Evaluating Pipeline Integrity Using ILI Mapping Data
Proceedings Publication Date
Presenter
Ian Murray
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Author
Ian Murray, Jane Dawson
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Abstract
Running an IMU (Inertial Mapping Unit) tool as part of an in-line inspection (ILI) survey is becoming routine practice for many pipeline operators. The IMU provides a synchronized stream of mapping information which aligned to the ILI data provides the means to accurately and easily locate pipeline anomalies, features and fittings. The mapping information can be further used in the determination of the out-of-straightness indicating potential deviation from the pipelines’ original position. In addition the data collected by the IMU can also be used to determine equivalent bending strains along the pipeline. When the bending strain information is combined with the anomaly data collected by other ILI sensors (ovalities, dents, buckles, girth or spiral weld cracks or anomalies and widespread metal loss) this facilitates the identification and assessment of integrity concerns in the pipeline that may otherwise have been missed in the absence of the mapping data. Furthermore the comparison of repeated mapping runs enables accurate identification and assessment of the areas showing pipeline shape change indicating the in-situ movement that has occurred between inspections, providing further information for the assessment of the on-going integrity of the pipeline. This paper describes the pipeline integrity assessments that are possible from the single and repeat IMU runs and the associated multiple integrity management benefits. The assessment techniques and the stress and strain limits that can be applied to both anomaly-free pipe and when anomalies are coincident with the bending strain are discussed. Real case studies are used to illustrate various pipeline integrity concerns and how the combined mapping and ILI data is used to address and assess the severity of the problem. Further discussion is included regarding how the IMU mapping, curvature and strain results are checked in-field in order to validate the findings.

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