Ocean Engineering Equipment and Technology ›› 2025, Vol. 12 ›› Issue (2): 31-34.doi: 10.12087/oeet.2095-7297.2025.02.07

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Research on the Development of Artificial Intelligence-Assisted System for FPSO Equipment Maintenance

WU Bin, SHI Yabo, JIANG Chunqi   

  1. Oil Production Service Shenzhen Branch, CNOOC Energy Technology & Services Limited, Shenzhen 518054, Guangdong, China
  • Online:2025-06-05 Published:2025-07-12

Abstract: Floating production storage offloading (FPSO) plays a crucial role in the offshore oil industry, and the stable operation of FPSO equipment is directly related to production safety. However, its equipment has been in a complex marine environment for a long time, far away from land and without external technical support for a short period of time. Maintenance personnel rely entirely on their own knowledge reserves and experience to carry out equipment maintenance, and its maintenance work faces many challenges. Based on the characteristics and requirements of FPSO equipment maintenance, combined with the current development status of artificial intelligence technology, we will conduct in-depth research and development of an artificial intelligence assisted system for FPSO equipment maintenance. The system aims to improve maintenance efficiency, reduce costs, ensure safe and stable operation of equipment, and promote the intelligent development of FPSO through modules such as data collection, fault diagnosis, repair plan recommendation, predictive maintenance, and knowledge management.

Key words: FPSO, artificial intelligence, data collection, fault diagnosis, maintenance plan, intelligent assistant

CLC Number: