Understanding ESPs Through Machine Learning

Electric submersible pumps (ESPs) are one of the go-to mechanisms for artificial lift, with as many as 150,000 ESPs in operation around the world, according to Schlumberger. Although ESPs are remarkably efficient for pumping large volumes, they are highly susceptible to prolonged failures. Post-mortems on ESPs reveal that produced gas and solids have proven to be their undoing. But with the advent of Big Data and machine learning, predicting when an ESP may fail well in advance of any potential mechanical problems is improving. At the Unconventional Resources Technology Conference held in July in Austin, Texas, Devon Energy reported on its recent efforts to do just that.