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
• Institution: Universiti Teknologi Petronas

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...