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Abstract Earthquake focal mechanisms provide critical in-situ insights about the subsurface faulting geometry and stress state. For frequent small earthquakes (magnitude< 3.5), their focal mechanisms are routinely determined using first-arrival polarities picked on the vertical component of seismometers. Nevertheless, their quality is usually limited by the azimuthal coverage of the local seismic network. The emerging distributed acoustic sensing (DAS) technology, which can convert pre-existing telecommunication cables into arrays of strain/strain-rate meters, can potentially fill the azimuthal gap and enhance constraints on the nodal plane orientation through its long sensing range and dense spatial sampling. However, determining first-arrival polarities on DAS is challenging due to its single-component sensing and low signal-to-noise ratio for direct body waves. Here, we present a data-driven method that measures P-wave polarities on a DAS array based on cross-correlations between earthquake pairs. We validate the inferred polarities using the regional network catalog on two DAS arrays, deployed in California and each comprising ~ 5000 channels. We demonstrate that a joint focal mechanism inversion combining conventional and DAS polarity picks improves the accuracy and reduces the uncertainty in the focal plane orientation. Our results highlight the significant potential of integrating DAS with conventional networks for investigating high-resolution earthquake source mechanisms.
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This content will become publicly available on March 12, 2026
A Deep Learning-Aided Workflow for Decoding the Stress Regime of Southern Nevada
Abstract The Rock Valley fault zone in southern Nevada has a notable history of seismic activity and is the site of a future direct comparison experiment of explosion and earthquake sources. This study aims to gain insight into regional tectonic processes by leveraging recent advances in seismic monitoring capabilities to elucidate the local stress regime. A crucial step in this investigation is the accurate determination of P-wave first-motion polarities, which play a vital role in resolving earthquake focal mechanisms of small earthquakes. We deploy a deep learning-based method for automatic determination of first-motion polarities to vastly expand the polarity dataset beyond what has been reviewed by human analysts. By the integrating P-wave polarities with new measurements of S/P amplitude ratios, we obtain robust focal mechanism estimates for 1306 earthquakes with a local magnitude of 1 and above occurring between 2010 and 2023 in southern Nevada. We then use the focal mechanism catalog to examine the regional stress orientation, confirming an overall trans-tensional stress regime with smaller scale complexities illuminated by individual earthquake sequences. These findings demonstrate how detailed analyses of small earthquakes can provide fundamental information for understanding earthquake processes in the region and inform future experiments at the Nevada National Security Site.
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- PAR ID:
- 10598006
- Publisher / Repository:
- Seismological Society of America
- Date Published:
- Journal Name:
- Seismological Research Letters
- ISSN:
- 0895-0695
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Abstract Earthquake focal mechanisms provide crucial information about subsurface fault geometry and stress orientations. Focal mechanisms are typically inferred through analysis of seismic radiation patterns, for example, using P-wave first-motion polarities, potentially in combination with S/P amplitude ratios, to identify nodal planes. The motivation for this procedure is well-founded, as P- and S-wave radiation patterns depend fundamentally on the fault orientation. However, in practice, S/P amplitude ratio measurements can be strongly influenced by factors that are unrelated to the source mechanism. In this study, I characterize several underappreciated issues with S/P amplitude ratio data that are relevant to focal mechanism inversion. The analysis combines synthetic tests with new waveform measurements from ∼64,000 ML≥1.0 earthquakes in Nevada and California. Key findings include that (1) the statistical distribution of S/P amplitude ratio data differs markedly in shape and width from the theoretical expectation, (2) S/P amplitude ratios decay systematically with source-station distance beyond ∼60 km or so, (3) this distance effect is more severe for smaller earthquakes than for larger ones, and (4) modifying the frequency band in which amplitudes are measured can shift the observed amplitude ratio distribution but does not significantly mitigate issues (1)–(3). Taken together, these findings indicate that S/P amplitude ratio measurements are influenced by differential path attenuation and signal-to-noise effects that are not accounted for with existing workflows. Using independent moment tensor solutions, I systematically test various strategies to incorporate S/P amplitude ratios into focal mechanism solutions. The best-performing strategies transform S/P amplitude data to better match the theoretical expectation. Overall, S/P amplitude ratio data appear helpful in improving a typical mechanism solution, but even with the best-performing strategies considered here, the inclusion of S/P amplitude ratio data is expected to hinder rather than improve the solution for a subset of events.more » « less
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