Jeremy Faller’s research while affiliated with Google Inc. and other places

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Figure 1. Examples of two static stress fields considered in this analysis and corresponding ROC curves for one slip distribution (Cohee & Beroza, 1994) from the 1992 M w = 7.3 Landers earthquake in California. (a-c) Map view of ΔCFS(σ, 0.4) values within 100 km of the fault at 2.5 km, 7.5 km, and 22.5 km depth, respectively. Black squares represent grid cells in which one or more aftershocks occurred within 1 year of the mainshock. Thick yellow and black line represents extent of the mainshock rupture at each depth. Scale bar is shown in Figure 1a as a thick black line. (d) ROC curve for this particular slip distribution (Cohee & Beroza, 1994) and ΔCFS(σ, 0.4), including all grid cells and all aftershocks within a year after the mainshock. Black dotted line is a 1:1 line for reference. (e-h) Analogous to Figures 1a-1d for a different static stress field, Δτ max (σ).
Figure 2. ROC curves for all 38 stress metrics, in ranked order by merged AUC value (A m ). Category I metrics (1-23) have red titles; Category II metrics (24-38) have black titles. See Table 1 for detailed descriptions of the symbols in the titles. Vertically averaged AUC values A v , threshold averaged AUC values A t , and the fraction of statistically significant (α = 0.005) empirical p values Ψ are included for each metric. ROC curves for every slip distribution (213 in total) are shown with thin gray lines for each stress metric. Gray circles represent the locations on the ROC curves where Youden's index is maximized. Merged, vertically averaged, and threshold averaged ROC curves across all slip distributions are shown in thick blue, black, and red lines, respectively.
What Is Better Than Coulomb Failure Stress? A Ranking of Scalar Static Stress Triggering Mechanisms from 10 5 Mainshock-Aftershock Pairs: Static Stress Triggering Mechanisms
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November 2017

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266 Reads

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43 Citations

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Phoebe M. R. DeVries

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Jeremy Faller

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Aftershocks may be triggered by the stresses generated by preceding mainshocks. The temporal frequency and maximum size of aftershocks are well described by the empirical Omori and Bath laws, but spatial patterns are more difficult to forecast. Coulomb failure stress is perhaps the most common criterion invoked to explain spatial distributions of aftershocks. Here we consider the spatial relationship between patterns of aftershocks and a comprehensive list of 38 static elastic scalar metrics of stress (including stress tensor invariants, maximum shear stress, and Coulomb failure stress) from 213 coseismic slip distributions worldwide. The rates of true-positive and false-positive classification of regions with and without aftershocks are assessed with receiver operating characteristic (ROC) analysis. We infer that the stress metrics that are most consistent with observed aftershock locations are maximum shear stress and the magnitude of the second and third invariants of the stress tensor. These metrics are significantly better than random assignment at a significance level of 0.005 in over 80% of the slip distributions. In contrast, the widely-used Coulomb failure stress criterion is distinguishable from random assignment in only 51-64% of the slip distributions. These results suggest that a number of alternative scalar metrics are better predictors of aftershock locations than classic Coulomb failure stress change.

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... Numerous studies have shown a strong correlation between aftershocks spatial pattern and changes in static Coulomb Failure Stress (CFS) resulting from mainshocks (e.g., Asayesh et al., 2018Asayesh et al., , 2019Asayesh, Zarei, & Zafarani, 2020;Harris & Simpson, 1992;Jamalreyhani et al., 2020;King et al., 1994;Toda et al., 1998). Recently, some studies using receiver operating characteristic (ROC) analysis have shown that several alternative scalar metrics are better predictors of aftershock locations than ΔCFS (DeVries et al., 2018;Meade et al., 2017;Mignan & Broccardo, 2019). Later, Sharma et al. (2020), by using available slip models from the SRCMOD database (Mai & Thingbaijam, 2014) and repeating the analysis with more appropriate stress calculations, showed that ΔCFS resolved on optimally oriented planes (OOP) or calculated for variable mechanism (VM) significantly improved the ΔCFS results for receiver mechanisms identical to the mainshock mechanism (on master fault orientation, MAS). ...

Reference:

Improved Aftershock Forecasts Using Mainshock Information in the Framework of the ETAS Model
What Is Better Than Coulomb Failure Stress? A Ranking of Scalar Static Stress Triggering Mechanisms from 10 5 Mainshock-Aftershock Pairs: Static Stress Triggering Mechanisms