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1
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 (August 28, 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 of ambient seismic auto- and cross-correlations, which have become preeminent seismological observables, in light of nonuniform ambient seismic sources. Written in the Python language, it is accessible for both usage and further development and efficient enough to conduct ambient seismic source inversions for realistic scenarios. Here, we introduce the concept and implementation of the tool, compare its model output to cross-correlations computed with SPECFEM3D_globe, and demonstrate its capabilities on selected use cases: a comparison of observed cross-correlations of the Earth's hum to a forward model based on hum sources from oceanographic models and a synthetic noise source inversion using full waveforms and signal energy asymmetry.
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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 (June 3, 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 cities of 11 countries are assessed using the 3 month records for decades. The annual seismic noise levels present strong correlations with gross domestic product (GDP), particularly with manufacturing and industrial GDP. The seismic noise levels increase quickly with GDP in low-GDP regions but slowly in high-GDP regions. This is because high-GDP regions already have large volumes of existing noise-inducing sources and because added sources contribute weakly. The seismic noise levels increased by 14%–111% for 5–23 yr depending on the economic conditions. The correlation between ambient seismic noise level and economy growth is a global feature. The high-frequency noise level may be a proxy to present the economic condition. Economic growth affects the Earth environment in a wide range of aspects.
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Krebes, Edward S. "Seismic Ambient Noise." Journal of the Acoustical Society of America 146, no. 1 (July 2019): 532–33. http://dx.doi.org/10.1121/1.5118247.
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Hussain, Yawar, Hernan Martinez-Carvajal, Cristobal Condori, Rogério Uagoda, Martín Cárdenas-Soto, André Luís Brasil Cavalcante, Luciano Soares da Cunha, and Salvatore Martino. "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 performed analyses, two frequency (ubiquitous (2Hz) and iniquitous (>2Hz)) peaks were observed over HVSR curves. The fluctuations in the secondary peak of HVSR curves are possibly related to the saturated soil properties of landslide mass in response to seasonal meteorological conditions. Experiments with a denser observation system are required to validate such a further behavior. The proposed method can be used for the monitoring of landslides as well as civil engineering structures like dams, bridges,and building.
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Li, Jian, Dongwei Hei, Gaofeng Cui, Mengmin He, Juan Wang, Zhehan Liu, Jie Shang, Xiaoming Wang, and Weidong Wang. "GAN-LSTM Joint Network Applied to Seismic Array Noise Signal Recognition." Applied Sciences 11, no. 21 (October 25, 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 seismic exploration, the prime objective in data processing is also to enhance the signal and suppress the noises. In this study, we combined a generative adversarial network (GAN) with a long short-term memory network (LSTM) to discriminate between noise and phases in seismic waveforms recorded by the International Monitoring System (IMS) array MKAR. First, using the beamforming data of the array as the input, we obtained the signal features of seismic phases through the learning of the GAN discriminator network. Then, we input these features and trained the joint network on mixed seismic phase and noise data, and successfully classified seismic phases and noise signals with a recall of 95.28% and 97.64%, respectively. Based on this model, we established a real-time data processing method, then validated the effectiveness of this method with real 2019 data of MKAR. We also verified whether improved noise signal identification improves the quality of phase association and event detection.
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MURUGAN, S. SAKTHIVEL, and V. NATARAJAN. "IMPLEMENTATION OF THRESHOLD DETECTION TECHNIQUE FOR EXTRACTION OF COMPOSITE SIGNALS AGAINST AMBIENT NOISES IN UNDERWATER COMMUNICATION USING EMPIRICAL MODE DECOMPOSITION." Fluctuation and Noise Letters 11, no. 04 (December 2012): 1250031. http://dx.doi.org/10.1142/s0219477512500319.
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Acoustic signals transmitted in underwater for distance communication are affected by numerous factors, random events, and corrupted with ambient noise, making them nonlinear and nonstationary in nature. Ambient noises are the background acoustic noises in the sea due to natural and manmade sources like wind, rain, seismic, marine species, harbor activities, motor on the boat, ship traffic, etc. In recent years, the application of Empirical Mode Decomposition (EMD) technique to analyze nonlinear and nonstationary signals has gained importance. In this paper an EMD system is proposed with an algorithm by implementing FFT to identify and extract all the acoustic stationary signals available in the underwater channel that are corrupted due to various ambient noises over a range of 100 Hz to 10 kHz in shallow water region. Further a new threshold detection technique is also incorporated in the algorithm for detection and extraction of composite signals that are not extracted properly. The threshold is calculated using the mean and variance of the noisy signal generated by various ambient noises in the ocean. The algorithm is also validated by transmitting three reference acoustic signals. The proposed EMD approach with threshold detector algorithm identifies and extracts all the signals transmitted along with other stationary signals available in the ocean against various ambient noises.
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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 (November 13, 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–Hong Kong–Macao Greater Bay Area (GBA) using the data recorded by 138 seismometers. Our results indicate that ambient seismic noise produced by human activity in the GBA is mainly concentrated between 2 and 20 Hz. The spatial distribution of ambient seismic noise exhibits a strong correlation with population and economy. Our results show that the analysis of ambient seismic noise can reveal the spatial and temporal impacts of different factors on human activity in the GBA, such as day and night, holidays, weather changes, national policies, and the coronavirus disease 2019 (COVID-19) pandemic. Furthermore, the analysis of 12-year-long ambient seismic noise at the Hong Kong seismic station shows a close connection between long-term changes in ambient seismic noise and local social development. This study suggests that the analysis of ambient seismic noise represents a novel method to gather critical information about human activity. Seismometers, which are widely deployed worldwide, have great potential as innovative tools for sensing human activity.
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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 (July 6, 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 and ambient noise. To address this issue, our approach proposes a machine learning (ML) modeling to recognize the “fingerprint” of a specific volcano by analyzing the background seismic noise from the continuous seismic acquisition. Specifically, two ML models, namely multi-layer perceptrons and convolutional neural network were trained to recognize one volcano from another based on the acquisition noise. Experimental results demonstrate the effectiveness of the two models in recognizing the noisy background signal, with promising performance in terms of accuracy, precision, recall, and F1 score. These results suggest that persistent volcanic signals share the same source information, as well as transient events, revealing a common generation mechanism but in different regimes. Moreover, assessing the dynamic state of a volcano through its background noise and promptly identifying any anomalies, which may indicate a change in its dynamics, can be a practical tool for real-time monitoring.
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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 (September 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 before crosscorrelation to suppress surface waves further. After comparing the retrieved results with data from an active seismic exploration survey along the same lines, we use the retrieved reflection data to obtain a migrated reflection image of the subsurface.
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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 (June 11, 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 (noise) source distribution estimation and should not be used in FWI. Taking this into account, we propose a complete workflow from the raw seismic noise recording through pre-processing procedures to the inversion. We present the workflow with a field data example in Hartoušov, Czech Republic, where the seismic sources are CO2 degassing areas at Earth’s surface (i.e. a fumarole or mofette). We discuss factors in the processing and inversion that can bias the estimations, such as inaccurate velocity model, anelasticity and array sensitivity. The proposed workflow can work for multicomponent data across different scales of field data.
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Anderson, Richard G., and George A. McMechan. "Noise‐adaptive filtering of seismic shot records." GEOPHYSICS 53, no. 5 (May 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 separate frequency and wavenumber filters. Noise‐adaptive filtering is often superior to conventional frequency or frequency‐wavenumber filtering because it adapts to spatial variations in the noise without parameter testing. Noise‐adaptive filters can achieve noise rejection ratios of up to 45 dB; their dynamic range is about 25 dB. These filters work best when the input signal‐to‐noise ratio is on the order of 0 dB and there are significant differences between the frequency‐wavenumber amplitude spectra of the signal and noise. Application of the method to field data can enhance events that are not visible in the input data.
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Li, Qianqian, Yaxin Liu, Lei Xing, Xiao Han, Yuzhao Lin, Jin Zhang, and Hongmao Zhang. "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 (August 26, 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 of ambient noise. In addition, by comparing the crowed number values of ambient noise in the Chukchi Sea area with the global new low-noise model (NLNM) and new high-noise model (NHNM), a more comprehensive understanding of the patterns, distribution characteristics, and sources of ambient noise in the Arctic Chukchi Sea area is gained. The study suggests that the overlying sea ice in the Arctic Chukchi Sea area can suppress the microseismic band ambient noise, and the overall level of ambient noise in the Chukchi Sea area lies between the land seismic ambient noise level and the ambient noise level in the middle- and low-latitude sea areas. Meanwhile, an abnormal power spectrum caused by different levels of natural earthquakes is observed. This study fills the gap by using seafloor seismic instruments to investigate ambient noise in the Chukchi Sea area.
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Li, Xiaomeng, Yan Xu, Chaodi Xie, and Shanshan Sun. "Global characteristics of ambient seismic noise." Journal of Seismology 26, no. 2 (January 17, 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, respectively. Since DF microseism is dominated by Rayleigh waves, its energy attenuates very quickly when it travels through shoreline to the continent crust. Our observations give a quality factor Q of about 83 for DF energy traveling from the middle of the Atlantic to the central of Europe. We observe a lower energy level of SPDF (short period DF) than that of LPDF (long period DF) for the continent stations, however a reversed situation for the island stations. It suggests that short period DF energy decays faster than the long period one. High-frequency ambient noise is called microtremor. The microtremor for the island station with low elevation has a semidiurnal modulation in phase with ocean tide. The microtremor for the station at other locations are from the anthropogenic activities which have diurnal, weekly, and annually variations.
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Sens-Schönfelder, Christoph. "Synchronizing seismic networks with ambient noise." Geophysical Journal International 174, no. 3 (September 2008): 966–70. http://dx.doi.org/10.1111/j.1365-246x.2008.03842.x.
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Laske, Gabi. "Book Review of ‘Seismic Ambient Noise’." Geophysical Journal International 221, no. 3 (March 3, 2020): 1667–68. http://dx.doi.org/10.1093/gji/ggaa101.
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de Ridder, Sjoerd A. L., and Biondo L. Biondi. "Ambient seismic noise tomography at Ekofisk." GEOPHYSICS 80, no. 6 (November 2015): B167—B176. http://dx.doi.org/10.1190/geo2014-0558.1.
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Edme, Pascal, and David F. Halliday. "Near-surface imaging using ambient-noise body waves." Interpretation 4, no. 3 (August 1, 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 data and real data recorded during a small point-receiver land seismic survey.
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Maciel, Susanne Taina Ramalho, Marcelo Peres Rocha, and Martin Schimmel. "Urban seismic monitoring in Brasília, Brazil." PLOS ONE 16, no. 8 (August 5, 2021): e0253610. http://dx.doi.org/10.1371/journal.pone.0253610.
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Urban seismology has gained scientific interest with the development of seismic ambient noise monitoring techniques and also for being a useful tool to connect society with the Earth sciences. The interpretation of the sources of seismic records generated by sporting events, traffic, or huge agglomerations arouses the population’s curiosity and opens up a range of possibilities for new applications of seismology, especially in the area of urban monitoring. In this contribution, we present the analysis of seismic records from a station in the city of Brasilia during unusual episodes of silencing and noisy periods. Usually, cultural noise is observed in high-fequency bands. We showed in our analysis that cultural noise can also be observed in the low-frequency band, when high-frequency signal is attenuated. As examples of noisy periods, we have that of the Soccer World Cup in Brazil in 2014, where changes in noise are related to celebrations of goals and the party held by FIFA in the city, and the political manifestations in the period of the Impeachment trial in 2016, which reached the concentration of about 300,000 protesters. The two most characteristic periods of seismic silence have been the quarantine due to the COVID-19 pandemic in 2020, and the trucker strike that occurred across the country in 2018, both drastically reducing the movement of people in the city.
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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 (December 15, 2015): 307–12. http://dx.doi.org/10.1785/0120150031.
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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 (November 1, 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, dense power grids, and irregular buildings. These features make active source reflection seismic exploration difficult for wide application due to its drawbacks of high cost and the necessary use of explosives. In contrast, ambient noise seismic surveys have the advantages of continuous ambient noise sources, low cost, and fast deployment. These advantages are good for urban exploration. Although ambient noise seismic surveys have a lower resolution than active seismic surveys, their ultrahigh-density layout can improve the resolution. We have conducted two active source seismic lines and two ambient noise seismic lines near the Huangzhuang-Gaoliying fault (HGF) in a northern suburb of Beijing. The autocorrelation and crosscorrelation results are consistent with the active source reflection seismic results. They revealed the location of the HGF, which is composed of a set of steep dip faults. The study of the combination of the two techniques demonstrates that ambient noise seismic surveys are effective for urban active fault detection, especially for larger scale area surveys, and active source reflection seismic surveys can be used for detailed surveys. The combination of the two techniques has a higher efficiency and lower costs and can be widely used in blind urban active fault surveys.
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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 (March 28, 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 spectral density (PSD) is analyzed. In addition, plotted graphs show the relationship between the occurrence of extreme weather events, such as hurricanes and cold fronts through Cuban eastern and western regions, respectively, and the increase of noise level, specifically for marine microseisms period band. Finally, the influence of instrumental variations in noise level of seismic stations is characterized.
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Murugan, S. Sakthivel, V. Natarajan, and R. Rajesh Kumar. "Noise Model Analysis and Estimation of Effect due to Wind Driven Ambient Noise in Shallow Water." International Journal of Oceanography 2011 (December 26, 2011): 1–4. http://dx.doi.org/10.1155/2011/950838.
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Signal transmission in ocean using water as a channel is a challenging process due to attenuation, spreading, reverberation, absorption, and so forth, apart from the contribution of acoustic signals due to ambient noises. Ambient noises in sea are of two types: manmade (shipping, aircraft over the sea, motor on boat, etc.) and natural (rain, wind, seismic, etc.), apart from marine mammals and phytoplanktons. Since wind exists in all places and at all time: its effect plays a major role. Hence, in this paper, we concentrate on estimating the effects of wind. Seven sets of data with various wind speeds ranging from 2.11 m/s to 6.57 m/s were used. The analysis is performed for frequencies ranging from 100 Hz to 8 kHz. It is found that a linear relationship between noise spectrum and wind speed exists for the entire frequency range. Further, we developed a noise model for analyzing the noise level. The results of the empirical data are found to fit with results obtained with the aid of noise model.
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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 (March 19, 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 and the location of a horizontal drainage pipe and gravel bed connecting neighboring water shafts. Ambient-noise data were analyzed by computing amplitude values of the seismic records in spectral passbands. The results indicated an amplification of seismic amplitudes above the shaft for low-frequency passbands and a sharp decrease in amplitude values for high-frequency passbands. The high- and low-amplitude values displayed as a function of the receiver position allowed for accurate detection and location of the shaft in space. Ground truthing of the imaging results confirmed the accuracy of the seismic techniques, whereas numerical modeling supported the interpretation of the ambient-noise data. The techniques used do not require knowledge of the seismic velocities in the subsurface, but they depend on a priori information about the approximate location of the target.
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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 (October 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 earth’s crust and the upper mantle, to know the thickness of the sedimentary basins, to know the tectonic settings and geological structures, to know volcanic systems and geothermal systems, knowing near-surface geological features and as a monitoring effort the Ambient Noise Tomography method carried out by repeated measurements or time lapse. In this study, we investigate the characteristics of the ambient noise seismic tomography method, both its advantages and limitations of the method by utilizing synthetic data modeling using a simple geological model. Synthetic data is generated based on 1D dispersion curve forward modelling and the forward modeling of surface waves travel time for each period, which is then convoluted with the wavelets of each periods, then doing reverse correlation using a reference signal to produce synthetic recording data. We found that the estimate target depth and vertical resolution depend on the recorded data periods and the synthetic data modeling can be used as a basis in determining the acquisition design.
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Ermert, L. A., K. Sager, T. Nissen-Meyer, and A. Fichtner. "Multifrequency inversion of global ambient seismic sources." Geophysical Journal International 225, no. 3 (February 6, 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 prominent exception being the Izu-Bonin-Mariana arc, which is the most active source region between 12 and 20 mHz. Generally, strong hum sources seem to be associated with either coastlines or bathymetric highs. In contrast, deep ocean basins are devoid of hum sources. While being based on the relatively small number of STS-1 broad-band stations that have been recording continuously from 2004 to 2013, our results demonstrate the practical feasibility of a frequency-dependent noise source inversion that accounts for the complexities of 3-D wave propagation. It may thereby improve full-waveform ambient noise inversions and our understanding of the physics of noise generation.
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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 (December 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 interferometry. At the same time, body wave exploration has larger exploration depth and higher resolution. In this paper, we propose an ambient noise detection technology of mixed active sources, namely, imposing artificial seismic sources in the continuous ambient noise data acquisition process. We refer to the ambient noise of mixed active sources as "mixed ambient noise". It is found that the virtual refraction wave obtained by the ambient noise detection method of mixed active sources has high signal-to-noise ratio, strong anti-interference ability, and can obtain the real velocity information of the deeper subsurface medium, but cannot reflect the accurate time information. Supplementing the active source signal in the far field can obtain virtual refractions with higher signal-to-noise ratio, while effectively reducing the mixing phenomenon of surface wave and surface interference waves in the virtual common-shot record.
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Takagi, Ryota, Genti Toyokuni, and Naotaka Chikasada. "Ambient noise correlation analysis of S-net records: extracting surface wave signals below instrument noise levels." Geophysical Journal International 224, no. 3 (November 17, 2020): 1640–57. http://dx.doi.org/10.1093/gji/ggaa548.
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SUMMARY We applied ambient noise cross-correlation analysis to the cabled ocean bottom seismic network offshore northeast Japan (Seafloor observation network for earthquakes and tsunamis along the Japan Trench: S-net) to extract surface waves propagating in the ocean area of the forearc region. We found two types of peculiar pulses in the cross-correlation functions (CCFs) of ambient seismic noise records: periodic pulses mainly every minute and sharp pulses around the lag time zero. These pulses strongly contaminate the surface wave signals in the CCFs at frequencies below ∼0.1 Hz. The periodic pulses originate from periodic instrument noises, while the zero-lag pulses originate from random instrument noises which are coherent within station pairs. By developing solutions to remove the periodic and zero-lag pulses based on the characteristics of the pulses, we succeeded in extracting Rayleigh and Love wave signals from the S-net records at 0.03–0.3 Hz, while the surface wave signals at 0.03–0.1 Hz were not visible without the application of these solutions. These solutions widen the frequency range of analysis, and may be applicable to other seismic networks, particularly to recent dense but non-broad-band networks. We identified the fundamental and first higher modes of Rayleigh waves and the fundamental mode of the Love wave. The extracted surface wave signals can constrain the shear wave velocity structure from the sediment to seismogenic zone around the megathrust plate boundary in the forearc region.
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Vassallo, M., G. Festa, and A. Bobbio. "Seismic Ambient Noise Analysis in Southern Italy." Bulletin of the Seismological Society of America 102, no. 2 (March 29, 2012): 574–86. http://dx.doi.org/10.1785/0120110018.
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de Ridder, S. A. L., and J. R. Maddison. "Full wavefield inversion of ambient seismic noise." Geophysical Journal International 215, no. 2 (August 7, 2018): 1215–30. http://dx.doi.org/10.1093/gji/ggy328.
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Stephen, Ralph A. "Ambient seismic noise below the deep seafloor." Leading Edge 19, no. 3 (March 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 (January 2010): 116–25. http://dx.doi.org/10.1016/j.tecto.2008.11.013.
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Weemstra, Cornelis, Lapo Boschi, Alexander Goertz, and Brad Artman. "Seismic attenuation from recordings of ambient noise." GEOPHYSICS 78, no. 1 (January 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 required an additional loss of energy with distance. We quantified this observed attenuation in the frequency domain using a modified Bessel function to describe the cross-spectrum in a stationary field. We averaged cross-spectra of equally spaced station couples and sorted these azimuthally averaged cross-spectra with distance. We then obtained frequency-dependent estimates of attenuation by minimizing the misfit of the real parts to a damped Bessel function. The resulting quality factors as function of frequency are indicative of the depth variation of attenuation and correlated with the geology in the survey area.
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Overduin, Pier P., Christian Haberland, Trond Ryberg, Fabian Kneier, Tim Jacobi, Mikhail N. Grigoriev, and Matthias Ohrnberger. "Submarine permafrost depth from ambient seismic noise." Geophysical Research Letters 42, no. 18 (September 16, 2015): 7581–88. http://dx.doi.org/10.1002/2015gl065409.
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Olivier, Gerrit, and Florent Brenguier. "Interpreting seismic velocity changes observed with ambient seismic noise correlations." Interpretation 4, no. 3 (August 1, 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 calibrate the seismic velocity changes in terms of known stress changes so the effect of mining activities can be quantified in units that can be used by geotechnical engineers. To this end, we used coda-wave interferometry to measure relative velocity variations during times where no significant blasting or microseismic activity occurred and compared it to atmospheric air pressure changes, temperature variations, and modeled tidal strain. The results indicate that atmospheric air pressure changes have a measurable influence on the long-term seismic velocity variations at depth in the absence of large dynamic stress perturbations. This influence enabled us to determine the sensitivity of the relative velocity changes to stress, where a value of [Formula: see text] was found. This calibration essentially enables us to turn each sensor pair in an underground mine into a stress meter, paving the way for geotechnical engineers to use ambient seismic noise correlations to monitor the evolution of stress and to assess seismic hazard in conjunction with conventional microseismic methods.
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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 (October 11, 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. We first compute horizontal-to-vertical spectral ratios to determine the resonant frequency distribution in the entire basin. Secondly, we cross-correlate seismic stations operating simultaneously to retrieve interstations surface-wave Green’s functions in the frequency range of 0.1–2 Hz. We find that Love waves travelling in the basin’s longitudinal direction (NNE–SSW) show much clearer correlograms than those from Rayleigh waves. We then compute Love wave phase-velocity dispersion curves and invert them in conjunction with the HVSR curves to obtain shear-wave velocity profiles throughout the city. The inversions highlight a clear difference in the basin’s structure between its northern and southern parts. In the centre and northern areas, the estimated basin depth and mean shear-wave velocity are about 200 m and 1800 ms−1, respectively, showing resonance frequency values between 0.6 and 0.7 Hz. On the contrary, the basement’s depth and shear-wave velocity in the southern part are about 900 m and 2500 ms−1, having a low resonance frequency value of around 0.3 Hz. This difference in structure between the centre-north and the south of the basin explains the spatial distribution of low-frequency seismic amplifications observed during the Mw 7.8 Pedernales earthquake in April 2016 in Quito.
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Saadia, Benjamin, and Georgia Fotopoulos. "Characterizing Ambient Seismic Noise in an Urban Park Environment." Sensors 23, no. 5 (February 22, 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, modeling the seismic response of infrastructure, surface monitoring, noise mitigation, and urban activity monitoring, which may exploit the use of well-distributed seismograph stations within an area of interest, recording on a days-to-years scale. An ideal well-distributed array of seismographs may not be feasible for all sites and therefore, it is important to identify means for characterizing the ambient seismic noise in urban environments and limitations imposed with a reduced spatial distribution of stations, herein two stations. The developed workflow involves a continuous wavelet transform, peak detection, and event characterization. Events are classified by amplitude, frequency, occurrence time, source azimuth relative to the seismograph, duration, and bandwidth. Depending on the applications, results can guide seismograph selection (sampling frequency and sensitivity) and seismograph placement within the area of interest.
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Galone, Luciano, Francesco Panzera, Emanuele Colica, Enrique Fucks, Eleonora Carol, Francisco Cellone, Lluís Rivero, Matthew R. Agius, and Sebastiano D’Amico. "A Seismic Monitoring Tool for Tidal-Forced Aquifer Level Changes in the Río de la Plata Coastal Plain, Argentina." Sustainability 16, no. 4 (February 8, 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 cyclical patterns correlated with estuarine levels, suggesting a relationship between variations in seismic velocities and tidal dynamics. Comparisons with aquifer data support the hypothesis that tidal variations influence subsurface mechanical properties, impacting the HVSR function. The study hints at the potential of ambient seismic noise analysis as a non-invasive and cost-effective method for studying coastal aquifers and understanding groundwater dynamics. Ongoing research aims to further explore these relationships for enhanced groundwater resource management.
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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 (April 1, 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-noise seismology. NoisePy provides most of the processing techniques for the ambient field data and the correlations found in the literature, along with parallel download routines, dispersion analysis, and monitoring functions. NoisePy takes advantage of adaptable seismic data format, a parallel input and output enabled HDF5 data format designed for seismology, for a structured organization of the cross-correlation data. The parallel computing of NoisePy is performed using Message Passing Interface and shows a strong scaling with the number of cores, which is well suited for embarrassingly parallel problems. NoisePy also uses a small memory overhead and stable memory usage. Benchmark comparisons with the latest version of MSNoise demonstrate about four-time improvement in compute time of the cross correlations, which is the slowest step of ambient-noise seismology. NoisePy is suitable for ambient-noise seismology of various data sizes, and it has been tested successfully at handling data of size ranging from a few GBs to several tens of TBs.
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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 (March 14, 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 China is a typical deposit formed by volcanic eruption. It is rich in resources and possesses good prospecting potential in its deeper and peripheral areas. We performed ambient noise tomography to investigate a near-surface 3D S-wave velocity ([Formula: see text]) structure above a depth of 0.7 km in the Ashele mining area (approximately 8 × 12 km) using 25 days of continuous ambient noise data. From the combined interpretation of the 3D [Formula: see text] structure and the existing 2D seismic reflection profile, we infer that there may be ore-bearing rock masses in the western and northern sides of the research area. We report the discovery of an ancient volcano at a depth of 500 m on the western side of this region. The banded velocity anomalies and the existence of the ancient volcano signify the formation process of a bimodal volcanic rock association. It has been proven that the combination of ambient noise tomography and 2D seismic reflection exploration methods can produce important results in metallic mineral exploration. Therefore, ambient noise tomography can be used as an economical, convenient, and efficient method for future explorations, complementing the 2D seismic reflection exploration method.
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Kementzetzidou, D., P. Paradisopoulou, K. Gkogkas, E. Arampatzi, E. Kyriakidou, E. Melissanidou, and N. Theodoulidis. "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 (July 27, 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 performance as far as the station quality and noise level at each site concerns in order to provide possible structural improvements, seismic station relocations or to detecting operational problems.
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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 (September 11, 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 well on the noise recorded by the array. Directional energy is significantly suppressed and the background diffuse component of the noise is relatively enhanced. The shear-wave tomography shows a 4-layer subsurface structure of the area covered by the array, with relatively homogeneous distribution of the shear-wave velocity values in the top three layers and a complicated structure in the bottom layer. Moreover, 3 high-velocity zones can be recognized in the bottom layer. The result is compared with several other tomography results using different methods and data. It demonstrates that, although the ambient noise used in this paper is very short and severely contaminated, a reasonable tomography result can be obtained by applying the adapted eigenvalue-based filter. Since it is the first application of the adapted eigenvalue-based filter in seismic tomography using ambient noise, the paper proves the effectiveness of this technique and shows the potential of the technique in ambient noise processing and passive seismic interferometry.
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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 (December 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 sensors with traditional inertial seismometers, a novel six-component seismic sensor has been developed. This innovative sensor enables the local observation of six degrees of freedom pertaining to ground motion, encompassing three orthogonal components of translational motion and three orthogonal components of rotational motion. In order to demonstrate the seismological significance of rotational ground-motion data, we applied the modified frequency-Bessel transform method (MFJ) to six-component ambient noise recordings for surface wave analysis. To underscore the practical utility of the MFJ method, a real-world case study is presented, illustrating its effectiveness in quantifying Rayleigh and Love wave dispersion from six-component ambient noise recordings.
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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 (May 28, 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 sensor networks, the cross-correlation is the most intensive communication process since nodes need to communicate their data with neighbor nodes. In this paper, a new communication-reduced method for cross-correlation is presented to meet bandwidth and cost of communication constraints in networks while ambient noise imaging is performed using dSPAC method. By applying the proposed communication-reduced method, we show that energy and computational cost of the nodes is also preserved.
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Ayala-Garcia, Daniella, Andrew Curtis, and Michal Branicki. "Seismic Interferometry from Correlated Noise Sources." Remote Sensing 13, no. 14 (July 9, 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 noise are uncorrelated in time. However, many real-world noise sources such as trains, highway traffic and ocean waves are inherently correlated in space and time, in direct contradiction to the these theoretical foundations. Applying standard interferometric techniques to recordings from correlated energy sources makes the Green’s function liable to estimation errors that so far have not been fully accounted for theoretically nor in practice. We show that these errors are significant for common noise sources, always perturbing or entirely obscuring the phase one wishes to retrieve. Our analysis explains why stacking may reduce the phase errors, but also shows that in commonly encountered circumstances stacking will not remediate the problem. This analytical insight allowed us to develop a novel workflow that significantly mitigates effects arising from the use of correlated noise sources. Our methodology can be used in conjunction with already existing approaches, and improves results from both correlated and uncorrelated ambient noise. Hence, we expect it to be widely applicable in ambient noise studies.
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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 (February 22, 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 sparsely represent periodic noise. The noise dictionary is constructed based on ambient noise. An advantage of our method is that it can automatically suppress monochromatic periodic noise, multitoned periodic noise and even periodic noise with complex waveforms without pre-known noise frequencies. In addition, the method does not result in any notches in the spectrum. Synthetic and field examples demonstrate that our method can effectively subtract periodic noise from raw seismic data without damaging the useful seismic signal.
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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 (March 1, 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 used for processing and analyzing a continuous data of seismic ambient noise; a wide range of geophysical problems was demonstrated, which use the results of seismic monitoring.
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Corciulo, Margherita, Philippe Roux, Michel Campillo, and Dominique Dubucq. "Instantaneous phase variation for seismic velocity monitoring from ambient noise at the exploration scale." GEOPHYSICS 77, no. 4 (July 1, 2012): Q37—Q44. http://dx.doi.org/10.1190/geo2011-0363.1.
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Recent studies in geophysics have investigated the use of seismic-noise correlations to measure weak-velocity variations from seismic-noise recordings. However, classically, the existing algorithms used to monitor medium velocities need extensive efforts in terms of computation time. This implies that these techniques are not appropriate at smaller scales in an exploration context when continuous data sets on dense arrays of sensors have to be analyzed. We applied a faster technique that allows the monitoring of small velocity changes from the instantaneous phase measurement of the seismic-noise crosscorrelation functions. We performed comparisons with existing algorithms using synthetic signals. The results we have obtained for a real data set show that the statistical distribution of the velocity-change estimates provides reliable measurements, despite the low signal-to-noise ratio obtained from the noise-correlation process.
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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 (September 2011): 558–70. http://dx.doi.org/10.1016/j.crte.2011.03.007.
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Li, Zhengbo, Jie Zhou, Gaoxiong Wu, Jiannan Wang, Gongheng Zhang, Sheng Dong, Lei Pan, 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 (June 9, 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 method, we use the Nvidia’s graphics processing unit to accelerate the computation, which can achieve a 100-fold computational efficiency. We have encapsulated our experiences and technologies into CC-FJpy and tested the CC-FJpy by ambient-noise and earthquake data to ensure its speed and ease of use. Our open-source package CC-FJpy can benefit the development of surface-wave studies using ambient noise and make it easier to start with high-mode surface waves.
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Ścisło, Łukasz, Łukasz Łacny, and Michael Guinchard. "COVID-19 lockdown impact on CERN seismic station ambient noise levels." Open Engineering 11, no. 1 (January 1, 2021): 1233–40. http://dx.doi.org/10.1515/eng-2021-0124.
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Abstract Seismic measuring stations do not only record seismic waves. They also pick up tremors caused by other factors: these are known as seismic background noise. In normal conditions, this environmental background is steady over a long time. This article presents the influence of high reduction of human activity due to COVID-19 initial lockdown on ground vibration in the Large Hadron Collider tunnel at the European Organization for Nuclear Research.