When oil and gas operations break down, it can have a significant domino effect on energy supply – making predictive maintenance technology a key ally for companies in the sector.

Industry giants Shell, ExxonMobil and BP are among those spearheading the use of artificial intelligence and internet of things (IoT) technologies to save costs and optimise machinery.

Data and analytics firm GlobalData says the companies are using the technology to evaluate the condition of their operational equipment and predict maintenance requirements, in order to reduce the likelihood of failures.

Its latest industry report, Predictive Maintenance in Oil & Gas, analyses how recent advancements in cloud-based data analytics and the rise of digital twins in oil and gas operations are extending the boundaries of predictive maintenance technologies.

Listed below are nine major upstream companies it highlights to be at the forefront for adopting predictive maintenance technologies in the oil and gas industry.


Companies using predictive maintenance in oil and gas

Royal Dutch Shell

Shell has been at the forefront of adopting predictive maintenance technologies to enhance equipment reliability and extend the overall operational life of its assets.

The company’s use of artificial intelligence and machine learning in predictive maintenance is helping it in lowering operational expenses and environmental risks arising due to equipment breakdown.



ExxonMobil uses predictive maintenance to evaluate its diverse portfolio of upstream, midstream and downstream assets.

It has installed sensors at several facilities to capture data regarding equipment condition, which is analysed to ensure optimal performance and detect potential failures.

The company has collaborated with Microsoft to use its Microsoft Azure cloud computing platform and data analytics tools to deploy predictive maintenance technologies at Permian shale assets in west Texas and south-east New Mexico.



BP has vast experience in collaborating with technology companies and deploying digital technologies across its global oil and gas operations to maximise productivity.

It has deployed predictive maintenance technologies at its upstream operations, garnering higher equipment uptime along the way.

BP’s Kinneil Terminal, which is an oil stabilisation and gas separation plant (Credit: Mat Fascione)



Chevron relies on digital technologies to optimise drilling and completion, as well as to improve oil recovery and performance of its equipment and downstream facilities.

The company runs diagnostics to identify faults that could lead to a breakdown and capture sensor data on the cloud.

Chevron has adopted the cloud-based data analytics approach for predictive equipment failure in its refinery operations.



Rosneft is investing in the latest technologies to explore the unchartered territories in the Arctic and the Far East regions in order to offset the downward production from maturing oilfields in Russia.

The company is using predictive maintenance and other digital technologies to boost growth and sustainability.

It has collaborated with multinational conglomerate company General Electric since 2013 to develop and implement IoT technology for its liquefied natural gas (LNG) liquefaction units, refineries, and petrochemical plants.



Equinor is implementing digitalisation of its upstream operations to lower operational costs and reduce carbon footprint.

In 2018, it established an integrated operations support centre in Bergen, Norway, to perform remote monitoring and diagnostics of its oil and gas assets in the continental shelf.

These onshore support centres strengthen existing monitoring centres and speed up the decision-making process.

Predictive maintenance oil and gas
Equinor is implementing digitalisation of its upstream operations to lower operational costs and reduce carbon footprint (Credit: Pixabay/Anita Starzycka)



Repsol is embracing digital transformation to enhance productivity and equipment health.

The company has witnessed about a 15% decline in maintenance and $200m in annual savings in operational expenses.

Repsol is harnessing analytics, machine learning, and AI to enhance its predictive maintenance solutions and logistics optimisations.



AI-driven predictive maintenance has become a mainstay of Total’s global operations.

The company is using this expertise to deploy predictive maintenance and other digital technologies on the cloud.

It has collaborated with Google Cloud to develop and deploy AI-driven software for the analysis of geophysical data and equipment monitoring.



ConocoPhillips has deployed predictive maintenance technologies to optimise maintenance operations and reduce breakdowns and costs.

The company makes use of state-of-the-art technologies such as drones and data analytics to inspect equipment and infrastructure and schedule maintenance activities.