Articles | Volume 10, issue 6
Research article
15 Nov 2019
Research article |  | 15 Nov 2019

Prediction of seismic P-wave velocity using machine learning

Ines Dumke and Christian Berndt


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 Anna Wenzel on behalf of the Authors (27 Aug 2019)  Author's response
ED: Referee Nomination & Report Request started (10 Sep 2019) by Tarje Nissen-Meyer
RR by Taylor Lee (25 Sep 2019)
ED: Publish subject to technical corrections (02 Oct 2019) by Tarje Nissen-Meyer
ED: Publish subject to technical corrections (02 Oct 2019) by Federico Rossetti(Executive Editor)
AR by Christian Berndt on behalf of the Authors (08 Oct 2019)  Author's response    Manuscript
Short summary
Knowing the velocity with which seismic waves travel through the top of the crust is important both for identifying anomalies, e.g. the presence of resources, and for geophysical data evaluation. Traditionally this has been done by using empirical functions. Here, we use machine learning to derive better seismic velocity estimates for the crust below the oceans. In most cases this methods performs better than empirical averages.