Five digital trends revolutionising the pipeline sector
Published by Emilie Grant,
Editorial Assistant
World Pipelines,
More than 3 billion l of water leak from pipes in England and Wales every day. In the oil and gas sector, unplanned outages, including those caused by pipeline failures, can cost operators over £100 000/h in lost production.
What links both is the same systemic strain: infrastructure built for a different era, now operating under modern pressures. From climate volatility to tighter regulatory controls, pipeline networks are being forced to perform with greater reliability, efficiency and transparency, yet without fundamental redesign, many can’t.
Faced with these operational and structural pressures, the sector is transforming towards smarter, data-led operations. Real-time monitoring, autonomous inspections, and predictive analytics are replacing reactive maintenance and routine checks. Pipeline management is being reengineered around data, automation and machine learning, across oil, gas and water networks alike.
Danny Peachey from HTL Group, the leading provider the leading provider of hydraulic cutters, looks at five digital trends already influencing pipeline operations, from AI-driven monitoring to predictive maintenance.
1. AI is moving decision-making closer to the problem
Pipeline operators now deal with thousands of data points every second, from flow rates to vibration patterns, pressure fluctuations to acoustic anomalies. Traditionally, much of that data was stored but rarely used, but AI is changing that.
Where AI is making the biggest impact isn’t in replacing engineers, but in accelerating decision-making. Shell, for example, has deployed AI-driven predictive maintenance across more than 10 000 assets, including pumps, compressors and control valves, analysing billions of sensor readings to detect early signs of mechanical failure. This helped cut unplanned downtime by 20% and reduced maintenance costs by 15%.
But AI’s applications extend far beyond equipment uptime. In pipeline integrity programmes, it is increasingly being used to detect leaks, corrosion, and structural fatigue. According to recent research, machine learning models trained on pressure, flow, and acoustic data can pinpoint the location and severity of leaks with high accuracy in controlled test environments, demonstrating their potential for real-world deployment.
2. Robotics are enabling inspection without disruption
Much of the UK’s water network is underground, and in many cases, no accurate maps exist. Inspections often involve trial-and-error digging, surface disruption, and costly delays.
Pipebots, autonomous micro-robots developed by the University of Sheffield, designed to navigate live water mains, can identify cracks and material defects from within the pipe itself, transmitting data without excavation.
The goal is long-term: reduce reliance on surface-level detection, minimise disruption, and shift from reactive to proactive maintenance. For the oil and gas sector, drone inspections now replace foot patrols in remote areas, and submersible crawlers inspect internal welds and detect corrosion at depths that were once inaccessible.
As inspection becomes automated, operators can increase frequency, improve resolution, and reduce exposure to confined spaces, all while cutting operational costs.
3. IoT is turning pipelines into live networks
Digital transformation doesn’t work without live data, and the proliferation of low-power, high-precision IoT sensors has changed how pipelines are monitored, not every few days, but every few seconds.
UK trials have already shown the value, with Ovarro’s EnigmaREACH system, tested across five utilities in 2024–25, reducing average leak detection time by 50%. By deploying wireless acoustic loggers overnight, utilities identified 5-6 hidden leaks per session, many of which would have gone unnoticed using conventional methods.
This is particularly significant in the context of Ofwat’s 2050 target to halve leakage. While legacy SCADA systems provide bulk data at fixed intervals, modern IoT infrastructure enables near-continuous condition monitoring. And when that data feeds into machine learning platforms, it becomes a foundation for faster, risk-based decisions across the network.
4. Digital twins are changing how systems are designed and operated
Rather than relying on static models or assumptions, pipeline engineers are increasingly working with digital twins - dynamic, real-time virtual replicas that simulate how an asset is performing under current conditions.
Anglian Water’s Strategic Pipeline Alliance (SPA) uses a digital twin to monitor a 192-mile water transfer system designed to bolster drought resilience in Eastern England. The twin integrates sensor data, hydraulic models and operational constraints, allowing engineers to simulate network changes and test responses in advance. That’s already translated to a 65% reduction in capital carbon through better-informed design and delivery decisions.
In oil and gas, twins are now being used to model stress points in ageing steel pipelines, optimise compressor loads, and test emergency shutdown scenarios. The benefit isn’t just better oversight, it is operational confidence. Operators can see in advance how the network would respond under strain, rather than waiting to find out the hard way.
5. Predictive maintenance is becoming embedded, not experimental
Until recently, most maintenance was either reactive – fix it when it fails, or preventive – fix it on a schedule, even if nothing’s wrong. Both approaches come with cost inefficiencies and risk.
Predictive maintenance changes the model entirely. By using sensor data and historical performance patterns, operators can forecast when components are likely to fail, and intervene just before they do.
Equipment failures cost oil and gas firms an average of £115 million/y , with worst-case scenarios exceeding £400 000/h. Predictive maintenance systems, increasingly being adopted on offshore platforms in the North Sea, are helping to reduce this by extending the lifespan of valves, pumps, and control systems.
In the water sector, similar models are used to identify high-risk pipe sections before a burst, factoring in ground movement, age, material type and pressure fluctuation. The result is better capital planning and fewer emergency call-outs.
The new baseline
None of these trends are future promises, as they’re already being rolled out in UK water networks, gas transmission corridors, and offshore infrastructure. Individually, they offer operational gains. Together, they represent a shift in how the sector defines reliability, cost control, and compliance.
Regulators now expect continuous monitoring, not annual reporting. Investors expect risk reduction, not reactive maintenance. And customers expect uninterrupted service, whether it’s heating a home or drawing water from the tap.
The pipeline sector’s digital transformation isn’t being driven by technology for its own sake. It’s being driven by a need to do more, with less, under greater scrutiny. These trends aren’t revolutionising the sector, in fact, they’ve become the new baseline.
Sources
https://waterplant.tech/news/91674-enigmareach-cutting-leak-detection-time-by-50-in-uk-trials
Read the article online at: https://www.worldpipelines.com/business-news/07082025/five-digital-trends-revolutionising-the-pipeline-sector/
You might also like
The World Pipelines Podcast - What the science says: pipeline safety with PRCI
A conversation about the research, collaboration, and science behind safer, cleaner, and more efficient pipeline operations. Featuring Gary Choquette, Executive Director of Research at the Pipeline Research Council International (PRCI).
Tune in to the World Pipelines Podcast on your favourite podcast app today.
