This article explains the meaning of predictive maintenance and also the crucial role it plays in the oil and gas industry.
What is the meaning of predictive maintenance?
This is a technique that uses condition-monitoring tools and techniques to monitor the performance of a structure or a piece of equipment during operation.
It helps improve productivity through timely maintenance intervention.
Maintenance strategies in the oil and gas industry have gradually transformed from their early days in the nineteenth century. To achieve operational longevity, timely maintenance is necessary to prevent expensive repair works and unplanned production outages. Technologies, such as AI, machine learning, and the internet of things (IoT) add enormous value to predictive maintenance strategies.
Global Data’s thematic report, this Maintenance in Oil and Gas’, explores the use of predictive maintenance technologies in the oil and gas industry. It benchmarks the oil majors, such as BP, Chevron, ExxonMobil, Total Energies, and Shell, for their adoption of these technologies. It also identifies the various trends influencing the them
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Ravindra Puranik, Oil and Gas Analyst at Global Data, comments: “Predictive maintenance enables decision-makers to schedule maintenance activities without affecting the normal functioning. These insights can also be utilized to determine whether any machinery or infrastructure requires a substantial overhaul. It’s strategies have evolved in the oil and gas industry to harness newer digital technologies for improved prediction models.”
Apart from helping set up more agile operations in newer projects, predictive maintenance also helps extend the lifetime of ageing assets. It also aids to detect unwanted leakages that contribute to emissions. Thus, it can help oil and gas companies to efficiently fulfil their ESG obligations.
Predictive maintenance capability is becoming increasingly useful in the oil and gas industry due to competitive energy market scenarios. It helps maximize the operational life of the equipment and infrastructure by using an innovative data-driven approach to assess the state of the field equipment or infrastructure and provide a detailed picture of its expected operating life.
Puranik continues: “The proficiency of digital technologies has grown tremendously in the last few decades. The advancements in sensors, connectivity networks, and computing power, offer a strong foundation for the adoption of predictive maintenance strategies.”
Several prominent integrated oil companies (IOCs) have actively sought to digitalize their operations by employing technologies, such as AI, IoT, cloud computing, big data, and others. This has led to the generation of a vast amount of data from routine oil and gas operations. Growing digitalization has facilitated the adoption of predictive maintenance technologies in the industry.
Puranik concludes: “A Day of unplanned downtime of an oilfield, pipeline, or refinery can incur over a million dollars in losses for the operator. This maintenance helps to identify potential problem areas and resolve them in a timely manner. It could be profitable to implement enterprise-wide predictive maintenance strategies in the long-run.”