Award Abstract # 1663709
CyberSEES: Type 2: Collaborative Research: Real-time Ambient Noise Seismic Imaging for Subsurface Sustainability

NSF Org: CCF
Division of Computing and Communication Foundations
Recipient: UNIVERSITY OF GEORGIA RESEARCH FOUNDATION, INC.
Initial Amendment Date: November 2, 2016
Latest Amendment Date: November 2, 2016
Award Number: 1663709
Award Instrument: Standard Grant
Program Manager: David Corman
CCF
 Division of Computing and Communication Foundations
CSE
 Directorate for Computer and Information Science and Engineering
Start Date: August 5, 2016
End Date: December 31, 2019 (Estimated)
Total Intended Award Amount: $444,028.00
Total Awarded Amount to Date: $444,028.00
Funds Obligated to Date: FY 2014 = $444,028.00
History of Investigator:
  • WenZhan Song (Principal Investigator)
    wsong@uga.edu
Recipient Sponsored Research Office: University of Georgia Research Foundation Inc
310 E CAMPUS RD RM 409
ATHENS
GA  US  30602-1589
(706)542-5939
Sponsor Congressional District: 10
Primary Place of Performance: University of Georgia
310 East Campus Rd
Athens
GA  US  30602-1589
Primary Place of Performance
Congressional District:
10
Unique Entity Identifier (UEI): NMJHD63STRC5
Parent UEI:
NSF Program(s): CyberSEES
Primary Program Source: 01001415DB NSF RESEARCH & RELATED ACTIVIT
Program Reference Code(s): 8208
Program Element Code(s): 821100
Award Agency Code: 4900
Fund Agency Code: 4900
Assistance Listing Number(s): 47.070

ABSTRACT

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).

Real-time imaging of shallow earth structures is essential to assess the sustainability and potential hazards of geological structures. The ability to deploy large wireless sensor arrays in challenging environments is significant for any real-time hazard monitoring and early warning system. The new approach taken is general, and can be implemented as a new field network paradigm for real-time imaging of highly dynamic and complex environments, including both natural and man-made structures. Results from this research will be shared with Yellowstone National Park management (NPS), rangers, and staff. The real-time subsurface images can be used in visitor education centers, official handouts, ranger led field trips, and for public safety management. The educational activities of this project include enhancing undergraduate and graduate curricula and research programs at the three collaborative universities, and the project provides many opportunities for a collaborative cross-disciplinary exchange of ideas among them.

PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH

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(Showing: 1 - 10 of 27)
Liang Zhao and WenZhan Song "Decentralized Consensus in Distributed Networks" International Journal of Parallel, Emergent and Distributed Systems , 2016 10.1080/17445760.2016.1233552
Kohler, MD and Allam, A and Massari, A and Lin, F-C "Detection of Building Damage Using Helmholtz Tomography" Bulletin of the Seismological Society of America , v.108 , 2018 , p.2565--257
Bowden, Daniel C and Tsai, Victor C and Lin, Fan-Chi "Amplification and attenuation across USArray using ambient noise wavefront tracking" Journal of Geophysical Research: Solid Earth , v.122 , 2017
Chengwei Zhou and Yujie Gu and Wen-Zhan Song and Yao Xie and Zhiguo Shi "Robust Adaptive Beamforming Based On DoA Support Using Decomposed Coprime Subarrays" The 41st IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2016) , 2016 10.1109/ICASSP.2016.7472225
Fangyu Li and Maria Valero and Yifang Cheng and Tong Bai and WenZhan Song "Distributed Sensor Networks based Shallow Subsurface Imaging and Infrastructure Monitoring" IEEE Transactions On Signal And Information Processing Over Networks , 2020
Fangyu Li and Maria Valero and Yifang Cheng and WenZhan Song "High-Frequency Time-Lapse Seismic Spatial Autocorrelation Imaging Shallow Velocity Variations" IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing , 2020
Fangyu Li and Rui Xie and WenZhan Song and Hui Chen "Optimal Seismic Reflectivity Inversion: Data-driven lp-loss-lq-regularization Sparse Regression" IEEE Geoscience and Remote Sensing Letters , 2019
Fangyu Li and Tong Bai and Nori Nakata and Bin Lyu and WenZhan Song "Efficient Seismic Source Localization Using Simplified Gaussian Beam Time Reversal Imaging" IEEE Transactions on Geoscience and Remote Sensing , 2020
Fangyu Li and WenZhan Song "Automatic arrival identification system for real-time microseismic event location" SEG Technical Program Expanded Abstracts 2017 , 2017 , p.2934--293 10.1190/segam2017-17667176.1
Fangyu Li and Yan Qin and WenZhan Song "Waveform Inversion Assisted Distributed Reverse-Time Migration for Microseismic Location" IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing , 2019 10.1109/JSTARS.2019.2904206
Farrell, Jamie and Wu, Sin-Mei and Ward, Kevin M and Lin, Fan-Chi "Persistent noise signal in the FairfieldNodal three-component 5-Hz geophones" Seismological Research Letters , v.89 , 2018 , p.1609--161
(Showing: 1 - 10 of 27)

PROJECT OUTCOMES REPORT

Disclaimer

This Project Outcomes Report for the General Public is displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed in this Report are those of the PI and do not necessarily reflect the views of the National Science Foundation; NSF has not approved or endorsed its content.

This project creates a real-time Ambient Noise Seismic Imaging system in sensor networks, which enables the study and monitoring of the subsurface sustainability and potential hazards. The system is comprised of a self-sustaining seismic sensor network that can autonomously perform in-network computing of the 3D shallow earth structure images based on ambient seismic noises. We have developed distributed communication-efficient algorithms for in-situ imaging,  including new fog computing architectures and non-uniform subsampling of Fourier transform of the raw signal; delay map recovery algorithm from local cross-correlation using matrix-completion; statistical change-point detection based algorithms for event picking; and multiple new ambient noise imaging methods were developed to best utilize the dense array configuration and adopt to the unique noise environment. We have also successfully demonstrated that high-resolution subsurface imaging can be achieved by combining rapid deployment of geophone dense arrays and passive seismic imaging. For example, double beamforming tomography was developed to image detailed 2D velocity structure across linear dense arrays and interferometry based polarization analysis was developed to resolve spatial-temporal hydrothermal tremor source migration beneath iconic Yellowstone geysers. Throughout this project, we have applied our techniques to better understand a variety of interesting geological structures in the US, including the subsurface infrastructure imaging and security, the magmatic and hydrothermal system of Yellowstone, the subduction structure associated with the Juan de Fuca Plate, fault zone structure in Southern California, and the continental scale lithospheric structure across the US. The results of the studies are published in multiple prestigious peer reviewed journals and conferences of computer, electrical and geological fields. Other broader impacts include the support of six PhD students (four females) and one postdoc. Some have graduated as early career faculty and scientists.


Last Modified: 02/17/2020
Modified by: Wenzhan Song

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