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.

Corrosion under insulation (CUI) is a major problem for petroleum and petrochemical process industries that affects the plant mechanical integrity and attacks assets. CUI can result in sudden and hazardous leaks (safety concern), and plant shutdowns with high losses of production (economical concern).
Traditional detecting methods of CUI to cut a window in thermal insulation used to inspect visually, to measure the thickness, and then return thermal insulation back, giving high chance for water and moisture ingress, accelerating CUI, moreover big amount of scaffolding erection along with thermal insulation removal required.
SHARQ (Eastern Petrochemical Company, one of SABIC companies) is pioneer to study CUI, evaluating many Non–Destructive techniques has proven Pulsed Eddy Current (PEC) as the most effective technique in terms of integrity and cost optimization.
Considering all available techniques, all aspects studied, such as range of applications, features, and limitations, it is concluded and verified to meet our inspection plan strategy needs.
PEC does not require thermal insulation removal; optimize scaffolding erection, has a wide range of applications related to thickness, and temperature. PEC approved by international codes and standards (API) to meet RBI Meridium software requirements.
The validation study results show cost savings of more than 50% compared to traditional thickness measurement methodology, moreover it reduces EHSS (Environment, Health, Safety, and Security) negative impact reduces the probability of safety incidents due to reducing labor, man-hours, and eliminating many associated activities with potential hazard and risk.
PEC has high productivity, easily operated, and provides comprehensive and professional inspection report

The continuous improvements in the Oil&Gas Industry to deal with reliability and maintainability objectives, higher operational reliability, improved safety, and emergency readiness for potential risk of unexpected events have led the Offshore Companies to be in the forefront of development of design and analysis methodology for integrity assessment and safety operation. The architecture of an integrated model targeting the major residual risks to the asset, new generations of internal and external inspection techniques, real-time monitoring sensors, material degradation prediction related to the actual and future operational conditions and machine learning methods are, as identified from the experiences of the authors, the new frontiers for the Pipeline Integrity Management. The advance in automation process to build pipeline digital twin, looking at new predictive and diagnosis tool by advanced FE models allows not only thinking defensively but also in taking an aggressive position toward safety and asset optimization. Plenty of attention was devoted to the 40 years of pipeline integrity assessment through which the engineering assessment takes advantage from inspection and operational data. Suite of services for an integrated solution including ad-hoc engineering and repair system readiness have been identified as the main pillars for best-in-class Operators. Case histories and integrated solution to ensure satisfactory performance and safety have been presented.