Advanced Integrity Assessment and Identification of Buckled Pipe Using High-Resolution Ultrasound Imaging

Tubing deformation represents a critical challenge for maintaining well integrity, especially in complex operational environments where early detection is vital for safe and efficient production. This study explores the application of high-resolution ultrasound imaging to identify and characterize structural anomalies—such as buckling—within production tubing. By employing a multi-pass inspection approach under varying tension conditions, the method enables precise visualization of internal tubing geometry, supporting a more accurate assessment of well integrity and promoting proactive maintenance practices across onshore and offshore operations. High-resolution ultrasound imaging was deployed via an e-line system to perform detailed, real-time inspections of production tubing. The assessment consisted of two operations: an initial operation with a single-pass scan to identify structural deformations, followed by a second operation involving a more detailed three-pass inspection conducted under increasing weight on hook (tension) values of 454 klbf, 498 klbf, and 546 klbf. Together, the two operations—comprising a total of four full passes—enabled accurate imaging and precise characterization of the tubing's internal geometry under different mechanical loads, providing a realistic evaluation of its structural integrity. The initial single-pass operation identified localized buckling in the 5 ½ in tubing section between 1904 m and 1929 m, while the adjacent 6 5/8 in section from 1870 m to 1904 m remained unaffected. The subsequent operation consisting of three additional passes—conducted under increasing weight on hook—confirmed that the buckling was stable and non-progressive, with no changes detected across the different loading conditions. These combined four passes highlight the capability of high-resolution ultrasound imaging to reliably detect and characterize structural anomalies, even under varying mechanical stresses. The results demonstrate the value of this technology in well integrity assessments, supporting a proactive, data-driven approach to monitoring and maintenance aimed at enhancing operational reliability and reducing risk.