The pipeline industry strives to keep pipelines running safely and reliably. The process involves many steps, including selecting the lines/segments to be inspected with in-line inspection (ILI); maintenance, repair, digs; ILI validation; growth predictions and risk-based programs to establish maintenance and repair practices. Most operators' programs start with in-line inspections, which generate large data sets and provide interpretations about the pipeline integrity without a validation process. Although ILI information is thorough, it is generated by non-destructive and/or indirect measurements. As with any non-destructive examination (NDE) technique, comparisons must be made to direct observations and measurements to ensure accuracy. This paper overviews validation of the ILI data through four case studies: determining whether the tool is functioning per its listed specification, discussing the applicability of validating crack tool ILI runs and presenting two examples of feature misidentification by the ILI tool. Together, these case studies demonstrate the importance of validating ILI data to ensure the integrity of the pipeline is adequately assessed.
The pipeline industry strives to keep pipelines running safely and reliably. The process involves many steps, specialized groups, and decisions:1, 2, 3
1. The group that chooses the lines or segments to be inspected with in-line inspection (ILI). This work entails choosing the ILI tools for the anticipated integrity threat.
2. The ILI tool runs to detect and identify defects.
3. Maintenance, repair, and excavation digs.
4. The ILI validation.
5. Defect growth predictions and risk-based programs to establish maintenance and repair practices.
To date, many operators' integrity assessment programs include In-Line Inspections (ILI). Without excavating, ILI generates large data sets and provides interpretations about:
1. Pipeline integrity.
2. The presence of anomalies/features such as dents, metal loss, mill defects, girth weld cracks, etc.
3. The size of the anomalies (length, width, depth, clustering, etc.)
4. Regulatory key performance indicators (KPIs) include the ASME B31G burst pressure, the Rupture Pressure Ratio (RPR), feature density, etc.
