考虑间歇井壁接触的水平煤矿井钻柱动力学模型

IF 0.7 Q4 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Jie Hu, Chengda Lu, Luefeng Chen, Quanxin Li, Wangnian Li, Hongchao Wei, Min Wu
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引用次数: 1

摘要

在钻井过程中,水平钻柱经常出现粘滑和背压现象,破坏钻井安全,影响钻井成本。然而,现有文献中提出的大多数模型仅适用于钻柱运动状态的分析,与煤矿旋转钻井过程无关。本文建立了水平井钻柱的集总质量模型。首先,基于合理的假设,将钻柱系统视为四个集总质量单元。基于拉格朗日动力学理论建立了横向-扭转动力学模型。此外,结合横向移动,描述了钻柱与井壁之间的间歇性接触,并计算了这种间歇性接触引起的摩擦扭矩。结合Karnopp钻头-岩石相互作用,建立了考虑间歇接触摩擦的水平井钻柱动力学模型。所建立的水平井钻柱模型更适合于煤矿旋转钻井,非线性影响因素考虑更全面。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Drill-String Dynamics Model of Horizontal Coal Mine Wells Considering Intermittent Borehole Wall Contact
During the drilling process, horizontal drill strings are often subject to stick-slip and back-pressure phenomena, which undermine drilling safety and affect drilling costs. However, most of the models proposed in the existing literature apply only to the analysis of the drill string motion state and are irrelevant to the rotary drilling process in coal mines. This paper presents a lumped-mass model of a drill string in a horizontal coal mine well. First, based on reasonable assumptions, the drill-string system was considered as four lumped-mass units. The lateral-torsional dynamics model was established based on the Lagrange dynamics theory. Further, combined with lateral movement, the intermittent contact between the drill string and borehole wall is described, and the friction torque due to this intermittent contact is calculated. Combined with the Karnopp bit-rock interaction, a drill-string dynamics model of horizontal wells that considers intermittent contact friction was developed. The proposed horizontal well drill-string model is more suitable for rotary drilling in a coal mine, and the nonlinear influencing factors are considered more comprehensive.
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来源期刊
CiteScore
1.50
自引率
14.30%
发文量
89
期刊介绍: JACIII focuses on advanced computational intelligence and intelligent informatics. The topics include, but are not limited to; Fuzzy logic, Fuzzy control, Neural Networks, GA and Evolutionary Computation, Hybrid Systems, Adaptation and Learning Systems, Distributed Intelligent Systems, Network systems, Multi-media, Human interface, Biologically inspired evolutionary systems, Artificial life, Chaos, Complex systems, Fractals, Robotics, Medical applications, Pattern recognition, Virtual reality, Wavelet analysis, Scientific applications, Industrial applications, and Artistic applications.
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