Predictive maintenance (PdM) is indisputably the future for the oil and gas industry, which relies on reliably functioning physical assets for the production that drives revenue and growth. The benefits of a predictive maintenance approach are clear. As sensors and machine learning work together to pinpoint issues in advance, operators…
Neil Eklund is one of the most innovative, forward-thinking researchers in the field of Prognostics and Health Management (PHM). With 20 years of deep technical experience in machine learning, data science and industrial analytics, Dr. Eklund serves as principal data scientist at Novity, the industrial predictive maintenance venture recently launched by Xerox PARC. Before joining Novity, Dr. Eklund served as the chief data scientist and scientific advisor at Schlumberger, where his work led to the creation of a new PHM-focused business segment, Technology Lifecycle Management. Prior to that, he spent 14 years in the machine learning laboratory at GE Global Research where he was responsible for bringing advanced analytics as a shared service to GE businesses for better and faster utilization of the company’s industrial data assets. Dr. Eklund holds a PhD in Machine Learning and he is also a PHM Society Fellow.
Oil and gas operations are commonly found in remote locations far from company headquarters. Now, it's possible to monitor pump operations, collate and analyze seismic data, and track employees around the world from almost anywhere. Whether employees are in the office or in the field, the internet and related applications enable a greater multidirectional flow of information – and control – than ever before.