马立军,黄战卫,贾志鹏,等. 新质生产力驱动下的庆城页岩油数智油田开发关键技术与实践[J]. 石油钻采工艺,2026,48(4):551-561. DOI: 10.13639/j.odpt.202510022
引用本文: 马立军,黄战卫,贾志鹏,等. 新质生产力驱动下的庆城页岩油数智油田开发关键技术与实践[J]. 石油钻采工艺,2026,48(4):551-561. DOI: 10.13639/j.odpt.202510022
MA Lijun, HUANG Zhanwei, JIA Zhipeng, et al. Key technologies and practices of a digital-intelligent oilfield development of Qingcheng shale oil driven by new quality productive forces[J]. Oil Drilling & Production Technology, 2026, 48(4): 551-561. DOI: 10.13639/j.odpt.202510022
Citation: MA Lijun, HUANG Zhanwei, JIA Zhipeng, et al. Key technologies and practices of a digital-intelligent oilfield development of Qingcheng shale oil driven by new quality productive forces[J]. Oil Drilling & Production Technology, 2026, 48(4): 551-561. DOI: 10.13639/j.odpt.202510022

新质生产力驱动下的庆城页岩油数智油田开发关键技术与实践

Key technologies and practices of a digital-intelligent oilfield development of Qingcheng shale oil driven by new quality productive forces

  • 摘要: 针对鄂尔多斯盆地庆城页岩油储层埋藏深、地质条件复杂、开发效率低、安全管控难度大等行业技术瓶颈,以培育新质生产力为导向,融合人工智能、物联网、云计算与大模型等新一代信息技术,首创性构建了页岩油数智化开发“416”技术管理体系。该体系以智能感知、高可靠工业网络、全域数据治理、工控安全加密等四项技术保障为底层支撑,以全生命周期物联网云平台为核心中台,以现场作业智能操控、技术管理智能分析、生产运行智能管控、经营办公智能协同、安全环保智能预警、绿色低碳智能管控等六大核心业务场景为落地载体,实现了页岩油开发全流程、全要素的数字化重塑。现场应用结果表明:该体系使庆城页岩油生产现场实现100%数字化覆盖率,油藏动态分析效率提升30%,热洗管理效率提升60%,联合站人员配置降低85%,页岩油完全成本降至47.7美元/桶,百万吨用工控制在200人以内(为常规油田的1/10)。该体系支撑建成国内首个200万吨级页岩油开发示范基地,为我国页岩油规模效益开发提供了可复制、可推广的技术范式。

     

    Abstract: To address the technical challenges featured as deep burial depth, complex geological conditions, low development efficiency, and high difficulty in safety management in Qingcheng shale oil reservoirs in the Ordos Basin, guided by the goal of cultivating new quality productive forces, this study integrates new-generation of information technologies including artificial intelligence, Internet of Things, cloud computing, and large models to innovatively establish a "416" technology management system for digital-intelligent development of shale oil. This system is based on four technical guarantees covering intelligent perception, highly reliable industrial networks, all-domain data governance, and industrial control security encryption as its underlying foundation. It uses a full lifecycle Internet of Things cloud platform as its core middle platform, and six core business scenarios such as intelligent on-site operation control, intelligent analysis of technical management, intelligent control of production and operation, intelligent collaboration of business and office management, intelligent early warning of safety and environmental protection, and intelligent control of green and low-carbon development as its implementation carriers. It has achieved digital transformation of the entire process and all elements of shale oil development. On-site application results show that this system enables the production site in Qingcheng shale oil to achieve a 100% digital coverage, improves the reservoir performance analysis efficiency by 30%, enhances the efficiency of thermal cleaning by 60%, reduces the staffing of joint stations by 85%, and lowers the total cost of shale oil to 47.7 USD/bbl, with the workforce per million tons controlled within 200 personnel (one-tenth of that of conventional oil fields). This system supports the establishment of China's first 2-million-ton shale oil development demonstration base, providing a replicable and scalable technical model for the large-scale and efficient development of shale oil in China.

     

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