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 …

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 …

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 …

Corrosion is one of the most common defects of buried pipelines. Accurate prediction of the
maximum pitting depth of corroded pipelines is conducive to assessing the remaining …

Pitting corrosion is a primary type of external corrosion that poses a critical challenge in the
oil and gas industry, potentially leading to severe environmental, health, and economic …

Understanding the corrosion risk of a pipeline is vital for maintaining health, safety and the
environment. This study implemented a data-driven machine learning approach that relied …

The main objective of this paper is to develop accurate novel frameworks for the estimation
of the maximum pitting corrosion depth in oil and gas pipelines based on data-driven …

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 …

This paper proposes a practical implementation of robust ensemble learning models for
accurate prediction of the internal corrosion rate in oil and gas pipelines. A correct …

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 …