Transcript Determination of source parameters and full moment tensors of

Determination of Source Parameters
and Full Moment Tensors
in a Very Heterogeneous Mining
Environment
Václav Vavryčuk1, Daniela Kühn2
1 Institute
of Geophysics, Prague
2 NORSAR, Kjeller
Motivation
Waveform
modelling
Polaities and
amplitudes
MTI
strategy
Application
to real data
Summary
Motivation
Pyhäsalmi ore mine, Finland
• microseismic monitoring:
 since January 2003
 safety of the underground
personnel
 optimisation of mining
process
Motivation
Waveform
modelling
Polaities and
amplitudes
• network:
 12 1-C geophones
+ 6 3-C geophones (ISS)
 3-D geometry
 sampling rate: < 3000 Hz
MTI
strategy
Application
to real data
Summary
owned by Inmet Mining Co.,
installation of seismometer network by the ISS Int. Ltd.
• events:
 1500 events /months
(including blasting)
 -2 < Mw < 1.5
Velocity model
Strongly heterogeneous velocity model
Motivation
Waveform
modelling
• ore body: vp = 6.3 km/s
• host rock: vp = 6.0 km/s
• excavation area: vp = 0.3 km/s
Polaities and
amplitudes
MTI
strategy
Application
to real data
Summary
U
W
E
D
Motivation
Waveform
modelling
Polaities and
amplitudes
MTI
strategy
Application
to real data
Summary
Waveform modelling
Waveform modelling: 2D
• E3D: viscoelastic 3-D FD code (Larsen and Grieger, 1998)
Motivation
Waveform
modelling
Polaities and
amplitudes
MTI
strategy
Application
to real data
Summary
• strong interaction with mining cavities: reflection,
scattering, conversion
620 m
Waveform modelling: 3D
Motivation
Waveform
modelling
Polaities and
amplitudes
MTI
strategy
Application
to real data
Summary
Waveform modelling
synthetic seismograms
Motivation
- complex waveforms
Waveform
modelling
- long, strong coda
Polaities and
amplitudes
- complex secondary arrivals
- difficult to interpret P-wave
polarities
MTI
strategy
- difficult to identify S-wave
arrivals
Application
to real data
Summary
observed seismograms
Motivation
Waveform
modelling
Polaities and
amplitudes
MTI
strategy
Application
to real data
Summary
Polarities and amplitudes
of direct P waves
Geophone network (artificial)
Motivation
Waveform
modelling
Polaities and
amplitudes
.
MTI
strategy
source mechanisms
Application
to real data
Summary
source
location
Comparison 1-D/3-D
Motivation
Waveform
modelling
Polaities and
amplitudes
MTI
strategy
Application
to real data
Summary
+ polarity: red
- polarity: blue
Moment tensor inversion
for a homogeneous model
Motivation
Waveform
modelling
Synthetic source
mechanism
Observed
amplitudes
Retrieved source
mechanism
Polaities and
amplitudes
MTI
strategy
Application
to real data
Summary
ISO = 0 %
DC = 100 %
CLVD = 0 %
ISO = 23 %
DC = 48 %
CLVD = 52 %
Source depth
Motivation
Waveform
modelling
Polaities and
amplitudes
.
MTI
strategy
Application
to real data
Summary
U
W
E
D
Motivation
Waveform
modelling
Polaities and
amplitudes
MTI
strategy
Application
to real data
Summary
Moment tensor inversion
Moment tensor inversions
Motivation
Waveform
modelling
Polaities and
amplitudes
wave amplitudes
amplitude ratios
(Vavryčuk et al. 2008;
Fojtíková et al. 2010;
Godano et al. 2011)
(Miller et al. 1998;
Hardebeck & Shearer
2003; Jechumtálová &
Šílený 2005)
• applicable to simple
media
• applicable to simple
media
• insensitive to
amplifications
• non-linear
MTI
strategy
Application
to real data
Summary
• linear
• fast
full
waveforms
(Šílený et al. 1992
Cesca et al. 2006;
Cesca & Dahm 2008;
Sokos & Zahradník
2009)
• applicable to complex
media
• linear
• more time consuming
Moment tensor inversions
Motivation
Waveform
modelling
Polaities and
amplitudes
wave amplitudes
amplitude ratios
(Vavryčuk et al. 2008;
Fojtíková et al. 2010;
Godano et al. 2011)
(Miller et al. 1998;
Hardebeck & Shearer
2003; Jechumtálová &
Šílený 2005)
• applicable to simple
media
• applicable to simple
media
• insensitive to sensor
amplifications
• non-linear
MTI
strategy
Application
to real data
Summary
• linear
• fast
full
waveforms
(Šílený et al. 1992
Cesca et al. 2006;
Cesca & Dahm 2008;
Sokos & Zahradník
2009)
• applicable to complex
media
• linear
• more time consuming
Proposed MTI strategy
• accurate locations using the eikonal solver
Motivation
Waveform
modelling
Polaities and
amplitudes
MTI
strategy
Application
to real data
Summary
– the first arrival need not correspomd to a direct wave
– eikonal solver takes into account refractions and diffractions
• Green’s functions computed using viscoelastic 3D FD
code
– detailed 3D velocity model with spatial sampling of 2 m
– time sampling: 10 KHz
• waveform inversion in time domain
– source time function assumed as Dirac delta function
– waveforms low-pass filtered (f < 80 Hz)
– waveform alignment using cross-correlation of observed data and
synthetics (maximum time shift: ± 0.01 s)
– errors estimated using repeated inversions of waveforms
contaminated by random noise and with random time shift
Motivation
Waveform
modelling
Polaities and
amplitudes
MTI
strategy
Application
to real data
Summary
Application to real data
Motivation
5 Blasts
Waveform
modelling
U
Polaities and
amplitudes
N
S
D
MTI
strategy
Application
to real data
Summary
5 Events
N
U
W
E
D
W
E
S
blast 1
Motivation
Waveform
modelling
blast 2
Polaities and
amplitudes
MTI
strategy
Application
to real data
Summary
blast 4
Results: blasts
1E
7Z
12Z
1N
8Z
13N
2Z
9E
13E
4Z
9N
13Z
5N
9Z
14Z
5E
10Z
15Z
6Z
11Z
16Z
1E
6Z
12Z
1N
7Z
13N
1Z
8Z
13E
2Z
9N
13Z
4Z
9Z
14Z
5N
10Z
15Z
5Z
11Z
16Z
1E
7Z
12Z
1N
8Z
13N
1Z
9E
13E
3Z
9N
13Z
4Z
9Z
14Z
5E
10Z
15Z
6Z
11Z
16Z
event 2
Motivation
Results: events
1E
11Z
1N
5E
5Z
1Z
6Z
13N
2Z
7Z
13E
3Z
9E
13Z
4Z
9Z
14Z
10Z
15Z
1E
5Z
11Z
1N
6Z
12Z
1Z
7Z
13E
3Z
9E
13Z
4Z
9N
14Z
5N
9Z
15Z
5E
10Z
16Z
1E
5E
11Z
1N
5Z
12Z
1Z
7Z
13N
2Z
8Z
13E
3Z
9N
13Z
4Z
9Z
14Z
5N
10Z
16Z
5N
Waveform
modelling
event 3
Polaities and
amplitudes
MTI
strategy
Application
to real data
Summary
event 4
12Z
Blast 1: stability of ISO
Mean value
stable and positive
isotropic components
Motivation
ISO > 65%
Waveform
modelling
Polaities and
amplitudes
MTI
strategy
Application
to real data
Summary
Standard deviation
Results: overview
DC [%] CLVD [%] ISO [%]
Waveform
modelling
Polaities and
amplitudes
MTI
strategy
Application
to real data
Summary
• high and positive ISO %
Blasts
Motivation
Blasts:
Blast 1
19.5
14.6
65.9
• DC is minor
Blast 2
38.5
3.1
58.4
Blast 3
21.2
-12.7
66.1
• DC may reflect minor shearing
induced during blasting or errors
Blast 4
19,9
15.0
65,1
Blast 5
12,1
-6,6
81,3
Events
Event 1
4,9
-36,2
-58,9
Event 2
63,7
-19,6
-16,7
Event 3
52,6
-10,3
-37,1
Event 4
10.6
-24.7
-64.7
Event 5
38,2
-0,6
-61,2
Events:
• CLVD and ISO are implosive
• predominant mechanism is
probably related to collapse of
rock due to mining activity
Summary I
Motivation
Waveform
modelling
Polaities and
amplitudes
structural model in mines
usually is very complex
large and abrupt changes in
velocity at cavities
the model varies in time
MTI
strategy
Application
to real data
Summary
earthquake source is complex
(single forces, non-DC
components, complex source
history)
Summary II
Motivation
Waveform
modelling
radiated wave field is
complex
(reflected, converted,
scattered waves, head waves)
Polaities and
amplitudes
MTI
strategy
Application
to real data
Summary
inversion in a homogeneous
model may lead to erroneous
results
Summary III
Amplitude inversion:
• simple approach
Motivation
Waveform
modelling
Polaities and
amplitudes
MTI
strategy
• limited applicability (simple Green’s functions are not adequate)
• no control on frequency bands
• amplitudes can be wrongly interpreted
Full waveform inversion:
• accurate model
and accurate location needed
• eikonal solver for event location
Application
to real data
Summary
• complex Green’s functions can be calculated by 3-D FD codes
• frequency band of inverted waves can be controlled
• promising, but computationally demanding and laborious
Thank you!