Volcanic glass and its mixture with smectite are commonly observed in shallow parts of subduction zones. As volcanic glass layers often act as a glide plane to induce mass transportation such as submarine landslides, and because its alteration product, smectite, is one of the frictionally weakest geological materials, the frictional characteristics of volcanic glass-smectite mixtures are important for fault slip behavior in shallow parts of subduction zones. We performed a series of friction experiments on volcanic glass-smectite mixtures with different smectite contents at various velocity conditions from 10 μm/s to 1 m/s under an effective normal stress of 5 MPa and pore pressure of 10 MPa. In general, friction coefficients negatively depend on the smectite content at any velocity tested. We found that samples with smectite contents of 15-30 % showed a drastic slip-weakening behavior at intermediate velocities of 1-3 mm/s with a characteristic slip displacement of ~0.1 m. Finite element method modeling shows that thermal pressurization does not contribute to the observed weakening behavior. We propose that gouge fluidization or compaction-induced pore pressure increase may be the cause of the weakening. The slip-weakening behavior at intermediate velocities enlarges a critical nucleation length for frictional instability to 1-30 km, or prevent acceleration to seismic slip velocities. Therefore, gouges with minor amount of clay, such as subducting volcanic ash layers, may contribute to the occurrence of the at shallow depths in subduction zones.

Microseismicity is expected in potash mining due to the associated rock-mass response. This phenomenon is known, but not fully understood. To assess the safety and effciency of mining operations, producers must quantitatively discern between normal and abnormal seismic activity. In this work, statistical aspects and clustering of microseismicity from a Saskatchewan, Canada, potash mine are analyzed and quantified. Specifically, the frequency-magnitude statistics display a rich behavior that deviates from the standard Gutenberg-Richter scaling for small magnitudes. To model the magnitude distribution, we consider two additional models, i.e., the tapered Pareto distribution and a mixture of the tapered Pareto and Pareto distributions to fit the bi-modal catalog data. To study the clustering aspects of the observed microseismicity, the nearest-neighbor distance (NND) method is applied. This allowed the identification of potential cluster characteristics in time, space, and magnitude domains. The implemented modeling approaches and obtained results will be used to further advance strategies and protocols for the safe and effcient operation of potash mines.