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SUMMARY 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.
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Fault Roughness Promotes Earthquake‐Like Aftershock Clustering in the Lab
Abstract Earthquakes rarely occur in isolation but rather as complex sequences of fore, main and aftershocks. Assessing the associated seismic hazard requires a holistic view of event interactions. We conduct frictional sliding experiments on faulted Westerly Granite samples at mid‐crustal stresses to investigate fault damage and roughness effects on aftershock generation. Abrupt laboratory fault slip is followed by periods of extended stress relaxation and aftershocks. Large roughness promotes less co‐seismic slip and high aftershock activity whereas smooth faults promote high co‐seismic slip with few aftershocks. Conditions close to slip instability generate lab‐quake sequences that exhibit similar statistical distributions to natural earthquakes. Aftershock productivity in the lab is linearly related to the residual strain energy on the fault which, in turn, is controlled by the level of surface heterogeneity. We conclude that roughness and damage govern slip stability and seismic energy partitioning between fore, main and aftershocks in lab and nature.
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- Award ID(s):
- 2142489
- PAR ID:
- 10409472
- Publisher / Repository:
- DOI PREFIX: 10.1029
- Date Published:
- Journal Name:
- Geophysical Research Letters
- Volume:
- 50
- Issue:
- 8
- ISSN:
- 0094-8276
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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