Improving pipeline integrity management using machine learning
Challenge
Optimizing pipeline coating rehabilitation scopes is challenging, requiring a balance between reducing capital expenditure and mitigating pipeline integrity risks.
Solution
A cloud-based machine learning system was developed to automate the inspection alignment process, generate corrosion KPIs, and classify scopes for rehabilitation. This system mimics human decision-making in prioritizing coating rehabilitation with high accuracy.
Impact
The automation alone delivered a 5-20x return on investment (ROI). Additional benefits include reduced costs from avoiding unnecessary rehabilitation and decreased risk of pipeline integrity failures.
