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Report Identifies Technologies for Increased Productivity and Reduced Risks in Subsurface Energy Systems

A team led by NETL and Carnegie Mellon University’s Wilton E. Scott Institute for Energy Innovation and consisting of experts from national laboratories, academia and private industry, have released a report summarizing information presented in a workshop called “Real-Time Decision-Making for the Subsurface.” The report is available here.

Several dozen technical experts from industry, universities, national laboratories, and the U.S. Department of Energy (DOE) convened for two days in Pittsburgh to discuss the current state of technology that could enable autonomous monitoring and subsurface control for unconventional oil and gas recovery and carbon storage. However, the approaches discussed have applications for other subsurface activities, such as geothermal energy, subsurface energy storage, and enhanced oil recovery.

The report indicated that real-time decision-making for subsurface energy systems is a long-term, transformational goal that is likely to take a decade or more to achieve. However, several technologies that can enable better decision-making for increased productivity and reduced risks are ready for development in the near-term.

“Collectively, these approaches have the potential to completely change the way that oil and gas and other subsurface fields are operated,” the report’s authors wrote.

According to the report, technological advances such as machine learning (ML), data analytics and data management have expanded and now provide an array of resources that can be leveraged for subsurface applications. In addition, novel sensors can now provide information that was not available a decade ago. Together, the technologies under development may revolutionize how the subsurface is imaged in the coming decade.

“Developments in sophisticated physics-based simulators, coupled with high-performance computing capabilities, enable better prediction of subsurface systems than ever before,” the report indicated. “Finally, ML, computational speed, and the ability to handle very large data streams have markedly advanced. In short, it is the ideal time to pursue the development of real-time decision-making capabilities that could transform approaches used to develop subsurface energy systems.”

Grant Bromhal, senior fellow for geologic and environmental systems at NETL, served as editor for the report. 
The report’s authors included: Giorgia Bettin, geothermal research manager at Sandia National Laboratory; Mike Brudzinski, professor at Miami University; Alan Cohen, director of the Office of Oil and Natural Gas Research, Department of Energy’s Office of Fossil Energy; George Guthrie, technical project manager at Los Alamos National Laboratory; Paul Johnson, senior fellow and technical staff member at Los Alamos National Laboratory; Lewis Matthews, data scientist at CrownQuest Operating LLC; Srikanta Mishra, senior research leader, Battelle; and Derek Vikara subsurface analysis program manager, KeyLogic Systems Inc.