title three-dimensional velocity models and probabilistic earthquake location stephan husen...
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Title
Three-dimensional velocity models and probabilistic earthquake location
Stephan Husen
Scientific Software, Mouans-Sartoux, France, [email protected]
Institute of Geophysics, ETH Zurich, Switzerland, [email protected]
Anthony Lomax
with contributions from
Edi Kissling
Institute of Geophysics, ETH Zurich, Switzerland
Linearized earthquake locationIntroduction
3D Velocity Model
Probabilistic Earthquake Location
Location Examples
Conclusions
linearized earthquakelocation Traditional earthquake location
• linearized methods (HYPO71, HYPOELLIPSE, HYPOINVERSE,..)
• 1-D velocity models (plus station delays)
• error bars or error ellipses (linear)
• efficient
…. but linearized methods and 1-D velocity models are only approximations!
what do we needIntroduction
3D Velocity Model
Probabilistic Earthquake Location
Location Examples
Conclusions
improvement
How can we improve the situation?
• 3-D velocity models (Local earthquake tomography, controlled-source experiment)
• Non-linear earthquake location (NonLinLoc)
Example mine blastIntroduction
3D Velocity Model
Probabilistic Earthquake Location
Location Examples
Conclusions
relocation mine blast
True location
Linear solution (1D)
True location
Linear solution (1D)
Non-linear solution (3D)
Mine Blast - True location is known
Data qualityIntroduction
3D Velocity Model
Probabilistic Earthquake Location
Location Examples
Conclusions
earthquake data in Switzerland
729 earthquakes with 10,044 P-observations
only highest quality data (impulsive onsets)
Moho topographyIntroduction
3D Velocity Model
Probabilistic Earthquake Location
Location Examples
Conclusions
Moho topography
3-D Moho topography beneath Switzerland as determined by controlled-source seismology data
Waldhauser et al., 1998
Min. 1D modelIntroduction
3D Velocity Model
Probabilistic Earthquake Location
Location Examples
Conclusions
min. 1D modelSubset of 200 earthquakes
Simultaneous inversion for 1D velocity models, hypocenter locations, and station delays
Software VELEST
Initial modelsFinal models
CSS modelIntroduction
3D Velocity Model
Probabilistic Earthquake Location
Location Examples
Conclusions
controlled-source data
3-D P-wave velocity model determined by controlled-source seismology (CSS) data
Final modelIntroduction
3D Velocity Model
Probabilistic Earthquake Location
Location Examples
Conclusions
final (combined) model
Final 3D P-wave velocity model determined by earthquake data and controlled-source data
crust is controlled by earthquake data
Lower crust / Moho is controlled by CSS data
NonLinLocIntroduction
3D Velocity Model
Probabilistic Earthquake Location
Location Examples
Conclusions
software NonLinLoc
Posteriori Probability Density Function (x) (PDF):
relies on known a priori information (x) on model parameters and on observations.
PDF gives complete location uncertainties.
Software NonLinLoc: www.alomax.net/nlloc
(x) = K(x)*exp[-1/2misfitL2(x)]
Tarantola and Valette (1982)
PDF is computed using global sampling techniques - grid search or Oct-Tree importance sampling.
Global sampling methodsIntroduction
3D Velocity Model
Probabilistic Earthquake Location
Location Examples
Conclusions
Grid-Search
Grid-Search
complete mapping
inefficient and slow
Global sampling methodsIntroduction
3D Velocity Model
Probabilistic Earthquake Location
Location Examples
Conclusions
Grid-Search vs. Oct-Tree sampling
Grid-Search
complete mapping
inefficient and slow
Oct-Tree sampling
importance sampling
efficient and fast
Location uncertaintiesIntroduction
3D Velocity Model
Probabilistic Earthquake Location
Location Examples
Conclusions
solution and location uncertainties
Grid-search Oct-Tree importance sampling
confidence contours scatter clouds
maximum likelihood hypocenter location
68% confidence ellipsoid
Example 1Introduction
3D Velocity Model
Probabilistic Earthquake Location
Location Examples
Conclusions
non-linear uncertainties
Nobs: 8
RMS: 0.04 s
GAP: 193
Dmin: 1.9 km
SED error:
ERRH: 1.9 km
ERRZ: 2.6 km
Difference:
dx: 1.0 km
dy: 5.2 km
dz: 0.1 km
1987 05 08 09:59 46.146 N 8.614 E 4.1km
Non-linear(3D)
Linear(1D)
Example 2Introduction
3D Velocity Model
Probabilistic Earthquake Location
Location Examples
Conclusions
no control on focal depth
Nobs: 8
RMS: 0.14 s
GAP: 164
Dmin: 16.9
km
SED error:
ERRH: 2.2
km
ERRZ: 2.6
km
Difference:
dx: 2.5 km
dy: 3.0 km
dz: 15.7 km
1993 04 15 13:57 46.921 N 9.607 E -0.9 km
Non-linear(3D)
Linear(1D)
ConclusionsIntroduction
3D Velocity Model
Probabilistic Earthquake Location
Location Examples
Conclusions
• combination of local earthquake data and controlled-source data provides reliable 3-D velocity models
• probabilistic earthquake location combined with global sampling algorithms is efficient and reliable
• location uncertainties obtained by probabilistic earthquake location prove to be much more reliable, important for planetary data sets with few instruments
Conclusions
ConclusionsIntroduction
3D Velocity Model
Probabilistic Earthquake Location
Location Examples
Conclusions
Outlook
• application and tuning of existing geophysical methods to planetary data sets (real and synthetic) considering their peculiarities, i.e. small number of receivers