{"id":64,"date":"2016-06-22T14:18:02","date_gmt":"2016-06-22T14:18:02","guid":{"rendered":"http:\/\/sensorweb.engr.uga.edu\/?page_id=64"},"modified":"2020-05-07T00:19:34","modified_gmt":"2020-05-07T00:19:34","slug":"ansi","status":"publish","type":"page","link":"https:\/\/sensorweb.engr.uga.edu\/index.php\/ansi\/","title":{"rendered":"Real-time Ambient Noise Seismic Imaging for Subsurface Sustainability"},"content":{"rendered":"

Funded by\u00a0NSF CyberSEES Program<\/a> (NSF-1663709, $1.2M, 1\/2015-1\/2020) and Jet Propulsion Laboratory (10\/2019-10\/2021)<\/strong><\/p>\n

Summary<\/h2>\n

This project creates a real-time Ambient Noise Seismic Imaging system, to study and monitor the subsurface sustainability and potential hazards of geological structures. Understanding and addressing the subsurface sustainability has significant impact on the natural, social, and economic issues of the region and across the globe. The system is comprised of a self-sustainable sensor network of geophones that can autonomously perform in-network computing of the 3D shallow earth structure images based on ambient noise alone. The project will study the subsurface sustainability of Long Beach, California and Yellowstone using their existing seismic array datasets and design the imaging system accordingly. In the late stages of the project, a field demonstration of the prototype system in Yellowstone expects to image the subsurface of some geysers. The techniques developed find further utility in monitoring and understanding the dynamics of subsurface oil, mine and geothermal resources, alongside concomitant hazards in oil exploration, mining, hydrothermal eruption, and volcanic eruption).<\/p>\n

\"ANSI\"<\/p>\n