Distributed Acoustic Sensing (DAS) Research Coordination Network (RCN)

Subscribe to the DAS mailing list through the IRIS Message Center here. Messages can be sent to das@lists.ds.iris.edu.

Motivation

Distributed Acoustic Sensing (DAS) is a transformative technology in geosciences and engineering. DAS records ground motion along fiber-optic cables that are comparable to those obtained by single-component accelerometers or geophones. The transformative potential arises from the fiber itself being the sensor and allowing for a spatially continuous measurement. The fiber can be tens of kilometers in length and it can be located in shallowly buried trenches, in boreholes, or in some combination. The fiber geometry can encompass a large volume that can be tens of cubic kilometers in size. DAS inherently possesses properties of a large-N seismic array. The rapidly increasing interest in DAS arises from its potential to be used in continuous arrays that are kilometers in length while providing spatial resolution of meters and frequency response from millihertz to kilohertz.

DAS applications in geosciences and engineering are numerous and growing including opportunities for deploying early warning systems for earthquakes, volcanic eruptions, continental and marine landslides, and avalanches, and for monitoring reservoirs and civil infrastructure. DAS can complement and supplement conventional seismic sensors and arrays already used across a wide range of disciplines.

The DAS Research Coordination Network (RCN) has four main goals:

  1. Identify applications of DAS and develop a network of potential DAS users.
  2. Train a community of DAS users in the acquisition, handling and processing of DAS data.
  3. Identify needed technical development (engineering and scientific).
  4. Identify major challenges and next steps for supporting DAS science beyond the RCN.

The proposed DAS RCN will use the mechanisms of workshops and short courses to engage a range of potentially interested groups. Workshops will focus on producing white papers in areas of science applications, data management, and future technology developments. Short courses will provide hands-on instruction in DAS-specific subjects such as data analysis, data management, and best field practices. The RCN will run for three years, after which it is expected that DAS will become permanently incorporated into new or existing facilities, and the community will become self-sustaining through community-wide facilities and professional societies. This research coordination network is supported by funding from the National Science Foundation under award EAR-1948737.

 

Left) Map of a subsection of the ESNet Dark Fiber Testbed in West Sacramento, California. Right) Example earthquakes recorded by the Sacramento Dark Fiber DAS array, a subset of the ESNet Dark Fiber Testbed. From Ajo-Franklin et al., Scientific Reports, 2019, DOI: 10.1038/s41598-018-36675-8.

Featured Articles

Opportunities for Participation

The DAS RCN plans to gather community input through a variety of methods.  A DAS mailing list is available through the IRIS Message Center at: https://ds.iris.edu/message-center/topic/das/ to provide a forum for discussion and for announcements of events, workshops, meetings, or other opportunities in the DAS community. Please consider joining us at one or more of the following events to provide your input and get involved.

Calls for contributions:

  • DAS RCN Global Monitoring Month (February 1-28, 2023 | Globally)

Upcoming events (RCN and community organized):

Past events:

Steering Committee

Comments are welcome, and we encourage you to get in touch with the steering committee members with any suggestions, questions, or concerns. Queries can also be directed to das-rcn@iris.edu.

Herbert Wang University of Wisconsin-Madison Co-PI
Scott Tyler University of Nevada, Reno Co-PI
Robert Woodward IRIS Co-PI
Kasey Aderhold IRIS Co-PI
Jonathan Ajo-Franklin Rice University  
Matt Becker California State University, Long Beach  
Dante Fratta University of Wisconsin-Madison  
Mark Hausner Desert Research Institute  
Zuyuan He Shanghai Jiao Tong University  
Charlotte Krawczyk GFZ-Potsdam  
Yingping Li BlueSkyDas  
Nate Lindsey FiberSense  
Eileen Martin Colorado School of Mines  
Whitney Trainor-Guitton Colorado School of Mines/Zanskar Geothermal & Minerals  
Zhongwen Zhan Caltech  
Lucas Zoet University of Wisconsin-Madison  
Danica Roth Colorado School of Mines  
DAS RCN Meeting Reports
2020: March  April  May  June  July  August  September  October  November
2021: January  February  April  June  August  October
2022: January  February March  April May July October 


DAS RCN Community Forum Recordings
2022: February April 

Working Groups

In addition to attending RCN-wide events, you can join one or more topical working groups simply by sending an email to the lead whose email is provided under the Working Group tab. They range in membership from half a dozen to two dozen. They meet with frequencies that range from monthly to twice a year. Meetings often include short presentations in order to discuss current topics. Working groups prepare resources for the RCN, such as bibliographies, event notices, and write brief reports on the state-of-the-art in their topical areas. 

Please reach out to the working group leads to get involved. If groups have regular meeting times these are noted in the table below.

Data Management Robert Mellors (UCSD) rmellors@ucsd.edu 2nd Tuesdays at 10am ET
Energy Technologies and CO2 Monitoring Aleksei Titov (Fervo Energy) and Marie Macquet (Carbon Management Canada) aleksei.titov@fervoenergy.com and Marie.Macquet@cmcghg.com
Earthquake and Array Seismology Cliff Thurber (University of Wisconsin-Madison) cthurber@wisc.edu
Instrumentation Kasey Aderhold (IRIS) and Zuyuan He (Shanghai Jiao Tong University) kasey@iris.edu and zuyuanhe@sjtu.edu.cn
Machine Learning Eileen Martin (Colorado School of Mines) and Whitney Trainor-Guitton (Colorado School of Mines/Zanskar Geothermal & Minerals) eileenrmartin@mines.edu and wtrainor@mines.edu 3rd Thursdays at 1pm ET
Engineering and Urban Seismology Dante Fratta (University of Wisconsin-Madison) and Biondo Biondi (Stanford) fratta@wisc.edu and biondo@sep.stanford.edu
Hydrology Mark Hausner (DRI) mark.hausner@dri.edu
Geomorphology Danica Roth (Colorado School of Mines) and Claire Masteller (WUSTL)

droth@mines.edu and cmasteller@wustl.edu

Cryosphere Luke Zoet (University of Wisconsin-Madison) and Brad Lipovsky (University of Washington) lzoet@wisc.edu and bpl7@uw.edu
Volcanic and Seismic Hazard Monitoring Lotte Krawczyk (GFZ Potsdam) lotte@gfz-potsdam.de
Marine Geophysics Nate Lindsey (FiberSense) nate.lindsey@fiber-sense.com 
Geotechnical Matt Becker (Cal State-Long Beach) matt.becker@csulb.edu 
Early-Career DAS Network (Pigtails) Nate Lindsey (FiberSense) nate.lindsey@fiber-sense.com 
Research and Development Test Sites Andreas Wuestefeld (NORSAR) Andreas.Wuestefeld@norsar.no 

 

Structure of a fault damage zone and trapped phases from a local earthquake as recorded by a fibre-optic cable on Reykjanes Peninsula, Iceland. From Jousset et al., Nature Communications, 2018, DOI: 10.1038/s41467-018-04860-y.

New to DAS?

If you are new to Distributed Acoustic Sensing and are looking for places to start, please see the following resources.

Frequently Asked Questions… and Answers!

  • What are average sample rates and data volumes?
    • That it is a tough question to answer as it would depend on applications. For example, in seismological applications sampling rates less than 100 Hz are adequate, for monitoring leaks on pipelines 1 kHz would be more appropriate, and for audio recording higher sampling rates (> 4kHz) would be required. However the data volume also depends on the number channels on the array and the length of the recording. The volume of data could be controlled with pretriggering while monitoring. 
    What is the difference between channel separation and gauge length?
    • Gauge length is the section of fiber that DAS uses to capture scattered signals. It is like a fingerprint that DAS uses to sense strains between consecutives laser pulses. The center of the change length is a channel and the distance between channels is the channel separation. The channel separation might be smaller than the gauges length, so channel overlap.
    Is calibration necessary? How is it done?
    • It is necessary for applications involving amplitudes, such as moment tensor estimation. It can be done in the field by comparing known seismometer instrument response and DAS response. Another way for calibration is using fiber stretchers in the lab and comparing applied strain with recorded strain.
  • What is the future of DAS? Other than being optimized for earthquake source studies?
    • There are a number of current applications for DAS beyond earthquake source studies: from near surface geophysics, to surveillance, to civil infrastructure monitoring, to evaluation of deformations, to early warning systems.There is plenty of work in those areas. There are a few leads on the future use of DAS including the increasing use of dark fiber, using arrays to monitor storms, tapping into undersea cables, extending range by running DAS signals across internet communication devices. But the future really depends on researchers and investigators finding new and exciting applications for DAS.