A geostatistical Markov chain Monte Carlo inversion algorithm for electrical resistivity tomography-Reference-Cited by-同舟云学术

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

Published:2020-11-14 Issue:1 Volume:19 Page:7-26
ISSN:1569-4445
Container-title:Near Surface Geophysics
language:en
Short-container-title:Near Surface Geophysics

Author:

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

Affiliation:

1. Earth Sciences Department University of Pisa via S. Maria 53 Pisa 56126 Italy

2. Earth Sciences Department University of Florence via. G. La Pira 4 Florence 50121 Italy

3. Department of Mining Engineering Shahid Bahonar University of Kerman Kerman 76188 Iran

4. Department of Civil and Environmental Engineering Politecnico di Milano Piazza Leonardo da Vinci 32 Milano 20133 Italy

Funder

Ministero dell'Ambiente e della Tutela del Territorio e del Mare

Publisher

Wiley

Subject

Geophysics

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/nsg.12133

Reference62 articles.

1. Combining discrete cosine transform and convolutional neural networks to speed up the Hamiltonian Monte Carlo inversion of pre‐stack seismic data;Aleardi M.;Geophysical Prospecting,2020

2. A two-step inversion approach for seismic-reservoir characterization and a comparison with a single-loop Markov-chain Monte Carlo algorithm

3. Probabilistic estimation of reservoir properties by means of wide-angle AVA inversion and a petrophysical reformulation of the Zoeppritz equations

4. 1D elastic full-waveform inversion and uncertainty estimation by means of a hybrid genetic algorithm-Gibbs sampler approach

5. Markov chain Monte Carlo algorithms for target‐oriented and interval‐oriented amplitude versus angle inversions with non‐parametric priors and non‐linear forward modellings

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