摘要
在全球能源消费总量以年均2.3%增速攀升、工业数字化转型指数突破150的双重背景下,油田勘探开发正面临数据量级呈指数级增长的严峻挑战。文章聚焦大模型Agent技术,揭示该技术如何通过多模态数据融合算法提升跨域数据关联效率40%,通过动态调度为智慧油田建设提供可量化的技术参照体系。
In the dual context of global energy consumption rising at an average annual growth rate of 2.3%and the industrial digital transformation index exceeding 150,oilfield exploration and development is facing the severe challenge of exponential expansion of data volume.The article focuses on large model Agent technology,revealing how this technology can enhance cross-domain data association efficiency by 40%through multimodal data fusion algorithms,and provide a quantifiable technical reference system for the construction of smart oilfields through dynamic scheduling.
作者
戎昊
RONG Hao(Daqing Oilfield Digital Technology Company,Daqing Heilongjiang 163000,China)
出处
《信息与电脑》
2025年第20期57-59,共3页
Information & Computer
关键词
大模型Agent
油田勘探开发
数据汇总
large model Agent
oilfield exploration and development
data summary
