Several companies in the oil and gas industry, including Shell, ExxonMobil and BP, are using predictive maintenance to evaluate the condition of their operational equipment and predict maintenance requirements, according to GlobalData.
The company’s latest report, ‘Predictive Maintenance in Oil & Gas’, reveals that the 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, making it a reliable tool for monitoring asset integrity.
Listed below are the leading companies that are adopting predictive maintenance technologies in the oil and gas industry, as identified by GlobalData.
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 (AI) and machine learning in predictive maintenance is helping it in lowering operational expenses while also lowering 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.
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.
Chevron relies on digital technologies to optimise drilling and completion, as well as 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 GE since 2013 to develop and implement Internet of Things (IoT) solutions for its LNG liquefaction units, refineries, and petrochemical plants.
Equinor is implementing digitalisation of its upstream operations to lower operational costs and reduce carbon footprint. It established an integrated operations support centre in Bergen, Norway, in 2018 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 expedite the decision-making process.
Repsol is embracing digital transformation to enhance productivity and equipment health. The company has witnessed approximately 15% decline in corrective maintenance activities and US$200 million 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 solutions 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.
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