Skip to content Skip to navigation

Parashar receives NSF BIGDATA grant.

Wednesday, November 4, 2015

Congratulations to Prof. Manish Parashar, who has just received an NSF BIGDATA grant for his project entitled “Fractured Subsurface Characterization using High Performance Computing and Guided by Big Data.” The grant is for an amount of $214571, and the project runs from September 2015 to September 2018. The project is a collaborative effort with Prof. Mary F. Wheeler (Lead PI) and Prof. Mrinal Sen (co-PI) of The University of Texas at Austin, and Prof. Sanjay Srinivasan (Co-PI), of the Pennsylvania State University.Natural fractures act as major heterogeneity in the subsurface that control flow and transport of subsurface fluids and chemical species. Their importance cannot be underestimated, because their transmissivity 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. This project will address the following key BIG data and computer science challenges: (1) Computation of seismic wave propagation in fractured media; (2) BIG data analytics for inferring fracture characteristics; (3) High Performance Computation of flow and transport in fractured media; and (4) Integration of data from disparate sources for risk assessment and decision-making. This will enable design of technologies for addressing key societal issues such as safe energy extraction from the surface, long-term sequestration of large volumes of greenhouse gases, and safe storage of nuclear waste. The project will provide interdisciplinary training for a team of graduate students and postdoctoral fellows. Outreach to high schools teachers and minorities through a planned workshop will inspire interest in environmental green-engineering, mathematics, and computational science. Numerous applications will benefit from this research, including Computer and Information Science and Engineering (CISE), Geosciences (GEO), and Mathematical and Physical Sciences (MPS).]]>