国际石油经济2025，Vol.33Issue(5)：10-18,9.DOI:10.3969/j.issn.1004-7298.2025.05.002
油气人工智能技术发展综述与体系框架构想
Review of AI technology development in oil and gas fields and framework architecture conceptualization
摘要
Abstract
The application of AI in oil and gas fields is accelerating the energy sector's digital transformation.The technological evolution has progressed through three distinct phases.The initial phase features single-point intelligence applications focused on specific business link or scenarios and applied lightweight and modular solutions through AI implementations,which validates technological feasibility and whose technologies are intelligent image recognition,intelligent data prediction,and knowledge graph implementations.The subsequent phase establishes intelligent platforms by integrating critical components knowledge,data,algorithmic,computing power,and application scenarios,provides full-stack AI development ecosystems,achieves a close loop from date integration,data labeling,algorithm workshop,and model deployment to inference implementations,enhancing large-scale operational deployment capabilities.The current phase is characterized by specialized oil and gas great foundation models built on Transformer architecture and realizes a breakthrough from AI tools to cognitive collaborators by Utilizing"pre-training+fine-tuning"technologies adaptable to multiple business scenarios.At present,the oil and gas AI ecosystem comprises coordinated developments across such four key dimensions as computer vision systems,predictive analytics,knowledge graph technology,AI development platforms,and domain-specific great foundation models.Future advancements will focus on developing intelligent autonomous systems that integrate sensing,decision-making,and execution capabilities,which helps to achieve an autonomous closed-loop from planning to execution and solve specific complex problems in oil and gas professional fields.关键词
油气人工智能/智能图像识别/油气数据预测/油气智能平台/油气大模型/油气智能体Key words
oil and gas artificial intelligence/intelligent image recognition/oil and gas data prediction/oil and gas intelligent platform/oil and gas large-scale model/oil and gas agent分类
能源科技引用本文复制引用
李欣,王洪亮,闫林,李小波,刘俊榜,邵艳伟,李宁,姚尚林,任义丽..油气人工智能技术发展综述与体系框架构想[J].国际石油经济,2025,33(5):10-18,9.基金项目
中国石油天然气股份有限公司科技项目"油气勘探开发人工智能关键技术研究"(2023DJ84) （2023DJ84）
