As Stress Corrosion Cracking (SCC) and other cracking related issues become a more recognised hazard or threat that can be monitored by in-line inspection (ILI), there have been high expectations for the pipeline inspection industry to produce a reliable solution for identifying and sizing cracks. The current leading ILI technologies provided for pipeline crack detection are Ultrasonic (UT) and Electromagnetic Acoustic Transducer (EMAT). The introduction of EMAT In-Line Inspection technologies has provided a proven solution for crack detection that can be used in gas pipelines without having to introduce a liquid couplant into the pipeline.

With the development of these technologies worldwide pipeline regulators are putting more pressure on the industry to monitor integrity issues relating to cracking. For example USA pipeline operators are required by the Office of Pipeline Safety to inspect and assess their pipelines that operate within high consequence areas for integrity issues, such as SCC, and repair or replace affected pipe. The inspection options for this include the use of Inline inspection tools — “smart pigs”. These regulations in combination with the majority of pipeline incidents relating to SCC occurring in gas pipelines have led to a significant increase in the use of EMAT ILI technology in recent years.

With repeat EMAT ILIs now being conducted on some pipelines there is the option to compare data sets to identify any changes between inspections. Due to the complexities of the EMAT measurement principle and the volumes of data recorded, the process of directly comparing raw signal data from two runs is still in its infancy and cannot currently be used to confirm or discount evidence of crack growth, such as the industry has seen with estimation of corrosion growth based on Magnetic Flux Leakage (MFL) technology signal comparison. However the comparison of EMAT data sets can aid the identification of crack initiation. This technical paper presents a method for identifying the initiation of crack growth (the development of newly detectable cracks) based on repeat EMAT ILI, using feature matching and comparison of raw EMAT inspection data. The implications for integrity management of the identification of newly detectable SCC are discussed, and possible future improvements are outlined. The paper includes a case study that illustrates some of the issues.

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