SEMI-SUPERVISED MACHINE LEARNING FOR OIL AND GAS PIPELINE CRASHES DETECTION

Authors

  • Dmytro Mahas Ivano-Frankivsk National Technical University of Oil and Gas
  • Vitalia Kropyvnytska Ivano-Frankivsk National Technical University of Oil and Gas https://orcid.org/0000-0001-5231-7104

DOI:

https://doi.org/10.30890/2567-5273.2023-26-01-010

Keywords:

Oil and gas pipelines, machine learning, failures, pipelines.

Abstract

The article covers the usage of machine learning for oil and gas pipelines failure detection. It describes main types of machine learning with a main focus being on semi-supervised ML in oil and gas industry.

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References

Ani, M., Oluyemi, G., Petrovski, A., Rezaei-Gomari, S. // SPE Intelligent Energy International Conference and Exhibition. (OnePetro, 2016).

El-Abbasy, M. S., Senouci, A., Zayed, T., Mirahadi, F. & Parvizsedghy, L. // Artificial neural network models for predicting condition of offshore oil and gas pipelines. Autom. Constr. 45, 50–65 (2014).

Senouci, A., Elabbasy, M., Elwakil, E., Abdrabou, B. & Zayed, T. // A model for predicting failure of oil pipelines. Struct. Infrastruct. Eng. 10, 375–387 (2014).

Kabir, G., Sadiq, R. & Tesfamariam, S. // A fuzzy Bayesian belief network for safety assessment of oil and gas pipelines. Struct. Infrastruct. Eng. 12, 874–889 (2016).

H. Alobaidi, M., Meguid M., Zayed, T. // Semi-supervised learning framework for oil and gas pipeline failure detection

Published

2023-04-30

How to Cite

Магас, Д., & Кропивницька, В. (2023). SEMI-SUPERVISED MACHINE LEARNING FOR OIL AND GAS PIPELINE CRASHES DETECTION. Modern Engineering and Innovative Technologies, 1(26-01), 33–36. https://doi.org/10.30890/2567-5273.2023-26-01-010

Issue

Section

Articles