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Template matching has proven to be an effective method for seismic event detection, but is biased toward identifying events similar to previously known events, and thus is ineffective at discovering events with non‐matching waveforms (e.g., those dissimilar to existing catalog events). In principle, this limitation can be overcome by cross‐correlating every segment (possible template) of a seismogram with every other segment to identify all similar event pairs, but doing so has been previously considered computationally infeasible for long time series. Here we describe a method, called the 'Matrix Profile' (MP), a "correlate everything with everything" calculation that can be efficiently and scalably computed. The MP returns the maximum value of the correlation coefficient of every sub‐window of continuous data with every other sub‐window, as well as the best‐correlated sub‐window location. Here we show how MP methods can obtain valuable results when applied to months and years of continuous seismic data in both local and global case studies. We find that the MP can identify many new events in Parkfield, California seismicity that are not contained in existing event catalogs and that it can efficiently find clusters of similar earthquakes in global seismic data. Either used by itself, or as a starting point for subsequent template matching calculations, the MP is likely to provide a useful new tool for seismology research. Plain Language Summary: Detecting and cataloging earthquakes through analysis of seismic data—the shapes of seismic waves, recorded by seismometers—is foundational to our understanding of Earth's interior structure and processes, as well as geological hazards such as earthquakes. Methods to improve the efficiency and sensitivity of earthquake detection while maintaining accuracy are critical, as seismic data volumes have grown exponentially in recent decades. Recently, methods that use recorded earthquakes as template patterns to identify in seismic data, have proven capable of detecting several times more earthquakes than traditional methods. However, such methods require knowledge of the template earthquakes ahead of time, and are best at identifying earthquakes whose waveforms are similar to the templates. We present here a new method, called the 'Matrix Profile' (MP), that takes short windows of data from a seismic data stream, and compares them to all other parts of that data stream, identifying parts of the data that are highly similar. The MP effectively identifies earthquakes, even those which are hidden within noise, does not require any templates to be provided upfront, and can be efficiently calculated. We demonstrate its success at detecting earthquakes in different types of seismic data, and provide practical guidelines for applying the method and interpreting the results. Key Points: The matrix profile finds the maximum autocorrelation of every subsequence in a time seriesPeaks of high similarity in the matrix profile can be used to identify seismic events and similar event pairsThe matrix profile method has similar sensitivity to template matching but does not require a priori templates [ABSTRACT FROM AUTHOR]

We use a dense seismic array of 1,108 vertical‐component geophones within a 600‐m footprint to detect thousands of small earthquakes near an active strand of the San Jacinto fault zone in southern California during a 26‐day period. We first correct site effects using multichannel cross‐correlations of the P‐waves of 256 cataloged earthquakes, and then perform beamforming analysis on the continuous waveforms in a slowness range from −0.4 to 0.4 s/km in both the east and north directions. At each time step, we identify the beam slowness with maximum amplitude and apply a picking algorithm to identify 13,408 events. These detections include over 55.6% of the events in the Quake Template Matching (QTM) catalog for all of southern California during the same time period and 70% of those within 100 km of the array. In addition, we detect over 10,000 new events, not in the QTM catalog. Many of these events can also be seen in records from nearby borehole seismic stations. Measured slownesses for the catalog and newly‐discovered events group into clusters that can be associated with QTM earthquake locations, but with slowness values considerably distorted from predictions based on a 1‐D velocity model, presumably owing to strong velocity heterogeneity near the San Jacinto Fault. Amplitudes of the detected events obey a Gutenberg‐Richter distribution with a b‐value close to one. Foreshocks are common among these detected events, increasing in rate before mainshocks following an inverse Omori's law. Plain Language Summary: We show that an array of over 1,000 seismometers located on a small patch of the San Jacinto Fault in southern California can detect many times more earthquakes than those in standard earthquake catalogs. Although accurate locations cannot be obtained for most of these newly identified events, their amplitudes indicate they obey similar scaling with size as larger magnitude earthquakes. Many of the larger events are preceded by foreshocks and the foreshock rate increases in the time leading up to the mainshocks. Our results suggest that future deployments of small‐aperture seismometer arrays could be used to complement existing seismic networks to probe earthquake activity in great detail. Key Points: We detect over 13,000 seismic events during 26 days in 2014 using a dense nodal array on the San Jacinto fault zone in southern CaliforniaMost of the detections are newly discovered earthquakes not in existing catalogsForeshocks are common among these earthquakes, increasing in the rate before their mainshocks following an inverse Omori's law [ABSTRACT FROM AUTHOR]

Utilizing the surface-wave (Rayleigh-wave) dispersion properties to estimate subsurface S-wave velocity structure has become a popular method due to simple data collection and analysis procedure during the past decades. In particular, the promotion of distributed acoustic sensing (DAS) technique enhances its popularity due to the low-cost of ultra-dense observations. Moreover, under the same exploration requirement, the cost of the DAS data collection is much lower than that of the traditional acquisition implemented by the nodal seismographs. Therefore, it is necessary to expand the DAS application. Here, the multimodal surface-wave dispersion curves are successfully extracted from the phase-weighted stack of cross-correlation functions (CCFs) of the DAS data collected at Garner Valley Downhole Array field site, California by the proposed cylindrical-wave phase-shift. Then, the dispersion curves are inverted by the inversion workflow (expected to avoid the mode-misidentification) proposed by Yan et al. (2022a), consisting of staging strategy and pattern search with embedded Kuhn-Munkres (PSEKM) algorithm. Compared with other inversion schemes, the novel inversion method allows the presence of the observed values without prior mode-order definition in the inversion system, which omits the tedious and risky manual mode identification, and the mode-orders would be predicted dynamically during the inversion. The dispersion fittings for certain survey points indicate that the mode losses and aliasings appear to be widespread for the surface waves recorded on the free-surface. Finally, the S-wave velocity tomogram consistent with the geological materials of survey area is revealed. Our study demonstrates the feasibility of extracting the DAS-derived multimodal dispersion information and consequently obtaining a physical-reasonable subsurface S-wave velocity model. • Propose the cylindrical-wave phase-shift for dispersion spectrum calculation. • Construct a dedicated workflow for DAS data analysis. • The inversion method without high-mode order-label is adopted. • Mode-losses and aliasings of dispersion curves are revealed by our method. [ABSTRACT FROM AUTHOR]

We present a new method to locate low-frequency earthquakes (LFEs) within tectonic tremor episodes based on time-reverse imaging techniques. The modified time-reverse imaging technique presented here is the first method that locates individual LFEs within tremor episodes within 5 km uncertainty without relying on high-amplitude P-wave arrivals and that produces similar hypocentral locations to methods that locate events by stacking hundreds of LFEs without having to assume event co-location. In contrast to classic time-reverse imaging algorithms, we implement a modification to the method that searches for phase coherence over a short time period rather than identifying the maximum amplitude of a superpositioned wavefield. The method is independent of amplitude and can help constrain event origin time. The method uses individual LFE origin times, but does not rely on a priori information on LFE templates and families. We apply the method to locate 34 individual LFEs within tremor episodes that occur between 2010 and 2011 on the San Andreas Fault, near Cholame, California. Individual LFE location accuracies range from 2.6 to 5 km horizontally and 4.8 km vertically. Other methods that have been able to locate individual LFEs with accuracy of less than 5 km have mainly used large-amplitude events where a P-phase arrival can be identified. The method described here has the potential to locate a larger number of individual low-amplitude events with only the S-phase arrival. Location accuracy is controlled by the velocity model resolution and the wavelength of the dominant energy of the signal. Location results are also dependent on the number of stations used and are negligibly correlated with other factors such as the maximum gap in azimuthal coverage, source-station distance and signal-to-noise ratio. [ABSTRACT FROM AUTHOR]

The article focuses on the EarthScope project examining the San Andreas fault in California. It states that a major element of the project, a suite of instruments and detectors buried deep in the San Andreas fault, stopped functioning. Geophysicist Mark Zoback said that the instruments stopped functioning a few days after they were installed in the fault line. It mentions that there is insufficient funding to recover the detectors, which included seismometers and accelerometers.

In this article the authors have analyzed seismic noise to obtain new information on the structure of Earth's crust. By correlating the data from a month of ambient noise due in part to wave-wave interactions in the ocean 2 detected by 62 long-period seismograph stations in southern California, they determined the seismic response that they would have obtained from Earth's crust if they had applied forces at each of their stations. In particular, they measured the times that it took for seismic surface waves to propagate between every pair of stations. They then used lomographic techniques to create a map of seismic wave velocity with an unprecedented horizontal resolution of 75 to 100 km.

The observation of continuously excited free oscillations of the Earth, in the absence of earthquakes, was first made by Japanese scientists in 1998. Since then, attention has focused on elucidating the physical mechanism responsible for them. The mechanism must be shallow, as fundamental modes appear to be preferentially excited and it shows seasonal variability. An array-based method has been developed to detect and locate sources of very long period surface wave energy, utilizing the dispersive properties of Rayleigh waves and data from two large aperture arrays of very long period seismometers, in California and in Japan. It is shown that, for each array, there is a well defined preferential direction, which is stable over one season but changes significantly from winter to summer. The fluctuations as a function of time of the maximum stack amplitudes are correlated across the two arrays and point to the northern Pacific Ocean in the northern hemisphere winter and the southern oceans in the summer, correlating with the distribution of maximum wave height. It is inferred that the background oscillations originate primarily in the oceans, and are caused by a non-linear coupling mechanism involving the atmosphere (winds), the oceans (infragravity waves) and the seafloor. [ABSTRACT FROM AUTHOR]

The article reports that every day, several of California's more than 1000 shifting faults shake some part of the state. This clearinghouse of earthquake data keeps check on the ones that rattle northern California. Sponsored by the University of California, Berkeley, and the U.S. Geological Survey, the site catalogs magnitude, depth, location, and other measurements for earthquakes dating back to 1967. One should check out near-real-time recordings from a network of seismographs scattered around northern and central California.