevention-in-the-process-industries/ ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.jlp.2016.04.002 ↗
- Languages:
- English
- ISSNs:
- 0950-4230
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 5010.562000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 2451.xml