Course Overview
Pipeline operators and inspection providers can generate detection and sizing results faster than ever — but detecting a signal and trusting a call remain two different problems, and the second is getting harder, not easier, as AI tools spread through the ILI data-evaluation workflow. This course is for analysts, engineers, and operator personnel who work with in-line inspection results — whether producing them or acting on them — and need to move from reading a result to defending a decision.
Why does training still matter when technical information is one AI query away? Starting from this direct question, the course builds on the statistical and procedural foundations: probability of detection and identification, sizing accuracy and confidence, and the three-tier validation framework in API 1163. It connects that foundation to advanced ILI, AI-supported data processing and analysis and to the regulatory and data-governance landscape areas (incl. EU AI Act). Furthermore, geohazards and its monitoring are addressed.
Format: one intensive day, judgment-focused, concluding with a hands-on exercise designed to translate course insights into daily operational decisions.
Agenda
- Introduction and the “WHY”: The shift from information retrieval to human judgment and verification in an AI-driven industry.
- Foundations of Anomaly Interpretation: Physical characteristics of dents, metal loss, and cracks; raw sensor data stream ingestion, data corrections, noise filtering, and an easy introduction to AI.
- Applied Statistics and API Standard 1163: POD, POI, sizing accuracy; applying these metrics directly to validation digs and unity plots.
- Advanced Data Analysis & Processing: Data-alignment methodologies, basic concepts of Geometry/MFL/UT/EMAT processing, HMI workflows (Human-in-the-Loop HITL), and the state-of-the-art in multi-technology data fusion.
- Geohazards & IMU Curvature Mapping: Mitigating geotechnical/hydrotechnical threats; leveraging Inertial Measurement Unit (IMU) bending-strain analysis for active pipeline displacement monitoring.
- Regulatory Compliance & AI Governance: Pipeline data-lineage under the PHMSA Mega Rule and the legal impact of the EU AI Act’s Article 4 “AI Literacy” mandate.
- Practical Capstone Workshop: single hands-on group exercise which helps translating course insights into daily operational decisions.
Approval (for German engineers)
This training course is recognized as a training session in accordance with §6 FuWo. Consulting engineers and members of the German Chambers of Engineers receive 8 training points for participation.
Target Group
Pipeline integrity engineers, ILI data analysts, and technical managers who evaluate, verify, or oversee ILI-based anomaly and integrity decisions — together with pipeline operator personnel who need a working understanding of how ILI data analysis results are produced and how much to trust them. It assumes basic familiarity with inspection technologies and metal-loss/crack/dent threats, as e.g. given by the EITEP Training Courses of M. Beller and K. Reber. Suited to anyone who must trust, or defend, an ILI-based call and who also sees the growing importance of data analysis and AI-supported technologies in the future.
