INDUSTRY WATCH

Computer vision in particular is emerging as an essential tool for operators in the industry to improve safety and private LLMs are helping to analyse huge amounts of data and democratise access to information within organisations. Other predictive AI techniques are helping operators to avoid costly repairs and plant shutdowns.

The companies that are using AI successfully are those who start by looking at a business problem rather than organisations who deploy AI for its own sake – with forward-thinking organisations in the sector already seeing measurable business value from AI in everything from employee safety to exploration.

Seeing results

For many companies, computer vision is already seen as transformative to operations and new use cases keep emerging.

Analytic models have long been widely used in predictive maintenance in the oil and gas sector, but computer vision is transforming how this is delivered, offering a 360-degree view of what is happening at a site.

For example, a company can opt to use computer vision to monitor whether people are wearing protective equipment at various operational stages in the oilfield and then act rapidly if needed. It’ s mature technology – an extension of what many companies were doing during COVID with mask detection. You get immediate results, but once you have that infrastructure there, it’ s a net-zero investment to add more use cases and use the cameras to detect other issues. You can detect more things at a much lower incremental cost, because you are not having to add sensors.

In the oil and gas sector, hazardous environments such as well pads, drilling rigs and other high-risk sites often pose challenges for deploying IoT sensors due to strict safety requirements and high costs. To overcome these limitations, computer vision enabled cameras placed outside these zones can provide predictive monitoring from a safe distance. Other important uses of computer vision in the sector include corrosion identification, leak detection, gauge surveillance and brownfield site safety monitoring.

Machine learning and AI innovator nybl, part of Lenovo’ s AI Innovator program, is already using AI to great effect in the oil and gas sector, with an AI capability built for oil wells which utilizes real-time operational data like vibration, temperature, pressure and other metrics. By integrating this data, nybl’ s AI helps predict potential failure, reduce downtime by up to 97 %, increasing productivity by 15 – 20 % and extending the life of wellhead assets by up to 30 %.

Among other tools like n. lift, designed for Electric Submersible Pumps( ESPs), nybl is also building models capable of deep computer vision analytics around human behaviours and are researching around how computer vision can be used in upstream oil field services in the future.

Finding value

In the exploration stage, AI can also have a powerful impact. When identifying oil and gas prospects, organisations have to deal with enormous amounts of seismic and geological data. High-performance computing and AI algorithms can make sense of this data, identifying oil prospects rapidly and accurately.

When it comes to operating plants, AI also has multiple uses, from event prediction to production optimisation, using techniques such as pattern recognition to predict outcomes. Combining multiple AI techniques such as predictive simulations and closed-loop optimisation can help operators to boost efficiency, by adjusting

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