Machine-learning earthquake prediction in lab shows promise

Researchers at Los Alamos National Laboratory are working with machines that may make future prediction of earthquakes possible. By listening to the acoustic signal emitted by a laboratory-created earthquake, a computer science approach using machine learning can predict the time remaining before the fault fails. "At any given instant, the noise coming from the lab fault zone provides quantitative information on when the fault will slip," said Paul Johnson, LANL fellow and lead investigator on the research, which was published Wednesday in Geophysical Research Letters. "The novelty of our work is the use of machine learning to discover and understand new physics of failure, through examination of the recorded auditory signal from the experimental setup. I think the future of earthquake physics will rely heavily on machine learning to process massive amounts of raw seismic data.