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Hi, everyone. My name is Noha Farghal.
I’m a Mendenhall postdoctoral fellow at the USGS Earthquake Science Center
in Moffett Field, California. Today, I will talk about the potential
of fiber optic sensing in earthquake early warning.
But first I would like to acknowledge and thank
my collaborators, Jessie Saunders and Grace Parker.
Recently, there has been a focus on using data from borehole strainmeters
in earthquake early warning and creating different strain seismology
tools to calculate various source and ground motion parameters from strain.
Using records from the July 2019 Ridgecrest sequence magnitude 7.1
main shock, we demonstrated that reliable magnitude estimates –
the blue and yellow lines – can be derived from strain
through this empirical relation between earthquake moment
magnitudes, peak dynamic strains, and hypocentral distances.
And we showed that incorporating strain would have possibly helped the
ShakeAlert system reach the threshold number of stations for alerting faster
and possibly contributed to a more accurate system performance.
In another recent work, we derived a magnitude scale entirely based on
strain data with corrections for source and site effects.
Which was also tested using the Ridgecrest main shock records
and further confirms the utility of strain data
in providing robust strain magnitude updates.
It is also worth mentioning that this strain-based magnitude scale is
currently used by UNAVCO for strain magnitude estimation.
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We also did a proof of concept for calculating peak ground velocities,
or PGVs, from strain for several recent earthquakes in California
and found that strain-derived PGVs are practically indistinguishable
from seismic-derived ones. And we are currently working on
calculating peak ground accelerations, or PGAs, from strain.
And so far, we are getting promising results comparing
strain-derived and seismic-derived PGAs.
In deriving all these relations, we have been using data from
borehole strainmeters of the USGS, a Network of the Americas networks
along the U.S. West Coast, which are sparse, and it’s quite unlikely
that more such strainmeters will be installed on a large scale in the future
to complement traditional seismic data in earthquake early warning.
So we looked to fiber optic distributed acoustic sensing, or fiber optic DAS,
for its potential for scalability, real-time telemetry, cost-effective dense sensing.
It has been used for years through arrays of different sizes and layouts,
vertical and horizontal arrays, for various applications all over the world.
Dark-fiber-type installations also successfully recorded earthquakes
with high signal-to-noise ratios, and there is a growing discussion now
about how to leverage the extensive network of infrastructure
subsea cables for improving offshore hazard monitoring.
Google is currently working on tracking state of polarization of light
to detect seismic activity over tens of thousands of kilometers
using infrastructure cables. They detected the January 28th, 2020,
magnitude 7.7 earthquake off of Jamaica and were able to
compare their data to those from traditional seismic stations.
Although this is not fiber optic DAS, I found it to be an interesting
recent demonstration of the potential of infrastructure cables
in hazard monitoring in general.
Just a quick reminder of how fiber optic DAS works.
It starts with an interrogator unit generating and sending short laser
pulses down the optical fiber. Some of this energy is backscattered
by the naturally occurring scatters in the fiber, which are basically
imperfections or inconsistencies in the refractive index.
When the backscattered energy reaches the interrogator unit,
interferometry is performed, and if the fiber is subjected to
some acoustic field that causes strain or deformation somewhere on the fiber,
there will be a resulting phase difference between the pulses.
And, depending on the optical setup,
you can end up either measuring strain or strain rate.
And, of course, the two-way travel time of the received pulse is used
to determine the location of measurement down the fiber.
This location is called channel location, or sensing point.
And the length of fiber in which the strain or strain rate measurement
is averaged is called the gauge length, which is typically
8 to 16 meters for earthquake surface recordings
and 4 to 7 meters for microseismic borehole recordings.
DAS has many applications, including vertical seismic profiling;
earthquake detection and monitoring; soil property estimation and
hydrological characterization; structural monitoring;
CO2 monitoring; hydraulic fracturing process monitoring in oil and gas plays;
and long-term strain sensing, such as melting of the permafrost
and oceanic properties, to mention a few.
And there are many works that compare the performance of DAS
to seismometers and geophones that demonstrate the good signal-to-noise
ratio that DAS is capable of providing. And, while DAS measures strain
or strain rate, particle velocity can be derived from DAS data
if apparent slowness in the cable direction is known.
It is also worth mentioning that one interrogator can be used
to analyze fiber cables that are 50 or even 100 kilometers long.
Moreover, an interrogator unit can be placed onshore
with a marine cable or be placed underwater if needed.
So now let’s think about the role that fiber optic DAS can play in
enhancing the performance of various earthquake early warning systems.
When it comes to earthquake locations and arrival times, the current DAS
capabilities can provide high signal-to-noise ratios for accurate
source location and origin time estimation, which are useful for
point-source source parameter algorithms,
like the ShakeAlert system EPIC algorithm.
We can further enhance the signal-to-noise ratio if needed
by using interrogators with higher sensitivities and lower noise floors.
While data with good signal-to-noise ratios were obtained using standard
telecom fibers, dedicated installations that require high fiber sensitivity and
exception signal-to-noise ratios utilize special or engineered fibers.
Engineered fibers provide higher backscattering capabilities without
significantly increasing fiber losses, which allows for the detection of
very small signals at distances of about 1 kilometer from the interrogator.
They can offer 100 times’ improvement in fiber sensitivity compared to telecom
fiber varieties and up to 30-decibel enhancement in noise levels.
However, the cost of engineered fibers can be significantly higher than those
of standard telecom fibers, which cost about $1 to 2 per meter.
But we’re not considering only the fibers but the whole cable bundle –
engineered fiber cables can cost up to 15 times more than telecom fiber cables.
We also need to make sure that the cables are oriented in such a way
as to have optimal azimuthal or directional sensitivity to P waves.
So, if the fiber is oriented this way – horizontally – when a seismic wave
of wavelength much longer than the gauge length propagates through the
fiber, the fiber will be highly sensitive to longitudinal waves propagating
along the fiber and to transverse waves at 45 degrees through the fiber.
And I will show an example fiber layout
for multi-components acquisition in a minute.
One issue that there isn’t an update on is how a DAS array would perform
when installed very close to a large rupture or a large earthquake and
whether there is an equivalent of clipping in DAS systems as there is
in seismometers, for example, as well as the effect of high strain
and high strain rates on the fiber cables themselves.
Clipping in the optical system may be thought of as a phase wraparound as a
result of the signal rising too quickly. This can presumably be adjusted
by pre-setting the phase quantization increment in the hardware if the
expected strain rates are known. However, this increment will
become a hard limit, as it is not user-selectable
and will not be easy to change afterwards.
When talking about P wave displacements for rapid magnitude
estimation, DAS capabilities to provide good signal-to-noise ratio
is well-established. But several studies show that
DAS strain amplitude accuracy highly depends on the quality
of strain coupling between the ground and the fiber
and the conditions of the installation.
For example, the top figure shows how the installation conditions,
being a single conduit, a cased conduit, or an attached conduit, can affect
recorded data, possibly due to variations in coupling.
This work by Nate Lindsey and others shows that, while the phase response
remained practically flat for the entire range of seismic frequencies they
studied, there is an elevated amplitude response at higher frequencies,
which the authors think might be due to coupling issues of the cable
that leads to such frequency-dependent response.
Even in dedicated installations, poor strain coupling has resulted
in mismatches between DAS data and co-located geophones
and uncemented fiber segments were thought to be problematic.
A few studies of cable packaging have shown some minor differences in
cable response compared to the more prominent effect of
the strength of strain coupling. So this is also a need for further
research for different array installations and to investigate
whether infrastructure or dark fiber installations
would be suitable for earthquake early warning applications.
PGVs or PGAs used in ground motion-based finite fault parameter
estimation algorithms, such as FinDer, or wavefield propagation algorithms
such as PLUM, can be derived from dynamic strains.
But they additionally require multi-component DAS acquisition,
which can be achieved with helically wound fibers.
And you can reconstruct the full strain tensor from this layout of five helically
wound fibers and one straight fiber that isn’t shown in the figure.
And it’s been confirmed in field tests that at least the P wave response
of the cable was angle independent. I know the cable looks large in the
figure, but the next-generation cables have diameters as small as
1.8 centimeter, and you can get multi-component response
without complicated layouts.
Finally, since we derived a number of useful relations between dynamic
strains and earthquake magnitudes and ground motion parameters,
if at some point in the future, we can develop a new algorithm
based on strain data from fiber optic sensors or strainmeters,
it can be used for calculating different earthquake source parameters
and ground motion metrics directly from strain and sent to
the earthquake early warning system.
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In summary, there are many ways that DAS data can contribute to
different types of earthquake early warning algorithms through
contributing ground motion observations directly to existing
earthquake early warning algorithms after conversion to the data types
ingested by these algorithms and through augmenting the current
earthquake early warning systems by supplying additional earthquake source
parameters through the development of an independent strain-based algorithm.
In our upcoming paper, we highlighted a few DAS-related issues in need
of further investigation, such as amplitude accuracy
in weak or non-uniform coupling installations and
array performance very close to large ruptures.
I would like to thank Martin Karrenbach, Sarah Minson,
Andrew Barbour, Scott DeWolf, Evelyn Roeloffs, John Lanbein, Julian Bunn,
and Elizabeth Cochran for their feedback and help with this work.
And, with that, I thank you very much for your attention,
and I look forward to your questions and the discussion.
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