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Natural fractures act as major heterogeneity in the subsurface that control flow and transport of subsurface fluids and chemical species. Their presence may result in undesired migration during geologic sequestration of CO2, they strongly control heat recovery from geothermal reservoirs, and they may lead to induced seismicity due to fluid injection into the subsurface. Advanced computational methods are critical to design subsurface processes in fractured media for successful environmental and energy applications. The recently funded NSF project will address the BIG data and computer science challenges associated with the inference of fracture pattern statistics and computation of the physical processes of wave propagation and flow and transport in fractured media.

An integral aspect of this project is to provide interdisciplinary training for a team of students and research fellows.  While the project budget explicitly includes funding for graduate students and post-doctoral fellows, the involvement of undergraduate student researchers within the project will greatly enhance the diversity of skills within the project team and will help satisfy one of the key goals of the project to reach out to a large community of developers and users of the technologies who will propagate their skills within the society at large. Keeping this important objective in mind, supplemental funding was sought and received in order to support undergraduate researchers in this challenging area.