Unused Fiber-Optic Cables Repurposed as Seismic Sensors

During the 1990s, telecommunications companies installed thousands of kilometers of fiber-optic cables underground in anticipation of the dot-com boom. What can we do now with all of that unused dark fiber? Turn it into an extensive seismic activity sensor, according to a recent study.

The team used a relatively new technique called distributed acoustic sensing, or DAS, to measure how seismic waves affect the underground cables. “The neat thing about the technique is that you can use it to measure seismic waveforms at a very large number of locations on an existing fiber,” Jonathan Ajo-Franklin, lead author on the study, told Eos. “Dark fiber is just a term for fiber that has been installed as part of a network but isn’t currently used for communications,” he explained.

When applied to existing dark-fiber networks, DAS gives the same data at a lower cost than a comparable number of above-ground seismic stations, he said.

Earthquakes Near and Far

In a fiber-optic cable, pulses of light that contain data travel along glass or plastic fibers. The fibers are designed to perfectly reflect and trap the signal within the filaments, but if a filament has any imperfections, a small amount of light scatters back toward the source. By studying changes to the backscattered light in underground cables, scientists can infer how movement in the ground—say, from seismic waves—strains the fibers. This technique, DAS, has been used to study localized seismic activity in Alaska, California, and Iceland.

Ajo-Franklin, who is a geophysicist at Lawrence Berkeley National Laboratory in Berkeley, Calif., and his team have now demonstrated that DAS can detect and monitor seismic activity across a much larger region and also detect distant quakes. “We knew that we could do distributed acoustic sensing, and we knew the fiber was in the ground, so we had a good feeling that we would be able to record something,” he said. “The big question was what the quality of the data would be and what kind of applications it could be used for.”

The researchers studied a 27-kilometer stretch of dark fiber near Sacramento, Calif. They recorded 7 months of passive seismic data and got measurements of the seismic wave field 500 times per second every 2 meters along the cable.

The sampling rate let the researchers monitor both low- and high-frequency seismic activity. With this, the researchers detected earthquakes that ranged from 4.4 to 8.1 in magnitude and some that were more than 7,700 kilometers away. They looked closely at the M8.2 earthquake that struck Chiapas, Mexico, in September 2017 to measure postevent seismic activity at low frequencies.

The team also used ambient seismic noise from cars, trucks, and a nearby train line to map the subsurface. “There’s a train that runs colinear to the cable, and we were using energy from that train to do seismic imaging underneath the cable,” said Ajo-Franklin. The high spatial density of the measurements let the researchers create a 2-D map of the seismic wave field beneath different sections of cable and also measure the depth of groundwater along the fiber.

The team published these results last month in Scientific Reports.

Seismic Networks of Opportunity

The results show that “there is quite a bit more variability in the subsurface than what could have been observed through direct measurements in a well,” according to Eileen Martin, an assistant professor of computational modeling at Virginia Polytechnic Institute and State University in Blacksburg who was not involved with the research. “It would not be affordable to drill test wells with this kind of [spatial] density, and the ambient noise analysis of dark fiber provided a cost-effective solution to resolve this subsurface variability,” she told Eos.

This study “is a roadmap to applying DAS technology,” Herbert Wang, a professor of geomechanics at the University of Wisconsin–Madison, told Eos. “DAS can unlock the telecommunications infrastructure to be seismic networks of opportunity on local and regional scales and maybe on up to continental and ocean-basin scales,” said Wang, who was not involved with this study.

The technique’s potential application to earthquake monitoring is “compelling,” Martin said. “These high-density, continuous measurements increase the likelihood that a sensor is near any small earthquake source. This hopefully means finding more small earthquakes and fixing the current biases in small quake observation counts, [as well as] faster detection of earthquakes for early earthquake warning systems.”

A Versatile Seismic Tool

The team noted that the combination of dark-fiber networks and DAS in general could provide high-quality monitoring for many seismically interesting phenomena. Subsurface hydrology, melting ice sheets, and maybe even geodetic studies might benefit from dark-fiber seismology, Ajo-Franklin said.

Ajo-Franklin said that DAS also shows a lot of potential for measuring seismic activity offshore. Many seismically active areas 20 to 30 kilometers offshore don’t have any offshore monitoring, he said, but fiber cables installed offshore could help monitor those areas in situ.

Dark-fiber networks preferentially run beneath highways and train tracks, Ajo-Franklin noted, so DAS would be particularly useful for studying subsurface geology and seismology in urban areas. Seismology with DAS could also be beneficial in areas that are not tectonically active but experience induced seismicity from human activity, he said.

“There’s a lot of fiber already in the ground for telecom applications,” Ajo-Franklin said. “Fiber with no information on it is not very valuable at all.”

—Kimberly M. S. Cartier (@AstroKimCartier), Staff Writer

Citation:

Cartier, K. M. S. (2019), Unused fiber-optic cables repurposed as seismic sensors, Eos, 100, https://doi.org/10.1029/2019EO118025. Published on 08 March 2019.

Text © 2019. AGU. CC BY-NC-ND 3.0
Except where otherwise noted, images are subject to copyright. Any reuse without express permission from the copyright owner is prohibited.

Text © 2019. AGU. CC BY-NC-ND 3.0
Except where otherwise noted, images are subject to copyright. Any reuse without express permission from the copyright owner is prohibited.