Abstract

Current coiled tubing (CT) inspection technology is based predominantly on magnetic flux leakage (MFL). This approach is useful for detecting flaws on both the outer and inner surface of tubing. However, MFL is currently incapable of consistently providing information about the geometry of the flaw, which is adequate to assess its influence on fatigue endurance.

The use of 3D laser imaging has demonstrated the potential to detect flaws, but more importantly, to completely characterize their geometry. With the full three-dimensional mapping of the defect surface, critical defect parameters can be computed. For example, the system provides immediate information about the depth, length, width and projected surface area with a high degree of accuracy. Additionally, other features can be extracted from the laser images, including the volume of the defect and the notch root radius, which could be used to refine quantitative estimates of the flaw's severity.

Promising results from prototype systems are presented. A CT specific tool is being developed to scan known defects, detected visually or with existing inspection technology, and compute their influence on remaining fatigue life. This could serve as the basis for the development of stand-alone laser-based CT inspection systems. Additionally, a system has been developed that is capable of passing through coiled tubing in order to characterize flaws on its inner surface.

Background

Mechanical imperfections on the surface of CT are unfortunately inevitable. Surface flaws can have a detrimental impact on the fatigue life of CT and have thus been the focus of considerable research (Tipton 1998). Through these efforts, analytical models have been developed to quantify the influence of surface defects on CT life.

Current techniques to assess the influence of a defect require not only knowledge of a defect's depth, width and length, but also its shape and how it was imposed. For example, three "defects" are shown in Fig. 1 that have the same depth, width and length, but each has a different shape and a different influence on fatigue life. The "shape" parameter used to model this influence is the projected surface area on a cross sectional plane (Murakami 1983, 1984, Tipton 2002), also illustrated in Fig. 1.

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