The integrity management of unpiggable pipelines continues to present a major challenge to operators, as conventional in-line inspection (ILI) technologies cannot always be applied. While customized ILI solutions are sometimes possible, alternative above-ground methodologies are required when ILI is not feasible, or when a screening assessment is needed before further inspection.

Non-Intrusive Pipeline Assessment (NIPA) has been developed to address this gap by integrating construction and operational records with above-ground survey techniques such as Large Stand-off Magnetometry (LSM), Cathodic Protection (CP) measurements, Geographic Information Systems (GIS), and AI-supported pipeline condition predictions (Virtual-In-Line Inspection) powered by ROSEN’s Integrity Data Warehouse (IDW). With data from over 28,000 ILIs covering more than 1,000,000 km of pipeline, the IDW enables robust predictive modelling and benchmarking, enhancing confidence in anomaly detection and integrity assessment.

This paper presents an overview of NIPA and a case study involving sour service, unpiggable flowlines. The case study demonstrates the effectiveness of NIPA in identifying critical defects and supporting targeted excavation strategies where classical External Corrosion Direct Assessment (ECDA) would have failed.

By combining data-driven analytics with advanced non-intrusive survey technologies such as LSM, NIPA significantly improves the effectiveness of Direct Assessment. This approach reduces unnecessary excavations, increases confidence in Fitness-for-Service evaluations, and provides operators with a viable and reliable solution for managing the integrity of unpiggable pipelines.