Comparing the performances of four stochastic optimisation methods using analytic objective functions, 1D elastic full-waveform inversion, and residual static computation-Reference-Cited by-同舟云学术

Comparing the performances of four stochastic optimisation methods using analytic objective functions, 1D elastic full-waveform inversion, and residual static computation

Published:2017-10-04 Issue: Volume:65 Page:322-346
ISSN:0016-8025
Container-title:Geophysical Prospecting
language:en
Short-container-title:Geophysical Prospecting

Author:

Sajeva Angelo¹^ORCID,Aleardi Mattia¹^ORCID,Galuzzi Bruno²^ORCID,Stucchi Eusebio²^ORCID,Spadavecchia Emmanuel³,Mazzotti Alfredo¹^ORCID

Affiliation:

1. Department of Earth Sciences; University of Pisa; Pisa 56126 Italy

2. Department of Earth Sciences; University of Milan; Milan 20129 Italy

3. Eni; Upstream and Technical Services, San Donato Milanese; Milan 20097 Italy

Publisher

Wiley

Subject

Geochemistry and Petrology,Geophysics

Link

http://onlinelibrary.wiley.com/wol1/doi/10.1111/1365-2478.12532/fullpdf

Reference66 articles.

1. Seismic velocity estimation from well log data with genetic algorithms in comparison to neural networks and multilinear approaches;Aleardi;Journal of Applied Geophysics,2015

2. Assessment of different approaches to rock-physics modeling: a case study from offshore Nile Delta;Aleardi;Geophysics,2017

3. 1D elastic full-waveform inversion and uncertainty estimation by means of a hybrid genetic algorithm-Gibbs sampler approach;Aleardi;Geophysical Prospecting,2017

4. Characterisation of shallow marine sediments using high-resolution velocity analysis and genetic-algorithm-driven 1D elastic full-waveform inversion;Aleardi;Near Surface Geophysics,2016

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