![]() ![]() For instance, significant effort has been devoted to using ML to improve event detection, arrival‐time picking, phase association, and earthquake location (McBrearty et al., 2019 Mousavi et al., 2020 Perol et al., 2018 Ross et al., 2018 Trugman & Ross, 2019 Wu et al., 2018 Yoon et al., 2015 Zhu & Beroza, 2019). Machine learning (ML) methods have followed improvements in geophysical techniques, instrumentation, and data availability over the past decade to rapidly emerge as indispensable toolkits for the geophysical community (Bergen et al., 2019 Kong et al., 2019). Broadly, our results demonstrate the utility of physics‐informed ML in forecasting the imminence of fault slip at the laboratory scale, which may have important implications for earthquake mechanics in nature. Our results demonstrate that the relationship between the ultrasonic parameters and fault slip rate, and in turn, the systematically evolving real area of contact and asperity stiffness allow the gradient boosting algorithm to “learn” about the state of the fault and its proximity to failure. The ML predictions improve in accuracy closer to fault failure, demonstrating that the predictive power of the ultrasonic signals improves as the fault approaches failure. The ML methods utilize systematic changes in P‐wave amplitude and velocity to accurately predict the timing and shear stress during labquakes. We show that elastic waves passing through the lab fault zone contain information that can predict the full spectrum of labquakes from slow slip instabilities to highly aperiodic events. Here, we address this knowledge gap by coupling active‐source seismic data, which probe asperity‐scale processes, with ML methods. However, the underlying physical mechanisms that allow lab earthquake prediction and seismic forecasting remain poorly resolved. Lab‐based studies have used acoustic emission data to predict time‐to‐failure and stress state, and in a few cases, the same approach has been used for field data. ![]() Machine learning (ML) techniques have become increasingly important in seismology and earthquake science. ![]()
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February 2023
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