Song Wins $1.2 Million NSF Grant for Seismic Imaging
The National Science Foundation has awarded a $1.2 million grant to a team of researchers from Georgia State University, Georgia Tech, and the University of Utah for a real-time ambient noise seismic imaging system.
Dr. WenZhan Song is the lead principal investigator for the grant. He is a professor in GSU’s Department of Computer Science and director of the Sensorweb Research Laboratory. GSU will receive $525,000 from the four-year Collaborative Research grant, which was funded by NSF’s Cyber-Innovation for Sustainability Science and Engineering (CyberSEES) Program.
Dr. Song’s system could be used to study and monitor the sustainability of the subsurface (area below the ground surface) and the potential hazards of geological structures. A key part of the system is a sensor network of geophones, which convert ground movement into voltage. The deviations of the measured voltage from ambient seismic noise are used to compute 3D shallow earth structure images.
The team plans to study subsurface sustainability in Long Beach, California, and Yellowstone National Park, first using existing datasets and then designing the imaging system accordingly. In the late stages of the project, a prototype system will be used to image the subsurface of geysers in Yellowstone.
The proposed system could be used for developing early warning systems for natural hazards, such as volcanoes, by determining how close magma is to the surface. It could also benefit oil exploration. Until now, what was going on under the subsurface was only known many days and even months later, because it takes a very long time to process and analyze data from oil exploration instruments. Dr. Song’s system could reduce this time to seconds. The real-time images produced by his system could also be used in Yellowstone visitor education centers, official handouts, and ranger-led field trips, as well as for public safety management.
Both computer scientists and earth scientists are involved in the research. Besides Dr. Song, the team members are Dr. Yao Xie and Dr. Fan-Chi Lin. Dr. Xie is an assistant professor in the School of Industrial and Systems Engineering at Georgia Tech, where she specializes in statistics, big data, and signal/information processing. Dr. Lin is an assistant professor in the Department of Geology and Geophysics at the University of Utah, specializing in seismic interferometry and seismic tomography.