Tuesday, 27th April 2021 at 12:00 – 13:00 UK BSTime

Virtual In-Line Inspection for Corrosion Management in Un-piggable Pipelines

1 hr | Free

Michael Smith | Senior Engineer Data Scientist | ROSEN UK

Over the past 30 years, ILI data have been collected all around the world. Although pipelines are diverse in their characteristics, many share similar risk profiles for common pipeline threats such as external and internal corrosion. This has led the industry naturally towards machine learning as a complementary corrosion monitoring solution for pipelines that cannot be inspected using ILI. For a given uninspected pipeline, we can source data for similar inspected pipelines and use machine learning algorithms to generate predictive models. The results of a “Virtual ILI” create clear justification for planning actual inspections or maintenance in challenging pipelines.

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