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The Use of Finite-Element-Calculated Magnetic-Flux-Leakage Signals To Study the Characterization of Defects in Steel Coiled Tubing

机译:利用有限元计算的漏磁信号研究钢卷管缺陷的特征

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A primary consideration with coiled tubing (CT) is that it is consumed by fatigue loading during routine operations. Also, rugged oilfield conditions routinely lead to corrosion and other mechanical surface damage. Since fatigue is a surface phenomenon, the presence of a surface imperfection has a significant influence on fatigue-damage mechanisms. This paper describes the study of magnetic-flux-leakage (MFL) inspection signals caused by surface defects in the form of milled circumferential grooves in steel CT. The focus of the investigation is to identify and estimate the size of surface defects on the basis of characteristic MFL signal features. It is demonstrated that this effort is greatly enhanced by finite-element analysis (FEA). The ultimate objective is to extract surface-flaw dimensions accurately from conventional MFL signals. These dimensions are used in computer CT life-prediction models. An axisymmetric FEA model is developed and used to calculate leakage flux density solutions for milled circular and rectangular shaped grooves in 1.75-in.-outside-diameter (OD), 0.156-in.-wall-thickness (WT), 90-ksi CT samples. FEA results are compared to axial and radial MFL signals measured with an experimental inspection unit. Favorable agreement is observed between experimental and FEA data. Furthermore, signal features are correlated with the known slot geometries to identify basic geometry-recognition patterns for different circumferential grooves. Signal features reveal qualitative and quantitative trends relative to surface-flaw dimensional characteristics. The need persists to make the operator's string-management decision-making process more reliable and automatic with respect to determining fatigue life expectancy. The obstacle here is that because of the inherent inaccuracies in commonly used MFL inspection techniques, reliable real-time flaw-evaluation and -characterization capability is limited.
机译:连续油管(CT)的主要考虑因素是在常规操作过程中疲劳负荷会消耗它。同样,崎ged的油田条件通常会导致腐蚀和其他机械表面损坏。由于疲劳是一种表面现象,因此表面缺陷的存在会对疲劳损伤机理产生重大影响。本文介绍了由钢CT中铣削的圆周槽形式的表面缺陷引起的磁通量泄漏(MFL)检查信号的研究。研究的重点是基于特征性MFL信号特征来识别和估计表面缺陷的大小。结果表明,有限元分析(FEA)大大提高了这种效果。最终目的是从常规MFL信号中准确提取表面缺陷尺寸。这些尺寸用于计算机CT寿命预测模型中。建立了轴对称的有限元分析模型,用于计算外径为1.75英寸(壁厚),壁厚为(厚度)0.156英寸(WT),90 ksi CT的铣削圆形和矩形凹槽的漏磁通密度解样品。将FEA结果与使用实验检查装置测量的轴向和径向MFL信号进行比较。实验和FEA数据之间观察到良好的一致性。此外,信号特征与已知的缝隙几何形状相关,以识别用于不同圆周凹槽的基本几何形状识别图案。信号特征揭示了相对于表面缺陷尺寸特征的定性和定量趋势。持续需要使操作者的弦线管理决策过程在确定疲劳寿命方面更加可靠和自动化。这里的障碍是,由于常用的MFL检查技术固有的不准确性,可靠的实时缺陷评估和表征能力受到限制。

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