Corrosion is one of the most significant integrity risks to global infrastructure. According to the NACE Impact Study, the worldwide cost of corrosion is estimated at 2.5 trillion US dollars annually—a figure that exemplifies the threat corrosion poses to all industrial sectors, especially oil and gas.
Corrosion Under Insulation (CUI) is a particularly complex and costly challenge within the energy sector. Across the sector, companies insulate pipelines, pressure vessels, and other high-temperature equipment to maintain process conditions and protect personnel. However, the insulation can create ideal conditions for moisture ingress, allowing water to reach the asset surface. The result is hidden corrosion that develops out of sight.
The impact is significant. CUI has been identified as the cause of up to 60% of pipeline failures in oil and gas (NZTC UK). This accelerated deterioration can lead to sudden failures with limited warning, and the consequences are not confined to repair costs—they include environmental exposure, production loss, and increased regulatory scrutiny. Worse still, materials like carbon steel can corrode up to 20 times faster under insulation than in aerated conditions.
Yet detection remains difficult. Physical inspection is often labour-intensive, dependent on scaffolding, and unable to offer continuous insight into all insulated assets.
Asset owners must also balance inspection frequency with operational demands, which can result in prolonged periods without sufficient visibility into evolving corrosion risks.
But a shift is now underway. With the emergence of sensor-based CUI monitoring and digital analytics solutions, operators are beginning to take a more predictive, data-driven approach to integrity management.
Why CUI Management Is Evolving – and Why It Matters Now
Non-destructive testing (NDT) has always played a central role in this industry. Still, its traditional reliance on scheduled inspections, manual access, and localised results can make it difficult to scale across insulated systems.
Predictive CUI monitoring is emerging as a complementary approach. Rather than replacing physical inspection, it extends its reach, providing ongoing visibility into traditionally hidden or inaccessible areas. This shift aligns with broader industry drivers: the need for better data, more targeted maintenance, and improved asset availability.
What makes this particularly relevant now is the maturity of the technology. Advances in sensor design, connectivity, and analytics mean that predictive systems can be deployed at scale and integrated into existing asset integrity programmes. This offers a practical route to reduce risk without increasing inspection burden for energy operators facing a mix of operational, financial, and safety pressures.
Below, we explore how this transition plays out in practice in one of the largest operators in the world. This example illustrates how predictive CUI monitoring is helping teams reduce inspection burden, improve safety, and optimise maintenance strategy.
Major Oil and Gas Producer in Saudi Arabia: Managing Risk in Intermittent Operations
Assets exposed to extreme temperature fluctuations—ranging from freezing to ambient—are particularly susceptible to CUI. These shifts create ideal conditions for condensation, especially on systems that experience intermittent operation, such as pipelines cycling between service and standby. When moisture becomes trapped beneath insulation, it accelerates the corrosion process and often goes undetected until significant damage has occurred.
Operator identified this challenge on several critical pipeline sections. In these areas, moisture ingress presented a long-term integrity risk. With the potential for failure being both operationally and financially disruptive, the company recognised the need for a more predictive monitoring approach.
Operator deployed the CorrosionRADAR: LR CUI monitoring solution as part of a planned shutdown. This involved the installation of sensors across several kilometres of pipeline. These sensors were designed to continuously monitor for changes in moisture levels and corrosivity rates beneath the insulation, even in inaccessible areas.
LoRa (Long Range) communication protocol was utilised connecting to the CR Clarity Dashboard. This setup enables continuous visibility for corrosion and integrity teams, with data delivered directly to engineers responsible for asset condition assessment.
Operator’s teams receive updates indicating where CUI risk is present, supporting targeted inspections and more efficient maintenance scheduling. Rather than inspecting assets based on fixed intervals or assumptions, the approach allows for prioritisation based on actual conditions observed in the field.
Now, they have a more targeted understanding of their asset CUI risk levels, future unplanned shutdowns will be significantly reduced in cost and impact. With continuous monitoring in place, operator has increased its ability to safeguard high-risk assets while optimising inspection resources and extending asset life in challenging operating environments.
The Broader Shift: From Time-Based Inspection to Data-Driven Monitoring
These examples reflect a growing shift in integrity management strategies across the energy sector. While non-destructive testing remains foundational, the ability to continuously assess corrosion risk beneath insulation has redefined what’s possible when managing CUI.
Sensor-based monitoring enables operators to build a much clearer picture of how environmental and operational conditions impact corrosion—asset by asset. This insight supports more precise maintenance window planning, allocation of inspection resources, and long-term lifecycle cost management.
There are also environmental and safety advantages. By catching problems earlier, operators reduce the likelihood of leaks, insulation waste, or urgent intervention. This contributes not only to operational efficiency but also to more sustainable site operations.
A New Phase for NDT in Energy
We are seeing a steady shift in how NDT is applied across the energy sector. Predictive CUI monitoring complements established inspection practices by providing continuous visibility into previously difficult conditions to assess without insulation removal.
As shown in this example, this approach supports more informed decision-making, helps optimise inspection planning, and improves safety and cost control, particularly on assets where access is limited or operational disruption is a concern.
These are practical, grounded solutions to well-recognised industry challenges. As operators increasingly adopt risk-based monitoring, NDT continues to evolve as a discipline, supporting the energy sector with tools better aligned with today’s integrity, operational, and sustainability priorities.
This evolution also reflects a broader trend: a move away from reactive strategies towards proactive, insight-led maintenance across critical infrastructure. In doing so, predictive techniques are helping operators reduce waste, extend asset life, and manage integrity more efficiently over time.
The application of sensor-based CUI monitoring also opens new possibilities for integration with asset performance systems, digital twins, and remote decision-making workflows, further extending its value in data-driven environments.
In that context, predictive CUI monitoring is one of several meaningful industry advances that help deliver real solutions to the energy sector's worldwide challenges.
Author: Dr. Prafull Sharma
