The ability to predict where stress-corrosion cracking is likely to be most severe within a portion of a pipeline is essential to the success of SCC direct assessment and would be very useful for prioritizing exploration and validation excavations, hydrostatic testing and In-line inspection. Some valuable information has been obtained from company experience and data mining projects, however, significant uncertainties remain. By collecting additional SCC based ILI data and correlating them with the characteristics of locations where SCC occurs, improved site-selection models could be developed. The primary objective of this project is to establish better correlations between SCC severity and operational and geotechnical characteristics using currently available and/or further collected SCC related ILI data. This correlation can lead to improved models for selecting sites for SCC DA excavations, hydrostatic testing and ILI.
The first phase of this work delivered an improved correlation models to predict where SCC is most likely will take place. The research continues in 2013 to further validate the developed correlation models including data from liquids pipeline operators, as the focus to date has been gas pipeline systems only. Some valuable information has been obtained from company experience and data mining projects, but significant uncertainties remain. By collecting additional data about the characteristics of locations where SCC occurs, this project will result in improved site-selection models and will be used to validate the results of SCC-1 project, “Development of Guidelines for Identification of SCC Sites and Estimation of Re-inspection Intervals for SCC Direct Assessment.”