Search

We search for earthquake swarms along the Chilean subduction, from −18° to −39° of latitude, 2003–2020 by developing an objective, model-based method that detects potential swarms as anomalous changes in earthquake rate. A set of 16 swarms is obtained after careful inspection of the candidate swarms; this assessment allows to reject cases for which model errors, rather than 'true' anomalous rate changes, are likely the cause of the detection. Averaging the activity over these 16 episodes, we find indirect evidence for a mostly aseismic driving mechanism, and a mean aseismic to seismic ratio estimated to range between 40 and 90 when using the seismicity rate as a proxy for slip. All the swarms are found in the 20–50 km depth range with the notable exception of one 60–100-km-deep swarm that occurs several days after the 2010 Maule earthquake and downdip of it. The dominant depth range (20–50 km) is in agreement with previous studies that suggest this range to be a transition zone from the shallower, locked part of the subduction, to the freely slipping interface at greater depth and intraslab earthquake activity. The swarms can be separated into three spatial groups, two of which being related to a subducting oceanic ridge. This structural control by fluid-rich geological features is modulated by stress control, that is swarms cluster in time with intermediate to large ruptures, both prior and following them, pointing to a close interplay between seismic slip and aseismic deformation in specific, well separated segments of the Chilean subduction. [ABSTRACT FROM AUTHOR]

Earthquakes come in clusters formed of mostly aftershock sequences, swarms and occasional foreshock sequences. This clustering is thought to result either from stress transfer among faults, a process referred to as cascading, or from transient loading by aseismic slip (pre-slip, afterslip or slow slip events). The ETAS statistical model is often used to quantify the fraction of clustering due to stress transfer and to assess the eventual need for aseismic slip to explain foreshocks or swarms. Another popular model of clustering relies on the earthquake nucleation model derived from experimental rate-and-state friction. According to this model, earthquakes cluster because they are time-advanced by the stress change imparted by the mainshock. This model ignores stress interactions among aftershocks and cannot explain foreshocks or swarms in the absence of transient loading. Here, we analyse foreshock, swarm and aftershock sequences resulting from cascades in a Discrete Fault Network model governed by rate-and-state friction. We show that the model produces realistic swarms, foreshocks and aftershocks. The Omori law, characterizing the temporal decay of aftershocks, emerges in all simulations independently of the assumed initial condition. In our simulations, the Omori law results from the earthquake nucleation process due to rate and state friction and from the heterogeneous stress changes due to the coseismic stress transfers. By contrast, the inverse Omori law, which characterizes the accelerating rate of foreshocks, emerges only in the simulations with a dense enough fault system. A high-density complex fault zone favours fault interactions and the emergence of an accelerating sequence of foreshocks. Seismicity catalogues generated with our discrete fault network model can generally be fitted with the ETAS model but with some material differences. In the discrete fault network simulations, fault interactions are weaker in aftershock sequences because they occur in a broader zone of lower fault density and because of the depletion of critically stressed faults. The productivity of the cascading process is, therefore, significantly higher in foreshocks than in aftershocks if fault zone complexity is high. This effect is not captured by the ETAS model of fault interactions. It follows that a foreshock acceleration stronger than expected from ETAS statistics does not necessarily require aseismic slip preceding the mainshock (pre-slip). It can be a manifestation of a cascading process enhanced by the topological properties of the fault network. Similarly, earthquake swarms might not always imply transient loading by aseismic slip, as they can emerge from stress interactions. [ABSTRACT FROM AUTHOR]