Real-time Ambient Noise Seismic Imaging for Subsurface Sustainability

Funded by NSF CyberSEES Program (NSF-1663709, $1.2M, 1/2015-1/2020) and Jet Propulsion Laboratory (10/2019-10/2021)


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.

Sensor Devices

Project Updates

During the first stages, the USArray Transportable Array has been used to obtain seismic-data. The Transportable Array is a network of 400-high quality broadband seismographs and atmospheric sensors that have been operated at temporary sites across the conterminous United States from west to east in regular grid pattern.

In the following map, it can be visualized 1211 stations used for this project stage. (Click on each station to visualize station names).



  • Maria Valero (UGA)
  • Sili Wang (UGA)
  • Sin-Mei Wu (UU)
  • Shixiang Zhu (GT)
  • Hongao Yang (GT)


Fangyu Li; Maria Valero; Yifang Cheng; 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.

Danye Xu; Bingqing Song; Rui Zhang; Yao Xie; Sin-Mei Wu; Fan-Chi Lin; WenZhan Song, Low-rank matrix completion for distributed ambient noise imaging systems. 53nd Asilomar Conference on Signals, Systems and Computers, 2019.

Jose Clemente; Fangyu Li; Maria Valero; An Chen; WenZhan Song. ASIS: Autonomous Seismic Imaging System with In-situ Data Analytics and Renewable Energy. IEEE Systems Journal, 2019.

Maria Valero; Fangyu Li; Jose Clemente; WenZhan Song. Distributed and Communication-Efficient Spatial Auto-Correlation Subsurface Imaging in Sensor Networks. Sensors, 19 (11), 2019.

Sili Wang; Fangyu Li; Maria Valero; Wenzhan Song. Tracking Underground Moving Targets with Wireless Seismic Networks. 5th IEEE International Conference on Smart Computing (SMARTCOMP), 2019.

Fangyu Li; Yan Qin; 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.

Maria Valero; Fangyu Li; WenZhan Song. Smart Seismic Network for Shallow Subsurface Imaging and Infrastructure Security. International Journal of Sensor Networks (IJSNet), 2019.

WenZhan Song; Fangyu Li; Maria Valero; Liang Zhao. Toward Creating Subsurface Camera. Sensors, 19 (2), pp. 301, 2019.

Maria Valero; Fangyu Li; Sili Wang; Fan-Chi Lin; WenZhan Song. Real-time Cooperative Analytics for Ambient Noise Tomography in Sensor Networks. IEEE Transactions on Signal and Information Processing over Networks, 2018

Maria Valero; Fangyu Li; Xiangyang Li; WenZhan Song. Imaging Subsurface Civil Infrastructure with Smart Seismic Network. 37th IEEE International Performance Computing and Communications Conference (IPCCC) 2018

Rui Xie; Fangyu Li; Zengyan Wang; WenZhan Song. Large Scale Randomized Learning guided by Physical Laws with Applications in Full Waveform Inversion. 6th IEEE Global Conference on Signal and Information Processing (GlobalSIP), 2018.

Liyan Xie; Yao Xie; Sin-Mei Wu; Fan-Chi Lin; WenZhan Song. Communication Efficient Signal Detection for Distributed Ambient Noise Imaging. The 52nd Asilomar Conference on Signals, Systems and Computers, 2018.

Fangyu Li; WenZhan Song. Automatic arrival identification system for real-time microseismic event location. SEG Technical Program Expanded Abstracts 2017, 2017.

Fangyu Li; Rui Xie; WenZhan Song; Tao Zhao; Kurt Marfurt. Optimal Lq norm regularization for sparse reflectivity inversion. SEG Technical Program Expanded Abstracts 2017, 2017.

Maria Valero, Goutham Kamath, Jose Clemente, Fan-Chi Lin, Yao Xie, and WenZhan Song. Real-time Ambient Noise Subsurface Imaging in Distributed Sensor Networks. The 3rd IEEE International Conference on Smart Computing (SMARTCOMP 2017), 2017.

Liang Zhao; WenZhan Song; Xiaojing Ye; Yujie Gu. Asynchronous Broadcast-based Decentralized Learning in Sensor Networks. International Journal of Parallel, Emergent and Distributed Systems, 2017.

Janire Prudencio; Yosuke Aoki; Minoru Takeo; Jesus Ibanez; Edoardo Del Pezzo; WenZhan Song. Separation of scattering and intrinsic attenuation at Asama volcano (Japan): Evidence of high volcanic structural contrastsJournal of Volcanology and Geothermal Research, 333 pp. 96-103, 2017.

Shuang Li; Yang Cao; Christina Leamon; Yao Xie; Lei Shi; WenZhan Song. Seismic event picking via sequential change-point detection. The 54th Annual Allerton Conference on Communication, Control, and Computing, 2016.

Goutham Kamath; Lei Shi; WenZhan Song; Jonathan Lees. Distributed Travel-time Seismic Tomography in Large-Scale Sensor Networks. Journal of Parallel and Distributed Computing (JPDC), 89 2016.

Lei Shi; WenZhan Song; Fan Dong; Goutham Kamath. Sensor Network for Real-time In-situ Seismic Tomography. International Conference on Internet of Things and Big Data (IoTBD 2016), 2016.

Sufri, O., Xie, Y., Lin, F-C., and W. Song, 2015. Optimization of Ambient Noise Cross-Correlation Imaging Across Large Dense Array. American Geophysical Union 2015 Fall Meeting, San Francisco.