Deep learning for laboratory earthquake prediction and autoregressive forecasting of fault zone stress. (arXiv:2203.13313v2 [physics.geo-ph] UPDATED)

Earthquake forecasting and prediction have long and in some cases sordid
histories but recent work has rekindled interest based on advances in early
warning, hazard assessment for induced seismicity and successful prediction of
laboratory earthquakes. In the lab, frictional stick-slip events provide an
analog for earthquakes and the seismic cycle. Labquakes are ideal targets for
machine learning (ML) because they can be produced in long sequences under
controlled conditions. Recent works show that ML can predict several aspects of
labquakes …

arxiv deep learning earthquake forecasting laboratory learning physics prediction stress