Stochastic waveform inversion for probabilistic geotechnical site characterization

S. S. Parida, K. Sett, P. Singla

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

This study develops a stochastic inverse analysis methodology to probabilistically estimate site-specific soil modulus from geophysical test measurements by accounting for the uncertain spatial variability of the soil deposit, any measurement uncertainty and uncertainty due to limited data. Hypothesizing the soil modulus to be a three-dimensional, heterogeneous, anisotropic random field, the methodology first formulates and solves a forward model that mimic a geophysical experiment using a stochastic collocation approach to characterize the effect of spatially variable, uncertain soil modulus on the model response variables, for example, accelerations at the sensor locations. The stochastic collocation approach utilizes recently developed non-product quadrature method, conjugate unscented transformation, to accurately estimate statistical moments corresponding to the model response variables in a computationally efficient manner. The methodology then employs a minimum variance framework to merge the information obtained from the model prediction and the sparse geophysical test measurements to update the statistical information pertaining to the soil modulus. The methodology is illustrated using synthetic data from a fictitious geophysical experiment.

Original languageEnglish (US)
Title of host publicationProceedings of the 5th International Conference on Geotechnical and Geophysical Site Characterisation, ISC 2016
EditorsBarry M. Lehane, Hugo E. Acosta-Martinez, Richard Kelly
PublisherAustralian Geomechanics Society
Pages1459-1464
Number of pages6
ISBN (Electronic)9780994626127
StatePublished - Jan 1 2016
Event5th International Conference on Geotechnical and Geophysical Site Characterisation, ISC 2016 - Gold Coast, Australia
Duration: Sep 5 2016Sep 9 2016

Publication series

NameProceedings of the 5th International Conference on Geotechnical and Geophysical Site Characterisation, ISC 2016
Volume2

Other

Other5th International Conference on Geotechnical and Geophysical Site Characterisation, ISC 2016
CountryAustralia
CityGold Coast
Period9/5/169/9/16

Fingerprint

site characterization
soils
waveforms
inversions
Soils
methodology
collocation
soil
uncertainty
inverse analysis
distribution moments
soil heterogeneity
estimates
quadratures
Deposits
experiment
Experiments
deposits
testing
inversion

All Science Journal Classification (ASJC) codes

  • Geotechnical Engineering and Engineering Geology
  • Geophysics
  • Soil Science

Cite this

Parida, S. S., Sett, K., & Singla, P. (2016). Stochastic waveform inversion for probabilistic geotechnical site characterization. In B. M. Lehane, H. E. Acosta-Martinez, & R. Kelly (Eds.), Proceedings of the 5th International Conference on Geotechnical and Geophysical Site Characterisation, ISC 2016 (pp. 1459-1464). (Proceedings of the 5th International Conference on Geotechnical and Geophysical Site Characterisation, ISC 2016; Vol. 2). Australian Geomechanics Society.
Parida, S. S. ; Sett, K. ; Singla, P. / Stochastic waveform inversion for probabilistic geotechnical site characterization. Proceedings of the 5th International Conference on Geotechnical and Geophysical Site Characterisation, ISC 2016. editor / Barry M. Lehane ; Hugo E. Acosta-Martinez ; Richard Kelly. Australian Geomechanics Society, 2016. pp. 1459-1464 (Proceedings of the 5th International Conference on Geotechnical and Geophysical Site Characterisation, ISC 2016).
@inproceedings{1d637b59bb2c468b9fceed117d29ffeb,
title = "Stochastic waveform inversion for probabilistic geotechnical site characterization",
abstract = "This study develops a stochastic inverse analysis methodology to probabilistically estimate site-specific soil modulus from geophysical test measurements by accounting for the uncertain spatial variability of the soil deposit, any measurement uncertainty and uncertainty due to limited data. Hypothesizing the soil modulus to be a three-dimensional, heterogeneous, anisotropic random field, the methodology first formulates and solves a forward model that mimic a geophysical experiment using a stochastic collocation approach to characterize the effect of spatially variable, uncertain soil modulus on the model response variables, for example, accelerations at the sensor locations. The stochastic collocation approach utilizes recently developed non-product quadrature method, conjugate unscented transformation, to accurately estimate statistical moments corresponding to the model response variables in a computationally efficient manner. The methodology then employs a minimum variance framework to merge the information obtained from the model prediction and the sparse geophysical test measurements to update the statistical information pertaining to the soil modulus. The methodology is illustrated using synthetic data from a fictitious geophysical experiment.",
author = "Parida, {S. S.} and K. Sett and P. Singla",
year = "2016",
month = "1",
day = "1",
language = "English (US)",
series = "Proceedings of the 5th International Conference on Geotechnical and Geophysical Site Characterisation, ISC 2016",
publisher = "Australian Geomechanics Society",
pages = "1459--1464",
editor = "Lehane, {Barry M.} and Acosta-Martinez, {Hugo E.} and Richard Kelly",
booktitle = "Proceedings of the 5th International Conference on Geotechnical and Geophysical Site Characterisation, ISC 2016",

}

Parida, SS, Sett, K & Singla, P 2016, Stochastic waveform inversion for probabilistic geotechnical site characterization. in BM Lehane, HE Acosta-Martinez & R Kelly (eds), Proceedings of the 5th International Conference on Geotechnical and Geophysical Site Characterisation, ISC 2016. Proceedings of the 5th International Conference on Geotechnical and Geophysical Site Characterisation, ISC 2016, vol. 2, Australian Geomechanics Society, pp. 1459-1464, 5th International Conference on Geotechnical and Geophysical Site Characterisation, ISC 2016, Gold Coast, Australia, 9/5/16.

Stochastic waveform inversion for probabilistic geotechnical site characterization. / Parida, S. S.; Sett, K.; Singla, P.

Proceedings of the 5th International Conference on Geotechnical and Geophysical Site Characterisation, ISC 2016. ed. / Barry M. Lehane; Hugo E. Acosta-Martinez; Richard Kelly. Australian Geomechanics Society, 2016. p. 1459-1464 (Proceedings of the 5th International Conference on Geotechnical and Geophysical Site Characterisation, ISC 2016; Vol. 2).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

TY - GEN

T1 - Stochastic waveform inversion for probabilistic geotechnical site characterization

AU - Parida, S. S.

AU - Sett, K.

AU - Singla, P.

PY - 2016/1/1

Y1 - 2016/1/1

N2 - This study develops a stochastic inverse analysis methodology to probabilistically estimate site-specific soil modulus from geophysical test measurements by accounting for the uncertain spatial variability of the soil deposit, any measurement uncertainty and uncertainty due to limited data. Hypothesizing the soil modulus to be a three-dimensional, heterogeneous, anisotropic random field, the methodology first formulates and solves a forward model that mimic a geophysical experiment using a stochastic collocation approach to characterize the effect of spatially variable, uncertain soil modulus on the model response variables, for example, accelerations at the sensor locations. The stochastic collocation approach utilizes recently developed non-product quadrature method, conjugate unscented transformation, to accurately estimate statistical moments corresponding to the model response variables in a computationally efficient manner. The methodology then employs a minimum variance framework to merge the information obtained from the model prediction and the sparse geophysical test measurements to update the statistical information pertaining to the soil modulus. The methodology is illustrated using synthetic data from a fictitious geophysical experiment.

AB - This study develops a stochastic inverse analysis methodology to probabilistically estimate site-specific soil modulus from geophysical test measurements by accounting for the uncertain spatial variability of the soil deposit, any measurement uncertainty and uncertainty due to limited data. Hypothesizing the soil modulus to be a three-dimensional, heterogeneous, anisotropic random field, the methodology first formulates and solves a forward model that mimic a geophysical experiment using a stochastic collocation approach to characterize the effect of spatially variable, uncertain soil modulus on the model response variables, for example, accelerations at the sensor locations. The stochastic collocation approach utilizes recently developed non-product quadrature method, conjugate unscented transformation, to accurately estimate statistical moments corresponding to the model response variables in a computationally efficient manner. The methodology then employs a minimum variance framework to merge the information obtained from the model prediction and the sparse geophysical test measurements to update the statistical information pertaining to the soil modulus. The methodology is illustrated using synthetic data from a fictitious geophysical experiment.

UR - http://www.scopus.com/inward/record.url?scp=85015807689&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85015807689&partnerID=8YFLogxK

M3 - Conference contribution

AN - SCOPUS:85015807689

T3 - Proceedings of the 5th International Conference on Geotechnical and Geophysical Site Characterisation, ISC 2016

SP - 1459

EP - 1464

BT - Proceedings of the 5th International Conference on Geotechnical and Geophysical Site Characterisation, ISC 2016

A2 - Lehane, Barry M.

A2 - Acosta-Martinez, Hugo E.

A2 - Kelly, Richard

PB - Australian Geomechanics Society

ER -

Parida SS, Sett K, Singla P. Stochastic waveform inversion for probabilistic geotechnical site characterization. In Lehane BM, Acosta-Martinez HE, Kelly R, editors, Proceedings of the 5th International Conference on Geotechnical and Geophysical Site Characterisation, ISC 2016. Australian Geomechanics Society. 2016. p. 1459-1464. (Proceedings of the 5th International Conference on Geotechnical and Geophysical Site Characterisation, ISC 2016).