Seismic arrival-time picking on distributed acoustic sensing data using semi-supervised learning.

Distributed Acoustic Sensing (DAS) is an emerging technology for earthquake monitoring and subsurface imaging. However, its distinct characteristics, such as unknown ground coupling and high noise level, pose challenges to signal processing. Existing machine learning models optimized for conventional seismic data struggle with DAS data due to its ultra-dense spatial sampling and limited manual labels. We introduce a semi-supervised learning approach to address the phase-picking task of DAS data. We use the pre-trained PhaseNet model to generate noisy labels of P/S arrivals in DAS data and apply the Gaussian mixture model phase association (GaMMA) method to refine these noisy labels and build training datasets. We develop PhaseNet-DAS, a deep learning model designed to process 2D spatio-temporal DAS data to achieve accurate phase picking and efficient earthquake detection. Our study demonstrates a method to develop deep learning models for DAS data, unlocking the potential of integrating DAS in enhancing earthquake monitoring.

The magmatic web beneath Hawai'i.

The deep magmatic architecture of the Hawaiian volcanic system is central to understanding the transport of magma from the upper mantle to the individual volcanoes. We leverage advances in earthquake monitoring with deep learning algorithms to image the structures underlying a major mantle earthquake swarm of nearly 200,000 events that rapidly accelerated after the 2018 Kilauea caldera collapse. At depths of 36 to 43 kilometers, we resolve a 15-kilometers-long collection of near-horizontal sheeted structures that we identify as a sill complex. These sills connect to the lower depths of Kilauea's plumbing by a 25-kilometers-long belt of seismicity. Additionally, a column of seismicity links the sill complex to a shallow décollement near Mauna Loa. These findings implicate the mantle sill complex as a nexus for magma transport beneath Hawai'i and furthermore indicate widespread magmatic connectivity in the volcanic system.

A unified perspective of seismicity and fault coupling along the San Andreas Fault.

The San Andreas Fault (SAF) showcases the breadth of possible earthquake sizes and occurrence behavior; in particular, the central SAF is a microcosm of such diversity. This section also exhibits the spectrum of fault coupling from locked to creeping. Here, we show that the observations of aseismic slip, temporal clustering of seismicity, and spatial variations in earthquake size distributions are tightly connected. Specifically, the creep rate along the central SAF is shown to be directly proportional to the fraction of nonclustered earthquakes for the period 1984-2020. This relationship provides a unified perspective of earthquake phenomenology along the SAF, where lower coupling manifests in weaker temporal clustering, with repeating earthquakes as an end-member. This new paradigm provides additional justification for characterizing the northwest ∼75 kilometers of the creeping segment as a transition zone, with potential implications for seismic hazard.

Basal nucleation and the prevalence of ascending swarms in Long Valley caldera.

Earthquake swarms are ubiquitous in volcanic systems, being manifestations of underlying nontectonic processes such as magma intrusions or volatile fluid transport. The Long Valley caldera, California, is one such setting where episodic earthquake swarms and persistent uplift suggest the presence of active magmatism. We quantify the long-term spatial and temporal characteristics of seismicity in the region using cluster analysis on a 25-year high-resolution earthquake catalog derived using leading-edge deep-learning algorithms. Our results show that earthquake swarms beneath the caldera exhibit enlarged families with statistically significant tendency for upward migration patterns. The ascending swarms tend to nucleate at the base of the seismogenic zone with a spatial footprint that is laterally constrained by the southern rim of the caldera. We suggest that these swarms are driven by the transport of volatile-rich fluids released from deep volcanic processes. The observations highlight the potential for extreme spatial segmentation of earthquake triggering processes in magmatic systems.

3D fault architecture controls the dynamism of earthquake swarms.

The vibrant evolutionary patterns made by earthquake swarms are incompatible with standard, effectively two-dimensional (2D) models for general fault architecture. We leverage advances in earthquake monitoring with a deep-learning algorithm to image a fault zone hosting a 4-year-long swarm in southern California. We infer that fluids are naturally injected into the fault zone from below and diffuse through strike-parallel channels while triggering earthquakes. A permeability barrier initially limits up-dip swarm migration but ultimately is circumvented. This enables fluid migration within a shallower section of the fault with fundamentally different mechanical properties. Our observations provide high-resolution constraints on the processes by which swarms initiate, grow, and arrest. These findings illustrate how swarm evolution is strongly controlled by 3D variations in fault architecture.

Hierarchical interlocked orthogonal faulting in the 2019 Ridgecrest earthquake sequence.

A nearly 20-year hiatus in major seismic activity in southern California ended on 4 July 2019 with a sequence of intersecting earthquakes near the city of Ridgecrest, California. This sequence included a foreshock with a moment magnitude (M w) of 6.4 followed by a M w 7.1 mainshock nearly 34 hours later. Geodetic, seismic, and seismicity data provided an integrative view of this sequence, which ruptured an unmapped multiscale network of interlaced orthogonal faults. This complex fault geometry persists over the entire seismogenic depth range. The rupture of the mainshock terminated only a few kilometers from the major regional Garlock fault, triggering shallow creep and a substantial earthquake swarm. The repeated occurrence of multifault ruptures, as revealed by modern instrumentation and analysis techniques, poses a formidable challenge in quantifying regional seismic hazards.

Searching for hidden earthquakes in Southern California.

Earthquakes follow a well-known power-law size relation, with smaller events occurring much more often than larger events. Earthquake catalogs are thus dominated by small earthquakes yet are still missing a much larger number of even smaller events because of signal fidelity issues. To overcome these limitations, we applied a template-matching detection technique to the entire waveform archive of the regional seismic network in Southern California. This effort resulted in a catalog with 1.81 million earthquakes, a 10-fold increase, which provides important insights into the geometry of fault zones at depth, foreshock behavior and nucleation processes, and earthquake-triggering mechanisms. The rich detail resolved in this type of catalog will facilitate the next generation of analyses of earthquakes and faults.

Abundant off-fault seismicity and orthogonal structures in the San Jacinto fault zone.

The trifurcation area of the San Jacinto fault zone has produced more than 10% of all earthquakes in southern California since 2000, including the June 2016 Mw (moment magnitude) 5.2 Borrego Springs earthquake. In this area, the fault splits into three subparallel strands and is associated with broad VP /VS anomalies. We synthesize spatiotemporal properties of historical background seismicity and aftershocks of the June 2016 event. A template matching technique is used to detect and locate more than 23,000 aftershocks, which illuminate highly complex active fault structures in conjunction with a high-resolution regional catalog. The hypocenters form dipping seismicity lineations both along strike and nearly orthogonal to the main fault, and are composed of interlaced strike-slip and normal faults. The primary faults change dip with depth and become listric by transitioning to a dip of ~70° near a depth of 10 km. The Mw 5.2 Borrego Springs earthquake and past events with M > 4.0 occurred on the main faults, whereas most of the low-magnitude events are located in a damage zone (several kilometers wide) at seismogenic depths. The lack of significant low-magnitude seismicity on the main fault traces suggests that they do not creep. The very high rate of aftershocks likely reflects the large geometrical fault complexity and perhaps a relatively high stress due to a significant length of time elapsed since the last major event. The results provide important insights into the physics of faulting near the brittle-ductile transition.