Research and Practice of CNOOC AI Application

doi:10.3969/j.issn.1002-302x.2023.03.003

Abstract

Abstract: Digital transformation is becoming an important driving force for modernization and high-quality development of oil and gas enterprises. The application scenarios for integration of artificial intelligence with oil and gas business is increasingly expanded with the application value gradually highlighted. AI application is currently tried by major oil and gas enterprises all over the world. The development trend has three characteristics – data drive, cross-disciplinary cooperation and gradual maturity. The AI construction of CNOOC has experienced two stages of application research and unified acceleration. The application research stage started from 2019 with AI application research focusing on maintenance of prediction, optimization of process, safety and early warning and awareness analysis. The technological application prospect and value were shown in a number of scenarios. However, some problems were also found in this area, such as a high threshold for development, low development efficiency, waste of calculation resources, and difficult model management. The unified acceleration stage entered into 2020. CNOOC identified the development scenarios, formulated the AI construction plan and steadily made acceleration in stages, achieving a series of results for infrastructure construction and pilot construction of AI application. Construction of the petroleum industrial AI application should be based fully on the oil business demands and continual accumulations of resources, technology and talents, while highlighting five areas of value guidance, data security, higher efficiency of platform, deregulation and cooperation, and security of talents.

Key words: petroleum and petrochemicals, digital transformation, AI, CNOOC

摘要： 数字化转型正在成为油气企业转型升级、高质量发展的重要推动力，人工智能和油气业务的融合应用场景不断拓展，应用价值逐渐凸显。全球主要油气生产企业目前均已开展人工智能试点应用，发展趋势呈现数据驱动、跨界合作、渐趋成熟3方面特征。中国海油的人工智能建设经历了应用探索和统筹推进两个时期。自2019年开始应用探索期，围绕预测维护、过程优化、安全预警、认知分析方面开展人工智能应用探索，在多个场景中展现了技术应用前景和价值，也暴露出开发门槛高、开发效率低、算力资源浪费、模型管理难等问题。2020年进入统筹推进期，中国海油明确发展愿景，制定人工智能建设规划，分阶段稳步推进，在基础设施建设、人工智能应用试点建设中取得系列成果。石油行业人工智能应用建设应充分基于石油业务需求，在资源、技术、人才等方面持续积累，重点关注价值导向、数据保障、平台提效、开放合作和人才保障5个方面。

关键词: 石油石化；数字化转型；人工智能；中国海油

CLC Number:

Xie Xiaohui, An Peng. Research and Practice of CNOOC AI Application[J]. Petroleum Science and Technology Forum, 2023, 42(3): 22-29.

谢晓辉　安鹏. 中国海油人工智能建设探索与实践[J]. 石油科技论坛, 2023, 42(3): 22-29.

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