Customer Profile: Apache Corporation


Apache turned to Ayata software for Prescriptive Analytics with Hybrid Data to help improve the performance of their ESPs. The first application in the Prescriptive Analytics process predicts ESP failures by taking into account data about pumps, production, completion, and subsurface characteristics. The software then prescribes actions to reduce pump failures and mitigate production losses. The second application predicts and prescribes the right pump for the right well to maximize production. The third application of the software helps Apache evaluate fields for their potential production capacity by taking into account ESP performance, before acquiring these fields.


According to GE, more than 130,000 ESPs operate around the world, generating 60 percent of global oil production. “Just a 1 percent improvement in global ESP performance would provide over a half-million additional barrels of oil per day given the amount of oil pumped through ESPs,” says Apache CTO Mike Bahorich. “Multiply that by $100 per barrel and you’d have $53 million-plus per day just from improvements made to ESPs.”


ESPs for ESPs?
Hart E&P Magazine
July 2013

Underground Analytics: The Value in Predicting When an Oil Pump Fails
DataInformed Magazine
May 2013

Atanu BasuCustomer Profile: Apache Corporation

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