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Gotowe bibliografie tematyczne / Anthropogenic Seismic Sources

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Artykuły w czasopismach

Gotowa bibliografia na temat „Anthropogenic Seismic Sources”

Autor: Grafiati

Data publikacji: 12 kwietnia 2025

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Artykuły w czasopismach na temat "Anthropogenic Seismic Sources"

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Lecocq, Thomas, Stephen P. Hicks, Koen Van Noten, et al. "Global quieting of high-frequency seismic noise due to COVID-19 pandemic lockdown measures." Science 369, no. 6509 (2020): 1338–43. http://dx.doi.org/10.1126/science.abd2438.

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Human activity causes vibrations that propagate into the ground as high-frequency seismic waves. Measures to mitigate the coronavirus disease 2019 (COVID-19) pandemic caused widespread changes in human activity, leading to a months-long reduction in seismic noise of up to 50%. The 2020 seismic noise quiet period is the longest and most prominent global anthropogenic seismic noise reduction on record. Although the reduction is strongest at surface seismometers in populated areas, this seismic quiescence extends for many kilometers radially and hundreds of meters in depth. This quiet period prov

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Schippkus, Sven, Mikaël Garden, and Götz Bokelmann. "Characteristics of the Ambient Seismic Field on a Large-N Seismic Array in the Vienna Basin." Seismological Research Letters 91, no. 5 (2020): 2803–16. http://dx.doi.org/10.1785/0220200153.

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Abstract The ambient seismic field is now routinely used for imaging and monitoring purposes. Most commonly, applications aim at resolving crustal-scale features and utilize ocean-generated surface waves. At smaller scales and at frequencies above the microseismic peaks, local sources of seismic energy, often anthropogenic, are dominant, and understanding of their contributions to the ambient seismic field becomes important to apply ambient noise techniques. This study uses data of an industrial-scale seismic deployment covering ∼500 km2 with 10,532 stations, each equipped with several colloca

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Zhu, Tieyuan, Junzhu Shen, and Eileen R. Martin. "Sensing Earth and environment dynamics by telecommunication fiber-optic sensors: an urban experiment in Pennsylvania, USA." Solid Earth 12, no. 1 (2021): 219–35. http://dx.doi.org/10.5194/se-12-219-2021.

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Abstract. Continuous seismic monitoring of the Earth's near surface (top 100 m), especially with improved resolution and extent of data both in space and time, would yield more accurate insights about the effect of extreme-weather events (e.g., flooding or drought) and climate change on the Earth's surface and subsurface systems. However, continuous long-term seismic monitoring, especially in urban areas, remains challenging. We describe the Fiber Optic foR Environmental SEnsEing (FORESEE) project in Pennsylvania, USA, the first continuous-monitoring distributed acoustic sensing (DAS) fiber ar

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Dobrorodny, Vladimir I., and Oksana A. Kopylova. "CHARACTERISTICS OF MICROSEISMS AND ACOUSTIC NOISES IN THE TRANSPORT POLYGON CONDITIONS." Interexpo GEO-Siberia 4, no. 1 (2021): 118–25. http://dx.doi.org/10.33764/2618-981x-2021-4-1-118-125.

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The work is related to numerical estimation and comparative analysis of microseismic and acoustic noise levels in transport polygon conditions. The aim of the work is to study and further define the difference between the signal and noise to improve the ability to detect poorly distinguishable events, as well as to study the propagation features of the interrelated seismic and acoustic wave fields. It is related to the fact that wave processes generated by many natural and anthropogenic sources are conjugate nature. In particular, it is related to simultaneous propagation of seismic waves in t

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Qin, Lei, Frank L. Vernon, Christopher W. Johnson, and Yehuda Ben‐Zion. "Spectral Characteristics of Daily to Seasonal Ground Motion at the Piñon Flats Observatory from Coherence of Seismic Data." Bulletin of the Seismological Society of America 109, no. 5 (2019): 1948–67. http://dx.doi.org/10.1785/0120190070.

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Abstract We investigate coherences of seismic data recorded during three years (2015–2017) at the Piñon Flats Observatory (PY) array and a collocated 148 m deep borehole station B084, along with oceanic data from a buoy southwest of the PY array. Seismic and barometric recordings at PY stations are analyzed with a multitaper spectral technique. The coherence of signals from seismic sources is >0.6 at 0.05–8 Hz between closely spaced (<65 m) surface stations and decreases to ∼0.2 in frequency bands in which the wavelengths are smaller than interstation distances. There are several local c

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Harris, David, Julie Albaric, Bettina Goertz-Allmann, Daniela Kuehn, Sebastian Sikora, and Volker Oye. "Interference suppression by adaptive cancellation in a high Arctic seismic experiment." GEOPHYSICS 82, no. 4 (2017): V201—V209. http://dx.doi.org/10.1190/geo2016-0452.1.

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Mechanical and electromagnetic interference (process noise) is common in seismic data recorded to monitor and characterize induced microseismicity during industrial injection and production operations. We have developed a case study of adaptive cancellation to reduce observed process noise in passive seismic data recorded during the 2014 injection test at the [Formula: see text] Lab research site in Spitsbergen. Our results suggest that adaptive cancellation is effective when major sources of interference are readily identifiable. Adaptive cancellation requires these sources to be instrumented

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Kumar, Santosh, R. Chaitanya Kumar, Ketan Singha Roy, and Sumer Chopra. "Seismic Monitoring in Gujarat, India, during 2020 Coronavirus Lockdown and Lessons Learned." Seismological Research Letters 92, no. 2A (2021): 849–58. http://dx.doi.org/10.1785/0220200260.

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Abstract The Gujarat region, situated in the westernmost part of India, experienced a deadly intraplate 2001 Mw 7.6 Bhuj earthquake. In the aftermath of the disaster, the Institute of Seismological Research established the Gujarat (India) seismic network in 2006. The network is being operated in online and offline modes, whereas, seismicity monitoring is being done in near-real-time, using data received from the online seismic stations. The Coronavirus disease-19 lockdown provided an opportunity to assess the network reliability in a difficult and challenging scenario. The positive aspect of t

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Lehujeur, Maximilien, Jérôme Vergne, Alessia Maggi, and Jean Schmittbuhl. "Vertical seismic profiling using double-beamforming processing of nonuniform anthropogenic seismic noise: The case study of Rittershoffen, Upper Rhine Graben, France." GEOPHYSICS 82, no. 6 (2017): B209—B217. http://dx.doi.org/10.1190/geo2017-0136.1.

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Correlating ambient seismic noise allows us to image the subsoil in various contexts and at different scales. Applying this technique to anthropogenic seismic noise can be challenging when the spatial distribution of the sources is not uniform. We have addressed the feasibility of exploiting this kind of noise in addition to microseismic noise to extend the reconstruction of Rayleigh-wave dispersion at periods between 0.2 and 1 s. We used data acquired with two small aperture arrays ([Formula: see text] stations with a 200 m helical distribution) deployed near the deep geothermal site of Ritte

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Ranguelov, Boyko, Ruben Paul Borg, Edelvays Spassov, Fathimath Shadiya, and Antoaneta Frantzova. "Determination of Vs_30 from existing geophysical investigation data." Engineering Geology and Hydrogeology 36, no. 1 (2023): 35–43. http://dx.doi.org/10.52321/igh.36.1.35.

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The Vs_30 refers to the velocity of transversal seismic waves in the upper earth crust (surface shallow depths) in the 0-30 m interval. This parameter reflects the integral ground properties and is used in almost all seismic hazard assessment software. The determination of Vs_30 is important, especially in the case of urban territories, where in-situ measurements are very difficult and sometimes impossible due to dense urban areas, large anthropogenic noise and the need of expensive boreholes. The paper presents a methodology for extracting necessary data and information from archival sources,

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10

Chai, Chengping, Omar Marcillo, Monica Maceira, et al. "Exploring Continuous Seismic Data at an Industry Facility Using Unsupervised Machine Learning." Seismic Record 5, no. 1 (2025): 64–72. https://doi.org/10.1785/0320240046.

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Abstract Seismic data recorded at industrial sites contain valuable information on anthropogenic activities. With advances in machine learning and computing power, new opportunities have emerged to explore the seismic wavefield in these complex environments. We applied two unsupervised machine learning algorithms to analyze continuous seismic data collected from an industrial facility in Texas, United States. The Uniform Manifold Approximation and Projection for Dimension Reduction algorithm was used to reduce the dimensionality of the data and generate 2D embeddings. Then, the Hierarchical De

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