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Big Data Seismology

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Summary: This study investigates the spatiotemporal changes of seismic velocity during the completion of hydraulic fracturing wells in the Fox Creek area, Alberta, Canada. It reveals a temporal correlation between velocity decreases and seismic activity, likely due to stress-induced subsurface deformation. By comparing injection parameters, it shows a correlation between induced seismicity and reduction in dv/v.

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Summary: This article presents a framework for automated detection of aircraft in seismic data using deep convolutional neural networks. The framework converts seismic data into spectrograms and classifies them as aircraft or non-aircraft using analyst-labeled data. The output is then combined across multiple channels using a majority voting scheme. The framework is applied to real data to demonstrate the advantage of using an array of sensors.

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Seismological observations on the 2019 March 21 accidental explosion at Xiangshui chemical plant in Jiangsu, China

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Summary: The study analyzed the Xiangshui chemical plant explosion in Jiangsu Province, China, and nearby chemical explosions and natural earthquakes using broad-band digital seismic data. Calculations of explosion magnitude and energy were consistent with ground truth, highlighting the characteristics of the explosion. Additionally, discriminants from P/S spectral ratios were found to effectively distinguish explosions from earthquakes.

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The Imbricated Foreshock and Aftershock Activities of the Balsorano (Italy) Mw 4.4 Normal Fault Earthquake and Implications for Initiation

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Humming Trains in Seismology: An Opportune Source for Probing the Shallow Crust

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Inconsistencies and Lurking Pitfalls in the Magnitude-Frequency Distribution of High-Resolution Earthquake Catalogs

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Summary: This study investigates if the magnitude-frequency distribution (MFD) of high-resolution earthquake catalogs can be extrapolated straightforwardly to an exponential-like distribution, and finds that high-resolution catalogs usually do not preserve the exponential-like MFD toward low magnitudes. These departures are mainly due to improper mixing of different magnitude types, spatiotemporal inhomogeneous completeness, or biased data recording or processing.

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Latency of Waveform Data Delivery from the Southern California Seismic Network during the 2019 Ridgecrest Earthquake Sequence and Its Effect on ShakeAlert

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Summary: The Ridgecrest earthquake sequence in July 2019 tested the readiness of the SCSN network for ShakeAlert, revealing some latency issues in data delivery, especially during peak demand. Improvements are being made to move telemetry links onto higher-bandwidth microwave systems and reduce dependence on unstable long-distance radio signals.

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Foreshocks of the 2018 ML 4.0 Shimian Earthquake in the Anninghe Fault and Its Implications for Earthquake Nucleation

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Summary: Our study scanned continuous waveforms before and after the 2018 ML 4.0 Shimian earthquake in Sichuan, China, using the match and locate method, revealing a significantly greater number of foreshock events than previously reported. The foreshocks of various magnitudes, occurring before the mainshock, showed consistent focal mechanisms and were found to rupture adjacent source patches along the same fault plane, indicating a cascade stress triggering mechanism.

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Large-Scale Fracture Systems Are Permeable Pathways for Fault Activation During Hydraulic Fracturing

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Summary: A study showed that preexisting fracture networks play a key role in transferring fluid pressures to larger faults during hydraulic fracturing. By analyzing sensor data from a hydraulic fracturing site in Alberta, Canada, researchers identified the significance of preexisting fracture corridors for understanding the mechanisms of induced seismicity.

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Characteristics of Frequent Dynamic Triggering of Microearthquakes in Southern California

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Summary: Studies have found that in the past decade, earthquake catalogs in Southern California can help systematically evaluate dynamic triggering patterns. It was discovered that approximately 1 out of every 5 global M-w >= 6 earthquakes can dynamically trigger microearthquakes in Southern California, showing both instantaneous and delayed triggering responses.

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Network analysis of earthquake ground motion spatial correlation: a case study with the San Jacinto seismic nodal array

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Summary: The spatial correlation of earthquake ground motion intensity is explored using strong motion data and graph analytics, revealing that site conditions and their interaction with the seismic wavefield strongly influence the spatial correlation of ground motion. Future progress in characterizing ground motion spatial variability will require dense wavefield measurements.

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Commentary: The Role of Geodetic Algorithms for Earthquake Early Warning in Cascadia

Jeffrey J. McGuire et al.

Summary: ShakeAlert earthquake early warning system issues alerts in California, and will soon expand to Oregon and Washington. Challenges and opportunities for EEW in the Cascadia subduction zone are significant. Initial expectations for geodetic algorithms providing improved warnings for specific types of earthquakes in Cascadia were found to be unrealistic, highlighting the need for rigorous testing.

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Rare Occurrences of Non-cascading Foreshock Activity in Southern California

L. Moutote et al.

Summary: Research suggests that not all mainshocks in Southern California are preceded by significantly elevated seismic activity, making anomalous foreshock activity relatively uncommon. Testing against a model, only a few mainshocks exhibit mainshock-specific anomalies with high predictive power.

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Machine learning in Earth and environmental science requires education and research policy reforms

Sean W. Fleming et al.

Summary: Leveraging advances in artificial intelligence has the potential to revolutionize Earth and environmental sciences, and it is crucial to ensure that the next generation of geoscientists are equipped with the necessary research funding and training choices to realize this potential.

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Exploring Approaches for Large Data in Seismology: User and Data Repository Perspectives

Javier Quinteros et al.

Summary: New data acquisition techniques are generating data at much finer resolution, posing challenges for data centers and users. With a potential increase in data flowing into data centers by orders of magnitude, management challenges exist throughout the data flow stages. Data centers are exploring storage solutions, formats, and delivery options to meet the needs of users working with large datasets.

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A Multi-Physics Experiment with a Temporary Dense Seismic Array on the Argentiere Glacier, French Alps: The RESOLVE Project

Florent Gimbert et al.

Summary: Recent work in cryo-seismology has shown that high-frequency seismic waves can provide key constraints on glacier processes, such as basal friction, surface crevassing, and subglacial water flow. A dense seismic array experiment conducted on the Argentiere Glacier in the French Alps in early spring 2018, combined with various complementary observations, has yielded new insights into the nature of glacier processes.

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Utilizing distributed acoustic sensing and ocean bottom fiber optic cables for submarine structural characterization

Feng Cheng et al.

Summary: This study demonstrates the usage of marine DAS application in characterizing submarine structures with high resolution. By extracting Scholte waves from ambient noise records on a 20 km section of fiber optic cable in Monterey Bay, California, researchers were able to recover a detailed 2D shear-wave velocity image of near seafloor sediments. The results offer improved constraints on shallow submarine features, such as fault zones and paleo-channel deposits, highlighting the potential geophysical uses of marine cable networks.

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Global Navigational Satellite System Seismic Monitoring

Timothy Melbourne et al.

Summary: The global earthquake deformation monitoring system uses data from around 2000 existing GNSS receivers to rapidly characterize large earthquakes and tsunamis. It provides precise point position time series globally and allows for real-time analysis of earthquake moment release and fault-slip distribution. The system is scalable and can offer a new and faster way of characterizing large earthquakes and tsunamis compared to existing systems.

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Multiscale, radially anisotropic shear wave imaging of the mantle underneath the contiguous United States through joint inversion of USArray and global data sets

Robert W. Porritt et al.

Summary: The study presents a new global shear wave velocity tomography model to investigate upper mantle structure and North American Plate dynamics, focusing on the contiguous United States using USArray data. The resulting model provides higher resolution and reveals short wavelength anomalies under the contiguous United States, bridging the gap between high-resolution regional models and global models for a better understanding of continental dynamics.

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Physical conditions and frictional properties in the source region of a slow-slip event

Adrien F. Arnulf et al.

Summary: Seismic imaging and data-constrained modelling reveal lateral variability in elastic properties and pore pressure, as well as near-velocity-neutral frictional properties in a shallow slow-slip source region along the Hikurangi subduction margin. The study suggests that fluid flow along thrust faults plays a crucial role in influencing mechanical properties and frictional stability along the subduction fault. This research also indicates that shallow subduction fault rocks must exhibit nearly velocity-neutral properties to generate shallow frictional slow slip events.

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Seismic Observations of Four Thunderstorms Using an Underground Fiber-Optic Array

Samuel Hone et al.

Summary: The article presents seismological observations of four thunderstorms in the spring and summer of 2019 recorded using a distributed acoustic sensing fiber-optic array in Pennsylvania. By analyzing the seismic waveform responses of thunderstorm events, the study tracks wave propagation and identifies source locations of thunderquakes.

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Distributed Acoustic Sensing Using Dark Fiber for Array Detection of Regional Earthquakes

Avinash Nayak et al.

Summary: The study tested the ability of a dark-fiber DAS array in northern California to detect small seismic phases from distant seismic events, showing significant potential of DAS for local and regional detection of small seismic events.

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Array-Based Convolutional Neural Networks for Automatic Detection and 4D Localization of Earthquakes in Hawai'i

Heather Shen et al.

Summary: By leveraging advances in machine learning, the study proposes an improved solution for earthquake monitoring using a convolutional neural network trained on continuous array data, achieving highly accurate event detection and localization in noisy environments. The model reduces localization errors significantly and shows potential for further enhancements through data augmentation and use of offshore earthquake data.

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Source location of volcanic earthquakes and subsurface characterization using fiber-optic cable and distributed acoustic sensing system

Takeshi Nishimura et al.

Summary: This study presents a novel method for source location determination of volcanic earthquakes and characterization of volcanic subsurfaces using a distributed acoustic sensing (DAS) system. By analyzing well-correlated waveforms and seismic amplitudes recorded along a fiber-optic cable, the hypocenters of volcanic earthquakes at Azuma volcano, Japan were successfully determined, showing a shallow depth beneath active volcanic areas. The spatial distribution of site amplification factors from coda waves of regional tectonic earthquakes is correlated with old lava flow distributions and volcano topography.

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SeismoGen: Seismic Waveform Synthesis Using GAN With Application to Seismic Data Augmentation

Tiantong Wang et al.

Summary: The text discusses the use of Generative Adversarial Networks (GANs) in earthquake detection, highlighting how the generation of realistic synthetic waveform data and data augmentation have improved earthquake detection algorithms with limited labeled training data.

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Precursory Slow Slip and Foreshocks on Rough Faults

Camilla Cattania et al.

Summary: Seismic activities on rough faults are influenced by the interaction between creep and foreshocks, rather than being solely driven by coseismic stress changes or creep.

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Immediate Foreshocks Indicating Cascading Rupture Developments for 527 M 0.9 to 5.4 Ridgecrest Earthquakes

Haoran Meng et al.

Summary: Understanding earthquake foreshocks is crucial for interpreting earthquake rupture physics and reducing seismic hazards. Immediate foreshocks identified in the 2019 Ridgecrest earthquake sequence show high resemblance to mainshock P waves, but their attributes do not necessarily scale with mainshock magnitudes. This suggests that earthquake rupture initiation may be universal but evolves stochastically, likely influenced by fine-scale fault heterogeneities.

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Observing the subglacial hydrology network and its dynamics with a dense seismic array

Ugo Nanni et al.

Summary: The study demonstrates the use of dense seismic array observations and a systematic seismic source location technique to retrieve a two-dimensional map of a subglacial drainage system and its day-to-day temporal evolution. With unprecedented detail, the researchers are able to identify regions where subglacial water flows enhance glacier flow through a cavity-like system and where water impedes glacier flow through a channel-like system. This information is crucial for understanding the long-term glacier response to climate warming.

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Deep Learning for Geophysics: Current and Future Trends

Siwei Yu et al.

Summary: Deep learning has attracted increasing attention in the geophysical community as a new data-driven technique, showing potential in accurately predicting complex system states and alleviating the curse of dimensionality. Various DL approaches have been applied and studied in geosciences, with promising future research directions including unsupervised learning, multimodal DL, among others.

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Ambient Noise Level in Eastern North China from ChinArray and Its Response to COVID-19

Weilai Wang et al.

Summary: This study in North China reveals that high-frequency ambient noise is correlated with surrounding sedimentary thickness and population density. The reduction in noise level during the Spring Festival in 2019 and 2020, as well as the epidemic control period, is influenced by the sedimentary thickness and population density in the region.

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Southern California Earthquake Data Now Available in the AWS Cloud

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Summary: The Southern California Earthquake Data Center has made its earthquake catalog and seismic waveform archive available through the Amazon Web Services Open Dataset Program, providing researchers with high data availability and scalability for analyzing large datasets. They have shared usage statistics and discussed both the challenges and opportunities of using a cloud-hosted archive.

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Summary: Cross-correlating seismic observations can estimate band-limited inter-receiver Green's functions, but issues arise from phase errors caused by correlated noise sources. Existing methods may not fully address this problem, but a new workflow has been developed to significantly mitigate these effects.

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Summary: The 2016 M7.8 Kaikoura earthquake is considered one of the most complex earthquakes in recorded history, involving significant rupture of at least 21 crustal faults. Through the use of various techniques, researchers constructed a catalog of seismic activities and fault ruptures, leading to key findings such as the earthquake nucleating on the Humps Fault and the reactivation of faults from previous sequences.

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Urban Basin Structure Imaging Based on Dense Arrays and Bayesian Array-Based Coherent Receiver Functions

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Summary: Urban basin investigation is crucial for seismic hazard assessment and mitigation. A novel Bayesian array-based Coherent Receiver Function (CRF) method is introduced in this study to constrain basin geometry, demonstrating its ability in the northern Los Angeles basin. The use of dense seismic networks and state-of-the-art CRF method provide a robust approach for subsurface structure imaging.

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Summary: A teleseismic P-wave travel-time tomography study examined the geometry and structure of subducted lithosphere in the upper mantle beneath the Alpine orogen. The study utilized data from the AlpArray Seismic Network, deploying over 600 temporary and permanent broadband stations to extract highly accurate absolute P-wave travel times and travel-time residuals. The resulting model provided a detailed image of slab configuration beneath the Alpine and Apenninic orogens, revealing complex structures and anomalies associated with European slab origins.

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Summary: Utilizing smartphones for earthquake early warning can provide reliable alerts at a significantly lower cost compared to scientific-grade networks. The system in Costa Rica showed successful implementation with no false alarms, fast response times, and the potential for even faster alerts in the future.

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Summary: Utilizing optical fibers for seismic monitoring allows for rapid response and critical data acquisition. Research shows that DAS technology successfully detected more aftershocks after the Ridgecrest earthquake. The widespread fiber optic networks globally provide great potential for high-resolution aftershock monitoring.

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