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

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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

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Outline

• Introduction

• Methodology– Double-Difference Tomography– Weighted Average Mean Analysis

• Results and Interpretation

• Conclusions

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West Bohemia Seismic Zone

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Swarm Triggers

Smrčiny Pluton

Babuška and Plomerová, 2008

Geissler et al., 2005

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Outline

• Introduction

• Methodology– Double-Difference Tomography– Weighted Average Mean Analysis

• Results and Interpretation

• Conclusion and Future Work

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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

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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

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HRC

A‘A

All Stations

A‘

A

HRED

A‘AA‘A

VAC

A‘A

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Outline

• Introduction

• Methodology– Double-Difference Tomography– Weighted Average Mean Analysis

• Results and Interpretation

• Conclusions

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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

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• 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

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Average Velocities

BaseModel

BaseModel

BaseModel

AverageModel

AverageModel

AverageModel

Weise et al., 2001

Weise et al., 2001

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Outline

• Introduction

• Methodology– Double-Difference Tomography– Weighted Average Mean Analysis

• Results and Interpretation

• Conclusions

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• 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

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Future Work…North – South Principal Fault Across-Strike

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Anomaly Restoration

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Starting Model Tests

Slow Model Base Model Fast Model