云边端协同高端钻探装备智能运维体系架构

厉曈曈; 张毅; 雷彪; 张鑫; 汪伟; 赵甜

doi:10.3799/dqkx.2026.024

Volume 51 Issue 8

Aug. 2026

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Article Navigation > Earth Science > 2026 > 51(8): 2940-2950

Li Tongtong, Zhang Yi, Lei Biao, Zhang Xin, Wang Wei, Zhao Tian, 2026. A Cloud-Edge-End Collaborative Architecture for Intelligent Operation and Maintenance of High-End Drilling Equipment. Earth Science, 51(8): 2940-2950. doi: 10.3799/dqkx.2026.024

Citation:

Li Tongtong, Zhang Yi, Lei Biao, Zhang Xin, Wang Wei, Zhao Tian, 2026. A Cloud-Edge-End Collaborative Architecture for Intelligent Operation and Maintenance of High-End Drilling Equipment. Earth Science, 51(8): 2940-2950. doi: 10.3799/dqkx.2026.024

Citation:

Li Tongtong, Zhang Yi, Lei Biao, Zhang Xin, Wang Wei, Zhao Tian, 2026. A Cloud-Edge-End Collaborative Architecture for Intelligent Operation and Maintenance of High-End Drilling Equipment. Earth Science, 51(8): 2940-2950. doi: 10.3799/dqkx.2026.024

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A Cloud-Edge-End Collaborative Architecture for Intelligent Operation and Maintenance of High-End Drilling Equipment

doi: 10.3799/dqkx.2026.024

Li Tongtong^{1
,
,},
Zhang Yi^{1
,
,
,},
Lei Biao²,
Zhang Xin³,
Wang Wei¹,
Zhao Tian¹

1.
State Key Laboratory of Deep Earth and Mineral Exploration, Chinese Academy of Geological Sciences, Beijing 100037, China
2.
Oil & Gas Technology Research Institute, CNPC Qinghai Oilfield, Dunhuang 736202, China
3.
Instrumentation Technology and Economy Institute, Beijing 100055, China

Received Date: 2026-01-09
Publish Date: 2026-08-25

Abstract

Abstract

To improve the safe and reliable operation of deep drilling equipment under extreme working conditions, this study focuses on high-end drilling equipment that integrates automated execution, digital control, multi-source sensing, and high-reliability design. A cloud-edge-end collaborative intelligent operation and maintenance (O&M) architecture is developed. The proposed architecture consists of four modules, namely the drilling equipment module, the data acquisition module, the intelligent O&M module, and the digital twin module. A data workflow based on MQTT and Kafka is designed. A data modeling strategy is established through hierarchical topic classification and message schema specification. An edge-side feature reporting mechanism and a cloud-side on-demand data acquisition mechanism are further introduced to cope with network conditions characterized by low bandwidth, high latency, and intermittent connectivity. The architecture supports multi-source data access, unified deployment across multiple drilling sites, and remote visualization and interaction. It meets the requirements of equipment condition monitoring, fault diagnosis, and predictive maintenance, and provides a systematic reference for the design and implementation of intelligent O&M platforms for high-end drilling equipment.
- drilling,
- intelligent operation and maintenance (O&M),
- cloud-edge-end collaboration,
- virtual-physical fusion,
- deep drilling equipment,
- predictive maintenance

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References(36)

References

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