Stress Corrosion Cracking (SCC) is an insidious, complex phenomenon that can be influenced by numerous factors such as pipeline age, steel microstructure and mechanical properties, environment, manufacturing and/or installation-induced stresses, coating type, degradation levels and disbondment, cathodic protection history, soil resistivity, redox potential, and anaerobic activity, to name a few. The availability of current and historical data, sources and format can vary greatly from one pipeline to another, even within the same company. An additional challenge is posed by the several mechanisms that can be found acting individually or concomitantly – along the pipeline and throughout time – as well as the fact that the modelling of some of those mechanisms remains controversial.
A hindrance to the successful implementation of a Crack Management Program, SCC susceptibility assessments have traditionally been considered costly sophisticated analyses that demand a considerable amount of manual labor and expert judgement.
This paper presents an adaptive pipeline data and integrity management platform, called NIMA, which can be used to facilitate the data mining/integration and to execute integrity management processes. To illustrate the framework capabilities, the SCC susceptibility of three pipelines, with different datasets, is analyzed and prioritized through the customizable, built-in library of integrity management technical templates. The assessment of the most critical pipeline is then refined, through input of additional ILI data and modifications to the graphic interface and model algorithms. At both stages, the framework not only expedites the process, but also provides evidential documentation and guarantees the assessments’ reproducibility.