Steel Coiled Tubing Defect Evaluation Using Magnetic Flux Leakage Signals

Abstract

AbstractMechanical defects, such as manufacturing imperfections, grinding marks, corrosion pits, slip marks, kinking, gouges, etc, whether occurred in the factory or in the field, can be readily found on CT strings. Extensive studies have demonstrated the detrimental effects of mechanical defects, over the integrity of the coiled tubing, both in the lab and in the field. Researchers in the field have been proposing theoretical models for the severity assessment of mechanical defects, particularly as it relates to the remaining fatigue life. For such models, the defect sizing is usually a prerequisite. In order to improve coiled tubing pipe management, it is important to assess the size of a defect, and its severity.MFL (magnetic flux leakage) based devices are volumetric and non-contact technology that is now commercially available for inspection and monitoring of CT strings. These devices have been demonstrated to be sufficiently sensitive in identifying mechanical defects. However, defect characterization and evaluation based on the devices’ MFL signals is rarely seen. To fully utilize these MFL based inspection devices for coiled tubing pipe management, it is important to establish correlation between the MFL inspection signals and the geometry and severity of the underlying mechanical defects.The current work developed a three dimensional Finite Element Analysis (FEA) model to calculate magnetic flux leakage for mechanical defects on steel coiled tubing. The fidelity of the FEA model was verified against analytical and experimental results over a series of benchmark defects. By using the analytical and FEA models, parametric studies were performed to evaluate how the MFL signals are affected by various factors. The results were used to identify defect geometry features based on MFL signals. Physical limits behind these results were identified and analyzed. Ways to overcome such limits were proposed. Further, a novel approach was presented and validated to reconstruct three-dimensional MFL field based on a single MFL component measurement. The benefit of using multiple MFL components was demonstrated for defect characterization.