石油科技论坛 ›› 2020, Vol. 39 ›› Issue (5): 16-23.DOI: 10.3969/j.issn.1002-302x.2020.05.003

• 专题策划 • 上一篇    下一篇

海上智能油田建设研究

陈溯1 安鹏2 吴刚1 张羽2   

  1. 1.中国海洋石油集团有限公司科技信息部;2.中国海洋石油集团有限公司信息技术中心
  • 出版日期:2020-11-25 发布日期:2020-11-25
  • 基金资助:
    中海石油(中国)有限公司前期研究项目“中国海油智能油田滚动规划编制”(编号:2019588)。

Research on Offshore Intelligent Oilfield Construction

Chen Su1, An Peng2,Wu Gang1,Zhang Yu2   

  1. 1. CNOOC Science & Information Technology Department, Beijing 100010, China; 2. CNOOC Information Technology Center, Beijing 100010, China
  • Online:2020-11-25 Published:2020-11-25
  • Supported by:
     

摘要: 在全球经济下行和油价持续低迷的挑战下,数字化转型成为石油公司保持行业竞争力、实现高质量发展的重要举措。研究分析了国内外智能油田建设现状,其中,BP公司的未来油田和壳牌公司的智能油田是建设的先行者,鲁迈拉油田、雷普索尔公司、诺布尔钻井公司及中国石油、中国石化、中国海油等,在探索符合自身特点的智能油田建设、转型增效中见到成效。智能油田正在向跨界合作的建设模式、一体化的运营模式、平台化的IT服务模式转变。中国海油的海上智能油田建设以勘探、开发、生产、钻井、工程和研究等核心业务智能化为重点,通过管理转变和流程优化,在基础服务、全面感知、整体协同、科学决策、自主优化5个方面取得成果,提出了“一个平台、一湖数据、两套体系、三级组织、四类应用”的下一步建设思路。

 

关键词: 智能油田, 海洋石油, 数字化转型, 信息化

Abstract: Under the challenges from global economic slide and the continuous low oil prices, digital transformation becomes an important measure for petroleum companies to maintain business competitiveness and bring about high-quality development. This paper studies and analyzes the present conditions of intelligent oilfield construction both in and outside China. The forerunners of intelligent oilfield construction include BP’s Field of the Future and Shell’s Smart Fields. In addition, Rumaila Oilfield, Repsol YPF, Noble Drilling Company, CNPC, Sinopec and CNOOC are also constructing intelligent oilfields in the light of their respective characteristics and achieving results in the efforts for efficiency-boosting transformation. Intelligent oilfields are in the transition to cross-disciplinary cooperative construction pattern, integrated operational pattern and platform-based IT service pattern. Offshore intelligent oilfields constructed by CNOOC are focused on intelligence of the company’s core business -- exploration, development, production, drilling, engineering and research work. Based on management transformation and process optimization, the achievements were made in the five areas of basic service, full sensing, overall coordination, scientific decision making and independent optimization. This paper puts forth the mindset for further construction of intelligent oilfields, namely “one platform, one lake of data, two sets of systems, organization at three levels and four classes of application”.

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