Use of Travel Time Tomography in Strong Motion Simulation

8/6/2019 Use of Travel Time Tomography in Strong Motion Simulation

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S E O F T R A V E L S E O F T R A V E L I M E T O M O G R A P H Y I N S T R O N G I M E T O M O G R A P H Y I N S T R O N G O T I O N S I M U L A T I O N O T I O N S I M U L A T I O N



CONTENTS

• Introduction• Travel time tomography

• Strong motion simulation using Semi-Empiricalapproach

• Case study- 1• Case study- 2

• Conclusion



Introduction

• The word ‘tomography’ means ‘slice picture’ ( from the Greekword ‘tomos’ meaning ‘slice’ ).• It was first used in medical imaging.• Seismologist use ‘tomography ’ word to describe the imaging of

2-D slices only.

• Tomography involve gathering projection data from multipledirections and feeding the data into a tomographicreconstruction software algorithm processed by a computer.

• In the present day, seismic travel time tomography is the one of the robust technique which is used in determining theappropriate velocity model.

•



Velocity ModelRay Tracing (Forward Modeling)

Seismic Data (Travel time)

Seismic Data (Travel time) Seismic Data (Travel time)Tomographic inversion (Inverse Modeling)



.



bjectives of PresentWork



ravel Time Tomography

Ø Introduction

•



t(ray) = ∫s(x,z) dl



∆t = D∆S

Ø Forward Modeling Vs Inversion



Ø Ray Tracing



Ø Problem StatementT = Dn×m ×Sm

Ø Experiment Data vs. Model Data

Treal = Dreal ×Sreal

Tmodel = Dmodel ×Smodel



Dreal = Dmodel = D

ØThe Damped least Squares Problem

mest = GT × dest

mest= (GTG + λ Ι )−1Γ Τ δ



S=||d-Gm||2 + λ ||m||2

•



sing

-emi empirical Approach

• Introduction





Ø Similarity relationships of earthquake



Ø Methodology



•



(a) white gaussian noise (b) filter representing basic spectral shape

(c) filtered white noise (d) envelope of accelerogram

(e) multiplication of the envelope with filteredwhite noise

(f) summation of all accelerogram (g) the simulated acceleration record

( after Joshi, 2004)



-ase Study 1

Ø Introduction

•



1 : Pre-Tertiary rocks

2 ： Mainly sedimentary rocks of lower tomiddle Miocene age

3 : Mainly volcanic rocks of lower to Middle Miocene age

4 ： Mainly sedimentary rocks of upper Miocene to Pliocene age

5 ： Mainly volcanic rocks of upper Miocene to Pliocene age

6：

Neogene intrusive

rocks7 ： Mainly sedimentary rocks of Pliocene to

lower Pleistocene age8 ： Mainly volcanic rocks of Pliocene to

lower Pleistocene age9 ： Mainly sedimentary rocks of middle to

late Pleistocene10 ： Mainly volcanic rocks of middle to late

Pleistocene

11： holocene sediments

(After Kakimi et al., 1982))



Ø Initial Model

•

Velocity(km/s) Thickness of thelayers(km)

2.8 0-8

2.9 8-22

3.5 22-35

(Courtesy: Junichi Nakajima, Toru Matsuzawa,and Akira Hasegawa et al., 2001)



Ø Data

(Courtesy: http://www.kik.bosai.go.jp-sitemap)

http://www.kik.bosai.go.jp-sitemap/




Figure: Diagram explainingthe format of Kik-net data

(Courtesy:http://www.kik.bosai.go.jp-sitemap)





Figure: Diagram showing the hypocenter of Events1 and 2 and location of various stationswhere it was recorded. (Courtesy: http://www.kik.bosai.go.jp)

http://www.kik.bosai.go.jp/




Figure 4.6: Diagram showing the hypocenter of Event 4 and location of various stationswhere it was recorded. (Courtesy: http://www.kik.bosai.go.jp, modified)





Ø Result



36.7

37

Event 1 Event 2


http://slidepdf.com/reader/full/use-of-travel-time-tomography-in-strong-motion-simulation 29/4636 7

37

36.7

37

Event 4 Event 3



Velocity(km/s) Thickness of thelayer(km)

1.72 0-8

2.78 8-22

3.5 22-35



v e

l o c

i t

y

depth





2.6

2.8

3

2.5

3

Figure (a): resolution matrix of inversion of the data

Figure (b): covariance matrix of inversion of the data



-ase Study 2

Ø Introduction

Ø Data



•

Station code Latitude Longitude PGA Epicentraldistance(km)

Station name NIGH 11 37.169 138.747 57.1515 24 KawanishiGNMH 09 36.618 138.91 3.45243 40 TakayamaFKSH 07 37.007 139.378 7.27059 55 HinoemataFKSH 21 37.339 139.317 7.93994 65 Tadami



Figure: Diagram showing the hypocenter of Event and location of various stationswhere it was recorded. (Courtesy: http://www.kik.bosai.go.jp)





•

Modelling Parameter

Rupture length L = 3.4kmWidth D = 3.0kmDip = 450

Depth = 14km



Ø Result

•



Figure: Comparison of the observed acceleration records at variousstations with the synthetic records

CONCLUSION



CONCLUSION

•

REFERENCES



REFERENCES

•










http://utam.gg.utah.edu/stanford/node2.html

http://earthquake.usgs.gov/learning/facts.php

http://www.wikipedia.com/



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Use of Travel Time Tomography in Strong Motion Simulation