School of Automаtion, Chinа University of Geosciences
Hubei Key Lаborаtory of Advаnced Control аnd Intelligent Automаtion for Complex Systems
Engineering Reseаrch Center of Intelligent Technology for Geo-Explorаtion, Ministry of Educаtion

复杂多变的地质环境和恶劣的施工条件给地质钻进过程控制提出了巨大挑战，大数据、人工智能等前沿技术的蓬勃发展给钻探行业带来了全新的发展机遇。首先，从钻进过程感知与建模、钻进过程智能优化与钻进过程控制3个方面阐述地质钻进过程智能控制的国内外发展现状。在钻进过程感知与建模方面，利用多源钻进过程信息，建立地质环境模型，实现地质环境变化和钻进过程状态的感知，基于钻进信息特征进行故障诊断和预警；在钻进过程智能优化方面，建立钻速预测模型，提出适合地质钻进过程的钻速优化算法，面向多样约束条件和优化指标探索最优钻进轨迹的设计；在钻进过程控制方面，通过建立钻柱、钻进轨迹、钻井液循环模型，设计控制器来调整钻压、转速、泵量等操作参数，保障钻进过程的安全高效。其次，论述了地质钻进过程智能控制系统及其工程应用情况。最后，展望了未来需要攻克的基于工业物联网的信息物理融合与钻进过程智能控制技术，包括多目标和高维约束的优化决策与控制一体化技术以及融合大数据、云边协同技术的网络化智能管控，从而提升地质钻进这类复杂工业系统的感知深度、综合调度和全局优化能力。随着新一轮找矿突破战略行动的开展，需加快推进人工智能、新一代信息技术与地质钻探相关工艺、理论方法和技术的深度融合，突破地质钻进过程智能控制的关键科学问题，研发先进的智能地质装备，为资源勘探和开发提供技术支撑。

The complex and ever-changing geological environment and harsh conditions pose enormous challenges to the control of geological drilling process. The flourishing development of frontier technologies such as big data and artificial intelligence has brought new opportunities to the development of drilling industry. Firstly, the development status of intelligent control of geological drilling process is elaborated from 3 aspects: Sensing and modelling of drilling process, intelligent optimization of drilling process and drilling process control. In terms of sensing and modelling of drilling process, various geological environment models have been established using multi-source information of drilling process, which enables the sensing of geological environment change and drilling process status, achieving fault diagnosis and early warning based on drilling information characteristics. In terms of intelligent optimization of drilling process, many prediction models of rate-of-penetration (ROP) have been established and ROP optimization algorithms have been developed for geological drilling process; facing various constraint conditions and optimization indicators, the design of optimal drilling trajectory has been investigated. In terms of drilling process control, the models of drill-string, drilling trajectory and drilling fluid circulation have been established, and suitable controllers have been put forward to adjust the operating parameters such as weight-on-bit, rotational speed and pumping volume to ensure the safety and efficiency of drilling process. Secondly, the intelligent control system for geological drilling process and its engineering applications are discussed. Finally, the future of cyber-physics fusion and intelligent control technology of drilling process based on industrial Internet of Things is envisioned, including the integrated technology of optimal decision-making and control with multi-objectives and high-dimensional constraints, and the networked intelligent management and control blending big data and cloud-edge collaborative technology, to enhance the sensation depth, comprehensive scheduling and global optimization capabilities of complex industrial systems like geological drilling. With the launch of a new round of National Exploration and Development Plan, it is urgent to promote the deep integration of artificial intelligence, new generation information technology and geological drilling related theoretical methods and technologies, to break through the key scientific problems of intelligent control of geological drilling process and develop advanced intelligent geological equipment, providing technical support for resource exploration and development.

国家自然科学基金项目(62003317，62273317)；武汉市知识创新专项曙光计划项目(2022010801020213)；教育部高等学校学科创新引智计划项目(B17040)

陆承达，甘超，陈略峰，等. 地质钻进过程智能控制研究进展与发展前景[J]. 煤田地质与勘探，2023，51(9)：31−43.

LU Chengda，GAN Chao，CHEN Luefeng，et al. Development and prospect of intelligent control of geological drilling process[J]. Coal Geology & Exploration，2023，51(9)：31−43.