Forecasting and understanding the seIsmic cycle through b-value

Seismology is a branch of science with many open questions, and predicting earthquakes is still a utopia. We know earthquakes interact with each other by changing the state of stress in their surroundings. Strong earthquakes are, for example, followed by countless smaller events, a posteriori called aftershocks, whose number decays with time. We have shown that aftershock sequences are systematically associated with changes in the average earthquake size distribution, an increase in the so-called b-value, unless a second large mainshock is still coming, in which case the b-value decreases. This exciting finding allows the use of the b-value for real-time discrimination between foreshocks and aftershocks, answering the most asked question following a moderate/big quake: Was this the mainshock or a bigger event has yet to come? The observation also aligns with the concept that the b-value can be used as an indirect stress meter in the earth’s crust. Building on these findings, I propose here now to develop and test a general model of the evolution of the b-value through the seismic cycle, building on the following hypothesis: 1) a stable background or gradual decreasing b-value during inter-seismic times, 2) occasionally a pre-mainshock decrease, 3) an increase after the mainshock and 4) recovery to the background value. According to my hypothesis, monitoring b-values in real-time allows us to understand and monitor for the first where a fault is in the seismic cycle. This would represent a major breakthrough in Earth science, with profound implications for understanding earthquake processes, seismic hazard assessment and risk mitigation. To achieve this ambitious goal, FARIA comprises a set of closely coordinated activities in data analytics, computational modeling, laboratory experiments, and formal testing. If successful, FARIA will represent transformative progress in earthquake predictability.