Geophysical applications of granular flows: probing earthquakes applying machine learning

The influence of granular flows is widespread in geophysics, from the physics of earthquakes, avalanche and landslide, to debris flow to the effects of strong ground motion due to earthquakes. In this presentation I focus on earthquakes and the influence of the granular core of the fault—the fault gouge. Earthquakes take place when two juxtaposed fault blocks are stressed sufficiently to overcome the frictional force holding them in place and they abruptly slip relative to each other. Earthquake faults exhibit a continuum of behaviors ranging from stick slip associated with strong shaking, to slow slip which is primarily aseismic, to very slow slip that is essentially aseismic and can take place over hours to months. The different slip behaviors appear to be controlled by the combined elasticity of the fault gouge the adjacent fault blocks. As faults slip, the fault core emits elastic waves. We analyze these waves applying machine learning continuous acoustic data streams in the laboratory and continuous seismic data streams in Earth. We use as labels characteristics of the measured fault slip behavior in the laboratory such as the fault friction, shear displacement and fault thickness. In Earth, we use surface displacement as determined by Global Positioning Systems (GPS). We find that the laboratory acoustic data and the Earth seismic data are a type of Rosetta Stone revealing fault characteristics at all times and fault displacements. This is a surprising observation because previously we believed most or much of the signal was noise. Here we describe an overview of recent work in this area and also describe recent efforts on parallel problems such as volcanoes and geysers.