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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.
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ARTICLE
Dynamic strain determination using bre-optic
cables allows imaging of seismological and
structural features
Philippe Jousset 1, Thomas Reinsch 1, Trond Ryberg1, Hanna Blanck2, Andy Clarke3
Rufat Aghayev3, GylP. Hersir2, Jan Henninges1, Michael Weber 1,4 & Charlotte M. Krawczyk 1,5
Natural hazard prediction and efcient 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 bre-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 bre-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 bre-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 assessment13, for efcient
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 rene images of the structure and better
understand fault rupture and processes, seismology requires
dense spatial coverage of individual sensors1214, 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 waves characteristics18. So far, con-
ventional recording instruments used in those networks provide
high quality waveforms but spatially aliased data. Accurate wave-
elds 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 rst strategy designs high quality
sensors (higher bandwidth, resolution, etc.), which however still
remain single points of observations in space21, whereas the
seismic wave-eld is constantly varying with location and time.
The second strategy, referred to as distributed bre-optic sensing,
uses the entire length of an optical bre as a sensing element
allowing a marked densication 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 bre-optic cable is therefore
stretched and compressed as well. Fibre-optic sensors measure
the response of the optical bre 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 bre and measuring the naturally back-
scattered light. The time-of-ight 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
bre. The phase of Rayleigh backscattered light along an optical
bre is well suited for monitoring dynamic strain changes, with a
high spatial and high temporal resolution (Methods: Distributed
bre-optic sensing). Whereas the physical principle24 is named
phase-OTDR (optical time domain reectometry), 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 prole (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. >510 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 eld3440. In the following, we refer to DASfor simplicity.
In this study, we nd new structural and dynamic features of
normal faults zones within the oblique rift of Reykjanes mid-
oceanic ridge. We achieve those ndings by using an existing
~15-km long conventional bre-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 bre-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 identi-
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 bre-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 prole dened by the bre 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. 24;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 (1100 Hz) are mostly generated by
anthropogenic sources, such as passing cars, uid circulating in
pipes of nearby geothermal power stations, hammer shots on the
ground, people walking, and distant active explosion shots
(Figs. 24). In addition, we detected local earthquakes
(0.520 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 ltered records (range 540 s) from
the optic cable and broadband seismometer for a Mb ~6.2
earthquake in Indonesia, including surface waves (period ranging
1030 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 bre exhibit high coherency, as well as with
signals from broadband seismometers located along the cable
(stations RAH and EIN, Fig. 1). Broadband signals (0.110 Hz)
associated with the ground deformation due to passing cars
along the bre 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 systems22,2527. 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 rst
solved. (1) We locate each DAS trace along the cable with a nal
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 conrmed 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 bre-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 bre. 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 quantied, 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 (Nyquists 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 identication 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 IMAGEperformed 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 45 km, seismic velocity increases rapidly from 1.8 to
4.2 km s1, 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 bre-optic cable in Reykjanes and main geological
features70. Location of the bre-optic cable (continuous green line) from
the telecommunication network (Míla Company) used for our
measurements within the Reykjanes ssure swarm (black lines). Small light
blue squares along the bre-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 12101240 (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 ow), 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 conrmed 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 nd 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 bre-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-eld 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, 12:3312:37). Only selected normalized traces (one trace out of 25, i.e. one trace every 100 m,
frequency range 0.01100 Hz) are shown. A local earthquake is revealed by higher frequencies in the signal from 135 to 140 s. Coherent oscillations of
56 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 (46 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 specic 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
bre-optic cable records allow us to follow details of the earth-
quake phases propagation within the fault zone. To our knowl-
edge, it is the rst time that such details of the wave propagation
are observed within a fault damage zone. From the geological
observation in the eld (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 s1,
which correspond to a velocity slower by 30-40% than outside the
fault damage zone. However, we also observe reected 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 nd 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 bre line (Fig. 1).
In Fig. 7c, records with much larger positive and negative strain
amplitudes suddenly appear at specic locations when the
earthquake waves are passing by. The strain in the bre 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 eld, 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 4060 m).
Wave-elds 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 bre-optic cables28,50 are required, so that newly deployed
cables could fulll the requirements for exploration and mon-
itoring (e.g. separating the bre sensitivity into the three com-
ponents). However, as demonstrated here, existing buried optical
bre 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 bre-optic cable within a telecommunication net-
work, not been specically 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 bre-
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 (at
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 ltered
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-eld 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- reected phases at two reectors or more,
which we interpret as being fault zone boundaries, dening the
fault damage zone, as inferred from our seismic observations.
Reected 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 inuence 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 bre-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 scientic 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 bre is more than 90% efcient for seismic frequencies
between several 10s Hz and long seismic periods52. By demon-
strating that the data acquired on a telecommunication network
of bre-optic cable fullls 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
Ofce) and bre-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
bre-optic telecommunication line. aP- and S-wavestravel times
automatically picked along the prole: 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
(SavitskyGolay) smoothing lter of order 5 with size frame ~3 km long
through the bre-optic V
p
/V
s
individual values
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Content courtesy of Springer Nature, terms of use apply. Rights reserved
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-eld 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 bre-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 bre-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 benet 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 trafc monitoring, theft protection, city
underground monitoring37 will promote telecommunication
companies as actors for Earth hazard monitoring, exploration and
security enhancement for the benet of research60 and human
societies.
Methods
Distributed bre-optic strain sensing. Various optical architectures have been
used to interrogate the backscattered Rayleigh light, ranging from relatively simple,
coherent-OTDR (optical time domain reectometer) 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 bre, a fraction of the light is elastically scattered (Rayleigh
scattering) due to random inhomogeneity distribution in the glass bre material.
During interrogation of an optical bre, the backscattered photons can be detected.
The position of the scattering inhomogeneity within the bre can be calculated
based on the speed of light within the bre. This method is called optical time
domain reectometry (OTDR)63. If a coherent laser pulse is launched into the bre,
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
bre, 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 eld (between 5.04 and 5.09 km). bThe fault damage zone is visible by the ~5060 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 reected 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 bre
is unperturbed, the length and, consequently, the phase-difference Δϕremains
unchanged. Any perturbation inducing a strain εon the bre will change that
difference. The strain rate can therefore be mapped along the sensing bre 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 bre64.
Abre-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 bre. Measurement systems with the capability to
resolve perturbations of 40 nϵare reported27.
Strain and displacement and velocity determination. In our study, we dene the
DAS system as comprising the deployed bre-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 lengthdx26,61.
Comparing successive pulses, phase changes are directly related to the distance
changes and therefore the strain rate in direction of the bre can be recorded. In
the iDAS system, each digital sample is indexed by the centre location of a moving
window along a cablesbre core (the sampleschannel,x) and recording time
(the samplestime,t). Thus, if u(x,t) represents the dynamic displacement of the
bre, 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

uxdx
2;t

uxþdx
2;tdt

uxdx
2;tdt

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
(Nyquists 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 sufcient 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 ltering 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 bre strain-
rate
t
u
x
 ð2Þ
or as an estimate of the spatial derivative of bre particle velocity
x
u
t
 ð3Þ
If we integrate the distributed strain-rate along the optical bre with respect to
time, local strain can be estimated for every section along the optical bre. If we
integrate the local strain with respect to space, the relative displacement can be
calculated at all points along the prole. 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 eld, 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 bre 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 bre 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 250500 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 identied
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 bre (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 bre 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 cars weight, we model the car by a series of 4 point loads moving on
an isotropic semi-innite elastic half-space66. As the speed of the car is slow
compared to the Rayleigh wave velocity in the ground, we use the
FlamantBoussinesq 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
r3þ34υðÞ
δi3
r12υðÞ
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, r¼ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi
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 h1with a sub-surface P-wave velocity of ~750 m s1. Note the
almost perfect match between observations and our simple prediction. The P-wave
velocity is consistent with velocities obtained (~5001000 m s1) from the refrac-
tion analysis of the seismic waves generated by hammer test shots68. We could use
this method to derive a prole 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 rst 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 1550 m depending on the ground velocity. A simplied 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 1020 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 trueground 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 nd the hypocentre location that minimises the
mist 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 mist value with respect to observations, represented in
the Supplementary Fig. 7. The DAS cable observations are sufcient to dene an
area where the true hypocentre might be. The minimum mist 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 eld (such as directional changes of the cable at curves of the
road), but also other features that we cannot identify accurately, without more eld
inspection. An example of auto-correlation computed at specic DAS/DVS
records, corresponding to the location of the geophones and along the whole
prole are shown in Supplementary Fig. 8b and c.
Data availability. The bre-optic data and the geophone datasets69 generated and
analysed in the current study and that supports the nding 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
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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 eld 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 rst manuscript draft and the nal
version of the manuscript. P.J., Th.R., J.H., H.B. designed, planned the experiment and
performed the eld 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
eld. 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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A new method of measuring dynamic strain in boreholes was used to record fracture displacement in response to head oscillation. Fiber optic distributed acoustic sensing (DAS) was used to measure strain at mHz frequencies, rather than the Hz to kHz frequencies typical for seismic and acoustic monitoring. Fiber-optic cable was mechanically coupled to the wall of a borehole drilled into fractured crystalline bedrock. Oscillating hydraulic signals were applied at a companion borehole 30 m away. DAS measured fracture displacement at frequencies of less than 1 mHz and amplitudes of less than 1 nm, in response to fluid pressure changes of less 20 Pa (2 mm H2O). Displacement was semi-logarithmically related to effective stress, a relationship typically explained by the effect of self-affine fracture roughness on fracture closure. These results imply that fracture roughness affects closure even when displacement is a million times smaller than the fracture aperture.
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Obtaining new seismic responses from existing recordings is generally referred to as seismic interferometry (SI). Conventionally, the SI responses are retrieved by simple crosscorrelation of recordings made by separate receivers: one of the receivers acts as a 'virtual source' whose response is retrieved at the other receivers.When SI is applied to recordings of ambient seismic noise, mostly surface waves are retrieved. The newly retrieved surface wave responses can be used to extract receiver-receiver phase velocities. These phase velocities often serve as input parameters for tomographic inverse problems. Another application of SI exploits the temporal stability of the multiply scattered arrivals of the newly retrieved surface wave responses. Temporal variations in the stability and/or arrival time of these multiply scattered arrivals can often be linked to temporally varying parameters such as hydrocarbon production and precipitation. For all applications, however, the accuracy of the retrieved responses is paramount. Correct response retrieval relies on a uniform illumination of the receivers: irregularities in the illumination pattern degrade the accuracy of the newly retrieved responses. In practice, the illumination pattern is often far from uniform. In that case, simple crosscorrelation of separate receiver recordings only yields an estimate of the actual, correct virtual-source response. Reformulating the theory underlying SI by crosscorrelation as a multidimensional deconvolution (MDD) process, allows this estimate to be improved. SI by MDD corrects for the non-uniform illumination pattern by means of a so-called point-spread function (PSF), which captures the irregularities in the illumination pattern. Deconvolution by this PSF removes the imprint of the irregularities on the responses obtained through simple crosscorrelation. We apply SI by MDD to surface wave data recorded by the Malargüe seismic array in western Argentina. The aperture of the array is approximately 60 km and it is located on a plateau just east of the Andean mountain range. The array has a T-shape: the receivers along one of the two lines act as virtual sources whose responses are recorded by the receivers along the other (perpendicular) line. We select time windows dominated by surface wave noise travelling in a favourable direction, that is, traversing the line of virtual sources before arriving at the receivers at which we aim to retrieve the virtual-source responses. These time windows are selected through a frequency-dependent slowness analysis along the two receiver lines. From the selected time windows, estimates of virtual-source responses are retrieved by means of crosscorrelations. Similarly, crosscorrelations between the positions of the virtual sources are computed to build the PSF. We use the PSF to deconvolve the effect of illumination irregularities and the source function from the virtual-source responses retrieved by crosscorrelation. The combined effect of time-window selection and MDD results in more accurate and temporally stable surface wave responses. © The Authors 2016. Published by Oxford University Press on behalf of The Royal Astronomical Society.
Conference Paper
Continuous seismic monitoring can be a crucial tool to optimize hydrocarbon production as well as to provide early warning of potentially hazardous conditions developing in the subsurface. However, the cost of continuous monitoring is a significant obstacle to its widespread application. Distributed Acoustic Sensors (DAS) recording systems hold the promise to enable the recording of seismic data at much lower cost. We deployed a 2.45 km long DAS array with 610 virtual receivers under Stanford University campus and started to record passive seismic data continuously in September 2016. Preliminary analysis show that the data recorded by our DAS array can be used to monitor dynamic processes in the subsurface thanks to sufficient sensitivity to low-amplitude wavefields in the frequency band between .5 and 10 Hz. Our conclusion is supported by the coherency and the frequency content of recorded events corresponding to teleseismic and regional earthquakes as well as of the virtual sources synthesized by using interferometry.
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In this paper we analyze the local and global boundary rigidity problem for general Riemannian manifolds with boundary $(M,g)$ whose boundary is strictly convex. We show that the boundary distance function, i.e., $d_g|_{\partial M\times\partial M}$, known over suitable open sets of $\partial M$ determines $g$ in suitable corresponding open subsets of $M$, up to the natural diffeomorphism invariance of the problem. We also show that if there is a function on $M$ with suitable convexity properties relative to $g$ then $d_g|_{\partial M\times\partial M}$ determines $g$ globally in the sense that if $d_g|_{\partial M\times\partial M}=d_{\tilde g}|_{\partial M\times \partial M}$ then there is a diffeomorphism $\psi$ fixing $\partial M$ (pointwise) such that $g=\psi^*\tilde g$. This global assumption is satisfied, for instance, for the distance function from a given point if the manifold has no focal points (from that point). We also consider the lens rigidity problem. The lens relation measures the point of exit from $M$ and the direction of exit of geodesics issued from the boundary and the length of the geodesic. The lens rigidity problem is whether we can determine the metric up to isometry from the lens relation. We solve the lens rigidity problem under the same global assumption mentioned above. This shows, for instance, that manifolds with a strictly convex boundary and non-positive sectional curvature are lens rigid. The key tool is the analysis of the geodesic X-ray transform on 2-tensors, corresponding to a metric $g$, in the normal gauge, such as normal coordinates relative to a hypersurface, where one also needs to allow microlocal weights. This is handled by refining and extending our earlier results in the solenoidal gauge.
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Proposed solution to geometry puzzle allows an object’s structure to be determined from limited information.