Acoustic Methods For Monitoring Earthquake Activity In The Global Oceans

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Acoustic Methods For Monitoring Earthquake
Activity In The Global Oceans
Sandra Mansor Cyrille Nofficial Bertrand de
Saint-Jean

• Journal of Geophysical Research, VOL. 106, NO.
  B3, PAGES 4183-4206, MARCH 10, 2001Monitoring
  Pacific Ocean seismicity from an autonomous
  hydrophone array
• Geophysical Research Letters, VOL. 22, NO. 2,
  PAGES 131-134, JANUARY 15, 1995Acoustic
  detection of a seafloor spreading episode on the
  Juan de Fuca Ridge using military hydrophones
  arrays
• Geophysical Research Letters, VOL. 28, NO. 17,
  PAGES 3401-3404, SEPTEMBER 1, 2001Modal
  Scattering a key to understanding oceanic
  T-waves

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Summary

• Brief history
• Basic principles
• SOFAR Channel
• Understanding T-Waves
• SOSUS system
• Autonomous hydrophones
• Conclusion

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Historic

• Data previously used for studying ocean-bottom
  seismicity OBS and land-based seismometers
• Problem areas of study are small and/or
  low-level seismicity ignored (mlt4)
• SOSUS (SOund SUrveillance System) was developed
  by US navy in order to monitor the oceans
  acoustically and is also now used by NOAA to
  monitor intra-oceanic seismicity

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SOFAR Channel

• As temperature decreases, the speed of sound
  decreases.
• As pressure decreases, the speed of sound
  decreases.

Creation of a low-velocity zone
Due to refraction, the acoustic rays are trapped
along the SOFAR channel
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T-Waves What are they ?

• T-Waves travel through the ocean
• Tertiary or (T-) wave Third-arriving seismic
  phase after the primary (P-) compressional wave
  (velocity 1.5 km/s in water and 8 km/s in the
  crust) and the secondary (S-) shear wave
• First identified by Linehan (1940)
• Why can we use T-waves ?
• Detailed ocean sound-speed models available
• SOFAR sound channel allows for lower detection
  threshold
• Less attenuation in water (1/distance) than in
  crustal (1/distance²)
• Smaller order of magnitude gtgt more earthquakes
  detected

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Seismo-acoustic propagation
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T-Waves Generation mechanisms

• How does seismic energy convert to horizontally
  propagating acoustic energy?

• Continental slope conversion (Tolstoy and Ewing,
  1950)
• Stonely wave coupling (interface shear wave
  Biot, 1952)
• Seafloor-sea surface reflection scattering
  (Johnson, 1967)
• Seafloor roughness scattering stonely wave
  coupling (Park and Odom, 2001)

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T-Waves Influence of depth of seisms
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T-Waves Influence of fault types
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SOSUS

• SOSUS SOund SUrveillance System
• System installation begun in the mid-1950s by
  the U.S. Navy and data are accessible to NOAA
  since 1993.
• Composed of sea-bottom hydrophone arrays
  connected by undersea communication cables.
• Datas are analysed in real-time on shore.
• Minimum magnitude 1.8

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SOund SUrveillance System SOSUS

• SOSUS performs adaptative beam formed on
  digitized hydrophone signals.

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An example of SOSUSJuan de Fuca Ridge

• Embedded Earthquakes series of small shocks
• Harmonic Tremor to be compared with magmatic
  flows observed on Kilauea Volcano

Localisation of all the earthquakes during the
event can allow to trace the dike injection
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Juan de Fuca Ridge Localization
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Autonomous hydrophoneAn array

• 6 hydrophones deployed on both flanks of the
  Juan de Fuca ridge.
• Hydrophone sites correspond to the pre-existing
  TAO mooring (Tropical Ocean-Global Atmosphere).
  This makes maintenance easier, because ships
  often go there!

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Autonomous hydrophonesInstruments
Mooring schematics
An autonomous hydrophone pressure case
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Autonomous hydrophonesData acquisition

• Data are band-pass filtered for low frequencies
  (1- 40 Hz)
• An analog pre-amplifier is used to flatten the
  response curve
• Data are bufferized in a RAM and downloaded on a
  hard disk every 6 hours
• 1-byte resolution each 0.01s (100 Hz)

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Autonomous hydrophonesData Processing

• Time resolution between 0.1 and 5 s
• 5 s rough picking
• 0.1 s accurate picking
• Spectral analysis over a window of 1 s (minimum
  of 1 Hz)

Time series and spectrogramssynchronized vs.
time on 5 hydrophones
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Autonomous hydrophonesData Processing (part 2)

• Data are interpreted by scanning tha data from
  several instruments simultaneously
• 3 instruments allow the computation of an
  approximate epicenter location (5s resolution)
• From this location, the theoretical travel time
  to the other instruments can be computed and used
  to synchronize the data recorded by these other
  instruments with those of the first three.
• Refine arrival time picks (0.1 s resolution)
• Re-compute a more accurate source location
• Save information (time picks, location, location
  errors, magnitude) about this event
• Origin of errors
• Incorrect sound speed in the SOFAR channel
• Errors on the positions hydrophones
• Errors on the picking of arrival times

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Autonomous hydrophonesCalibration
T wave source location

• By using accurately positioned earthquakes (both
  in time and location), such as the ones from
  Loihi Seamount in the Hawaiian archipelago
• Estimate the errors of the acquisition process
• Compute the resulting errors in latitude,
  longitude and time

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Autonomous hydrophonesError field
Time (s)

• Symmetry of the iso-error line
• Epicenter locations are less accurate when some
  hydrophones are in line with the epicenter

Latitude (km)
Longitude (km)
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Autonomous hydrophonesAn example

• 5 hydrophones

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Autonomous hydrophonesRemarks

• Difficulties in relating acoustic and seismic
  magnitudes !
• Other uses of hydrophone data (mammals studies,
  )
• Technology still under development (real-time
  data transmission)

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Advantages and disadvantages

• Autonomous hydrophones do not allowreal-time
  monitoring
• No determination of focal mechanisms
• High cost of ship-time needed for deployment
• Possible errors in locating the entry point into
  the SOFAR channel

• Record of low-level seismicity
• Portable stations
• Wide areas of studies with a single network
• Good precision

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Discussion

• Questions ?????

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T-Waves