Probabilistic inversions of electrical resistivity tomography data with a machine learning‐based forward operator-Reference-Cited by-同舟云学术

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Probabilistic inversions of electrical resistivity tomography data with a machine learning‐based forward operator

Published:2022-03-05 Issue:5 Volume:70 Page:938-957
ISSN:0016-8025
Container-title:Geophysical Prospecting
language:en
Short-container-title:Geophysical Prospecting

Author:

Aleardi Mattia¹^ORCID,Vinciguerra Alessandro¹²^ORCID,Stucchi Eusebio¹,Hojat Azadeh³⁴

Affiliation:

1. Earth Sciences Department University of Pisa Pisa Italy

2. Earth Sciences Department University of Florence Florence Italy

3. Department of Mining Engineering Shahid Bahonar University of Kerman Kerman Iran

4. Politecnico di Milano, Department of Civil and Environmental Engineering Milano Italy

Publisher

Wiley

Subject

Geochemistry and Petrology,Geophysics

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/1365-2478.13189

Reference60 articles.

1. Combining discrete cosine transform and convolutional neural networks to speed up the Hamiltonian Monte Carlo inversion of pre‐stack seismic data

2. A gradient‐based Markov chain Monte Carlo algorithm for elastic pre‐stack inversion with data and model space reduction

3. Hamiltonian Monte Carlo algorithms for target- and interval-oriented amplitude versus angle inversions

4. Elastic prestack seismic inversion through discrete cosine transform reparameterization and convolutional neural networks

5. A geostatistical Markov chain Monte Carlo inversion algorithm for electrical resistivity tomography

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