Deep neural networks for 1D impedance inversion
| Autor: | Chris Elders, Claus Otto, Anton Egorov, Vladimir Puzyrev, A. Pirogova |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
010504 meteorology & atmospheric sciences
Artificial neural network business.industry Deep learning General Engineering Inversion (meteorology) Geophysics 010502 geochemistry & geophysics 01 natural sciences Seismic wave Physics::Geophysics Deep neural networks Artificial intelligence business Electrical impedance Computer Science::Databases Geology 0105 earth and related environmental sciences |
| Zdroj: | ASEG Extended Abstracts. 2019:1-4 |
| ISSN: | 2202-0586 |
| DOI: | 10.1080/22020586.2019.12073187 |
| Popis: | We investigate the applicability of different types of deep neural networks for the estimation of subsurface properties from seismic data. The pre-trained networks can predict velocity models from ... |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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