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Pond investigated pressure vessel tank failures which are causing recurring maintenance of $250,000 per year. This challenging project had limitations of space, operational time pressures/vessel availability requirements, cost and replacement variables. This presentation will chronical problems and discuss best practices of specifications, material selection, surface preparation, and application inspection that would have prevented the aforementioned outcome. This paper discusses the fundamentals of composite coatings, industry accepted design standards for their use, and examples of typical uses for these materials that solve problems in varied industries.
This paper evaluates the resistances to CUI of three types of coatings under severe CUI conditions using a vertical pipe test method. Certain possible improvements in the test method are also discussed.
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Corrosion under insulation (CUI) is a critical challenge that affects the integrity of assets for which the oil and gas industry is not immune. Over the last few decades, both downstream and upstream industry segments have recognized the magnitude of CUI and challenges faced by the industry in its ability to handle CUI risk-based assessment, predictive detection and inspection of CUI. It is a concern that is hidden, invisible to inspectors and prompted mainly by moisture ingress between the insulation and the metallic pipe surface. The industry faces significant issues in the inspection of insulated assets, not only of pipes, but also tanks and vessels in terms of detection accuracy and precision. Currently, there is no reliable NDT detection tool that can predict the CUI spots in a safe and fast manner. In this study, a cyber physical-based approach is being presented to identify susceptible locations of CUI through a collection of infrared data overtime. The experimental results and data analysis demonstrates the feasibility of utilizing machine-learning techniques coupled with thermography to predict areas of concern. This is through a simplified clustering and classification model utilizing the Convolutional Neural Networks (CNN). This is a unique and innovative inspection technique in tackling complex challenges within the oil and gas industry, utilizing trending technologies such as big data analytics and artificial intelligence.
This paper will explain how to find CUI (Corrosion under Insulation within a refinery through proper inspection and, damage mechanisms, avoiding premature structural failure due to corrosion.