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