摘要
近年来人工智能技术发展迅猛,给各个行业都带来了前所未有的变革和机遇。人工智能技术在石油工业领域也得到了广泛的应用,尤其对石油井控培训的影响非常巨大。目前国内井控培训还是采用传统的培训方式,缺乏多样性和互动性。为了提升培训效果和培训质量,该文介绍了人工智能等技术在国内外井控培训领域的应用。通过人工智能技术和井控培训的融合,发挥人工智能技术的优势,改变目前的授课模式,并激发学员的互动性。同时针对现状,该文也列举了目前遇到技术融合难、如何保障数据隐私与安全、培训成本与投资回报等问题和挑战。最后该文前瞻性地阐述了在大模型时代,石油企业井控培训的发展方向是建立井控培训大模型人工智能体,开发智能化井控培训系统,打造因材施教的井控人才培养及管理平台,并且要主动探索人工智能技术,创新教学模式,为海上油气勘探开发的安全生产提供坚实保障,为国家能源生产安全贡献力量。
In recent years,the rapid development of artificial intelligence technology has brought unprecedented changes and opportunities to various industries.Artificial intelligence technology has also been widely used in the petroleum industry,especially for oil well control training.However,domestic well control training still adopts traditional training methods which lacks diversity and interactivity.In order to improve the training effect and training quality,this paper introduces the application of artificial intelligence and other technologies in the field of well control training at home and abroad.Through the integration of artificial intelligence technology and well control training,the advantages of artificial intelligence technology will be utilized to change the current mode of instruction and stimulate trainees interaction.At the same time,in response to the current situation,this article also lists the difficulties encountered in technology integration,how to ensure data privacy and security,training costs and investment returns,and other issues and challenges.Finally,this paper prospectively expounds that in the era of large model,the development direction of well control training in petroleum enterprises is to establish a large model artificial intelligence body for well control training,develop an intelligent well control training system,build a well control talent training and management platform for teaching trainees according to their aptitude,and actively embrace artificial intelligence technology,innovate teaching mode,provide a solid guarantee for the safe production of offshore oil and gas exploration and development,and contribute to the safety of national energy production.
作者
王哲
郑伟
杨欣雨
张帅
刘力宾
WANG Zhe;ZHENG Wei;YANG Xinyu;ZHANG Shuai;LIU Libin(CNOOC EnerTech-Drilling&Production Co.,Tianjin 300452,China)
出处
《海洋石油》
2025年第1期94-97,101,共5页
Offshore Oil
关键词
人工智能
井控培训
虚拟仿真
大模型
artificial intelligence
well control training
virtual simulation
large model
