A day of unplanned downtime of an oilfield, pipeline, or refinery can incur over a million dollars in losses for the operator, however, predictive maintenance (PM) helps to identify potential problem areas, which can be readily addressed.
It is profitable to implement PM strategies in the long run as it enables decision-makers to schedule maintenance activities without affecting normal functioning. These insights can also be utilized to determine whether any machinery or infrastructure requires a substantial overhaul. These strategies have evolved in the oil and gas industry and have gradually harnessed newer digital technologies to build improved prediction models.
Predictive maintenance-related contractual activity depicted in the figure above showcases the diversity across vendors and region.
Several prominent integrated oil companies have actively sought to digitalise 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 digitalisation has facilitated the adoption of PM technologies in the industry.
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 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.
Further details about various trends influencing the predictive maintenance theme, contracts analysis of maintenance activities, and the adoption of predictive maintenance among oil and gas companies is analysed in GlobalData’s new theme report, ‘Predictive Maintenance in Oil and Gas’.
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