Prediction of oil and gas pipeline failures through machine learning approaches: A systematic review

• Main Authors: Al-Sabaeei, A.M., Alhussian, H., Abdulkadir, S.J., Jagadeesh, A.
• Format: Article
• Published: Elsevier Ltd 2023
• Online Access: http://scholars.utp.edu.my/id/eprint/37299/; https://www.scopus.com/inward/record.uri?eid=2-s2.0-85168241856&doi=10.1016%2fj.egyr.2023.08.009&partnerID=40&md5=c11a628b554bd74ac80009361e25c404

Pipelines are vital for transporting oil and gas, but leaks can have serious consequences such as fires, injuries, pollution, and property damage. Therefore, preserving pipeline integrity is crucial for a safe and sustainable energy supply. The rapid progress of machine learning (ML) technologies pr...