ABSTRACT
The earthquake rupture process comprises complex interactions of stress, fracture, and frictional properties. New machine learning methods demonstrate great potential to reveal patterns in time-dependent spectral properties of seismic signals and enable identification of changes in faulting processes. Clustering of 46,000 earthquakes of 0.3 < ML < 1.5 from the Geysers geothermal field (CA) yields groupings that have no reservoir-scale spatial patterns but clear temporal patterns. Events with similar spectral properties repeat on annual cycles within each cluster and track changes in the water injection rates into the Geysers reservoir, indicating that changes in acoustic properties and faulting processes accompany changes in thermomechanical state. The methods open new means to identify and characterize subtle changes in seismic source properties, with applications to tectonic and geothermal seismicity.
ABSTRACT
Auditory display can complement visual representations in order to better interpret scientific data. A previous article showed that the free categorization of "audified seismic signals" operated by listeners can be explained by various geophysical parameters. The present article confirms this result and shows that cognitive representations of listeners can be used as heuristics for the characterization of seismic signals. Free sorting tests are conducted with audified seismic signals, with the earthquake/seismometer relative location, playback audification speed, and earthquake magnitude as controlled variables. The analysis is built on partitions (categories) and verbal comments (categorization criteria). Participants from different backgrounds (acousticians or geoscientists) are contrasted in order to investigate the role of the participants' expertise. Sounds resulting from different earthquake/station distances or azimuths, crustal structure and topography along the path of the seismic wave, earthquake magnitude, are found to (a) be sorted into different categories, (b) elicit different verbal descriptions mainly focused on the perceived number of events, frequency content, and background noise level. Building on these perceptual results, acoustic descriptors are computed and geophysical interpretations are proposed in order to match the verbal descriptions. Another result is the robustness of the categories with respect to the audification speed factor.
ABSTRACT
The volcanoes that lie along the Earth's tectonic boundaries are fed by melt generated in the mantle. How this melt is extracted and focused to the volcanoes, however, remains an unresolved question. Here we present new theoretical results with implications for melt focusing beneath mid-ocean ridges. By modelling laboratory experiments, we test a formulation for magma dynamics and provide an explanation for localized bands of high-porosity and concentrated shear deformation observed in experiments. These bands emerge and persist at 15 degrees-25 degrees to the plane of shear. Past theoretical work on this system predicted the emergence of melt bands but at an angle inconsistent with experiments. Our results suggest that the observed band angle results from a balance of porosity-weakening and strain-rate-weakening deformation mechanisms. Lower band angles are predicted for greater strain-rate weakening. From these lower band angles, we estimate the orientation of melt bands beneath mid-ocean ridges and show that they may enhance magma focusing toward the ridge axis.
