MTR meeting, Tutzing, FEB 2006 1

P. Martin MaiInstitute of Geophysics, ETH Zurich

mai@sed.ethz.ch

and the SPICE Local Scale Group

(Ampuero, Delouis, Festa, Holden, Madariaga, Moczo, Vilotte, Zarahdnik …)

Blindtest onBlindtest onKinematic Source InversionKinematic Source Inversion

Initial (sobering) resultsInitial (sobering) results

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► ► Goal:Goal: perform accurate kinematic finite-source perform accurate kinematic finite-source inversion to estimate the rupture process during inversion to estimate the rupture process during earthquake faultingearthquake faulting

► ► Approach:Approach: test various source-inversion methods, test various source-inversion methods, and assess their resolution, strength and weaknesses to and assess their resolution, strength and weaknesses to finally “design” the optimal inversion strategyfinally “design” the optimal inversion strategy

► ► Method:Method: generate synthetic near-source motions for generate synthetic near-source motions for some source rupture model (with increasing complexity some source rupture model (with increasing complexity as the project progresses) that is known to only one as the project progresses) that is known to only one person (M. Mai), while interested researchers can then person (M. Mai), while interested researchers can then apply their source-imaging technique “blindly”apply their source-imaging technique “blindly”

OUTLINEOUTLINE

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The Model SetupThe Model Setup

• Earthquake source geometry and station distribution chosen to be reminiscent of the 2000 Tottori earthquake (M = 6.9), but the details of the rupture process are not known.

MTR meeting, Tutzing, FEB 2006 4

The Model SetupThe Model Setup

• Synthetic seismograms are then computed, assuming (unknown to modelers) constant rupture velocity, constant rise time, simple slip-velocity function, and heterogeneous slip.

• A discrete wave-number integration method (0.01 < f < 3 .0 Hz) is used for wavefield calculations.

• In the first step, no noise is added to the synthetics; later, also the above conditions on vr, tr will be relaxed. • The modelers are given;

• seismic moment: 1.43 1019

Nm• dip = 90o

• rake = 150o

• hypocentral depth = 12.5 km• velocity-density structure

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INITIAL RESULTSINITIAL RESULTS

• So far, four researchers have sent in their inversion solution to this initial problem:

the results are remarkably diverse !!!!!

In alphabetical order …

Betrand Delouis: Non linear inversion by simulated annealing

Gaetano Festa: back-projection of the S -amplitudes along the rays

Catherine Holden: non linear inversion using the neighbourhood algorithm

Jiri Zahradnik: iterative moment-tensor deconvolution, combined with forward modeling

MTR meeting, Tutzing, FEB 2006 6

INITIAL RESULTSINITIAL RESULTS

Betrand Delouis: Non linear inversion by simulated annealing

vr = 3.1 km/s, tr = 1.0 s

NOTE THE GOOD DATA FITTING !!!

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INITIAL RESULTSINITIAL RESULTS

Gaetano Festa: back-projection of the S -amplitudes along the rays

vr = 2.8 km/s, tr = 1.0 s

NOTE THE GOOD DATA FITTING !!!

MTR meeting, Tutzing, FEB 2006 8

INITIAL RESULTSINITIAL RESULTS

Catherine Holden: non linear inversion using the neighbourhood algorithm

vr = 2.15 km/s, tr = ?? s

NOTE THE GOOD DATA FITTING !!!

MTR meeting, Tutzing, FEB 2006 9

INITIAL RESULTSINITIAL RESULTS

Jiri Zahradnik: iterative moment-tensor deconvolution, combined with forward

modelingvr = 2.6 km/s, tr = 1.0 s

NOTE THE GOOD DATA FITTING !!!

MTR meeting, Tutzing, FEB 2006 10

THE SOLUTIONTHE SOLUTION

… and here comes the long awaited answer ….

• vr = 2.7 km/s and tr = 0.8, using an isosceles triangle as SVF;• max. displacement ~ 2.5m, about 15 km north-west of the hypocenter• the rupture expanded primarily in the NW-direction

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CONCLUSIONSCONCLUSIONS

► Can we conclude anything from this exercise yet??

► First of all: work is needed to make this solutions agree

-- consistent definition which stations to use and how to perform the data preparation, to eliminate any bias coming from there-- differences due to Green’s function calculations ??-- differences due to inversion approach (linear vs. non-linear, parameterization, smoothing, misfit function, etc) ??

► Next step: quantitative comparison of inverted slip models:-- cross-correlation analysis with respect to input model-- slip values at selected points-- overall slip distribution-- ….