智能钻井技术在复杂构造地层中的适应性改进及效能提升

艾波 ,  刘锐

工程研究前沿 ›› 2026, Vol. 3 ›› Issue (1) : 37 -39.

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工程研究前沿 ›› 2026, Vol. 3 ›› Issue (1) : 37 -39. DOI: 10.12349/foer.v3i1.9092

智能钻井技术在复杂构造地层中的适应性改进及效能提升

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Adaptive improvement and efficiency enhancement of intelligent drilling technology in complex-structured strata

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摘要

此次研究针对油气勘探开发向深层复杂构造地层拓展时所引发的钻井效率与安全难题,围绕智能钻井技术体系的适应性优化,整合高精度随钻测量、智能导向控制及自适应井壁稳定等核心技术,融入基于机器学习的实时决策优化算法进行研究。通过研究分析,此效能提升策略能够大幅增强了该技术体系在断层、高陡构造、盐膏层及破碎带等复杂地质环境中的适配能力,通过优化钻进参数配置、实现风险超前预警及智能化导向控制,达成了工程作业效率与经济效益的协同提升。此次研究旨在为智能钻井技术在复杂地质场景下规模化推广应用,提供切实可行的技术改进方案与效能验证依据。

Abstract

This study focuses on the challenges of drilling efficiency and safety that arise when oil and gas exploration and development expand into deep and complex strata. It centers on the adaptive optimization of the intelligent drilling technology system, integrating core technologies such as high-precision measurement-while-drilling, intelligent guidance control, and adaptive wellbore stability, and incorporating real-time decision optimization algorithms based on machine learning for research. Through research and analysis, this efficiency improvement strategy has significantly enhanced the adaptability of the technical system in complex geological environments such as faults, high and steep structures, salt-gypsum layers, and fracture zones. By optimizing the configuration of drilling parameters, achieving advanced risk early warning, and intelligent guidance control, a coordinated improvement in engineering operation efficiency and economic benefits has been achieved. This research aims to provide practical and feasible technical improvement plans and performance verification basis for the large-scale promotion and application of intelligent drilling technology in complex geological scenarios.

关键词

智能钻井技术 / 复杂构造底层 / 随钻测量 / 自适应控制

Key words

Intelligent Drilling technology / Complex structural bottom layer / Measurement while drilling / Adaptive control

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艾波,刘锐. 智能钻井技术在复杂构造地层中的适应性改进及效能提升[J]. 工程研究前沿, 2026, 3(1): 37-39 DOI:10.12349/foer.v3i1.9092

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参考文献

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