Geoscientific Model Development
Geoscientific Model Development
GMD
Articles | Volume 18, issue 18
Articles | Volume 18, issue 18
https://doi.org/10.5194/gmd-18-6275-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-18-6275-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 18, issue 18
Model description paper
 | 
24 Sep 2025
Model description paper |  | 24 Sep 2025

A dynamic informed deep-learning method for future estimation of laboratory stick–slip

Enjiang Yue, Mengjiao Qin, Linshu Hu, Bryan Riel, Sensen Wu, and Zhenhong Du

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Latest update: 04 May 2026
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Short summary
Laboratory earthquakes are an important means to understand natural earthquakes. While previous work focused on transient prediction, lacking future prediction capability, we propose a method and evaluate on data from laboratory experiments with different slip behaviours. It shows stable predictions in modelling slip moments, intervals, and predictions beyond trained horizons, especially for challenging slip scenarios, which is crucial for cyclic geophysical process such as seismicity.
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