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Small magnitude earthquake in Malaysia not recorded in any earthquake catalogue. a) From top to bottom: Array spectrogram; waveform coherence function (0.5-3 Hz) ; Summed STA/LTA function (0.5-3 Hz); Absolute amplitude waveforms (filtered 2 -8 Hz) at all stations, ordered by latitude. b) Best-fitting event location (star) from grid search of picked P and S phases. Stations used for picking are plotted as triangles. There is one regional station that recorded the event (MS.KOM).
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Detection of seismic events at or below the noise level is enabled by the use of dense arrays of receivers and corresponding advances in data analysis methods. It is not only important to detect tectonic events, but also events from man-made, non-earthquake sources and events that originate from coupling between the solid Earth and the atmosphere....
Citations
... Because of that, the ratio between P and S wave energies can be used as a discriminator. The difference between body waves are used by using their amplitudes (Horasan et al., 2009;O'Rourke et al., 2016;Tibi et al., 2018), power spectrum (Bennett & Murphy, 1986;Kim et al., 1993;Arrowsmith et al., 2006;Yavuz et al., 2019;Lythgoe et al., 2021), and coda wave decay (Hartse et al., 1995). ...
Separation of seismic sources of seismic events such as earthquakes and quarry blasts is a complex task and, in most cases, require manual inspection. In this study, artificial neural network models are developed to automatically identify the events that occurred in North-East Italy, where earthquakes and quarry blasts may share the same area. Due to the proximity of the locations of the active fault lines and mining sites, many blasts are registered as earthquakes that can contaminate earthquake catalogues. To be able to differentiate various sources of seismic events 11,821 seismic records from 1463 earthquakes detected by various seismic networks and 9822 seismic records of 727 blasts manually labelled by the Slovenian Environment Agency are used. Three-component seismic records with 90 s length and their frequency contents are used as an input. Ten different models are created by changing various features of the neural networks. Regardless of the features of the created models, results show that accuracy rates are always around 99 %. The performance of our models is compared with a previous study that also used artificial neural networks. It is found that our models show significantly better performance with respect to the models developed by the previous study which performs badly due to differences in the data. Our models perform slightly better than the new model created by using our dataset, but with the previous study’s architecture. Developed model can be useful for the discrimination of the earthquakes from quarry blasts in North-East Italy, which may help us to monitor seismic events in the region.
... While classical gravimeters excel in survey applications, they tend to drift over time, a limitation ameliorated by the stability of atomic gravimeters, albeit at the cost of increased bulk which can be cumbersome for surveys. The measurements from the geophysical survey indicate the existence of a subterranean anomaly beneath the NTU geothermal site in Singapore, which is hypothesized to be a geothermal reservoir which resulted from the presence of a fault zone structure 50,[56][57][58][59] . After performing necessary corrections, the median uncertainty in the relative data was 6.4µGal. ...
Gravimetry is a versatile metrological approach in geophysics to accurately map subterranean mass and density anomalies. There is a broad diversification regarding the working principle of gravimeters, wherein atomic gravimeters are one of the most technologically progressive class of gravimeters which can monitor gravity at an absolute scale with a high-repetition without exhibiting drift. Despite the apparent utility for geophysical surveys, atomic gravimeters are (currently) laboratory-bound devices due to the vexatious task of transportation. Here, we demonstrated the utility of an atomic gravimeter on-site during a gravity survey, where the issue of immobility was circumvented with a relative spring gravimeter. The atomic gravimeter served as a means to map the relative data from the spring gravimeter to an absolute measurement with an effective precision of 7.7μ\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\upmu }$$\end{document}Gal. Absolute measurements provide a robust and feasible method to define and control gravity data taken at different sites, or a later date, which is critical to analyze underground geological units, in particular when it is combined with other geophysical approaches.
... We compute spectrograms to look at noise variations over short time windows. Spectrograms display power at different frequencies over time and are useful to identify signals from different sources [e.g., Lythgoe et al. (2021)]. Spectrograms are computed by calculating the short-term Fourier transform for overlapping time windows. ...
This study analyses the ambient noise field recorded by the seismic network, TREMBLE, in Bangladesh, operational since late 2016. Horizontal-vertical spectral ratios confirm the placement of stations on sediment, many situated on thick sedimentary columns, consistent with local geology. Noise across the broadband spectrum is systematically examined. A high amplitude local microseism (0.4–0.8 Hz) is recorded, originating near the coast and modulated by local tides. The secondary microseism (0.15–0.35 Hz) correlates strongly with wave height in the Bay of Bengal and varies with seasons, with greater power and higher horizontal amplitude in the monsoon season when the wave height is highest. The microseism increases in amplitude and decreases in frequency as a tropical depression moves inland. The primary microseism (∼0.07–0.08 Hz) exhibits no seasonal changes in power but display strong horizontal energy which changes with seasons. Low frequency (0.02–0.04 Hz) noise on the horizontal components has a 24-h periodicity, due to instrument tilt caused by atmospheric pressure changes. A station located next to the major Karnaphuli River shows elevated energy at ∼5 Hz correlated to periods of high rainfall. Anthropogenic noise (∼4–14 Hz) is station-dependent, demonstrating changing patterns in human activity, such as during Ramadan, national holidays and the COVID pandemic. Our work holds implications for seismic deployments, earthquake, and imaging studies, while providing insights into the interaction between the atmosphere, ocean, and solid Earth.
... Urban seismology is a specialized field that extends traditional seismological methods to economically developed urban areas. Originally, seismometers were strategically installed within cities to monitor earthquakes and characterize urban underground structures, thereby improving the assessment of seismic hazard and seismic risk management in densely populated areas Lythgoe et al., 2021;Wang et al., 2021). With the development of seismic ambient noise monitoring technology in the recent decades, the interpretation of various noise signals has gained scientific interest in detecting anthropogenic activities in the recent years (Groos and Ritter, 2009;Diaz et al., 2020). ...
Urban seismology has recently emerged as a vibrant scientific field, driven by the growing interest in seismic signals generated by major public events, sports gatherings, and transportation services. However, deploying dense traditional seismometers in economically active, densely populated urban areas with heavy traffic poses significant challenges. In this study, we conducted a field experiment utilizing distributed acoustic sensing (DAS) technology during a fireworks display in Guangzhou on 5 February 2023. About 572 m of optical fiber was turned into 286 seismic sensors and deployed on LingShan Island to monitor various vibration signals generated during the fireworks show. Our analysis revealed substantial correlations between crowd motions during different phases of the event and ambient noise features recorded by DAS. Moreover, the cross-correlation functions of the ambient noise with its dispersion characteristics pointed to near-field pedestrian activity as the primary noise source. Real-time heat maps of human crowd motions were reconstructed from DAS recording, offering significant insights into the variations of activity intensity across different locations. Discerning fireworks events on the DAS array is more effective than on a scattered seismometer array, because it is easier to ensure that the same event is picked for all the sites in the DAS dense linear configuration. The DAS data inspection allowed us to pick up a total of 549 firecracker explosions in comparison to the seismometer data that only allowed us to detect 116 firecracker events. The heights of fireworks were located by the grid-search method and predominantly distributed at 75–300 m, closely aligning with actual fireworks explosion locations. Our findings underscore that the DAS technology can monitor crowd motion and detect vibration signals in the air, bridging the gap between fundamental earth science research and human social activities.
... Results -The results of our geophysical gravity survey are displayed in Fig. (4b), presented as a Bouguer gravity anomaly, indicates a sharp dip of approximately 250µGal in the middle of the gravity profile. This result suggests the presence of a negative subterranean density anomaly, which could be accredited to a fault zone structure [48,[54][55][56][57]: a discontinuity in underground rock mass, which can act as a path way for fluid to travel from the underground geothermal reservoir to the hot spring at the surface. Geothermal reservoirs are a promising source of renewable energy for Singapore; supplying the means for an ecological and sustainable energy source [54,58], which could potentially reduce the net carbon emissions of the country. ...
... The measurements from the geophysical survey indicate the existence of a subterranean anomaly beneath the NTU geothermal site in Singapore, which is hypothesized to be a geothermal reservoir which resulted from the presence of a fault zone structure [48,[54][55][56][57]. After performing necessary corrections, the median uncertainty in the relative data was 6.4µGal. ...
... Fully-exploiting these technologies within an inversion context will doubtless motivate a new generation of analysis techniques (e.g. Lythgoe et al., 2021;Muir & Zhang, 2021), and ongoing innovation in the field of geophysical inversion. ...
In this chapter, we survey some recent developments in the field of geophysical inversion. We aim to provide an accessible general introduction to the breadth of current research, rather than focussing in depth on particular topics. We hope to give the reader an appreciation for the similarities and connections between different approaches, and their relative strengths and weaknesses.
... In general, seismic arrays composed of sensitive seismometers are installed worldwide to monitor earthquakes at regional or teleseismic distances Thomas, 2002, 2009;Schweitzer et al., 2012). Seismic array processing is commonly used to detect weak seismic signals or nuclear explosions (Douglas, 2002;Hao and Li, 2020;Lythgoe et al., 2021). Array processing enables the identification of the phase type and signal direction by estimating the back azimuth and slowness of seismic waves. ...
Earthquake early warning (EEW) systems systematically monitor ground motion and provide alerts prior to damaging shaking. However, these systems present certain challenges, which include avoiding alerts caused by false triggers or delayed alerts for earthquakes from outside the seismic network. Here, we show that an array processing approach, which is capable of identifying the propagation direction and type of seismic phase, can overcome these challenges. In this study, a new automatic array processing approach was implemented using a single mini array to determine the back azimuth and slowness of the phases for local events. Seismograms of local events with ML 2.0–4.6 that occurred in the Korean Peninsula were analyzed using three array processing methods: beam packing, frequency–wavenumber, and plane-wave fitting. In addition, a combined P-wave picking procedure was introduced, and its performance was evaluated. We developed the criteria associated with slowness range and consistency of back azimuths to determine a stable back azimuth from the three array processing methods, estimating the back azimuth of the seismic phase with more accuracy than any single method. It is expected that seismic mini arrays and the developed automatic array processing approach can be used for network EEW systems to discriminate alarms caused by false triggers. In addition, the developed approach can be used for rapid onsite and front-detection warnings using the array inside or on the outskirts of a network when combined with other estimations, such as an epicentral distance or another back azimuth.
... Research by Partridge on a three-layer neural network found that the influence of the training set on generalization capability is greater than that of neural number (Partridge 1996). Many researchers have combined principal component analysis (PCA), clustering analysis, and other methods with machine learning to optimize the training set to improve the generalization capability of the network (Basharat et al. 2016;Li et al. 2020;Lythgoe et al. 2021). Azar et al. (2021) used adaptive neuro-fuzzy inference system optimized by Harris hawk optimization to increase the performance of SVM model. ...
Rapid spatial evaluation of seismic disaster after earthquake occurrence is required in disaster emergency rescue management, because of its importance in decreasing casualties and property losses. Among many categories of seismic disaster, evaluation of earthquake-affected population is of great significance to clarify the severity of earthquake disaster. For simple classic regression model, it is difficult to describe the strong nonlinear relationship between multiple influencing factors and earthquake disasters. In present study, an optimized BP neural network model considering spatial characteristic of influencing factors is proposed to evaluate the population distribution affected by earthquake. The correlation between earthquake-affected population and influencing factors is analysed using data of 2013 Ms7.0 Lushan earthquake. Ten influencing factors including elevation, slope angle, population density, per capita GDP, distance to fault, distance to river, NDVI, PGA, PGV, and distance to the epicentre, were classified into environmental and seismic factors. Correlation analysis revealed that per capita GDP and PGA factor had a stronger correlation with the earthquake-affected population. The earthquake-affected population was evaluated using a BP neural network by optimizing training samples considering spatial characteristics of per capita GDP and PGA factors. Different numbers of sample points, instead of a random distribution of sample points, were generated in areas with different value intervals of the influencing factors. The optimized samples improved the convergence speed and generalization capability of neuron network compared to random samples. The trained network was applied to the 2017 Ms7.0 Jiuzhaigou earthquake to verify its prediction accuracy. The MAE of the estimated earthquake-affected populations of different counties under Jiuzhaigou earthquake were 1.276 people/km² using network model from optimized samples, smaller than the results of network model from random samples and linear regression model. The results indicate that BP neural network, which considers correlation characteristics of factors, has capability to evaluate spatial earthquake disaster.
... Fully-exploiting these technologies within an inversion context will doubtless motivate a new generation of analysis techniques (e.g. Lythgoe et al., 2021;Muir & Zhang, 2021), and ongoing innovation in the field of geophysical inversion. ...
Available here: https://arxiv.org/abs/2110.06017
Investigating lightning is of key significance in understanding the lightning mechanism and mitigating lightning hazards. We reported an experiment of investigating lightning through three‐dimensional (3D) thunder locating using a Distributed Acoustic Sensing (DAS) array in Hefei, China. In this experiment, we recast a 7.7 km long urban telecom optical fiber cable as 3,850 sensors using the DAS technique. From dense DAS recording, we manually identified 101 thunder events during six positive cloud‐to‐ground (CG) lightning flashes within 20 min. The DAS recorded thunder signals are dominated by direct acoustic waves rather than air‐ground coupled surface waves. The thunder events were then located using the arrival times of thunder signals. The locations and amplitudes of thunder events are generally consistent with those from the conventional lightning detection data set and broadband magnetic field. There is likely a correlation between the maximum strength of thunder events and the highest peak current for individual CG flashes. Moreover, the comparison with weather radar observations indicates that lightning usually originated from areas of high reflectivity (e.g., ≥50dBz) with diffusely distributed (from ground surface to ∼5 km altitude) thunder events and extended in a narrow altitude range of 3–5 km to areas with low radar reflectivity.
