Role of Advanced Prediction Techniques on Corrosion Management of Pipelines External Corrosion

Paper ID: C2025-00150 ABSTRACT: The most dependable and widely used techniques to inspect and manage external corrosion are inline inspection (ILI) for piggable pipelines and external corrosion direct assessment (ECDA) for non-piggable pipelines. However, ILI is the lagging indicator, i.e., it provides information on corrosion after metal loss has happened and ECDA is current indicator, i.e., it provides current status of corrosion. Therefore, is essential to integrate lagging and current indictors with prediction techniques so that pipeline operators cantake the required pre-emptive steps, plan ahead and implement corrective actions in a timely manner.
This paper reviews concepts and capabilities of various advanced prediction techniques including but not limited to 5M-Methodology, Machine Learning, and Artificial Intelligence along with their role in the corrosion management of external corrosion of oil and gas pipelines.
Furthermore, this paper describes the success of the approach, lessons learned, and future improvements using data from four (4) oil and gas pipelines,