Machine Listening reveals cyclic changes in seismic source spectra in The Geysers geothermal field, California; can we learn to hear changes in the thermal-mechanical state?

The earthquake rupture process reflects complex interactions of stress, fracture and frictional properties. In geothermal reservoirs, fluids, fluid pressure and thermal stresses add further complexity. Our unsupervised machine learning methods reveal patterns in temporal-spectral properties of seismic signals, based closely on those developed for music information retrieval, voice recognition and image analysis, using the spectrogram instead of the waveform. As an introduction, I will present results from human-listening experiments that are analogous to our unsupervised audio-based methods. Unsupervised learning involves identification of patterns based on differences among signals without any additional information provided to or training of the algorithm. Results from 46,000 earthquakes of 0.3

About the Series

The Friday Informal Seminar Hour [FISH, Earth Resources Laboratory] is a postdoc-run weekly seminar series within the ERL. Topics include research relating to geophysics, and in particular seismology, with applications in Earth resources exploration such as e.g. seismics exploration, microseismicity, earthquake physics, and Earth imaging techniques. The seminars usually take place on Fridays at 12 noon in 54-209 (term-time only).