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===Oilfield Equipment Maintenance===
In the realm of oilfield equipment maintenance, Prescriptive Analytics can optimize configuration, anticipate and prevent unplanned downtime, optimize field scheduling, and improve maintenance planning.<ref>{{cite journal |last=Presley, Jennifer |title=ESP for ESPs |journal=Exploration & Production |date=July 1, 2013}}</ref> According to [[General Electric]], there are more than 130,000 electric submersible pumps (ESP's) installed globally, accounting for 60% of the world's oil production.<ref>{{cite web | url=http://www.ge-energy.com/products_and_services/products/electric_submersible_pumping_systems/ | title=Electric Submersible Pumping Systems | GE Energy }}</ref> Prescriptive Analytics has been deployed to predict when and why an ESP will fail, and recommend the necessary actions to prevent the failure.<ref>{{cite journal |last=Wheatley, Malcolm |title=Underground Analytics |journal=DataInformed |date=May 29, 2013}}</ref>
In the area of [[health, safety and environment]], prescriptive analytics can predict and preempt incidents that can lead to reputational and financial loss for oil and gas companies.
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