【摘要】 随着油气田开发规模扩大及老井修复需求增长，井下油套管切割技术成为解决管柱遇卡、恢复生产的关键手段。传统切割技术（如聚能爆炸、化学腐蚀等）存在作业可控性弱、实时状态反馈不及时、作业时效长等问题。通过对比分析国内外技术参数，结合现场技术需求、工况和作业工艺，研制了一套针对■油管的智能电动切割系统，该系统由井下电动切割仪器、地面电源通信控制箱和切割工具控制软件3部分组成。重点从切割力学原理出发，计算出切割不同材质油管需要的切割力和切割力矩，确定了切割电机、减速结构、切割深度等关键技术参数，集成锚定模块、多传感器智能监控单元和电缆遥传单元，完成了井下电动切割仪器的设计与制造。还开发了可显示井下仪器实时状态参数的智能控制软件，形成了智能电动油管切割系统。现场试验表明：该套系统可实现切割状态精准控制，顺利完成了切割任务，同时对作业数据进行了完整存储。本设计研发的智能电动油管切割器为智能修井工具研发提供了重要技术范式与工程实践参考。更多还原

【Abstract】 With the expansion of oil and gas field development and the growing demand for well intervention in aging wells, downhole tubing and casing cutting technology has become a key solution for addressing stuck pipes and restoring production. Traditional non-electromechanical cutting methods, such as shaped charge explosion and chemical corrosion, are gradually being replaced by safer and more efficient electromechanical cutting technologies due to safety risks and poor operational controllability. Given the early-stage development of domestic downhole electric cutting tools and the current monopoly of foreign technologies, this study independently developed an intelligent downhole electric tubing cutting system particularly suitable for ■ tubing. Through comparative analysis of domestic and international technical parameters, an innovative structural system was integrated, including an anchoring module, a high-torque power drive system, and a multi-sensor intelligent monitoring unit. Key breakthroughs were made in critical technologies such as insufficient load capacity of the spindle motor and the design of cutting blades. Experimental results demonstrate that the tool, by incorporating multi-sensor real-time monitoring technology, achieves precise control of the cutting process, dynamic compensation of operational parameters, and complete storage of operation data. Field tests verified its reliability and adaptability in complex well conditions. The developed intelligent electric tubing cutter provides an important technical paradigm and engineering reference for the research and development of intelligent well work over tools.更多还原