An active learning framework assisted development of corrosion risk assessment strategies for offshore pipelines

Z Qu, X Jiang, X Zou, X Yue, Y Xing, J Zhu… - Process Safety and …, 2024 - Elsevier
Aggressive fluids and prolonged service life result in an increasing internal corrosion risk of
offshore pipelines, especially for perforation. A framework was constructed by active …

Prediction of the internal corrosion rate for oil and gas pipelines and influence factor analysis with interpretable ensemble learning

J Hu - International Journal of Pressure Vessels and Piping, 2024 - Elsevier
Corrosion is one of the major threats to the safety and reliability of oil and gas pipelines,
making accurate prediction of corrosion rate crucial for pipeline maintenance and …

Application of Machine Learning Approaches to Prediction of Corrosion Defects in Energy Pipelines

M Hussain, T Zhang, I Jamil, AA Soomro… - Advances in Corrosion …, 2024 - Springer
The integrity of energy pipelines is crucial for assuring the safe and reliable transportation of
resources. Corrosion defects significantly threaten pipeline infrastructure, necessitating …

Machine-learning-based classification for pipeline corrosion with monte carlo probabilistic analysis

MFH Ismail, Z May, VS Asirvadam, NA Nayan - Energies, 2023 - mdpi.com
Pipeline corrosion is one of the leading causes of failures in the transmission of gas and
hazardous liquids in the oil and gas industry. In-line inspection is a non-destructive …

Interpretable machine learning for maximum corrosion depth and influence factor analysis

Y Song, Q Wang, X Zhang, L Dong, S Bai… - npj Materials …, 2023 - nature.com
We have employed interpretable methods to uncover the black-box model of the machine
learning (ML) for predicting the maximum pitting depth (dmax) of oil and gas pipelines …

Evolution of corrosion prediction models for oil and gas pipelines: From empirical-driven to data-driven

Q Wang, Y Song, X Zhang, L Dong, Y Xi, D Zeng… - Engineering Failure …, 2023 - Elsevier
Oil and gas pipelines are under great threat of corrosion due to the harsh service
environment. It is critical to predict corrosion for the safe service of pipelines. Classical …

Predicting the External Corrosion Rate of Buried Pipelines Using a Novel Soft Modeling Technique

Z Ren, K Chen, D Yang, Z Wang, W Qin - Applied Sciences, 2024 - mdpi.com
External corrosion poses a significant threat to the integrity and lifespan of buried pipelines.
Accurate prediction of corrosion rates is important for the safe and efficient transportation of …

[HTML][HTML] Predictive deep learning for pitting corrosion modeling in buried transmission pipelines

B Akhlaghi, H Mesghali, M Ehteshami… - Process Safety and …, 2023 - Elsevier
Despite significant efforts and investments in the renewable energy sector, fossil fuels
continue to provide the majority of the world's energy supply. Transmission pipelines, which …

Deeppipe: Theory-guided prediction method based automatic machine learning for maximum pitting corrosion depth of oil and gas pipeline

J Du, J Zheng, Y Liang, N Xu, Q Liao, B Wang… - Chemical Engineering …, 2023 - Elsevier
Accurate monitoring of pipeline corrosion is important and necessary not only for the normal
operation of oil and gas pipelines but also for the reliable and stable supply of energy. To …

The utilization of supervised machine learning in predicting corrosion to support preventing pipelines leakage in oil and gas industry

S Zukhrufany - 2018 - uis.brage.unit.no
Pipelines have become indispensable in oil and gas industry to support transportation of
flammable and poisonous fluids such as crude oil, natural gas, and refined petroleum …