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Evidence for a low-permeability fluid trap in the Nový Kostel Seismic Zone from
double-difference tomography
3rd Annual AIM Workshop I October 10 – 12, 2012 | Smolenice Castle, Slovakia
Catrina Alexandrakis1,3, Marco Calò2, Fateh Bouchaala1 and Vaclav Vavryčuk1
1 Institute of Geophysics, CAS2 EOST, University of Strasbourg
3 Institute of Geophysics and Geoinformatics, TU BAF
2
Acknowledgements
• Data:– J. Horálek, A. Boušková and other members
of the WEBNET group
• Funding:– European Union Research Project AIM
‘Advanced Industrial microseismic Monitoring‘ - Marie Curie Actions
3
Outline
• Introduction
• Methodology– Double-Difference Tomography– Weighted Average Mean Analysis
• Results and Interpretation
• Conclusions
4
West Bohemia Seismic Zone
5
Swarm Triggers
Smrčiny Pluton
Babuška and Plomerová, 2008
Geissler et al., 2005
6
Outline
• Introduction
• Methodology– Double-Difference Tomography– Weighted Average Mean Analysis
• Results and Interpretation
• Conclusion and Future Work
7
Double-Difference TomographyTomoDD (Zhang and Thurber, 2003)
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Double-Difference TomographyTomoDD (Zhang and Thurber, 2003)
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Double-Difference Tomography
• Advantages:– Relocates hypocenter locations– 3D Vp and Vs model of focal zone– Gives the Derivative Weight Sum (DWS) at
each node
• Disadvantages:– No error estimate for the velocity models– Starting model parameterization introduces
bias and artifacts
10
Weighted Average Mean (WAM) Analysis (Calò et al., 2011)
• Solution to parameterization artifacts• Calculates the Weighted Standard Deviation
(WSTD) for the final model
Steps1. Define basic model parameters (e.g. Velocity
model, node locations, hypocenters)2. Perturb the basic parameters3. Average models together using tomoDD’s DWS4. Calculate the standard deviation using DWS as a
weighting factor
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Single InversionsWeighted Average Mean Model
Weighted Standard Deviation
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Input Data• Absolute P and S arrival times -- WEBNET
• Differential Times (two events, single station)– Catalog differential arrival times– Cross-correlated arrival times
• Event Locations -- WEBNET– 474 events – Magnitude 0 - 3.8– Initial hypocenter locations range from 7 to 12 km depth– HypoDD - relocated events
• 3D Velocity Model– Initial Vp model and Vp/Vs (1.70) -- Malek et al., 2000
13
HRC
A‘A
All Stations
A‘
A
HRED
A‘AA‘A
VAC
A‘A
14
Outline
• Introduction
• Methodology– Double-Difference Tomography– Weighted Average Mean Analysis
• Results and Interpretation
• Conclusions
15
Checkerboard Test
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WAM Model
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WAM Model
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Average Velocities
BaseModel
BaseModel
BaseModel
AverageModel
AverageModel
AverageModel
19
• P-Velocity– Expect a decrease in fluid-filled and fractured
materials– Overpressured conditions may produce a
velocity increase (Ito et al., 1979; Popp and Kern, 1993)
• Vp/Vs ratio:– Sensitive to the presence of fluids – Increases in fractured and fluid-filled materials
Wave speeds and fluids
20
Average Velocities
BaseModel
BaseModel
BaseModel
AverageModel
AverageModel
AverageModel
Weise et al., 2001
Weise et al., 2001
23
Outline
• Introduction
• Methodology– Double-Difference Tomography– Weighted Average Mean Analysis
• Results and Interpretation
• Conclusions
24
• 3D velocity analysis reveals:– Layer of low Vp/Vs ratio values corresponds
with the Smrčiny Pluton– May act as a low-permeability fluid trap
– High Vp/Vs and P-velocities occur along the fault plane
– Correspond with previously identified principal faults
– High Vp/Vs values extend to the surface and may reflect fluid pathways
25
Future Work…North – South Principal Fault Across-Strike
27
Anomaly Restoration
28
Starting Model Tests
Slow Model Base Model Fast Model