A deep learning approach to the inversion of borehole resistivity measurements-Reference-Cited by-同舟云学术

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A deep learning approach to the inversion of borehole resistivity measurements

Published:2020-04-13 Issue:3 Volume:24 Page:971-994
ISSN:1420-0597
Container-title:Computational Geosciences
language:en
Short-container-title:Comput Geosci

Author:

Shahriari M.,Pardo D.,Picon A.,Galdran A.,Del Ser J.,Torres-Verdín C.

Funder

H2020 Marie Skłodowska-Curie Actions

Ministerio de Economía y Competitividad

Eusko Jaurlaritza

Publisher

Springer Science and Business Media LLC

Subject

Computational Mathematics,Computational Theory and Mathematics,Computers in Earth Sciences,Computer Science Applications

Link

https://link.springer.com/content/pdf/10.1007/s10596-019-09859-y.pdf

Reference39 articles.

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2. Bakr, S.A., Pardo, D., Mannseth, T.: Domain decomposition fourier fe method for the simulation of 3d marine csem measurements. J. Comput. Phys. 255, 456–470 (2013)

3. Hardage, B.A.: Vertical seismic profiling. Lead. Edge 4(11), 59–59 (1985)

4. Alvarez-Aramberri, J., Pardo, D.: Dimensionally adaptive hp-finite element simulation and inversion of 2D magnetotelluric measurements. J. Comput. Sci. 18, 95–105 (2017)

5. Davydycheva, S., Wang, T.: A fast modelling method to solve Maxwell’s equations in 1D layered biaxial anisotropic medium. Geophysics 76(5), F293–F302 (2011)

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