Harnessing power of AI, edge, and private wireless to boost oil and gas operations
Imagine every pipeline, tank, and inch of your distribution network constantly monitored by connected AI-driven sensors, transmitting data analysed in real-time by smart, large language models to detect and alert you before corrosion can take hold. There's no need to wait for the results of periodic inspections and manually schedule maintenance windows to repair visible damage – automatic alerts are sent to your operations teams, prioritising their work instructions based on critical routes, severity, and risk.
It's not just humans who receive alerts; at the first signs of corrosion, your system instructs drones and robots or even use new fixed wireless cameras to be deployed in specific areas to scan infrastructure and identify cracks and vulnerabilities that human inspections may miss. It uses historical data and predictive modeling to forecast potential issues, proactively shaping worker inspection schedules for more efficient resource allocation. Digital twins allow you to simulate corrosion and test new repair strategies to minimise downtime and prolong asset lifecycles without the cost, fuel consumption, and vehicle wear and tear that occur when teams are dispatched on-site.
Every enterprise must harness the power of its operational data and use AI to solve challenges and achieve goals faster. For the oil and gas industry, tackling corrosion proactively is a compelling use case. The NACE figure doesn't just cover the cost of replacing parts and components, it includes production losses and environmental impact too. In an industry under pressure to improve its environmental credentials, this elevated level of operational intelligence will transform fragmented efforts into strategic, real-time capabilities.
So, how can oil and gas companies attain this next level of operational intelligence? Many have taken the first step toward digitally transforming their business, using robust, reliable 4G and 5G private wireless, which Wi-Fi can complement in certain areas for an extra capacity boost, to deliver mission-critical asset connectivity and access operational data. These industrial enterprises are beginning to produce and collect the massive amounts of data that AI needs to thrive, but it must be able to access it in a cohesive, uniform, and timely way.
Solving the data challenge with devices, connectivity and an industrial edge
The challenge lies in the number of systems that companies rely on. Looking at the way corrosion detection is managed as an example, it requires a complex patchwork of often siloed systems and teams for investigation, inspection, maintenance, repair, and compliance. Systems that leverage different communications protocols don't speak the same language, meaning manual effort is required to analyse data and manipulate it into a standard format to identify potential corrosion hotspots. Delays occur when relying on manual inspections, which can take days to weeks to complete. Once discovered, corrosion could have already caused significant degradation.
The transition towards the new way of working, leveraging AI to analyse and act on data across your systems and use it to automate and orchestrate corrosion detection, analysis, and repair, can only be achieved by collecting, harmonising and analysing comprehensive, real-time data from across your plant. This represents the next level of industrial digitalisation and must incorporate a unified, ecosystem-neutral industrial edge computing platform that integrates into existing technology environments.
Leveraging an industrial edge, enterprises can overcome the hurdles of unifying old and new assets to gain a holistic view of operational data and deliver support for Gen AI. It allows data to be processed and analysed in real-time, on-premises, and made available for consumption by applications for process optimisation through predictive maintenance, automated alerts, and more.
In short, by implementing a digitalisation platform that incorporates robust, reliable connectivity, including devices (cameras/sensors/gateways) that provide inputs through the mission-critical network, and an on-premises industrial edge, oil and gas operators can harness the full power of AI across a fully connected operation. They can stay ahead of corrosion, reduce costs, enhance safety, and avoid the environmental damage that can occur through leaks.
'Companies can begin using an industrial edge computing platform as an integral part of their digitalisation journey today. Those who act now will gain the competitive advantage.'
Using AI to continuously monitor and analyse data from industrial equipment to detect patterns, for example, in pressure, temperature, or flow rates, oil and gas companies can optimise delivery, detect leaks and isolate sections automatically, and schedule predictive maintenance and general maintenance windows. AI can identify workarounds while situations are being managed, to limit the impact on customers and the environment and protect workers.
Gaining an industry advantage
It's not only the oil and gas industry that will benefit, of course – any industrial organisation will gain a competitive advantage using a digitalisation platform that incorporates wireless connectivity with an industrial edge. Lone worker safety can be enhanced at mines, ports, chemical manufacturing plants, and in any harsh industrial environment using AI to track and analyse biometric data from wearable devices.
By detecting the early signs of stress or fatigue, alerts can be sent to workers advising them to rest or to first responder teams in extreme situations. AI will also assist industries with onboarding and worker training, and allow new workers to interact with systems more intuitively to manage their workloads more effectively. The other angle for gaining industry advantage is now the possibility of getting into autonomous operations or tele-remote operations, a reality happening today in several industries utilising the power of the digitalisation platform to enhance assets and protecting workers.
With every data reading and decision captured, companies can demonstrate how their actions enhance productivity, safety, and sustainability, as they maintain compliance. Studies have found that 79% of the early adopters of private wireless networks incorporating industrial edge platforms and digitalisation technologies see at least a 10% reduction in their emissions, while 75% improve their productivity by 10% or more, and all see a return on their investment within two years.
As new use cases emerge and more data is produced, a flexible edge compute and AI will support enterprises as they locate processing capabilities at the far edge, where data is generated. This will ensure they can maintain support for mission-critical applications even as their data and connectivity demands evolve.
This opinion piece is authored by Mahmoud El-Banna, Head of Enterprise Campus Edge, Middle East, Africa, and India, Nokia.
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