Ultrasonic NDE Technology Comparison for Measurement of Long Seam Weld Anomalies in Low Frequency Electric Resistance Welded Pipe

In the pipeline industry, a widely accepted methodology for integrity crack management involves running ultrasonic In-Line Inspection (ILI) technologies. After an ILI tool run is completed, the performance of the tool is typically validated by excavating the pipeline and conducting in-the-ditch investigations. Ultrasonic Non-Destructive Evaluation (NDE) techniques are used in the field to characterize and measure crack-like features. These in-the-ditch measurements are compared back to ILI results in order to validate tool performance and drive continuous technology improvements. Since validation of the ILI tool relies on NDE measurements, acquiring accurate and representative data in the field is a critical step in this integrity crack management approach. Achieving an accurate field inspection comes with its challenges, some of which relate to complex long seam weld conditions present in older vintage pipelines including: weld misalignment, weld trim issues, and dense populations of manufacturing anomalies. In order to better understand the challenges associated with complex long seam weld conditions, an evaluation and comparison of the performance of NDE technologies currently available was conducted. In this study, a portion of a Canadian pipeline with complex long seam weld conditions was cut-out and removed from service. Multiple NDE crack inspection technologies and methods from three different vendors were used to assess the condition of the long seam weld. Conventional Ultrasonic Testing (UT), Phased Array Ultrasonic Testing (PAUT), Time of Flight Diffraction (TOFD), and variations of Full Matrix Capture Ultrasonic Testing (FMCUT) were used to assess the long seam weld and their results were compared. The performance of all NDE technologies is baselined by comparing them with destructive examination of sections of the long seam weld. The newer NDE assessment methodologies were shown to be consistently more accurate in characterizing long seam features.