The integration of advanced technologies with non-destructive testing methods is significantly enhancing critical inspection procedures regularly carried out on oil and gas equipment and infrastructure.
Non-destructive testing (NDT) involves the use of non-invasive methods to quantitatively inspect, measure, and evaluate the integrity of critical infrastructure, equipment and systems without interfering with the overall operation of those assets.
Common problems detected using these techniques include surface corrosion, mechanical damage, and cracks in infrastructure, while the components that can fail and need testing include wiring, hydraulic cylinders, drills, bearings, circulating pumps, and motors.
The six main methods used in the industry are visual inspection, liquid penetrant testing, magnetic particle testing, electromagnetic or eddy current testing, radiography, and ultrasonic testing.
Additionally, emerging technologies are reshaping inspection workflows, with AI enabling predictive maintenance and drones providing defect detection in areas that are difficult or unsafe for personnel to access.
In particular, the digitalisation of NDT methods enables real-time data collection and analysis, increasing efficiency and lowering operational costs.
Robots also play an important role, as autonomous inspection systems have become the main development direction of energy industries – the capabilities of autonomous localisation, navigation, and inspection are crucial.
When robots are used to perform inspection and maintenance operations on industrial assets, it reduces human intervention, increases operational efficiency, and improves safety.
Robotic inspection solutions are predominantly used in the oil, gas, and petrochemical industries, and vary from subsea to mobile robotic systems.
The global NDT market was worth more than US$6 billion in 2020 and is expected to grow to nearly US$15 billion in 2028, according to market research, representing a compound annual growth rate of 12.98 per cent.
Stringent asset-quality and safety regulations have been the primary drivers of growth in the NDT and inspection market, reinforced by advances in robotics and the accelerating shift toward automation in manufacturing.
According to P&S Intelligence, digitalising methods such as condition monitoring allow embedded sensors to capture continuous measurements and automatically store them in secure cloud environments as the data is generated.
P&S said: “In combination with wireless communication through either a cellular or wireless local area network – coupled with the integration of connected solutions – IoT is expected to become a powerful tool to immediately share NDT and inspection data with collaborating partners or distribute reports to external parties.”
Given the combination of abrasive conditions and corrosive chemicals used in processing, corrosion damage to material handling equipment, processing systems, and supporting infrastructure is a major cause of planned shutdowns in oil and gas operations.
Ultrasonic and acoustic-emission methods are both effective for locating corrosion, with ultrasonic testing more widely adopted because its short-pulse waves can detect internal flaws and characterise both metallic and non-metallic materials.
Because sound waves travel at different velocities through different materials, ultrasonic testing identifies flaws by detecting changes in wave speed as the signal passes through an asset.
It is especially useful when testing for corrosion and potential mechanical failure in components and equipment, and can also provide important data to a predictive maintenance program.
Another important NDT method is magnetic particle testing, which utilises magnetic fields to detect cracks and distortions in ferromagnetic and electricity-conducting materials.
Magnetic particle testing is a time-efficient way to detect surface or subsurface defects and provides results immediately.
A key application for NDT is detecting corrosion under insulation (CUI), which is primarily caused by water or moisture intrusion through jacketing and insulation, coming into contact with the underlying steel surface.
A variety of environmental factors can influence the rate of CUI, such as operating temperature, pH, and contaminants.
The only current method that ensures effective screening of CUI is the removal of the external jacketing or cladding and visual inspection of piping conditions.
While several NDT methods are applicable, each with its own benefits and disadvantages, radiography and ultrasonic techniques are widely used to detect CUI.
Recent trends have seen the use of an electrochemical probe to detect local corrosion and the employment of modelling to predict CUI.
Machine learning has also been developed to collect data and train CUI models for better accuracy.
Forms of NDT for CUI include pulsed eddy current testing, long-range ultrasonic testing, computed radiography, and infrared thermography.
These methods all have various limitations, but do not require removing the insulation for visual inspection.
Computed radiography testing, which is accurate but time-consuming, can be undertaken on piping bends to check for corrosion.
On the other hand, pulsed eddy current testing is an advanced method that can be performed very rapidly and while the pipe is still in operation; however, its accuracy is very limited, with a variation of up to 10 per cent.
