Machine Learning Goes Viral In Oil Patch

Ask an upstream operator which area in the oil and gas patch they expect to have reliability problems and the answer will commonly come back "compressors." Compressors, used to increase the pressure of natural gas or air to improve flow, are the first on the list, said Ron Beck, industry marketing director for energy at Aspen Technology, an asset optimization software firm. But with no end to potential oilfield malfunctions, some oil and gas companies have turned to machine learning--a process in which software is used to search data, detect patterns and assess the likelihood of future failures. The software uses algorithms--a series of calculations and automated reasoning tasks--to help overcome potentially troublesome equipment. The digital shift is part of the oil and gas industry's acceptance of more efficient and cost-effective technologies to assist in extracting and producing oil and gas in a range-bound commodity-price environment.