SIPPI: a Matlab toolbox for sampling the solution to inverse problems with complex prior information: part 2—application to crosshole GPR tomography

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Standard

SIPPI: a Matlab toolbox for sampling the solution to inverse problems with complex prior information : part 2—application to crosshole GPR tomography. / Hansen, Thomas Mejer; Cordua, Knud Skou; Zibar, Majken Caroline Looms; Mosegaard, Klaus.

I: Computers & Geosciences, Bind 52, 2013, s. 481-492.

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningfagfællebedømt

Harvard

Hansen, TM, Cordua, KS, Zibar, MCL & Mosegaard, K 2013, 'SIPPI: a Matlab toolbox for sampling the solution to inverse problems with complex prior information: part 2—application to crosshole GPR tomography', Computers & Geosciences, bind 52, s. 481-492. https://doi.org/10.1016/j.cageo.2012.10.001

APA

Hansen, T. M., Cordua, K. S., Zibar, M. C. L., & Mosegaard, K. (2013). SIPPI: a Matlab toolbox for sampling the solution to inverse problems with complex prior information: part 2—application to crosshole GPR tomography. Computers & Geosciences, 52, 481-492. https://doi.org/10.1016/j.cageo.2012.10.001

Vancouver

Hansen TM, Cordua KS, Zibar MCL, Mosegaard K. SIPPI: a Matlab toolbox for sampling the solution to inverse problems with complex prior information: part 2—application to crosshole GPR tomography. Computers & Geosciences. 2013;52:481-492. https://doi.org/10.1016/j.cageo.2012.10.001

Author

Hansen, Thomas Mejer ; Cordua, Knud Skou ; Zibar, Majken Caroline Looms ; Mosegaard, Klaus. / SIPPI: a Matlab toolbox for sampling the solution to inverse problems with complex prior information : part 2—application to crosshole GPR tomography. I: Computers & Geosciences. 2013 ; Bind 52. s. 481-492.

Bibtex

@article{6046de57163b43ca8bdcffd59cf065aa,
title = "SIPPI: a Matlab toolbox for sampling the solution to inverse problems with complex prior information: part 2—application to crosshole GPR tomography",
abstract = "We present an application of the SIPPI Matlab toolbox, to obtain a sample from the a posteriori probability density function for the classical tomographic inversion problem. We consider a number of different forward models, linear and non-linear, such as ray based forward models that rely on the high frequency approximation of the wave-equation and {\textquoteleft}fat{\textquoteright} ray based forward models relying on finite frequency theory. In order to sample the a posteriori probability density function we make use of both least squares based inversion, for linear Gaussian inverse problems, and the extended Metropolis sampler, for non-linear non-Gaussian inverse problems. To illustrate the applicability of the SIPPI toolbox to a tomographic field data set we use a cross-borehole traveltime data set from Arren{\ae}s, Denmark. Both the computer code and the data are released in the public domain using open source and open data licenses. The code has been developed to facilitate inversion of 2D and 3D travel time tomographic data using a wide range of possible a priori models and choices of forward models.",
author = "Hansen, {Thomas Mejer} and Cordua, {Knud Skou} and Zibar, {Majken Caroline Looms} and Klaus Mosegaard",
year = "2013",
doi = "10.1016/j.cageo.2012.10.001",
language = "English",
volume = "52",
pages = "481--492",
journal = "Computers & Geosciences",
issn = "0098-3004",
publisher = "Pergamon Press",

}

RIS

TY - JOUR

T1 - SIPPI: a Matlab toolbox for sampling the solution to inverse problems with complex prior information

T2 - part 2—application to crosshole GPR tomography

AU - Hansen, Thomas Mejer

AU - Cordua, Knud Skou

AU - Zibar, Majken Caroline Looms

AU - Mosegaard, Klaus

PY - 2013

Y1 - 2013

N2 - We present an application of the SIPPI Matlab toolbox, to obtain a sample from the a posteriori probability density function for the classical tomographic inversion problem. We consider a number of different forward models, linear and non-linear, such as ray based forward models that rely on the high frequency approximation of the wave-equation and ‘fat’ ray based forward models relying on finite frequency theory. In order to sample the a posteriori probability density function we make use of both least squares based inversion, for linear Gaussian inverse problems, and the extended Metropolis sampler, for non-linear non-Gaussian inverse problems. To illustrate the applicability of the SIPPI toolbox to a tomographic field data set we use a cross-borehole traveltime data set from Arrenæs, Denmark. Both the computer code and the data are released in the public domain using open source and open data licenses. The code has been developed to facilitate inversion of 2D and 3D travel time tomographic data using a wide range of possible a priori models and choices of forward models.

AB - We present an application of the SIPPI Matlab toolbox, to obtain a sample from the a posteriori probability density function for the classical tomographic inversion problem. We consider a number of different forward models, linear and non-linear, such as ray based forward models that rely on the high frequency approximation of the wave-equation and ‘fat’ ray based forward models relying on finite frequency theory. In order to sample the a posteriori probability density function we make use of both least squares based inversion, for linear Gaussian inverse problems, and the extended Metropolis sampler, for non-linear non-Gaussian inverse problems. To illustrate the applicability of the SIPPI toolbox to a tomographic field data set we use a cross-borehole traveltime data set from Arrenæs, Denmark. Both the computer code and the data are released in the public domain using open source and open data licenses. The code has been developed to facilitate inversion of 2D and 3D travel time tomographic data using a wide range of possible a priori models and choices of forward models.

U2 - 10.1016/j.cageo.2012.10.001

DO - 10.1016/j.cageo.2012.10.001

M3 - Journal article

VL - 52

SP - 481

EP - 492

JO - Computers & Geosciences

JF - Computers & Geosciences

SN - 0098-3004

ER -

ID: 45955417