IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v15y2022i18p6820-d918034.html
   My bibliography  Save this article

A Novel Proposal for Optimal Performance of Blanket Gas System for FPSOs

Author

Listed:
  • Soon-kyu Hwang

    (Energy System R&D Department, Daewoo Shipbuilding and Marine Engineering, Siheung-si 15011, Korea)

  • Byung-gun Jung

    (Department of Marine System Engineering, Korea Maritime & Ocean University, Busan 49112, Korea)

  • Jong-kap Ahn

    (Training Ship Operation Center, Gyeongsang National University, Tongyeong-si 53064, Korea)

Abstract

The energy required for the transportation of raw materials and the production of most manufactured goods depends on crude oil. For these reasons, FPSOs (Floating, Production, Storage, and Offloading) have become the primary production units of crude oil offshore. It is leading to an increase in the number and expanding of the production and storage facilities of the FPSOs. An increase in the oil production at the topside facilities of FPSOs will contain more gases, which leads to a rise in blow-by gas. Changes to the blanket gas system may be necessary as the flow rate of the blow-by gas is expected to increase. The purpose of this paper is to suggest a novel blanket gas system with a proper control method for controlling the cargo tank pressure when the blow-by gas is occurring. Unlike the existing system, in this proposal, the purge header that supplies the inert gas is possible for a use of the vent purpose in the situation where the blow-by gas is generated. By using the vent header and purge header for the purpose of venting, the pipe size can be drastically reduced. To quickly convert the purge header for the purpose of venting, the application of an appropriate control method is essential. A simulation was carried out for confirming the efficacy of the pressure control and the processible blow-by gas quantity compared to the existing system. In addition, as the amount of blow-by gas increased, a study on the possibility of installing large pipes used in the existing system configuration and the dual pipes suggested by this proposal was investigated. As a result of the simulation, this proposal presented better results in terms of both the pressure control performance of the cargo tanks and the arrangement of the piping compared to the existing system.

Suggested Citation

  • Soon-kyu Hwang & Byung-gun Jung & Jong-kap Ahn, 2022. "A Novel Proposal for Optimal Performance of Blanket Gas System for FPSOs," Energies, MDPI, vol. 15(18), pages 1-19, September.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:18:p:6820-:d:918034
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/15/18/6820/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/15/18/6820/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Wang, Jue & Zhou, Hao & Hong, Tao & Li, Xiang & Wang, Shouyang, 2020. "A multi-granularity heterogeneous combination approach to crude oil price forecasting," Energy Economics, Elsevier, vol. 91(C).
    2. Allahyarzadeh-Bidgoli, Ali & Salviano, Leandro Oliveira & Dezan, Daniel Jonas & de Oliveira Junior, Silvio & Yanagihara, Jurandir Itizo, 2018. "Energy optimization of an FPSO operating in the Brazilian Pre-salt region," Energy, Elsevier, vol. 164(C), pages 390-399.
    3. Soon-Kyu Hwang & Byung-Gun Jung, 2021. "A Novel Control Strategy on Stable Operation of Fuel Gas Supply System and Re-Liquefaction System for LNG Carriers," Energies, MDPI, vol. 14(24), pages 1-22, December.
    4. Georgi N. Todorov & Andrey I. Vlasov & Elena E. Volkova & Marina A. Osintseva, 2020. "Sustainability in Local Power Supply Systems of Production Facilities Where There Is the Compensatory Use of Renewable Energy Sources," International Journal of Energy Economics and Policy, Econjournals, vol. 10(3), pages 14-23.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Zeng, Sheng & Su, Bin & Zhang, Minglong & Gao, Yuan & Liu, Jun & Luo, Song & Tao, Qingmei, 2021. "Analysis and forecast of China's energy consumption structure," Energy Policy, Elsevier, vol. 159(C).
    2. Hao, Jun & Feng, Qianqian & Yuan, Jiaxin & Sun, Xiaolei & Li, Jianping, 2022. "A dynamic ensemble learning with multi-objective optimization for oil prices prediction," Resources Policy, Elsevier, vol. 79(C).
    3. Jiang, He & Hu, Weiqiang & Xiao, Ling & Dong, Yao, 2022. "A decomposition ensemble based deep learning approach for crude oil price forecasting," Resources Policy, Elsevier, vol. 78(C).
    4. Ma, Xiaojuan & Wu, Xinghong & Wu, Yan & Wang, Yufei, 2023. "Energy system design of offshore natural gas hydrates mining platforms considering multi-period floating wind farm optimization and production profile fluctuation," Energy, Elsevier, vol. 265(C).
    5. Li, Mingchen & Cheng, Zishu & Lin, Wencan & Wei, Yunjie & Wang, Shouyang, 2023. "What can be learned from the historical trend of crude oil prices? An ensemble approach for crude oil price forecasting," Energy Economics, Elsevier, vol. 123(C).
    6. Liu, Mingxi & Li, Guowen & Li, Jianping & Zhu, Xiaoqian & Yao, Yinhong, 2021. "Forecasting the price of Bitcoin using deep learning," Finance Research Letters, Elsevier, vol. 40(C).
    7. Jiangwei Liu & Xiaohong Huang, 2021. "Forecasting Crude Oil Price Using Event Extraction," Papers 2111.09111, arXiv.org.
    8. Hajirahimi, Zahra & Khashei, Mehdi, 2022. "Series Hybridization of Parallel (SHOP) models for time series forecasting," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 596(C).
    9. Wu, Chunying & Wang, Jianzhou & Hao, Yan, 2022. "Deterministic and uncertainty crude oil price forecasting based on outlier detection and modified multi-objective optimization algorithm," Resources Policy, Elsevier, vol. 77(C).
    10. Wadim Strielkowski & Andrey Vlasov & Kirill Selivanov & Konstantin Muraviev & Vadim Shakhnov, 2023. "Prospects and Challenges of the Machine Learning and Data-Driven Methods for the Predictive Analysis of Power Systems: A Review," Energies, MDPI, vol. 16(10), pages 1-31, May.
    11. Li, Ranran & Hu, Yucai & Heng, Jiani & Chen, Xueli, 2021. "A novel multiscale forecasting model for crude oil price time series," Technological Forecasting and Social Change, Elsevier, vol. 173(C).
    12. Butler, Sunil & Kokoszka, Piotr & Miao, Hong & Shang, Han Lin, 2021. "Neural network prediction of crude oil futures using B-splines," Energy Economics, Elsevier, vol. 94(C).
    13. Allahyarzadeh-Bidgoli, Ali & Yanagihara, Jurandir Itizo, 2023. "Energy efficiency, sustainability, and operating cost optimization of an FPSO with CCUS: An innovation in CO2 compression and injection systems," Energy, Elsevier, vol. 267(C).
    14. M. Montañés, Rubén & Hagen, Brede & Deng, Han & Skaugen, Geir & Morin, Nicolas & Andersen, Marius & J. Mazzetti, Marit, 2023. "Design optimization of compact gas turbine and steam combined cycles for combined heat and power production in a FPSO system–A case study," Energy, Elsevier, vol. 282(C).
    15. Liang, Xuedong & Luo, Peng & Li, Xiaoyan & Wang, Xia & Shu, Lingli, 2023. "Crude oil price prediction using deep reinforcement learning," Resources Policy, Elsevier, vol. 81(C).
    16. Huang, Yisu & Xu, Weiju & Huang, Dengshi & Zhao, Chenchen, 2023. "Chinese crude oil futures volatility and sustainability: An uncertainty indices perspective," Resources Policy, Elsevier, vol. 80(C).
    17. Li, Zhuochao & Zhang, Haoran & Meng, Jing & Long, Yin & Yan, Yamin & Li, Meixuan & Huang, Zhongliang & Liang, Yongtu, 2020. "Reducing carbon footprint of deep-sea oil and gas field exploitation by optimization for Floating Production Storage and Offloading," Applied Energy, Elsevier, vol. 261(C).
    18. Allahyarzadeh-Bidgoli, Ali & Dezan, Daniel Jonas & Salviano, Leandro Oliveira & de Oliveira Junior, Silvio & Yanagihara, Jurandir Itizo, 2019. "FPSO fuel consumption and hydrocarbon liquids recovery optimization over the lifetime of a deep-water oil field," Energy, Elsevier, vol. 181(C), pages 927-942.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:15:y:2022:i:18:p:6820-:d:918034. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.