Articles | Volume 11, issue 4
Solid Earth, 11, 1527–1549, 2020
https://doi.org/10.5194/se-11-1527-2020
Solid Earth, 11, 1527–1549, 2020
https://doi.org/10.5194/se-11-1527-2020

Research article 24 Aug 2020

Research article | 24 Aug 2020

Deep learning for fast simulation of seismic waves in complex media

Ben Moseley et al.

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Interactive discussion

Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision
AR by Ben Moseley on behalf of the Authors (20 Apr 2020)  Author's response    Manuscript
ED: Referee Nomination & Report Request started (01 May 2020) by Caroline Beghein
RR by Andrew Curtis (11 May 2020)
RR by Andrew Valentine (03 Jun 2020)
ED: Publish subject to minor revisions (review by editor) (08 Jun 2020) by Caroline Beghein
AR by Ben Moseley on behalf of the Authors (21 Jun 2020)  Author's response    Manuscript
ED: Publish as is (26 Jun 2020) by Caroline Beghein
ED: Publish as is (30 Jun 2020) by CharLotte Krawczyk(Executive Editor)
AR by Ben Moseley on behalf of the Authors (04 Jul 2020)  Author's response    Manuscript
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Short summary
Simulations of seismic waves are very important; they allow us to understand how earthquakes spread and how the interior of the Earth is structured. However, whilst powerful, existing simulation methods usually require a large amount of computational power and time to run. In this research, we use modern machine learning techniques to accelerate these calculations inside complex models of the Earth.