This work provides a data-oriented overview of the rapidly growing research field covering
machine learning (ML) applied to predicting electrochemical corrosion. Our main aim was to …

Corrosion presents a daunting challenge to the oil and gas industry, resulting in substantial
maintenance expenses and productivity losses. Conventional corrosion monitoring …

Hydrocarbon fluid integrity evaluation in oil and gas pipelines is important for anticipating
HSE measures. Ignoring corrosion is unavoidable and may have severe personal …

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 …

One of the greatest challenges faced by industries today is corrosion and of which, one of
the most vital forms is stress corrosion cracking (SCC). It brings highest forms of risks to the …

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 …

Despite being considered the safest means to transport oil and gas, pipelines are
susceptible to degradation. Pipeline integrity management (PIM) is implemented to lower the …

This investigation proposes using Scanning Electrochemical Cell Microscopy (SECCM) as a
high throughput tool to collect corrosion activity from randomly probed locations on 316 L …

We have employed supervised machine learning methods to model measurements of
corrosion rates of carbon steel as a function of time when corrosion inhibitors are added in …

Energy industry is losing billions of dollars each year due to corrosion. However, publicly
accessible datasets on pipeline corrosion are limited, making it difficult to accurately predict …