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Journal articles on the topic 'Seismic ambient noise'

Author: Grafiati

Published: 28 June 2021

Last updated: 29 July 2025

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1

Krebes, Edward S. "Seismic Ambient Noise." Journal of the Acoustical Society of America 146, no. 1 (2019): 532–33. http://dx.doi.org/10.1121/1.5118247.

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2

Hussain, Yawar, Hernan Martinez-Carvajal, Cristobal Condori, et al. "Ambient seismic noise." Terrae Didatica 15 (February 14, 2019): e019012. http://dx.doi.org/10.20396/td.v15i1.8652455.

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Rainfall-induced variations in pore water pressures are the most common sources of significant disasters like landslides, dams’ failure, and other structural collapses. This study aimed at communicating preliminary results of seasonal monitoring of the Sobradinho landslide, Brasilia, Brazil, using ambient seismic noise. The noise was recorded before, during and after the rainy season with three L4-3A seismometers (2Hz) installed in a triangular array at the landslide mass. These records were processed using horizontal to vertical spectral ratio (HVSR) technique. As it resulted from the perform

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3

Ermert, Laura, Jonas Igel, Korbinian Sager, Eléonore Stutzmann, Tarje Nissen-Meyer, and Andreas Fichtner. "Introducing noisi: a Python tool for ambient noise cross-correlation modeling and noise source inversion." Solid Earth 11, no. 4 (2020): 1597–615. http://dx.doi.org/10.5194/se-11-1597-2020.

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Abstract. We introduce the open-source tool noisi for the forward and inverse modeling of ambient seismic cross-correlations with spatially varying source spectra. It utilizes pre-computed databases of Green's functions to represent seismic wave propagation between ambient seismic sources and seismic receivers, which can be obtained from existing repositories or imported from the output of wave propagation solvers. The tool was built with the aim of studying ambient seismic sources while accounting for realistic wave propagation effects. Furthermore, it may be used to guide the interpretation

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Hong, Tae-Kyung, Jeongin Lee, Giha Lee, Junhyung Lee, and Seongjun Park. "Correlation between Ambient Seismic Noises and Economic Growth." Seismological Research Letters 91, no. 4 (2020): 2343–54. http://dx.doi.org/10.1785/0220190369.

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Abstract Human activity is a major source of high-frequency seismic noise. Long-term ambient seismic noise levels and their influencing factors are investigated. The diurnal seismic noise level in 5–15 Hz display high correlation with human activities including traffic and industrial operations that are related to economic conditions. The temporal noise-level variations are consistent among three components. Analysis with seismic noises in three consecutive months of each year enables us to estimate the noise levels without seasonal effects. The daytime seismic noise-level changes in major cit

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Chen, Lihui, and Shaohong Xia. "Sensing Human Activity of the Guangdong–Hong Kong–Macao Greater Bay Area by Ambient Seismic Noise." Remote Sensing 15, no. 22 (2023): 5340. http://dx.doi.org/10.3390/rs15225340.

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Effective monitoring of human activity in urban areas is essential for social stability and urban development. Traditional monitoring methods include wearable devices, survey sensor networks, and satellite remote sensing, which may be affected by privacy and weather conditions. Ambient seismic noise recorded by seismometers contains rich information about human activity and exhibits significant temporal and spatial variations, which provides valuable insights into social mobility. In this study, we investigated the correlation between human activity and ambient seismic noise in the Guangdong–H

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Draganov, Deyan, Xander Campman, Jan Thorbecke, Arie Verdel, and Kees Wapenaar. "Reflection images from ambient seismic noise." GEOPHYSICS 74, no. 5 (2009): A63—A67. http://dx.doi.org/10.1190/1.3193529.

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One application of seismic interferometry is to retrieve the impulse response (Green’s function) from crosscorrelation of ambient seismic noise. Various researchers show results for retrieving the surface-wave part of the Green’s function. However, reflection retrieval has proven more challenging. We crosscorrelate ambient seismic noise, recorded along eight parallel lines in the Sirte basin east of Ajdabeya, Libya, to obtain shot gathers that contain reflections. We take advantage of geophone groups to suppress part of the undesired surface-wave noise and apply frequency-wavenumber filtering

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Li, Qianqian, Yaxin Liu, Lei Xing, et al. "Analysis of Regional Ambient Seismic Noise in the Chukchi Sea Area in the Arctic Based on OBS Data from the Ninth Chinese National Arctic Scientific Survey." Remote Sensing 15, no. 17 (2023): 4204. http://dx.doi.org/10.3390/rs15174204.

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Ambient noise plays a crucial role in influencing the observation quality at seismic stations. By studying the distribution patterns of ambient noise, we can gain initial insights into the noise conditions within a specific research area. This paper investigates the properties of ambient noise in different frequency bands under environmental settings in the Chukchi Sea region, utilizing data collected from ocean bottom seismometers (OBSs) deployed during the Ninth Chinese National Arctic Scientific Survey. The probability density function (PDF) method is used to reveal the distinctive features

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Xu, Zongbo, T. Dylan Mikesell, Josefine Umlauft, and Gabriel Gribler. "Rayleigh-wave multicomponent crosscorrelation-based source strength distribution inversions. Part 2: a workflow for field seismic data." Geophysical Journal International 222, no. 3 (2020): 2084–101. http://dx.doi.org/10.1093/gji/ggaa284.

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SUMMARY Estimation of ambient seismic source distributions (e.g. location and strength) can aid studies of seismic source mechanisms and subsurface structure investigations. One can invert for the ambient seismic (noise) source distribution by applying full-waveform inversion (FWI) theory to seismic (noise) crosscorrelations. This estimation method is especially applicable for seismic recordings without obvious body-wave arrivals. Data pre-processing procedures are needed before the inversion, but some pre-processing procedures commonly used in ambient noise tomography can bias the ambient (no

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9

Li, Xiaomeng, Yan Xu, Chaodi Xie, and Shanshan Sun. "Global characteristics of ambient seismic noise." Journal of Seismology 26, no. 2 (2022): 343–58. http://dx.doi.org/10.1007/s10950-021-10071-8.

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AbstractAmbient seismic noise becomes more and more important and helpful on assisting velocity model inversion, earthquake detection, and ground motion prediction. Based on the analysis of continuous seismic data and ocean wave height, we find that the ocean wave height and winter storms have a controlling factor on the DF microseismic energy level and its frequency extent in time scale. It shows that high and low DF microseismic energy accompanied with wide and narrow frequency range consistent with the high wave height period (when the ocean is stormier) and low wave height period, respecti

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10

Sens-Schönfelder, Christoph. "Synchronizing seismic networks with ambient noise." Geophysical Journal International 174, no. 3 (2008): 966–70. http://dx.doi.org/10.1111/j.1365-246x.2008.03842.x.

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11

Laske, Gabi. "Book Review of ‘Seismic Ambient Noise’." Geophysical Journal International 221, no. 3 (2020): 1667–68. http://dx.doi.org/10.1093/gji/ggaa101.

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12

de Ridder, Sjoerd A. L., and Biondo L. Biondi. "Ambient seismic noise tomography at Ekofisk." GEOPHYSICS 80, no. 6 (2015): B167—B176. http://dx.doi.org/10.1190/geo2014-0558.1.

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13

Shirzad, Taghi, and Zaher‐Hossein Shomali. "Extracting Stable Seismic Core Phases from Ambient Seismic Noise." Bulletin of the Seismological Society of America 106, no. 1 (2015): 307–12. http://dx.doi.org/10.1785/0120150031.

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14

Lei, Xiaoqiong, Jun Zhang, Wenyuan Jin, Chen Han, and Xiwei Xu. "The application of ambient noise and reflection seismic exploration in an urban active fault survey." Interpretation 8, no. 4 (2020): SU1—SU10. http://dx.doi.org/10.1190/int-2020-0085.1.

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As the detection of urban active faults becomes increasingly important, high-resolution detection of urban blind active faults is very important for urban planning, land use, and disaster risk reduction. However, it is difficult to determine the corresponding surface positions in the city environment for noise and building restrictions. The active source reflection seismic technique is considered the best technique to image faults with a high resolution and deep penetration. However, urban geophysical exploration must often consider the complex urban environment, which includes moving vehicles

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Edme, Pascal, and David F. Halliday. "Near-surface imaging using ambient-noise body waves." Interpretation 4, no. 3 (2016): SJ55—SJ65. http://dx.doi.org/10.1190/int-2016-0002.1.

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We have introduced a workflow that allows subsurface imaging using upcoming body-wave arrivals extracted from ambient-noise land seismic data. Rather than using the conventional seismic interferometry approach based on correlation, we have developed a deconvolution technique to extract the earth response from the observed periodicity in the seismic traces. The technique consists of iteratively applying a gapped spiking deconvolution, providing multiple-free images with higher resolution than conventional correlation. We have validated the workflow for zero-offset traces with simple synthetic d

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Poveda Brossard, Viana, and Eduardo Rafael Diez Zaldivar. "Ambient seismic noise in Cuba: analysis of broadband seismic stations in the Cuban Seismic Network." DYNA 89, no. 220 (2022): 145–53. http://dx.doi.org/10.15446/dyna.v89n220.96966.

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This paper analyses seismic noise from broadband seismic stations within the Cuban National Seismic Service, focusing on location sites, soil or rock quality at installation sites and the impact of various factors on the noise signature of these seismic stations. A brief technical description of deployed equipment is provided and the methodology for data selection and analysis is presented.The study provides annual performance assessment for each station, considering specific details for each particular case. Likewise, the effect of diurnal/nocturnal and seasonal variations on noise power spec

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Liu, Di. "Research on Body Wave Extraction Technology of Mixed Active Source Ambient Noise." Journal of Physics: Conference Series 2651, no. 1 (2023): 012149. http://dx.doi.org/10.1088/1742-6596/2651/1/012149.

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Abstract In complex surface environments, active source seismic exploration methods are difficult to stimulate and costly, while ambient noise detection technology is fast and convenient, with a little environmental damage and low cost. Therefore, it has aroused extensive research by scholars at home and abroad. At present, the use of passive source surface wave method for subsurface medium imaging has become mature. However, due to the low content and weak energy of the body wave signal in the actual ambient noise, it is particularly difficult to extract body waves using seismic interferometr

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18

Vassallo, M., G. Festa, and A. Bobbio. "Seismic Ambient Noise Analysis in Southern Italy." Bulletin of the Seismological Society of America 102, no. 2 (2012): 574–86. http://dx.doi.org/10.1785/0120110018.

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19

de Ridder, S. A. L., and J. R. Maddison. "Full wavefield inversion of ambient seismic noise." Geophysical Journal International 215, no. 2 (2018): 1215–30. http://dx.doi.org/10.1093/gji/ggy328.

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20

Stephen, Ralph A. "Ambient seismic noise below the deep seafloor." Leading Edge 19, no. 3 (2000): 276–81. http://dx.doi.org/10.1190/1.1438590.

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Saygin, Erdinc, and Brian L. N. Kennett. "Ambient seismic noise tomography of Australian continent." Tectonophysics 481, no. 1-4 (2010): 116–25. http://dx.doi.org/10.1016/j.tecto.2008.11.013.

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22

Weemstra, Cornelis, Lapo Boschi, Alexander Goertz, and Brad Artman. "Seismic attenuation from recordings of ambient noise." GEOPHYSICS 78, no. 1 (2013): Q1—Q14. http://dx.doi.org/10.1190/geo2012-0132.1.

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We applied seismic interferometry to data from an ocean-bottom survey offshore Norway and found that ambient seismic noise can be used to constrain subsurface attenuation on a reservoir scale. By crosscorrelating only a few days of recordings by broadband ocean bottom seismometers, we were able to retrieve empirical Green’s functions associated with surface waves in the frequency range between 0.2 and 0.6 Hz and acoustic waves traveling through the sea water between 1.0 and 2.5 Hz. We discovered that the decay of these surface waves cannot be explained by geometrical spreading alone and requir

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Overduin, Pier P., Christian Haberland, Trond Ryberg, et al. "Submarine permafrost depth from ambient seismic noise." Geophysical Research Letters 42, no. 18 (2015): 7581–88. http://dx.doi.org/10.1002/2015gl065409.

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24

Ermert, L. A., K. Sager, T. Nissen-Meyer, and A. Fichtner. "Multifrequency inversion of global ambient seismic sources." Geophysical Journal International 225, no. 3 (2021): 1616–23. http://dx.doi.org/10.1093/gji/ggab050.

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SUMMARY We develop and apply a method to constrain the space- and frequency-dependent location of ambient noise sources. This is based on ambient noise cross-correlation inversion using numerical wavefield simulations, which honour 3-D crustal and mantle structure, ocean loading and finite-frequency effects. In the frequency range from 3 to 20 mHz, our results constrain the global source distribution of the Earth’s hum, averaged over the Southern Hemisphere winter season of 9 yr. During Southern Hemisphere winter, the dominant sources are largely confined to the Southern Hemisphere, the most p

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Gritto, Roland, Ali Elobaid Elnaiem, Fateh Alrahman Mohamed, and Fadhil Sadooni. "Seismic detection and characterization of a man-made karst analog — A feasibility study." GEOPHYSICS 86, no. 3 (2021): WA35—WA48. http://dx.doi.org/10.1190/geo2020-0377.1.

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At the site of a water drainage shaft on the campus of Qatar University that serves as a man-made karst analog, two seismic imaging techniques were adapted to use resonant scattered waves recorded during active-source seismic surveys and during passive ambient-noise surveys. Data acquisition included two seismic transmission surveys that encompassed the shaft and a passive ambient-noise survey that extended across the top of the shaft. Seismic imaging of band-pass-filtered resonance waves correctly estimated the location and dimension of the shaft. Furthermore, the method detected the presence

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Li, Xiaolong, Fengjiao Zhang, Zhuo Xu, and Xiangbo Gong. "Separation of Body and Surface Wave Background Noise and Passive Seismic Interferometry Based on Synchrosqueezed Continuous Wavelet Transform." Applied Sciences 15, no. 7 (2025): 3917. https://doi.org/10.3390/app15073917.

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Passive seismic interferometry is a technique that reconstructs virtual seismic records using ambient noise, such as random noise or microseisms. The ambient noise in passive seismic data contains rich information, with surface waves being useful for the inversion of shallow subsurface structures, while body waves are employed for deep-layer inversion. However, due to the low signal-to-noise ratio in actual passive seismic data, different types of seismic waves mix together, making them difficult to distinguish. This issue not only affects the dispersion measurements of surface waves but also

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Olivier, Gerrit, and Florent Brenguier. "Interpreting seismic velocity changes observed with ambient seismic noise correlations." Interpretation 4, no. 3 (2016): SJ77—SJ85. http://dx.doi.org/10.1190/int-2015-0203.1.

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Recent results have shown that crosscorrelating ambient seismic noise recorded in underground mines can successfully extract the seismic Green’s function between sensors. We have revisited an earlier experiment that showed that these virtual seismic sources can be used to measure changes in seismic velocity accurately enough to monitor the short- and long-term influences of a blast in an underground mine. To use this method routinely, it is important to determine the cause of velocity variations in the absence of large dynamic stress perturbations (such as blasts). It also is important to cali

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Syaifuddin, Firman, Andri Dian Nugraha, Zulfakriza, and Shindy Rosalia. "Synthetic Modeling of Ambient Seismic Noise Tomography Data." IOP Conference Series: Earth and Environmental Science 873, no. 1 (2021): 012096. http://dx.doi.org/10.1088/1755-1315/873/1/012096.

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Abstract Ambient seismic noise tomography is one of the most widely used methods in seismological studies today, especially after a comprehensive Earth noise model was published and noise analysis was performed on the IRIS Global Seismographic Network. Furthermore, the Power Spectral Density technique was introduced to identify background seismic noise in the United States. Many studies have been carried out using the ambient seismic noise tomography method which can be broadly grouped into several groups based on the objectives and research targets, such as to determine the structure of the e

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Jiang, Chengxin, and Marine A. Denolle. "NoisePy: A New High-Performance Python Tool for Ambient-Noise Seismology." Seismological Research Letters 91, no. 3 (2020): 1853–66. http://dx.doi.org/10.1785/0220190364.

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Abstract The fast-growing interests in high spatial resolution of seismic imaging and high temporal resolution of seismic monitoring pose great challenges for fast, efficient, and stable data processing in ambient-noise seismology. This coincides with the explosion of available seismic data in the last few years. However, the current computational landscape of ambient seismic field seismology remains highly heterogeneous, with individual researchers building their own homegrown codes. Here, we present NoisePy—a new high-performance python tool designed specifically for large-scale ambient-nois

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Rincon-Yanez, Diego, Enza De Lauro, Simona Petrosino, Sabrina Senatore, and Mariarosaria Falanga. "Identifying the Fingerprint of a Volcano in the Background Seismic Noise from Machine Learning-Based Approach." Applied Sciences 12, no. 14 (2022): 6835. http://dx.doi.org/10.3390/app12146835.

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This work is devoted to the analysis of the background seismic noise acquired at the volcanoes (Campi Flegrei caldera, Ischia island, and Vesuvius) belonging to the Neapolitan volcanic district (Italy), and at the Colima volcano (Mexico). Continuous seismic acquisition is a complex mixture of volcanic transients and persistent volcanic and/or hydrothermal tremor, anthropogenic/ambient noise, oceanic loading, and meteo-marine contributions. The analysis of the background noise in a stationary volcanic phase could facilitate the identification of relevant waveforms often masked by microseisms an

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Wu, Guoli, Hefeng Dong, Ganpan Ke, and Junqiang Song. "Shear-Wave Tomography Using Ocean Ambient Noise with Interference." Remote Sensing 12, no. 18 (2020): 2969. http://dx.doi.org/10.3390/rs12182969.

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Ambient noise carries abundant subsurface structure information and attracts ever-increasing attention in the past decades. However, there are lots of interference factors in the ambient noise in the real world, making the noise difficult to be utilized in seismic interferometry. The paper performs shear-wave tomography on a very short recording of ocean ambient noise with interference. An adapted eigenvalue-based filter is adopted as a pre-processing method to deal with the strong, directional interference problem. Beamforming and the noise crosscorrelation analyses show that the filter works

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32

Galone, Luciano, Francesco Panzera, Emanuele Colica, et al. "A Seismic Monitoring Tool for Tidal-Forced Aquifer Level Changes in the Río de la Plata Coastal Plain, Argentina." Sustainability 16, no. 4 (2024): 1432. http://dx.doi.org/10.3390/su16041432.

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Ambient seismic noise has gained extensive applications in seismology and plays a pivotal role in environmental seismic studies. This study focuses on the Río de la Plata Coastal Plain, employing the horizontal-to-vertical spectral ratio (HVSR) method on ambient seismic noise records to analyze subsurface dynamics. The region’s hydrogeology is complex, featuring partially interconnected coastal aquifers. The HVSR analysis reveals two peaks, with P0 associated with the sediment-basement interface and P1 linked to a shallower stratigraphic discontinuity. Temporal analysis of P1 highlights cyclic

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Kementzetzidou, D., P. Paradisopoulou, K. Gkogkas, et al. "USE OF AMBIENT VIBRATIONS IN UNDERSTANDING LOCAL SITE EFFECTS AT BROADBAND SEISMIC STATIONS OF THE HELLENIC UNIFIED SEISMOLOGICAL NETWORK (HUSN)." Bulletin of the Geological Society of Greece 50, no. 3 (2017): 1505. http://dx.doi.org/10.12681/bgsg.11863.

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The evaluation of ambient seismic noise at the Hellenic Unified Seismic Network (HUSN) stations is investigated in this study. Ambient vibration recordings combined with the horizontal to vertical (H/V) spectral ratio technique helps in characterizing local site effects. This technique was applied at 17 sites ambient noise measurements. We selected a number of 1-hr waveform segments during day and night for summer and winter. For each site the H/V spectral ratio was calculated and the results were combined with geological and geophysical information. The goal was to show the network performanc

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Liu, Qian, Xuan Feng, Cai Liu, Minghe Zhang, You Tian, and Hesheng Hou. "Metallic mineral exploration by using ambient noise tomography in Ashele copper mine, Xinjiang, China." GEOPHYSICS 87, no. 3 (2022): B221—B231. http://dx.doi.org/10.1190/geo2020-0923.1.

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Rapid advances in the seismic exploration method have allowed its application in metallic mineral exploration. However, 2D seismic profiles are often insufficient to describe the shape and areal extent of ore-bearing rock masses away from survey lines. Although more complete, collecting 3D seismic data is expensive, time consuming, and may require considerable investment in surface access. The combination of ambient noise tomography and 2D seismic reflection exploration methods can produce acceptable results relatively quickly and at a low cost. The enormous Ashele copper deposit in northwest

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35

Zheng, Jun, Haofei Yan, and Guofeng Liu. "Static Correction of Passive-Source Seismic Reflection Exploration on Undulating Surfaces." Minerals 14, no. 10 (2024): 1010. http://dx.doi.org/10.3390/min14101010.

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Elevation static correction is an important step in seismic data processing used to eliminate distortions in events caused by surface fluctuations. There is a well-established processing sequence for active-source seismic data, with static correction applied first, followed by subsequent processing. For passive-source data, static correction can be carried out using two methods. The first method is similar to the static correction of active-source seismic data and involves performing static correction on virtual shot gathers. The second method involves directly applying static correction to am

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Xi, Chaoqiang, Ya Liu, Haibo Wu, Ling Ning, Hao Zhang, and Bo Guan. "Modified Frequency-Bessel Transform Method for Dispersion Imaging of Surface Wave from Six-Component Ambient Noise Recordings." Journal of Physics: Conference Series 2651, no. 1 (2023): 012032. http://dx.doi.org/10.1088/1742-6596/2651/1/012032.

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Abstract Surface wave analysis methods based on ambient noise have attracted considerable attention within the geophysical and civil engineering communities, particularly in light of the limitations associated with traditional seismic surveys in densely populated urban areas. Conventionally, translational seismic sensors have been employed for the observation of ambient noise. Nevertheless, recent advancements in rotational sensor technology have facilitated the direct measurement of ground motion induced by seismic waves in a rotational manner. Through the integration of these rotational sens

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Li, Jian, Dongwei Hei, Gaofeng Cui, et al. "GAN-LSTM Joint Network Applied to Seismic Array Noise Signal Recognition." Applied Sciences 11, no. 21 (2021): 9987. http://dx.doi.org/10.3390/app11219987.

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The purpose of seismic data processing in nuclear explosion monitoring is to accurately and reliably detect seismic or explosion events from complex ambient noises. Accurate detection and identification of seismic phases are of great significance to the detection and parameter estimation of seismic events. In seismic phase identification, discriminating between noise signals and real seismic signals is essential. Accurate identification of noise signals helps reduce false detections, improves the accuracy of automatic bulletins, and relieves the workload of analysts. At the same time, in seism

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Valero, Maria, Fangyu Li, Jose Clemente, and Wenzhan Song. "Distributed and Communication-Efficient Spatial Auto-Correlation Subsurface Imaging in Sensor Networks." Sensors 19, no. 11 (2019): 2427. http://dx.doi.org/10.3390/s19112427.

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A wireless seismic network can be effectively used as a tool for subsurface monitoring and imaging. By recording and analyzing ambient noise, a seismic network can image underground infrastructures and provide velocity variation information of the subsurface that can help to detect anomalies. By studying the variation in the noise cross-correlation function of the noise, it is possible to determine the subsurface seismic velocity and image underground infrastructures. Ambient noise imaging can be done in a decentralized fashion using Distributed Spatial Auto-Correlation (dSPAC). In dSPAC over

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Pacheco, D., E. D. Mercerat, F. Courboulex, L. F. Bonilla, A. Laurendeau, and A. Alvarado. "Profiling the Quito basin (Ecuador) using seismic ambient noise." Geophysical Journal International 228, no. 2 (2021): 1419–37. http://dx.doi.org/10.1093/gji/ggab408.

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SUMMARY Quito, the capital of Ecuador, with more than 2.5 M inhabitants, is exposed to a high seismic hazard due to its proximity to the Pacific subduction zone and active crustal faults, both capable of generating significant earthquakes. Furthermore, the city is located in an intermontane piggy-back basin prone to seismic wave amplification. To understand the basin’s seismic response and characterize its geological structure, 20 broad and medium frequency band seismic stations were deployed in Quito’s urban area between May 2016 and July 2018 that continuously recorded ambient seismic noise.

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Ayala-Garcia, Daniella, Andrew Curtis, and Michal Branicki. "Seismic Interferometry from Correlated Noise Sources." Remote Sensing 13, no. 14 (2021): 2703. http://dx.doi.org/10.3390/rs13142703.

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It is a well-established principle that cross-correlating seismic observations at different receiver locations can yield estimates of band-limited inter-receiver Green’s functions. This principle, known as Green’s function retrieval or seismic interferometry, is a powerful technique that can transform noise into signals which enable remote interrogation and imaging of the Earth’s subsurface. In practice it is often necessary and even desirable to rely on noise already present in the environment. Theory that underpins many applications of ambient noise interferometry assumes that the sources of

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Berezhnev, Y. M., N. N. Belovezhets, and G. D. Rukavishnikov. "Seismic shear-wave extraction from ambient seismic noise records at the Tashtagol iron using the passive interferometry method." Russian Journal of Geophysical Technologies, no. 3 (December 11, 2024): 65–73. https://doi.org/10.18303/2619-1563-2024-3-65.

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In this paper, the passive interferometry method was applied for the first time to seismic noise data recorded at the Tashtagol iron ore deposit. The passive interferometry method is based on the analysis of cross-correlation functions of seismic noise. Continuous seismic records from one day at six seismic stations formed the data set used in this analysis. We have successfully identified shear seismic waves propagating between seismic stations on the obtained cross-correlations. The results demonstrate the potential of using ambient seismic noise tomography to study mining data.

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Saadia, Benjamin, and Georgia Fotopoulos. "Characterizing Ambient Seismic Noise in an Urban Park Environment." Sensors 23, no. 5 (2023): 2446. http://dx.doi.org/10.3390/s23052446.

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In this study, a method for characterizing ambient seismic noise in an urban park using a pair of Tromino3G+ seismographs simultaneously recording high-gain velocity along two axes (north-south and east-west) is presented. The motivation for this study is to provide design parameters for seismic surveys conducted at a site prior to the installation of long-term permanent seismographs. Ambient seismic noise refers to the coherent component of the measured signal that comes from uncontrolled, or passive sources (natural and anthropogenic). Applications of interest include geotechnical studies, m

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Li, Zhengbo, Jie Zhou, Gaoxiong Wu, et al. "CC-FJpy: A Python Package for Extracting Overtone Surface-Wave Dispersion from Seismic Ambient-Noise Cross Correlation." Seismological Research Letters 92, no. 5 (2021): 3179–86. http://dx.doi.org/10.1785/0220210042.

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Abstract In the past two decades, seismic ambient-noise cross correlation (CC) has been one of the most important technologies in seismology. Usually, only the fundamental-mode surface-wave dispersion was extracted from the ambient noise. Recently, with the frequency–Bessel transform (F-J) method, overtone dispersion can also be extracted from the ambient noise and it adds significant value in inversion. This method has also been verified to be effective for array seismic records of earthquake events. In this article, we describe our algorithm and a Python package called CC-FJpy. For the F-J m

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Ritzwoller, Michael H., Fan-Chi Lin, and Weisen Shen. "Ambient noise tomography with a large seismic array." Comptes Rendus Geoscience 343, no. 8-9 (2011): 558–70. http://dx.doi.org/10.1016/j.crte.2011.03.007.

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Métivier, Ludovic, Grégory Bièvre, Romain Brossier, et al. "Elastic full-waveform inversion of seismic ambient noise." Leading Edge 44, no. 5 (2025): 373a1–373a12. https://doi.org/10.1190/tle44050373a1.1.

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Elastic full-waveform inversion (FWI) is appealing for an enhanced integration of wave physics propagation and the resulting improved characterization of the subsurface due to the reconstruction of P- and S-wave velocity models. While the high computational cost of elastic FWI can be controlled using adequate numerical methods, the increase in the nonlinearity of elastic FWI calls for dedicated strategies to design initial P- and S-wave velocity models and access low-frequency data. We believe that the recent surge in ocean-bottom sensor acquisition is an opportunity to develop such strategies

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Anderson, Richard G., and George A. McMechan. "Noise‐adaptive filtering of seismic shot records." GEOPHYSICS 53, no. 5 (1988): 638–49. http://dx.doi.org/10.1190/1.1442498.

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Ambient noise can obscure reflections on deep crustal seismic data. We use a spectral subtraction method to attenuate stationary noise. Our procedure, called noise‐adaptive filtering, is to Fourier transform the noise before the first arrivals, subtract the amplitude spectrum of the noise from the amplitude spectrum of the noisy data, and inverse Fourier transform. The phase spectrum is not corrected, but the method attenuates noise if the phase shift between the signal and noise is random. The algorithm can be implemented as a frequency filter, as a frequency‐wavenumber filter, or as two sepa

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Besedina, A. N., and Ts A. Tubanov. "Microseisms as a Tool for Geophysical Research. A Review." Вулканология и сейсмология 17, no. 2 (2023): 12–32. http://dx.doi.org/10.31857/s0203030623700116.

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Considering seismic ambient noise as a tool for geophysical research, the spatial and temporal characteristics of the noise itself are of a great interest. Characterization of energy and frequency distributions of the microseisms is an important stage of the research. The review considers the main mechanisms of generation of microseismic oscillations in a wide frequency range, including primary and secondary microseisms (0.05–0.3 Hz), low-frequency oscillations (0.2–50 mHz), high-frequency oscillations (2–60 Hz), lake microseisms (0.5–2 Hz). The paper also describes the most popular techniques

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Liner, Christopher L., Gokay Bozkurt, and V. Dale Cox. "Shooting direction and crosswell seismic data acquisition." GEOPHYSICS 61, no. 5 (1996): 1489–98. http://dx.doi.org/10.1190/1.1444074.

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Four crosswell seismic surveys were acquired in the Glenn Pool Field of northeastern Oklahoma as part of a multidisciplinary reservoir characterization project. The acquisition goal was to generate data suitable for tomographic traveltime inversion. Acquisition parameters and shooting geometry were selected by conducting a parameter test at the site. Following the parameter test, the first survey resulted in high quality data showing clear first arrivals, low ambient noise, some reflection events, and strong source‐generated tube waves. The second survey involved a different receiver well and

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Lu, Y., L. Stehly, R. Brossier, and A. Paul. "Imaging Alpine crust using ambient noise wave-equation tomography." Geophysical Journal International 222, no. 1 (2020): 69–85. http://dx.doi.org/10.1093/gji/ggaa145.

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SUMMARY We present an improved crustal Vs model and Moho depth map using ambient noise wave-equation tomography. The so-called ‘ambient noise wave-equation tomography’ is a method to invert seismic ambient noise phase dispersion data based on elastic waveform simulation, which accounts for 3-D and finite-frequency effects. We use cross-correlations of up to 4 yr of continuous vertical-component ambient seismic noise recordings from 304 high-quality broad-band stations in the Alpine region. We use model LSP_Eucrust1.0 obtained from traditional ambient noise tomography as initial model, and we i

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Sun, Lixia, Xinming Qiu, Yun Wang, and Chao Wang. "Seismic Periodic Noise Attenuation Based on Sparse Representation Using a Noise Dictionary." Applied Sciences 13, no. 5 (2023): 2835. http://dx.doi.org/10.3390/app13052835.

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Periodic noise is a well-known problem in seismic exploration, caused by power lines, pump jacks, engine operation, or other interferences. It contaminates seismic data and affects subsequent processing and interpretation. The conventional methods to attenuate periodic noise are notch filtering and some model-based methods. However, these methods either simultaneously attenuate noise and seismic events around the same frequencies, or need expensive computation time. In this work, a new method is proposed to attenuate periodic noise based on sparse representation. We use a noise dictionary to s

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