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Dynamic risk analysis of offloading process in floating liquefied natural gas (FLNG) platform using Bayesian Network
Institution:1. Australian Maritime College, University of Tasmania, Launceston, TAS 7250, Australia;2. Department of Civil Engineering, University of Kharazmi, Tehran, Iran;1. Department of Maritime Management, Bursa Technical University, Osmangazi 16190, Bursa, Turkey;2. Department of Marine Engineering, Istanbul Technical University, Tuzla 34940, Istanbul, Turkey;1. Intelligent Transport Systems Research Center, Wuhan University of Technology, Wuhan 430063, China;2. National Engineering Research Center for Water Transport Safety, Wuhan 430063, China;3. Graduate School for International Development and Cooperation, Hiroshima University, Higashi Hiroshima 7398511, Japan;1. Sciences & Research Branch, Tehran Science and Research Branch University, Hesarak, Tehran, Iran;2. Department of Maritime Management, Bursa Technical University, Osmangazi, Bursa, Turkey;1. School of Naval Architecture and Ocean Engineering, Dalian University of Technology (DUT), NO-116024 Dalian, China;2. Department of Marine Technology, Norwegian University of Science and Technology (NTNU), NO-7491 Trondheim, Norway;1. ExxonMobil Research Qatar Science and Technology Park, PO Box 22500, Doha, Qatar;2. Mary Kay O''Connor Process Safety Center at Qatar, Texas A&M University at Qatar, PO Box 27874, Doha, Qatar
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 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.
Keywords:FLNG  Accident  Dynamic risk analysis  Bayesian network  Safety barriers
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