Dynamic strain determination using fibre-optic cables allows imaging of seismological and structural features

Abstract

Natural hazard prediction and efficient crust exploration require dense seismic observations both in time and space. Seismological techniques provide ground-motion data, whose accuracy depends on sensor characteristics and spatial distribution. Here we demonstrate that dynamic strain determination is possible with conventional fibre-optic cables deployed for telecommunication. Extending recently distributed acoustic sensing (DAS) studies, we present high resolution spatially un-aliased broadband strain data. We recorded seismic signals from natural and man-made sources with 4-m spacing along a 15-km-long fibre-optic cable layout on Reykjanes Peninsula, SW-Iceland. We identify with unprecedented resolution structural features such as normal faults and volcanic dykes in the Reykjanes Oblique Rift, allowing us to infer new dynamic fault processes. Conventional seismometer recordings, acquired simultaneously, validate the spectral amplitude DAS response between 0.1 and 100 Hz bandwidth. We suggest that the networks of fibre-optic telecommunication lines worldwide could be used as seismometers opening a new window for Earth hazard assessment and exploration.

Full text

ARTICLE
Dynamic strain determination using fibre-optic
cables allows imaging of seismological and
structural features
Philippe Jousset 1, Thomas Reinsch 1, Trond Ryberg1, Hanna Blanck2, Andy Clarke3
Rufat Aghayev3, GylfiP. Hersir2, Jan Henninges1, Michael Weber 1,4 & Charlotte M. Krawczyk 1,5
Natural hazard prediction and efficient crust exploration require dense seismic observations
both in time and space. Seismological techniques provide ground-motion data, whose
accuracy depends on sensor characteristics and spatial distribution. Here we demonstrate
that dynamic strain determination is possible with conventional fibre-optic cables deployed
for telecommunication. Extending recently distributed acoustic sensing (DAS) studies, we
present high resolution spatially un-aliased broadband strain data. We recorded seismic
signals from natural and man-made sources with 4-m spacing along a 15-km-long fibre-optic
cable layout on Reykjanes Peninsula, SW-Iceland. We identify with unprecedented resolution
structural features such as normal faults and volcanic dykes in the Reykjanes Oblique Rift,
allowing us to infer new dynamic fault processes. Conventional seismometer recordings,
acquired simultaneously, validate the spectral amplitude DAS response between 0.1 and
100 Hz bandwidth. We suggest that the networks of fibre-optic telecommunication lines
worldwide could be used as seismometers opening a new window for Earth hazard assess-
ment and exploration.
DOI: 10.1038/s41467-018-04860-y OPEN
1GFZ German Research Centre for Geosciences, Telegrafenberg, Potsdam 14473, Germany. 2ÍSOR Iceland GeoSurvey, Grensásvegi 9, Reykjavik 108, Iceland.
3Silixa Ltd., Silixa House, 230 Centennial Park, Centennial Avenue, Elstree WD6 3SN, UK. 4Institute of Earth and Environmental Science, University of
Potsdam, Potsdam 14476, Germany. 5Institute for Applied Geosciences, Technical University Berlin, Ernst-Reuter-Platz 1, Berlin 10587, Germany.
Correspondence and requests for materials should be addressed to P.J. (email: philippe.jousset@gfz-potsdam.de)
or to T.R. (email: thomas.reinsch@gfz-potsdam.de)
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Seismic and ground-motion datasets quality (spatial density,
accuracy, bandwidth, etc.) determines our ability to char-
acterize crustal media properties distribution, seismic
source processes and wave propagation mechanisms. These are
mandatory for acute natural hazard assessment1–3, for efficient
resource exploration4, and for structural health monitoring and
security5. For example, faults are known to display different
elastic properties6, due to the existence of a damage zone7. The
structure and physical properties of faults control processes of
dynamic rupture and/or creep. Prior to rupture, tectonic stress
accumulates and rock damage grows, inducing deformation of the
Earth crust8. In addition, dynamic stress from remote earth-
quakes has also been proposed as a mechanism to trigger volcanic
eruptions, earthquakes, as well as micro-seismic activity9, and
may also explain inelastic ground response in compliant fault
zones10. Micrometre-scale deformation at faults were inferred
from GPS and broadband seismological observations during the
Barðabunga volcanic eruption in Iceland11. However, imaging the
internal structure of faults with high resolution as well as infer-
ring creeping processes of faults at sub-micrometre steps remains
challenging3. This prevents an accurate assessment of associated
near fault hazard7.
In order to refine images of the structure and better
understand fault rupture and processes, seismology requires
dense spatial coverage of individual sensors12–14, more accurate
recording instruments and new techniques for processing data11.
Seismic networks deployed for several decades15 produce
waveforms with increasing quality and broader frequency con-
tent. Data from those networks fostered many discoveries and
advanced knowledge, e.g. on crustal anisotropy, the core-mantle
boundary, and detailed images of the crust16. The deployment of
such networks requires great effort and resources, especially in
areas where access is limited. The rising cost of maintenance
makes it arduous to expand those networks much further.
Alternative solutions from space are being developed17 but
remain inaccurate. Complementary solutions on the ground have
also been proposed such as including GPS measurements to
detect earthquake surface wave’s characteristics18. So far, con-
ventional recording instruments used in those networks provide
high quality waveforms but spatially aliased data. Accurate wave-
fields in space are frequently acquired by increasing the density of
instruments at the surface, such as network deployment of cheap
geophones19. Those studies address mainly local structures
(typically several km2) and use limited frequency band (>4 Hz).
Fibre-optic technologies have been offering a range of solutions
for an increasing array of applications20. Two sensing strategies
are commonly proposed. The first strategy designs high quality
sensors (higher bandwidth, resolution, etc.), which however still
remain single points of observations in space21, whereas the
seismic wave-field is constantly varying with location and time.
The second strategy, referred to as distributed fibre-optic sensing,
uses the entire length of an optical fibre as a sensing element
allowing a marked densification of spatial sampling down to the
metre scale over a distance of tens of kilometres. A passing
seismic wave disturbs the sub-surface, locally stretching and
compressing the ground; a buried fibre-optic cable is therefore
stretched and compressed as well. Fibre-optic sensors measure
the response of the optical fibre to the external forces applied to it.
This can be done in a variety of ways22, but in general the
principle involves sending a pulsed coherent optical laser signal23
propagating along the fibre and measuring the naturally back-
scattered light. The time-of-flight of the laser signal and its
backscattered component are recorded and converted into a
distance value using the speed of light and refractive index of the
fibre. The phase of Rayleigh backscattered light along an optical
fibre is well suited for monitoring dynamic strain changes, with a
high spatial and high temporal resolution (Methods: Distributed
fibre-optic sensing). Whereas the physical principle24 is named
phase-OTDR (optical time domain reflectometry), its application
for ground-motion detection is often referred to as distributed
acoustic sensing (DAS)25 or distributed vibration sensing (DVS)
26. Sensitivities down to the nano-strain are achieved with current
technologies27.
The DAS/DVS technologies have been mainly developed in the
oil and gas industry. A common application is in seismic acquisi-
tion, with active sources. Fibre-optic cables that have been pre-
viously deployed in a borehole, for communication with a downhole
gauge, for example are regularly used. However, it is also possible to
design and deploy dedicated cables with improved characteristics for
certain applications28. The deployment of optical cables in boreholes
allows structural underground investigation and monitoring of
reservoirs properties29. The DAS/DVS technologies tend to com-
plement classical vertical seismic profile (VSP) measurements30,31.
Field studies on VSP data show that the frequency spectrum
recorded with DAS/DVS is comparable to conventional geophone
data32, where the bandwidth of the seismic record is limited by the
minimum frequency generated by the source, e.g. >5–10 Hz.
However, measurements performed with DAS/DVS in the labora-
tory33 produced acoustic bandwidth from 0.008 Hz to 49.5 kHz
suggesting possible applications at longer seismic periods (<1 Hz) in
the field34–40. In the following, we refer to “DAS”for simplicity.
In this study, we find new structural and dynamic features of
normal faults zones within the oblique rift of Reykjanes mid-
oceanic ridge. We achieve those findings by using an existing
~15-km long conventional fibre-optic cable, utilized for tele-
communication in Reykjanes Peninsula (SW-Iceland). This cable
was deployed in 1994 with a plough in a <1 m deep trench and
covered with sandy soil and gravel. We analyse the continuous
strain-rate data recorded with a dedicated acquisition system
(iDAS) over 9 days in March 2015 with high sampling both in
time (1000 Hz) and space (4 m). We thus demonstrate that
conventional fibre-optic cables already deployed in the ground for
telecommunication purposes can be used as quasi-continuous
lines of highly sensitive sensors, providing spatially un-aliased
strain data over a broad frequency band useful for seismological
research. This spatially dense acquisition over a large distance
allows (1) to record data yielding improved earthquake identifi-
cation and localizations, and (2) to detect small features of the
sub-surface which can then be compared to the local geology, e.g.
fault zones and volcanic dykes associated to the rift.
Results
Validation of the DAS records. We process our dense ground-
motion DAS strain-rate records both in terms of amplitude and
frequency content to evaluate the response characteristics of the
previously deployed fibre-optic cable (e.g. the ability to adequately
record broadband ground-motion signals for seismological
research), and to derive information about the crustal structure
and rifting processes at Reykjanes Peninsula (Supplementary
Note 1and Fig. 1).
We obtain characteristics of the DAS strain signals as
recorded along the profile defined by the fibre cable for
ground-motion studies. Over a broad frequency band, we show
that recorded strain rate signals are meaningful: after we
corrected for the instrumental response of both DAS and
seismometer data, the DAS signals accurately match those
derived from the seismometers (in terms of the frequency
content as well as the phase characteristics). This suggests the
data acquired by the DAS is a valid representation of the near
surface ground deformation, and can therefore be used for
shallow crustal exploration and monitoring with similar
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performance as broadband seismological sensors typically
deployed in an array (Figs. 2–4;Methods:Strainand
displacement and velocity determination).
We identify signals generated from a large variety of both
anthropogenic and natural sources (0.05 Hz up to >100 Hz).
High frequency signals (1–100 Hz) are mostly generated by
anthropogenic sources, such as passing cars, fluid circulating in
pipes of nearby geothermal power stations, hammer shots on the
ground, people walking, and distant active explosion shots
(Figs. 2–4). In addition, we detected local earthquakes
(0.5–20 Hz) associated with the seismic activity of the Mid-
Atlantic Ridge (Supplementary Table 1). We observed oceanic
micro-seism (ambient seismic noise with signal frequencies from
0.1 to several Hz), as well as Rayleigh waves from large remote
earthquakes (with ~20 s signal period, Fig. 3and Supplementary
Table 2). Figure 3shows the filtered records (range 5–40 s) from
the optic cable and broadband seismometer for a Mb ~6.2
earthquake in Indonesia, including surface waves (period ranging
10–30 s).
We validate our observations with records from co-located
short-period three-component geophones and broadband seismic
sensors deployed in the vicinity of the optic cable41 (Fig. 1;
Method: Cable localisation). Waveforms from individual traces
along the optical fibre exhibit high coherency, as well as with
signals from broadband seismometers located along the cable
(stations RAH and EIN, Fig. 1). Broadband signals (0.1–10 Hz)
associated with the ground deformation due to passing cars
along the fibre can be observed (Fig. 2a). We retrieve local average
sub-surface ground elastic properties from the response to a car
using simple ground deformation models (Methods).
To interpret DAS data, it is of primary importance to
evaluate the performance of the iDAS system with respect to
traditional acquisition seismic systems22,25–27. We compare single
record of the DAS data set with records from the closest
geophone and from a nearby broadband seismometer. We
perform this data comparison both on ambient noise (Fig. 4)
and during earthquakes. Several technical issues must be first
solved. (1) We locate each DAS trace along the cable with a final
spatial uncertainty of ±5 m, using hammer shots and GPS
locations from the geophone data. (Fig. 1and Methods). (2) We
orient the recorded horizontal components of the seismometers
along the local direction given by the cable. (3) We correct the
instrumental responses of the iDAS system (Methods), of the
geophones and the broadband seismometer on the respective
record, prior to the determination of the seismic signal phase and
amplitude.
The applied instrumental correction for the iDAS system can
be used to accurately represent amplitude and phase of the
seismic signal as confirmed by the comparison to classical seismic
recording equipment (Fig. 4). Although DAS data can be
converted to ground velocity, our conversion is valid in a certain
frequency range only. Therefore, it is more convenient to follow a
different approach when analysing fibre-optic DAS data, as
demonstrated in the analysis and modelling of the ground
deformation due to a passing car (Methods: Shallow sub-surface
crustal properties determination). DAS systems typically measure
strain rate or strain between two neighbouring positions within
an optical fibre. The integration of strain data in space (along the
cable) allows the calculation of the displacement of each data
point relative to a chosen reference. Given an appropriate
integration length, amplitude and phase, static local deformations
and passing seismic signals can be quantified, removing the need
to apply the instrumental correction. For localized deformations,
the integration length must exceed the distance over which the
deformation occurs. For passing seismic waves, at least half of the
maximum wavelength must be integrated to properly quantify
seismic amplitudes (Nyquist’s theorem). The required length for
long period signals easily exceeds the length of the sensor system
(cable), which is typically a couple of km. While focusing on
single traces and applying the instrumental correction is
appropriate to analyse passing waves with periods from 0.01 s
to several minutes, high frequency signals as well as localized
(static) deformation can be accurately analysed by integrating
DAS data in space. In the following, we apply time-integration of
the strain rate to obtain strain and space-integration to obtain
displacement (Methods: "Strain and displacement and velocity
determination").
Earthquake identification and localisation. Accurate earthquake
localisation is still one of the challenges in seismology42. The
accuracy of the seismic wave velocity model and the network
design determine the earthquake hypocentre accuracy. The
crustal structure of Reykjanes was the topic of investigation in
several geophysical and particularly seismic studies43. The EC
funded project “IMAGE”performed new passive seismic data
acquisition, including deployment of Ocean Bottom Seism-
ometers44. A structural analysis was performed using classical and
modern seismic methods41,45,46. In particular, we jointly inverted
earthquakes locations and P-wave (V
p
) and/or V
p
/V
s
ratio models
of Reykjanes by a local travel time tomography41. From surface
down to 4–5 km, seismic velocity increases rapidly from 1.8 to
4.2 km s−1, which is a typical velocity gradient for oceanic crust.
–22.7° −22.5°
63.8°
63.9°
RAH
5 km
Dyke E
Curve 1 Curve 2 Curve 3
Fault 1 Fault 2
Fault 3
Fault 4
I c e l a n d
Reykjanes Atlantic
Ocean
Fault zone
EIN
Fig. 1 Location of the fibre-optic cable in Reykjanes and main geological
features70. Location of the fibre-optic cable (continuous green line) from
the telecommunication network (Míla Company) used for our
measurements within the Reykjanes fissure swarm (black lines). Small light
blue squares along the fibre-optic cable represent geophones. Blue triangles
indicate broadband seismological stations from the European Project
IMAGE (Integrated Methods for Advanced Geothermal Exploration)
network41,44. RAH and EIN are the closest broadband stations to the optical
cable. The thick black lines indicate a series of cones and postglacial
craters, from the latest eruptive episode in Reykjanes in 1210–1240 (e.g.
Dyke E =Eldvörp crater row). The black star indicates a local earthquake
epicentre (depth ~3.5 km). The thin red curve indicates the limit of the Sh =
Sandfellshæð lava shield (most recent lava flow), hiding most of the faults
at the surface of the tip of the Peninsula. The inset represents the location
of the area in Iceland (North Atlantic), with black dots being epicentres of
68 earthquakes (Supplementary Table 1) recorded during the 9 days of our
optical DAS records
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V
p
/V
s
ratios are indicative of the absence of large magma reser-
voirs in Reykjanes, which is also confirmed by the recent IDDP-2
drilling47.
We focus here on one particular earthquake (Ml ~1.2) that
occurred almost beneath the cable at 3 ± 1 km depth in the
tomographic model41. Figure 5shows the geophone and DAS
records along the cable for this small local earthquake. We use an
automatic picker based on Akaike Information Criteria to obtain
more than 500 valid P- and S-wave arrival times along the cable.
P-wave picks have good coherency between neighbouring traces
whereas S-wave have poorer coherency (Fig. 6). Although the
telecommunication cable geometry was for sure not designed for
earthquake monitoring, we obtain a hypocentre location using P-
and S-wave travel times automatically picked on all traces
recorded along the cable. We find a hypocentre similar to the one
obtained from conventional seismological network41. The prob-
ability density function (pdf) of the earthquake hypocentre
location is obtained using only the travel time data derived from
the DAS record (Supplementary Figure 7). The pdf locates the
hypocentre within few hundred metres from the hypocentre
location obtained in the IMAGE velocity model demonstrating
that the iDAS system can be used for earthquake monitoring and
localization. In addition, we note the rather good match both in
amplitude and trend between the derived V
p
/V
s
ratio obtained
from DAS records for this earthquake (only one) and the V
p
/V
s
ratio from 3D local tomography (Fig. 6b).
Crustal structural features detection. Geometrical and physical
sub-surface properties of the damage fault zone could be derived
using waves from local earthquakes trapped within a fault damage
zone (Fig. 7). From the geological and structural maps of Rey-
kjanes48, we notice that the fibre-optic cable crosses several tec-
tonic and volcanic features, i.e. volcanic dykes and faults. One
prominent fault zone crosses the cable at a distance of about 5 km
along the road (Fig. 1). This fault zone crops out along the rift to
the north and the south of the road over several kilometres. The
Eldvörp crater row crosses the cable at a distance of about
10.5 km. Several observations indicate the signature of those
geological features in the DAS record. For example, in Figs. 5b
and 6a note the larger delay of P-wave arrival time at distance
~5 km, corresponding to the presence of a fault zone. Similarly,
note the faster arrival times at distance ~10.5 km, where the cable
crosses the Eldvörp crater row. In Fig. 5d, V
p
/V
s
ratio along the
cable shows kinks located at faults. Those features cannot be seen
in the sparser geophone records.
Dense arrays of seismometers give the opportunity to better
image the sub-surface, especially using recently developed
imaging techniques, such as ambient noise cross-correlation
and auto-correlation technologies49. Even when classical sources
(earthquakes, etc.) are absent, we show that ambient noise
analysis techniques reveal wave disturbances associated with fault
zones (Method: Ambient noise interferometric techniques with
DAS records). As ambient noise is rather strong in Reykjanes45,
we computed autocorrelations and cross-correlations in order to
illustrate the detection and imaging capabilities of those methods
with DAS records (Supplementary Figure 8). We observe similar
quality and good coherency between autocorrelations from DAS
record and co-located geophones and the classical X shape of
wave propagation from the virtual source towards larger offsets.
Those results demonstrate that geophysical studies (detection,
mapping, localisation, monitoring, etc.) from correlations meth-
ods could be performed using available telecommunication cable
networks for further structural interpretation.
Towards imaging the damage zone within fault systems. From
the analysis of trapped waves in fault damage zones, P-wave and
S-wave velocities were found to be typically 35 to 45% lower than
those of the surroundings rocks in California7. For all earth-
quakes recorded by the iDAS system, we observed similar char-
acteristic wave-field features at several places along the
telecommunication cable. As an example, we focus on a fault
damage zone (FDZ) with a clear surface expression (Fig. 7). We
observe an increase in both, duration and amplitude of trapped
waves excited by local earthquakes. Interestingly, we observe
similar trapped-wave features in the micro-seismic noise, even
when local earthquakes are absent (Supplementary Figure 9). Due
50 100 150 200
Time (s)
3
4
5
6
7
8
9
10
11
12
Distance (km)
Earthquake
Car
3
4
5
6
7
8
9
10
11
Distance (km)
20 40 60 80 100 120
Time (s)
–6
–5
–4
–3
–2
–1
0
1
2
3
4
5
6
Nanostrain
Fault 1
Fault zone
Curve 1
Fault 2
Curve 2
Fault 3
Curve 3 Dyke
Fault 4
ab
Fig. 2 DAS records. a4 min of strain signal (17 March 2015, 12:33–12:37). Only selected normalized traces (one trace out of 25, i.e. one trace every 100 m,
frequency range 0.01–100 Hz) are shown. A local earthquake is revealed by higher frequencies in the signal from 135 to 140 s. Coherent oscillations of
5–6 s period correspond to ocean-driven micro-seism. Traces between 10.5 and 11.6 km with large amplitude signals correspond to a car travelling on the
road along the cable (Methods: Shallow sub-surface crustal properties determination). b2 min of strain record (19.03.2015, 15:27 UTC) showing micro-
seism (4–6 s period) propagating from the south coast northwards along the cable. Beamforming computation (from the DAS record) indicates a source in
the Atlantic Ocean, SW of Iceland. Changes in cable direction along the road (black labels) induce a change in the incidence angle of the micro-seism
waves, and therefore amplitude change. Amplitudes and phases are disturbed at specific locations (indicated by the red labels), which correspond to
geological features such as faults or volcanic dykes (Fig. 1)
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to the existence of the fault zone with altered properties
(decreased velocities), we observe a phase shift and increased
amplitude of micro-seism in the fault damage zone. This obser-
vation suggests that a local structural feature associated to the
fault zone is responsible for the increased amplitude and longer
codas. Such trapped phases are often seen, although not normally
with this high spatial sampling. Thus, the spatially dense
fibre-optic cable records allow us to follow details of the earth-
quake phase’s propagation within the fault zone. To our knowl-
edge, it is the first time that such details of the wave propagation
are observed within a fault damage zone. From the geological
observation in the field (Fig. 1), the fault zone appears to have a
width of about 60 ± 10 m at the cable location. This is in agree-
ment with the distance over which we see larger amplitudes of the
seismic signals and where we observe seismic phases bouncing
from one side to the other side of the fault zone (Fig. 7c). From
the slope of the phases propagating within the fault damage zone,
we could estimate an apparent velocity of about 300-400 m s−1,
which correspond to a velocity slower by 30-40% than outside the
fault damage zone. However, we also observe reflected phases
further south-west of the fault zone visible at the surface, until
4.98 km. This observation suggests that we may have discovered a
hidden fault, which could mark the limit of the fault damage
zone, as indicated by the trapped waves. As there are many faults
in rift zones, and as observed in our records (Figs. 2b, 5and 6),
this result may support the recent suggested statement that crust
in a geological rifting environment is weaker than elsewhere11.
Fault dynamic processes triggered by remote earthquakes. Our
DAS data analysis brings new insights on geological rifting pro-
cesses. By analysing the ground position before and after local
earthquakes we find relative quasi-static displacement offsets that
do not relax within a period of a few minutes. This is seen in the
faults (Fig. 8) which are crossed by the optical fibre line (Fig. 1).
In Fig. 7c, records with much larger positive and negative strain
amplitudes suddenly appear at specific locations when the
earthquake waves are passing by. The strain in the fibre remains
after the seismic waves dissipate (Fig. 8a). Structural features such
as the low wave velocities of the damaged zone within the fault
may contribute to explain such observations. However, these
sudden local strain jumps are not observed for all earthquakes,
but always appear at the same locations. The location of the
jumps correspond to locations of geological features observed in
the field, e.g. faults. To better understand processes generating
those records, we calculated displacement records by spatial
integration of strain over a few traces (typically over 40–60 m).
Wave-fields generated by remote (or local) earthquakes may or
may not trigger sub-micrometre static displacement shifts of the
ground close to weaker crustal features, such as a fault zone.
Discussion
Development and research to evaluate and expand the capabilities
of fibre-optic cables28,50 are required, so that newly deployed
cables could fulfill the requirements for exploration and mon-
itoring (e.g. separating the fibre sensitivity into the three com-
ponents). However, as demonstrated here, existing buried optical
fibre telecommunication infrastructure offers a cheap alternative
to deployment of dense networks of various sensors and new
optical cables. We emphasize that our results are obtained with a
conventional fibre-optic cable within a telecommunication net-
work, not been specifically designed for seismic purposes. This
points to the extraordinary potential of this technology for new
applications in Earth hazard assessment and exploration all over
the world.
We have demonstrated that the DAS technology using fibre-
optic cables from existing telecommunication networks has many
applications. We analysed the records with metre-scale resolution
over a broad frequency band (tens of seconds until tens of Hz),
for sub-surface m- to km-scale exploration. We showed that the
DAS records can be compared with conventional seismic records.
10–2 10–1 100101
Frequency (Hz)
10–5
100
Spectral amplitude
Broadband seismometer
Geophone
Telephone optic cable
Fig. 4 DAS record conversion to seismic data. True amplitude spectra of
displacements of 1 h (20.03.2015 5:00-06:00) noise record for DAS
(green), geophone (natural frequency of 4.5 Hz, blue) and broadband (flat
amplitude response between 0.008 and 100 Hz, red) records, respectively,
after instrumental corrections (Methods: Instrumental correction of records
from the iDAS system)
80 100 120 140 160
Time (min)
–1
–0.5
0
0.5
1
Normalized amplitude
Telephone optic cable
Broadband seismometer
125 130 135 140
Time (min)
–1
–0.5
0
0.5
1
Normalized amplitude
a
b
Fig. 3 Record of a teleseism earthquake with DAS. aNormalized strain
(green curve) recorded during an Mb ~6.2 (USGS) earthquake (Kota
Ternate, Indonesia, 2015-03-17 22:12:28 UTC, 1.669°N; 126.522°E, 44 km
depth) superimposed with the normalized velocity record (red curve) from
the broadband station RAH (80 m from the optical cable). Data are filtered
between 16 and 50 s corresponding to highest amplitudes for surface
waves of remote earthquakes. bZoom from ashowing good phase
correspondence between seismometer velocity record and DAS strain
records at 20 s period
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We report applications focussing on sub-surface exploration for
elastic rock properties and earthquake monitoring. We also dis-
covered unusual wave-field features of fault structures and
dynamics in a geological active rift (Reykjanes, Iceland). The
spatial density increase over a long distance is one of the major
advantages for obtaining detailed information on Earth property
distribution. With only one earthquake (we did not use other
earthquakes), we determined structural rock properties at the km
scale and at the fault damage zone scale and inferred hints on
strain accumulation and creeping processes. For instance, the
trapped seismic phases observed in a fault damage zone are
single- or multiple- reflected phases at two reflectors or more,
which we interpret as being fault zone boundaries, defining the
fault damage zone, as inferred from our seismic observations.
Reflected waves in the micro-seism suggest that seismic energy is
trapped in the fault zone at various frequencies. Those results
suggest that when applied to many earthquakes, even more
detailed information could be retrieved. Our observations also
reveal potential creeping processes at faults and fault damage
zones induced by impinging seismic waves from local earth-
quakes. Dynamic strain perturbations due to the passing waves
from local earthquakes trigger relative displacements that may
correspond to tiny aseismic fault movements, interpreted as
creeping processes. Micro-seism may influence fault creeping
processes as well as remote earthquakes. Further analysis in this
direction could help solve questions related to co-seismic fault
deformation3,10,51, understand fault preparation prior to large
earthquakes as well as aseismic deformation. Those results open a
new window for the study of remote triggering of earthquakes
and stress build-up at faults, especially in cities where fibre-optic
cable networks may be dense and where seismic hazard is high
(San Francisco, Mexico, Tokyo, etc).
The dramatic increase in sensor density over a large distance
with unprecedented acquisition characteristics (sampling in space
and time and over a large frequency band) suggests that scientists
could test new approaches and unconventional data processing,
which then might obtain more accurate results compared to
classical seismological methods. The DAS technology thus offers
a great potential for Earth exploration and natural hazard
assessment, offering new scientific research opportunities.
Improving the sensitivity of cables in existing networks, deter-
mining accurate position and orientation of the observed traces
and understanding details of the ground/cable coupling issues25
are certainly great challenges when exploiting buried optical
communication lines. For the situation on Reykjanes Peninsula,
the analysis of the stress transfer from the ground to the sensing
core of the fibre is more than 90% efficient for seismic frequencies
between several 10’s Hz and long seismic periods52. By demon-
strating that the data acquired on a telecommunication network
of fibre-optic cable fulfills many requirements for improvement of
seismological analysis, we foresee a vibrant future for the use of
optical sensor technologies in seismology applications. Besides
the deployment of new dedicated and improved cables in order to
allow for observation of the full strain tensor, existing infra-
structures may allow for simultaneous monitoring of strain and
ground motion for natural hazard assessment. They could help in
more accurate earthquake localisation and focal mechanism
determination, volcanic activity monitoring and a more
complete characterisation of the range of volcanic and seismic
Time (s)
Distance (km)
3456 8 101112
b
1
2
3
4
P
S
a
3
1
2
4Geophone velocity
Fibre optic strain
Distance (km)
3 4 5 6 7 8 10 11 129
79
Fig. 5 Records of a local earthquake. aGeophone record (blue) of an Ml ~1.2
local earthquake (23.03.2015, 16:07:08.5 U.T.C.—Iceland Meteorological
Office) and fibre-optic (green) record at the corresponding locations of the
geophone. bDAS record of the same earthquake as in a
V
p
/V
s
1.7
1.8
1.6
1.9
1.5
Distance (km)
23456 8 1011
a
1
2
3
Fibre optic P-pick
Geophone P-pick
Synthetic P-arrival
Fibre optic S-pick
Synthetic S-arrival
Geophone S-pick
b
79
Fig. 6 Exploration studies using conventional seismological methods and a
fibre-optic telecommunication line. aP- and S-waves’travel times
automatically picked along the profile: each symbol represents a P- (black
star) and S- (grey dots) arrival times on the DAS records. The white
squares with black dot and the white circle with black dot correspond to P-
and S-wave travel times, respectively, picked on the geophone records with
the same automatic picker. The continuous grey (black) lines correspond to
theoretical arrival times for the inverted hypocentre using P- and S-wave
picks from the cable (respectively). bObserved V
p
/V
s
ratio computed at all
traces and compared with the results obtained from the travel time
tomography (green dots) obtained from more than 2000 local earthquakes
over 1.5 years41. The black line corresponds to the polynomial
(Savitsky–Golay) smoothing filter of order 5 with size frame ~3 km long
through the fibre-optic V
p
/V
s
individual values
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sources, seismic hazard assessment, global seismology studies,
exploration, etc.
We also suggest that our results may open the door to new
ways of data processing53. With the advent of spatially un-aliased,
i.e. densely sampled seismic data, array analysis methods (e.g.
Helmholtz tomography) becomes easier to implement54, poten-
tially providing a huge improvement in resolution by directly
inverting and/or imaging sub-surface structures utilizing full
wave-field recordings.
Can we also envisage a change of paradigm in theoretical
seismology? The classical stress/displacement approach in seis-
mology uses the basics of mechanics and observational seismol-
ogy is based mostly on displacement and/or velocity and/or
acceleration sensor recordings. With a fibre-optic cable providing
equivalent broadband seismometers records, the gradient of the
displacement, i.e. the strain, is uniquely measured at many more
locations than before. We believe new processing methods may be
needed. New mathematical progress for tomography has been
recently discovered55 but their application is hindered by the lack
of information at the Earth surface56. Since fibre-optic lines are
deployed very widely and densely on Earth, e.g. for tele-
communication (~106km cable deployed under the sea57), we
anticipate that our results will open a new era for strain and
ground-motion acquisition at all scales, for both seismic proces-
sing and modelling. For instance and non-exclusively, monitoring
of underground explosions in the framework of the CTBTO,
volcano monitoring, seismic hazard assessment, landslide
monitoring and, global seismology using transatlantic optical
cables could benefit from this technology with current and future
infrastructures. We may also envisage dedicated experiments to
compare new instrument development in rotational seismology58,
and detailed studies of surface wave properties59. Many other
applications, like car traffic monitoring, theft protection, city
underground monitoring37 will promote telecommunication
companies as actors for Earth hazard monitoring, exploration and
security enhancement for the benefit of research60 and human
societies.
Methods
Distributed fibre-optic strain sensing. Various optical architectures have been
used to interrogate the backscattered Rayleigh light, ranging from relatively simple,
coherent-OTDR (optical time domain reflectometer) schemes, which are unable to
determine acoustic phase and so are unsuitable for seismic measurements, to more
complex arrangements which provide the full acoustic amplitude, frequency and
phase. Both the simple and complex range of systems are generally described as
DAS25,33 or DVS26, though only the phase sensitive variants have been successfully
used for seismic applications60. The description of the underlying sensing princi-
ples of the DAS/DVS technology has been reported22,61,62. When a laser pulse is
launched into an optical fibre, a fraction of the light is elastically scattered (Rayleigh
scattering) due to random inhomogeneity distribution in the glass fibre material.
During interrogation of an optical fibre, the backscattered photons can be detected.
The position of the scattering inhomogeneity within the fibre can be calculated
based on the speed of light within the fibre. This method is called optical time
domain reflectometry (OTDR)63. If a coherent laser pulse is launched into the fibre,
with appropriate optical processing, not only the amplitude but also the phase of
the backscattered photons can be analysed (phase-OTDR). For any section of the
fibre, the phase-difference Δϕof photons scattered at both ends of that section is
100 m
Fault zone
Telephone
line
5.04 km
5.09 km
4.98 km
4.8
4.9
5
5.1
5.2
Distance (km)
P
S
Time (s)
Reflections
0
6
1
5
4
3
2
a
bc
Fault
zone
5.1
Fig. 7 Structure of a fault damage zone within an active geological rift. aThe road and the cable (distance ~5 km) cross several faults, e.g. a clearly visible
fault zone with more loose material in the field (between 5.04 and 5.09 km). bThe fault damage zone is visible by the ~50–60 m wide depression area
(picture taken at ~100 m SW of the road, looking towards SW). Note that at the cable location no depression area is visible. The depression is only the
surface expression at the position of the picture (Picture Martin Lipus, GFZ). cShort record (6 s) of strain phases from a local earthquake (Fig. 5) trapped in
the fault damage zone. Phases are reflected until ~4.98 km, which may indicate a hidden fault with surface expression. Waves inside and outside the fault
zone have different apparent velocities
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linearly related to the length of this section27. When the section of the sensing fibre
is unperturbed, the length and, consequently, the phase-difference Δϕremains
unchanged. Any perturbation inducing a strain εon the fibre will change that
difference. The strain rate can therefore be mapped along the sensing fibre by
examining the changes in the phase of the elastically backscattered photons
between successive measurements. For example, an imbalanced Mach-Zehnder
interferometer has been used to measure dynamic strain changes along the fibre64.
Afibre-optic cable can hence be considered a system consisting of a large number
of one component relative strain gauges. State of the art DAS systems are capable of
quantifying the frequency, amplitude, phase and location of dynamic perturbations
anywhere along the sensing fibre. Measurement systems with the capability to
resolve perturbations of 40 nϵare reported27.
Strain and displacement and velocity determination. In our study, we define the
DAS system as comprising the deployed fibre-optic cable (sensor) and the iDAS
interrogation system33. The phase-difference is a measure of the relative travel time
and hence the relative distance. The physical distance over which the phase-
difference measurement is performed, is referred to as the “gauge length”dx26,61.
Comparing successive pulses, phase changes are directly related to the distance
changes and therefore the strain rate in direction of the fibre can be recorded. In
the iDAS system, each digital sample is indexed by the centre location of a moving
window along a cable’sfibre core (the sample’s‘channel’,x) and recording time
(the sample’s‘time’,t). Thus, if u(x,t) represents the dynamic displacement of the
fibre, the DAS observation DASobs at axial location xand time tis a measure of the
strain rate at the distance xfrom the iDAS recorder and is expressed by:
DAS obsðx;tÞ¼ uxþdx
2;t

uxdx
2;t

uxþdx
2;tdt

uxdx
2;tdt

ð1Þ
where dxand dtare the spatial gauge length and temporal sample interval,
respectively. The typical gauge length for seismic applications spans dx=~10 m.
The longer the gauge length, the more sensitive the DAS system with increased
signal to noise ratio. Wavelength λbelow dx/2 can however not be resolved
(Nyquist’s theorem in space26). Together with the spatial sampling, the gauge
length determines the dependency between individual seismic traces. Although
data can be acquired with a high spatial resolution, the assumption of independent
traces only holds true if the gauge length of neighbouring traces does not overlap.
In order to achieve a sufficient intensity of the backscattered light for each data
point and every laser pulse, the laser pulse has a given width and the backscattered
light has to be integrated for a given time. Both, the pulse width as well as the
integration time acts as a moving averaging filtering in space26. In some imple-
mentations, post-acquisition averaging of individual traces is applied to suppress
unwanted optical noise and an increase in seismic signal/noise ratio.
DAS data can be equivalently regarded either as an estimate of the fibre strain-
rate
∂
∂t
∂u
∂x
 ð2Þ
or as an estimate of the spatial derivative of fibre particle velocity
∂
∂x
∂u
∂t
 ð3Þ
If we integrate the distributed strain-rate along the optical fibre with respect to
time, local strain can be estimated for every section along the optical fibre. If we
integrate the local strain with respect to space, the relative displacement can be
calculated at all points along the profile. Note that by differentiating with respect to
time, we obtain an estimate of the velocity of the ground, which we may compare
–300
–200
–100
0
100
200
300
Nanometers
Time (s)
Fault
zone
–100
0
100
200
4.8
4.9
5
5.1
5.2
Distance (km)
–100
–80
–60
–40
–20
0
20
40
60
80
100
Nanostrain
Fault
zone
–100
0
100
200
4.8
4.9
5
5.1
5.2
Distance (km)
Eq
Sudden
strain step
ab
Fig. 8 Dynamics of a fault damage zone within an active geological rift. aExtensive record (400 s) of strain observed in the vicinity of the damage fault
zone, from 100 s before, during and 300 s after the earthquake (Figs. 6and 7). Sudden strain steps (black arrows indicated at the time 0) occur over
several neighbouring traces simultaneously to the waves of the earthquake. Strain remains with the same value for at least 300 s, possibly more. The
location of the steps correspond to locations of geological features observed in the field, e.g. faults. bDisplacement computed by spatial integration at
selected traces along the same section of the cable as in Fig. 7a and c. The displacement is directly obtained from the spatial integration of the strain in
aover a 60-m-long sliding window. Eq: earthquake
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to local broadband seismometer records. We compare spectral data in
displacements (Fig. 4).
Cable localisation. Using an optical cable at the surface is driven by the idea that
there could potentially be a larger range of applications both in hazard assessment
and crustal exploration, although applications at the surface are described to be
more challenging26. Instead of deploying a new dedicated cable (with great amount
of expenses), we use an optical fibre within the commercial telecommunication
network on the Reykjanes peninsula, SW-Iceland. The geographical position of the
cable was provided by the telecommunication provider (Mila). The optical data is
given in terms of distance along the optical fibre within the cable to the iDAS
recorder. Each trace of the DAS record has an associated distance from the iDAS
recorder. In order to locate and check the accuracy of the observed distances from
the DAS record, we deployed an array of 33 geophones every 250–500 m along the
cable. We determine the position of each geophone using precise differential GPS
(accuracy better than ~0.5 m). To locate individual DAS traces, we assign the
geographical position of the geophones to the closest optical trace. At each geo-
phone, we performed six successive hammer shots for calibration purpose. We
compare DAS records of hammer shots in the vicinity of each geophone with the
records of these shots at different traces along the cable. We identify the DAS trace
with the earliest arrival time of seismic waves associated to the hammer shots. For
every geophone position, the shortest distance to the position of the cable was
calculated and the geographical position of this point assigned to the identified
DAS trace. In between individual reference points, the geographical position was
linearly interpolated along the cable. To verify the positions of the traces in the
intervals between geophones, the distance between individual DAS traces is cal-
culated using the number of traces and the distance along the cable and given by
the geophone localisation. We are able to localize every shot with an accuracy of
the sampling resolution along the optical fibre (i.e. 4 m). The localization accuracy
for records located in the range over which geophones were deployed, is therefore
in the order of 10 m for distant traces to the next shot point. The sensitivity of a
linear fibre is decreasing with increasing angle of the incident wave with respect to
the cable direction. Therefore, the comparison of the DAS data with other type of
records (geophone and broadband seismometer) requires the projection of seismic
motions (displacement, velocity or acceleration) in the local direction of the cable.
We oriented the broadband sensors using an Octans (IXSEA) gyro-compass65.
Shallow sub-surface crustal properties determination. The iDAS system is able
to record the ground deformation associated to cars passing by along the cable
(Fig. 2a and Supplementary Fig. 6). We use here those records to locally determine
average rock properties beneath the road. To predict the deformation of the ground
to the car’s weight, we model the car by a series of 4 point loads moving on
an isotropic semi-infinite elastic half-space66. As the speed of the car is slow
compared to the Rayleigh wave velocity in the ground, we use the
Flamant–Boussinesq approximation theory describing the static deformation of a
point load on the ground surface67. In this theory, the ground displacement u(u
x
,
u
y,
u
z
) in the ith direction is given by
ui¼F
4πμ
x3xi
r3þ34υðÞ
δi3
r12υðÞ
rþx3
δ3iþxi
r


ð4Þ
where Fis the force of the point load (weight of the car), μthe shear modulus of the
rock, υthe Poisson ratio, r¼ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi
u2
xþu2
yþu2
z
q, and δis the Kronecker sign (Einstein
notation). The centre of mass of the car (we computed 4 mass contributions at the
locations of the 4 wheels) is assumed to be located at a constant distance of 2.5 m
from the cable. The shape of the strain trace with time at one location is dependent
on the speed and weight of the car, on the distance to the cable, and on the elastic
properties of the ground, e.g. P-wave velocity. Supplementary Fig. 6shows an
example of ground property determination with this approach at one location
along the cable. The best match of the deformation curve we found for a car
moving at ~25 km h−1with a sub-surface P-wave velocity of ~750 m s−1. Note the
almost perfect match between observations and our simple prediction. The P-wave
velocity is consistent with velocities obtained (~500–1000 m s−1) from the refrac-
tion analysis of the seismic waves generated by hammer test shots68. We could use
this method to derive a profile of sub-surface velocities long the cable, a task that
we will pursue in a further study.
Instrumental correction of records from the iDAS system. The iDAS system
measures strain rate (Methods: Strain and displacement and velocity determina-
tion). In order to calibrate the amplitude and phase responses of the recorded
signal by the iDAS system, an impulse displacement signal is sent in the cable and
the output strain is measured at different frequencies. The amplitude and phase
responses both depend on the frequency (Supplementary Figure 1). To retrieve the
true amplitude over a frequency band of interest (<100 Hz) for our seismic
applications, we should correct the recorded signal from the amplitude and phase
shift introduced by the recording unit (iDAS). We focus only on the frequency of
interest for our seismological applications: from <0.01 Hz to 100 Hz. In this fre-
quency band, the response can be modelled with simple functions. We first deal
with the dependency of the instrumental wave response with an apparent ground
velocity v. The response of the iDAS is better expressed in apparent wavelength λ
along the cable. As v=λf,fbeing the frequency, we can express the response as a
non-velocity dependent function with the wavelength (Supplementary Fig. 2): the
gain and phase responses are the same for all wave velocities. We also notice that
the amplitude response is linear with wavelengths above roughly 20 m. The seismic
frequencies of interest are about <100 Hz, therefore wavelengths of interest for us
are above 15–50 m depending on the ground velocity. A simplified instrumental
response can be used. We note that the amplitude decay with diminishing fre-
quency is almost linear below 100 Hz (in logarithm versus logarithm scales). We
also note that the phase is almost constant below 10–20 Hz (in semi-l ogarithm
scale). We express both amplitude and phase responses as a linear function of the
wavelength or frequency. We correct from the recorded signals for the iDAS
instrumental response by multiplying, in the Fourier domain, the amplitude by the
simple function C*λ,Cbeing a constant. If we apply the correction to the
instrumental response, we can calibrate this constant to C=0.0159, by imposing
the corrected instrumental response to amplitude 1 for the frequencies of interest,
as shown in Supplementary Fig. 3. We also note that the phase shift is constant π/2
for long wavelengths (above 100 m). In practice, the processing steps to perform
the restitution of the “true”ground motion, consists of integrating strain rate into
strain, as iDAS records data as strain rate, and as the instrumental response is
expressed in strain. We assume that the initial strain is zero all along the cable, on
the basis that the average strain along the cable is zero. Then, the correction is
applied in the frequency domain as shown in Supplementary Fig. 4. The restitution
depends on the velocity of the medium. Supplementary Fig. 5shows smoothed
version of the restitution spectra for different velocities. Differences are due to
different amplitude and phase responses of the instrumental correction at different
velocities. Note that the transfer function that we used is valid only for the gauge
length used (10 m).
Probability density function of an earthquake location. The probability density
function is, in inversion theory, a way to represent the difference between obser-
vations and a model. In order to find the hypocentre location that minimises the
misfit difference between the synthetic travel times and DAS observations in the
least square sense (RMS), we performed systematic computation of synthetic travel
times for many hypothetic hypocentres within a 3D grid around the hypocentre
location found by the 3D tomographic velocity model in Reykjanes. Each hypo-
thetic hypocentres give a misfit value with respect to observations, represented in
the Supplementary Fig. 7. The DAS cable observations are sufficient to define an
area where the true hypocentre might be. The minimum misfit value is found at a
location which is at <1 km from the hypocentre determined from the 3D travel
time tomography.
Ambient noise interferometric techniques with DAS records. We used ambient
noise interferometric techniques to generate source gathers by cross-correlating
DAS records at different positions (Supplementary Fig. 8). Results indicate mostly
one-sided correlation because ambient noise has a strong directivity, the sources
being located in the Atlantic Ocean (South-Western). Strong perturbation of
ambient noise amplitude occurs at the location of fault damage zones. Other dis-
turbances in the signal amplitude and phase (Supplementary Fig. 8) reveal various
features visible in the field (such as directional changes of the cable at curves of the
road), but also other features that we cannot identify accurately, without more field
inspection. An example of auto-correlation computed at specific DAS/DVS
records, corresponding to the location of the geophones and along the whole
profile are shown in Supplementary Fig. 8b and c.
Data availability. The fibre-optic data and the geophone datasets69 generated and
analysed in the current study and that supports the finding of this study are
accessible via the data repository of “GFZ Data Services”(https://doi.org/10.5880/
GFZ.6.2.2018.003).
Received: 28 November 2017 Accepted: 21 May 2018
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ARTICLE NATURE COMMUNICATIONS | DOI: 10.1038/s41467-018-04860-y
10 NATURE COMMUNICATIONS | (2018) 9:2509 | DOI: 10.1038/s41467-018-04860-y | www.nature.com/naturecommunications
Content courtesy of Springer Nature, terms of use apply. Rights reserved

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Acknowledgements
We gratefully acknowledge help of the following people and institutions; Ernst Huenges,
David Bruhn, Christian Haberland, Kemal Erbas, Karl-Heinz Jäckel and Arthur Jolly for
fruitful discussions; Míla (Iceland) during the field implementation; ISOR staff and
University students for helping with the geophone and broadband sensors deployment.
HS Orka gave access to the road along the telephone line. Geophones, broadband
seismometers and data logger equipment are from the Geophysical Instrumental Pool of
Potsdam (GIPP). Map in Fig. 1was produced using the Generic Mapping Tool v5.0. This
work received funding from the European Union Seventh Framework Programme under
the Grant No. 608553 (project IMAGE), from the Iceland Geosurvey, the Geo-
ForschungZentrum Potsdam and the Helmholtz Association.
Author contributions
P.J. guided the whole experiment and wrote the first manuscript draft and the final
version of the manuscript. P.J., Th.R., J.H., H.B. designed, planned the experiment and
performed the field measurements. P.J., Th.R., T.R. and H.B. analysed the data. P.J. and
Th.R. produced most results shown in the manuscript. T.R. produced the noise corre-
lation results. R.A. and A.C. produced the instrumental response for iDAS technology.
G.P.H. supported the operational and organisational aspects in Iceland and helped in the
field. G.P.H., M.W. and C.M.K. supported the initial idea and gave strong input in the
interpretation and future perspectives. P.J. and Th.R. wrote the manuscript. C.K.
improved it. A.C. checked for English.
Additional information
Supplementary Information accompanies this paper at https://doi.org/10.1038/s41467-
018-04860-y.
Competing interests: The authors declare no competing interests.
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