Download intrinsic Q - University of Leeds

Using the seismic amplitude decay of low-frequency events to
constrain magma properties.
AGU Fall Meeting, San Francisco, December 2007. Session & Poster number: V51D-0782
P. J. Smith & J. Neuberg
School of Earth and Environment, University of Leeds., UK. ([email protected])
The island of Montserrat
and its location within the
Lesser Antilles volcanic
island chain.
1. Background
i. Soufrière Hills Volcano, Montserrat.
ii. Low-frequency seismicity.
Characteristics of low-frequency events
3
• Repeatable source mechanism
μ = shear modulus or
rigidity
moment:
Magma ascent rate
Apparent Q
Apparent Q value based on synthetic signal envelope
(explosive source)
Damped Zone
Domain Boundary
To include anelastic
‘intrinsic’ attenuation,
the rheology of the
material is
parameterized by an
array of Standard
Linear Solids (SLS).
Apparent Q
greater than
intrinsic Q:
log(Amplitude)
70
60
40
1  e 
Apparent Q less
than intrinsic Q:
Radiative
energy loss
dominates
Resonance
dominates
50
30
m
20
For a fixed parameter contrast
10
2 SLS in array
0
-23.4
0
10
20
30
40
50
60
70
80
90
100
Intrinsic Q
Apparent Q vs. intrinsic Q for the
synthetic signals, showing two regimes.
Gradient of line =-0.10496
Q value from gradient =
31.5287
0
2
4
6
Time [cycles]
8
10
Synthetic trace
12
Produce synthetic seismograms from
which an apparent Q is determined via the
gradient of log(Amplitude) against time.
We then see to what extent the apparent Q
is determined by the intrinsic Q given to
the model.
Amplitude
1Hz Küpper
wavelet
Fluid magma
(viscoelastic)
Variable Q
Linear Fit
Data
-23.6
Source Signal:
Intrinsic Q vs. Apparent Q
Intrinsic=Apparent
90
80
-24
Trigger mechanism: brittle
failure at conduit walls
-1
Qa =
-1
Qi +
Time [number of cycles]
Geometry and parameters chosen to
produce monochromatic smoothly
decaying synthetic signals
Preliminary apparent Q
analysis of the waveforms of
low-frequency events from
Montserrat. The ‘peaked’
amplitude spectra are used
to create a series of narrow
band-pass filters for the data.
-1
Qr
parabolic flow
τ
Gas
diffusion
Collier & Neuberg, 2006; Neuberg et al., 2006
i. Observations and modelling
Photographic evidence from an
extruded spine suggests a
widening of the conduit from 30m
to 50m.
Seismic observations: frequency
shift of low-frequency events over
extended period of time.
Results of numerical modelling
verify change in frequency of
resonance with width.
Comparison of a 30m and 50m wide
conduit: illustrating the change in
frequency content with widening
conduit
ii. Implications.
Changes overall flow behaviour, particularly velocity profiles,
mass flux and ascent rate and therefore also the velocity
and shear stresses. This will impact on the occurrence and
location of brittle fracturing, and also degassing processes.
Suggests flow behaviour and seismicity may be controlled
by shallow processes rather than the magma chamber.
6. Summary
Example low-frequency event from April 1997.
1
2
The amplitude decay of the
filtered
2
‘Peaked’
3
amplitude
signals is
1
spectrum used
used to
to choose
frequencies for
determine a
4
band-pass filters
set of
apparent Q
values.
  10 Pa
Increased conduit width is an important observation and may
mark a significant change in the volcano’s behaviour.
iii. Data Analysis
100
-22.6
ρ = 2600 kgm-3
α = 3000 ms-1
β = 1725 ms-1
Qa-1=Qi-1+Qr-1
Intrinsic Q vs. Apparent (coda) Q
ii. Calculation of apparent Q
Seismometers
rf
af
Intrinsic
Radiative (parameter
But requires full moment tensor inversion Apparent (coda)
(anelastic)
contrast)
of a non-couple source mechanism.
Need understanding of amplitude losses. (Aki, 1984)
true damping amplitude decay
Match/use as input
-23.2
Qi
Want to determine amount of slip, u, from
the seismic moment, so we then get
Both the viscosities and Q are highly
dependent on the gas-phase. Particularly
the gas-volume fraction, bubble number
density and also bubble size and shape.
Q
4. Conduit Widening
Amplitude spectra of synthetic low-frequency
signals for a 30m wide and 50m wide conduit.
Total amplitude decay is a
combination of these
contributions:
Magma
slowing
Link model for source mechanism to cycles of
deformation and seismicity.
T (transmission coefficient) Seismometer
rs
R (reflection coefficient)
a
s
M0 = µAu
Gives seismic
τ
Diffusion lags
behind
Qa-1
Qr-1
Collier & Neuberg, 2006;

τ
ii. Components of amplitude loss
u = average slip
Amount of slip × Event rate →
Unfiltered data
τ
A = area of fault rupture
ii. Magma
viscosities are ηb
ηm
derived
from
flow modelling:
ii. Magma
viscosities
are
derived from flow modelling:
-23
Generation of interface
waves at the conduit walls.
Stress threshold:
7
depth of
brittle failure
No seismicity
Gas loss
τ
Brittle fracturing on ring-fault as
seismic source:
Magma viscosity
-22.8
τ
3. Factors determining the seismic amplitude
i. Source mechanism
slip
Melt viscosity
Solid medium
(elastic)
Pressure
increasing
Most of the energy
remains
within the conduit
Conduit resonance: energy generated by a
Different types of volcanic seismicity. Low seismic source is trapped by the impedance
frequency events are characterized by their contrast between fluid and solid and travels
harmonic coda and spectral content.
as interface waves.
plug
flow
gas
loss
1
Pressure
decreasing
ii. Magma viscosities are
derived from flow modelling:
-23.8
Gas diffusion
slip
(P. Jousset)
This intrinsic Q is highly dependent on the properties of the magma. Q is quantified using the
phase-lag between stress and strain for a sinusoidal pressure wave – equivalent to using the
material properties (viscosities). The method includes the effects of bubble growth by diffusion.
Free surface
Swarm of low-frequency events merging
into tremor before a dome collapse.
Cylindrical shear fracturing at
the edge of the conduit as
seismic triggering mechanism
2
Seismicity
Seismic attenuation is quantified through the quality factor Q, the inverse of the attenuation.
2-D O(Δt2,Δx4) scheme based on Jousset et al. (2004).
Volcanic conduit modelled as a viscoelastic fluid-filled
body embedded in homogenous elastic medium.
Events are
recorded by
seismometer
as surface
waves
Interface
waves
i. Q and magma properties
i. Finite-difference model
No seismicity
• Swarms precede dome collapse
2. Seismic attenuation in bubbly magma
5. Wavefield modelling
4
• Tight clusters of source locations
The volcano has been well monitored throughout this period
of activity and in particular several types of volcanic seismic
signals have been observed including, rockfalls, volcanotectonic earthquakes and low-frequency events.
Effects of including bubble growth by diffusion and mass
flux on the seismic attenuation. Collier et al. (2006)
(Neuberg et al, 2006)
• Similar waveforms
Soufrière Hills Volcano is an andesitic stratovolcano situated
on the island of Montserrat at the northern end of the Lesser
Antilles volcanic arc, formed by the subduction of Atlantic
oceanic lithosphere beneath the Caribbean plate.
The current phase of eruptive
activity has been ongoing since
1995, beginning with phreatic
activity, and has since been
characterized by cycles of lava
dome growth followed by
subsequent dome collapses.
View of the lava dome of Soufrière Hills Volcano,
Montserrat, from the MVO in April 2007.
Photograph by P. Smith.
iii. Seismic trigger mechanism: brittle fracturing of the magma
3. Synthesise seismic wave propagation in such a
conduit and determine apparent Q from amplitude
decay of the signals produced.
4. Compare results with analysis of data from
Montserrat.
Event amplitude spectrum Band-pass filtered traces with apparent Q values
50
m
ux
30m
Magma velocity profiles for 30m and 50m wide conduits,
derived using a 2-D finite-element model of three-phase
magma flow in a conduit. (by M. Collombet)
Discussion and further work
1. Determine 2-D distribution of intrinsic Q values in Need to conduct more analysis of the apparent Q
a volcanic conduit through magma flow modelling, of data from Montserrat. Want to examine any
including the effects of bubble growth by diffusion. azimuthal variation for single events, variation with
distance from conduit and changes over time.
2. Transfer into finite-difference models of the
seismic wavefield by fitting an array of Standard
Further develop magma flow meter idea. Need full
Linear Solids (SLS) to model the 2-D intrinsic Q
moment tensor inversion to get seismic moment
distributions.
and hence determine the amount of slip per event.
3
4
50m conduit
30m conduit
5. By comparison of modelling results with data
analysis link the Q values back to the magma
properties and gain information about the system.
7. Acknowledgements
Aki, K., 1984. Magma intrusion during the Mammoth Lakes earthquake. JGR, 89, pp7689-7696.
Collier, L. & Neuberg, J., 2006, Incorporating seismic observations into 2D conduit flow modelling.
J. Volcanol. Geotherm.,, 152, pp331-346
Collier, L., Neuberg, J., Lensky, N. & Lyakhovsky, V., 2006, Attenuation in gas-charged magma.
J. Volcanol. Geotherm., 153, pp21-36.
Jousset, P., Neuberg, J. & Jolly, A., 2004, Modelling low-frequency volcanic earthquakes in a
viscoelastic medium with topography. J.GI.., 159, pp776-802.
Neuberg, J., Tuffen, H., Collier, L., Green, D., Powell T. & Dingwell D., 2006, The trigger
mechanism of low-frequency earthquakes on Montserrat. J. Volcanol. Geotherm., 153, pp37-50.
Patrick Smith's Ph.D. is funded by NERC grant
NER/S/A/2006/14150. The data collection and archiving by
staff of the Montserrat Volcano Observatory is fully
acknowledged.