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SUMMARY While distributed acoustic sensing (DAS) has been demonstrated to have great potential in seismology, DAS data often have much higher levels of stochastic and coherent noise (e.g. instrument noise, traffic vibrations) than data collected by traditional seismometers. The linearly, densely spaced nature of DAS arrays presents a suite of opportunities for more innovative processing techniques that can be used to address this issue. One way to take advantage of DAS’s array architecture is through the use of curvelets. Curvelets have a non-uniform scaling property that makes them an excellent tool for representing images with discontinuities along piecewise, twice continuously differentiable curves. This anisotropic scaling property makes curvelets an ideal processing tool for DAS data, for which the measured wavefield can be represented as an image composed of curved features. Here, we use the curvelet frame as a tool for the manipulation of DAS signal and demonstrate how this manipulation can improve our ability to identify important features in DAS data sets. We use the curvelet representation to partition the measured wavefield using DAS data collected near Ridgecrest, CA, following the 2019 Mw7.1 Ridgecrest earthquake. Here, we isolate the earthquake-induced wavefield from coherent and stochastic noise using the curvelet frame in an effort to improve the results of template matching of the Ridgecrest aftershock sequence. We show that our wavefield-partitioning technique facilitates the identification of over 30 per cent more aftershocks and greatly reduces the magnitude of diurnal depressions in the aftershock catalogue due to cultural noise. 

Abstract We cluster a global database of 3529 Mw>5.5 earthquakes in 1995–2018 based on a dynamic time warping distance between earthquake source time functions (STFs). The clustering exhibits different degrees of complexity of the STF shapes and suggests an association between STF complexity and earthquake source parameters. Most of the thrust events have simple STF shapes across all depths. In contrast, earthquakes with complex STF shapes tend to be located at shallow depths in complicated tectonic regions, exhibit long source duration compared with others of similar magnitude, and tend to have strike-slip mechanisms. With 2D dynamic modeling of dynamic ruptures on heterogeneous fault properties, we find a systematic variation of the simulated STF complexity with frictional properties. Comparison between the observed and synthetic clustering distributions provides useful constraints on frictional properties. In particular, the characteristic slip-weakening distance could be constrained to be short (<0.1  m) and depth dependent if stress drop is in general constant.