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We propose a method for capturing the near-surface elastic wave velocity variation using microtremors. The proposed method does not directly estimate the velocity of the medium; instead, it measures the spatial velocity change. We apply the stretching method, which is often used to detect the time variation of shear wave velocity based on the monitoring of seismic ambient noise, to microtremor recordings. Because spatially dense ambient noise records are unavailable, we performed microtremor measurements using multiple linear arrays with multiple sensors along the survey line to collect as many recordings as possible. The synchronised microtremor recordings of each array were used to compute the horizontal-to-vertical spectral ratio (H/V), cross-correlation (CC), autocorrelation (AC), and single-station cross-correlation (SC). The H/V ratio and the waveforms of these correlation functions showed significant spatial variation. The velocity variation was measured quantitatively using the stretching method, which correlates a compressed and stretched reference function with each function on the line. The velocity variation of the vertical and radial components of CC compares well with the variation of the H/V peak, indicating that the radial components of CC retrieved the Rayleigh-wave Green's function. The waveforms of AC and SC also showed spatial variation but the measured value of velocity change was smaller than that for CC. Further investigation is awaited to conclude if this is due to low-quality data or inappropriate measurement conditions. The reliability of the velocity change was confirmed by comparing the results to dispersion curves obtained using the conventional array method. [ABSTRACT FROM AUTHOR]

Spectral transform, known as a curvelet, enables sparse representations of complex data. Denoising wave propagation in disordered media and pattern recognition are just a few of the numerous domains in which denoising has a potential application. Based on directional basis functions, this spectral method represents objects with discontinuities along a smooth curve. In this study, we used this technique to eliminate ground roll, an unwanted feature signal that can be seen in seismic data obtained by sonating the earth's geological formations. Additionally, we improved the curvelet transform threshold denoising method combined with a fast non-local mean to remove seismic random noise. First, cyclic translation and block complex domain threshold methods were introduced into the curvelet transform threshold denoising, and the traditional curvelet threshold denoising method was improved to obtain the best denoising results; Subsequently, the removed noise was filtered using a fast non-local mean method to obtain a valid signal. Finally, the data obtained in the above two steps were added to obtain the final denoising result. The results of the model tests and actual seismic data denoising showed that the denoising results obtained using this method had a higher signal-to-noise ratio and fidelity than that using the other methods. [ABSTRACT FROM AUTHOR]

One of the significant challenges in processing and analyzing seismic data is the contamination of the seismic signal with noise from various sources. Coherent or incoherent noise, multiples, and other types of noise can all be eliminated using a number of techniques, but it is still complicated to attenuate random noise to the desired level. The non-homogeneous curvelet transform is first applied in this study, and the regularized calculation is then carried out using the inverted operator. Following the application of the linear calculation method, the threshold value is modified to remove the coefficient noise during the iteration process, allowing the homogeneous coefficients and noise-free seismic data to be obtained. We choose some real data as an example and apply the suggested curvelet theory to obtain homogeneous data in order to verify the denoising effect. Tests on real data show that, when the suggested approach interpolates sampled data to be homogeneous, random noise can be effectively reduced. The important benefit of this approach is that features like multi-resolution, and locality introduce minimal overlapping between coefficients representing signal and noise in curvelet domain. [ABSTRACT FROM AUTHOR]

Random noise, which has a significant impact on subsequent processing and interpretation, easily interferes with seismic data. Current convolutional neural networks (CNN) use a single-stage technique to boost network capacity by exploiting the complicated network structure, but the performance of the network becomes saturated and prone to overfitting at a certain stage. Hence, we propose a two-stage U-Net denoising network with a supervised attention module (UNet-SAM). In this supervised algorithm, the first stage obtains the pre-denoising results, while the second stage achieves more accurate data. The supervised attention module (SAM) block is inserted in the first stage, extracting features with supervised attention to utilise as a priori information and guide the fine denoising in the second stage. The combination of the attention mechanism and two-stage strategy provides prior information that helps to train a network with better denoising performance. Experiments on synthetic and field data illustrate that the proposed UNet-SAM not only has a superior denoising effect but also retains more of the original effective signal. [ABSTRACT FROM AUTHOR]

This paper analyses the feasibility of estimating the fundamental frequency of an 85 m high cycloned-sand tailings dam located in the Central-North area of Chile using the single-station H/V Spectral Ratio Method (HVSR), calculated from seismic ambient noise and earthquakes recorded by a temporal seismic array deployed along the embankment crest, the downstream slope, and the dam toe, directly over the foundation soil. The fundamental vibration frequencies obtained from the HVSRs show consistency with results from the Standard Spectral Ratio method (SSR) calculated between the crest and the toe using the available earthquake records, particularly in the dam central part. [ABSTRACT FROM AUTHOR]

The main purpose of this research is to evaluate the effectiveness of coherent noise clustering in reconstructing leaked signals after conventional noise attenuation filters. We use Generalised Auto Regressive Conditional Heteroskedasticity (GARCH) model. We apply clustering, conditional variance, and conditional standard deviation analysis to synthetic and experimental seismic field data. The conditional variance and conditional standard deviation of coherent noises that are attenuated by the Ormsby and f-k filter are calculated. Each cluster is labelled using the two-dimensional average clustering method and then leaked signals are reconstructed from the initially filtered data to improve the signal-to-noise ratio. Results show that the proposed method mostly reconstructs the leaked signals after conventional filters. [ABSTRACT FROM AUTHOR]

Understanding public activities and developing thoughtful public health strategies are key goals in efforts to manage the COVID-19 pandemic. This paper explores how seismic noise data can be used as part of such efforts. We show that the fluctuation of seismic noise levels has the capacity to demonstrate aggregate human movement. When considered in relation to major public health efforts, these data can help us evaluate the effectiveness of public health communication strategies that seek to limit social activity. We show evidence that, broadly speaking, Mexican national efforts to encourage "lockdown" worked for a few months in areas around seismic stations, and broke down as time went on. Further, we suggest that changes in the levels of human activity detected in seismic noise can be read alongside social data that provide some clues as to why people respond or not to health recommendations. Our findings have implications for both efforts to understand the nature and effects of public trust in the Mexican state and also the practicalities of using seismic noise data in this manner. An interdisciplinary analysis allows us to address these data and their possible use in a way that takes seriously the opportunities and challenges that emerge in the context of contemporary biopolitics and emerging configurations of surveillance technologies. Analyzing anthropogenic seismic activity opens up new opportunities for ethical data collection and use. [ABSTRACT FROM AUTHOR]

Distributed acoustic sensing (DAS) is an emerging technology increasingly employed to monitor changes of formation properties, production noise and micro-seismic activity, and as an array of sensors in active seismic surveys. The data recorded with the DAS systems are very rich; some features observed in DAS records are often not well understood, and thus are underutilised. A systematic analysis of the data recorded passively with a DAS system in a 900-m deep well over a period of 12 weeks in the Perth metropolitan area, Western Australia, reveals the presence of several types of ambient energy in the subsurface, such as earthquakes, ocean swell and urban noise. In particular, over 85 days of the experiment, the analysis detected sixteen earthquakes, with epicentres ranging from 126 km to 900 km (for the local events) and from 2300 km to 6400 km (for the remote events). Signals with frequencies below 0.9 Hz are dominated by the oceanic swell. The recorded urban noise includes mine blasting, machinery and traffic. The experiment shows the ability of DAS to detect these events and as such is potentially useful for subsurface characterisation and monitoring. [ABSTRACT FROM AUTHOR]

Source-generated linear noise is one of the most common types of noise in seismic data. One or more groups of slanted linear events with strong energy often appear in seismic records and severely degrade the quality of subsurface reflections. Therefore, how to effectively remove this noise is the key to improve the quality of reflections. Here, we use a method that combines a feed-forward denoising convolutional neural network (DnCNN) with asymmetric convolution blocks (ACB) to attenuate linear noise in seismic data. Compared with traditional filter methods, this method involves less assumptions concerning the signals and noise; we merely train the neural network to recognise the features of reflections in seismic data. The DnCNN is a supervised deep learning method. It needs sufficient training data to optimise network parameters. Therefore, we generate numerous pairs thereof – including synthetic and real seismic data – to feed to the network. This input of data enables the network to identify reflections in seismic data directly and thus obtain the denoised data. Based on the characteristics of linear noise in seismic data, we build an asymmetric network architecture by combining the DnCNN with ACB. This enables the network to develop an ability to automatically identify reflected signals in seismic data. To validate the performance of the proposed method, we apply it to synthetic and real seismic data. The results demonstrate the method can effectively identify signals from noisy data and obtain better results in attenuation of linear noise and preservation of signals compared with the four other methods. [ABSTRACT FROM AUTHOR]

The presence of noise degrades the quality of seismic data and makes the subsequent processing tasks and interpretation more challenging. Therefore, seismic noise attenuation is a key step in the processing of seismic data. We propose a novel convolutional neural network (CNN) framework with learning noise prior. Unlike conventional CNN-based seismic denoising methods, this new network is composed of a noise extractor and a denoiser. The noise extractor extracts noise from the original data to provide a high-precision noise prior to the denoising process. The denoiser uses the noise prior for denoising of the seismic data. This method is superior to the presently used networks in terms of the denoising effect. Additionally, the proposed network can be applied for random noise suppression as well as coherent noise attenuation. Synthetic and field tests illustrated the superiority of the proposed approach over the traditional denoising methods in suppressing noise and improving the signal-to-noise ratio (SNR) of seismic data. [ABSTRACT FROM AUTHOR]

Desert seismic data pose a particular problem due to its low signal-to-noise ratio and severe spectral overlapping. Most of the existing denoising methods have negative suppression effect on the desert mixed seismic noise, which mainly includes random noise and surface waves. The convolutional neural network (CNN) is a classical supervised deep-learning method that has proven to be an effective tool for noise suppression. The drawback is that CNN usually needs a large amount of ideal noise-free data to complete network training, which largely limits its applications to seismic data denoising. In this paper, we combine forward modelling with CNN to overcome this technical problem. Specifically, we construct multiple forward models from different physical parameters to obtain a noise-free seismic dataset by finite difference method. After adding noise data taken from a real desert noise record, we use the above data as the input for CNN training. Then, the MSE loss function allows us to obtain an optimal denoising model for the mixed noise suppression of desert seismic data. Continuing with this optimal model, we can predict mixed noise, which, once subtracted from the desert original seismic data, provide the denoised desert seismic data. Experiments with synthetic and real data demonstrate that this CNN-based denoising method can suppress the desert mixed seismic noise successfully. Several tests using artificially generated models with a different number of signal patches prove that the forward modelling can significantly improve the continuity of events and prevent the appearance of false events. In addition, analysis of the effect of network depth supports the effectiveness of our method through a trade-off among higher signal-to-noise ratio, lower root mean square error and shorter training time. [ABSTRACT FROM AUTHOR]

The moderate-size 2010 Yushu earthquake (Mw 6.9) caused severe seismic damage around the source region which is situated on the sparsely populated hinterland of the Tibetan Plateau. But until now the mechanisms have not been well understood. To this end, we constructed the model to simulate the fault spontaneous rupture propagation, in which the realistic fault with a curved bend is imbedded. Our modeling results show that the special fault geometry controlled the rupture behavior, which encouraged rupture propagation speed transition from subshear to supershear with the speed of 5.17 km/s larger than the local shear wave velocity. Moreover, calculation results demonstrated that strong ground motion acceleration was greatly intensified by supershear ruptures, leading to widespread destruction. This may be the main reason why serious earthquake damage happened in the Yushu earthquake. In particular, we can see from numerous numerical experiments that rupture styles will be different if geometries of fault are varied. It is confirmed that it is the special geometry of the seismogenic fault of the Yushu mainshock produced grave seismic hazard. Thus, deeply investigating fault geometry will be helpful to better understand seismic source process and seismic hazard assessment. Curved bend in the seismogenic fault for the 2010 Yushu earthquake encouraged the supershear rupture transition. Strong ground motion acceleration was greatly intensified by supershear ruptures. Special geometry of the fault of the Yushu mainshock lead to seriouos seismic damage. [ABSTRACT FROM AUTHOR]

The stability of a rock wedge is one of the main failure models of rock slopes. Although the strength parameters of the discontinuity planes are commonly deemed to be between the peak and residual strengths, the effect of a residual factor on the stability of a rock wedge still has not been considered. This paper presents an analytical stochastic method, considering the residual factor as a random variable, for determining the stability of a rock wedge. First, based on the Hoek–Bray method, this paper derives the formulas for evaluating the wedge stability in terms of the residual factor, and then, based on a jointly distributed random variables (JDRV) method, the calculation formulas for the probability distribution function of the safety factor is established. In the analytical method, the friction angle and cohesion are selected to satisfy the truncated normal distribution, and the residual factor is assumed to obey the generalized beta distribution. The study of a typical rock wedge shows that the results of the analytical method and the Monte Carlo simulation are almost consistent. Besides, it is also shown that the residual factor has a substantial influence on the estimation accuracy of the failure probability of the wedge. [ABSTRACT FROM AUTHOR]

We evaluated seismic background noise at national network in India using PSD, Fourier spectra, Spectrogram, and HVSR approach, before and during the nationwide lockdown declared due to COVID-19 pandemic. The analyses were performed to understand characteristics of noise wave-field in such unprecedented situation and its effect on site response at the station. SBN in long period (> 20 s), primary microseism band (10–20 s) and secondary microseisms (1–10 s) performed well and the noise levels found within the new LNM and HNM. However, in short period (< 1 s) the variation in SBN performance found significant before and during the lockdown. We observed that the SBN at each site in short period (< 1 s) is found to be about 10–12 dB noisier in the time segment prior to the lockdown. The HVSR analysis of SBN at recording sites clearly indicates that the predominant frequency for the entire region remains stable and independent of seismic noise generated before or during lockdown. A substantial variation in amplification factor, however, observed in either situation. Most of the stations across the country experienced diminished cultural noise subsequent to declaration of lockdown on 25 March 2020. Such drastic decrease in cultural noise significantly enhanced the performance of noisy stations, and the best recording stations picked the seismic phases originated from micro to small earthquakes. We suggest installation of seismometers at some depth below the surface, particularly at disturbed sites, may substantially reduce short period noise in earthquake recording. [ABSTRACT FROM AUTHOR]

Monowai is an active submarine volcanic centre in the Kermadec Arc, Southwest Pacific Ocean. Multi-beam data acquired during expedition SO225 aboard R/V SONNE in December 2012 indicates that the topography of the main stratocone has evolved significantly since the last survey in June 2011. Bathymetric measurements of the edifice reveal differences of up to 42 m in seafloor depth and indicate a net volume increase of ∼0.037 km3 across the summit area. Explosive volcanism observed onsite during the SO225 mapping campaign could be linked to a 20h-long swarm of unusually coherent T phase arrivals, suggesting that Monowai is a prime source of broadband seismic noise in the Southwest Pacific region during times of activity. Our findings further document the dynamic nature of volcanic processes at Monowai and have implications for future expedition planning. [ABSTRACT FROM AUTHOR]

Many birds rely on alarm calls during nest defence to communicate about risk, but anthropogenic disturbance, including noisy industrial infrastructure, has the potential to disrupt alarm communication. Birds may overcome these effects by altering the structure of vocalizations to improve signal transmission. While previous work has demonstrated that birds can alter the structure of songs in the presence of noise, few have considered effects of noise-producing infrastructure on alarm call structure. Here, we tested whether Savannah sparrows (Passerculus sandwichensis) altered the structure of alarm calls in the presence of natural gas compressor stations or grid-powered or generator-powered screw pump oil wells, and in relation to overall ambient noise levels. Savannah sparrows called at a lower peak frequency and first quartile frequency close to gas compressor stations, but call structure did not differ with proximity to either type of oil well, or in response to ambient noise levels, suggesting that factors beyond noise amplitude, such as the physical footprint of the infrastructure, affected call structure close to compressor stations. Our results demonstrate that even unlearned, structurally simple avian vocalizations can vary in structure, and that the impacts of anthropogenic infrastructure on acoustic communication may be driven by factors beyond just noise. [ABSTRACT FROM AUTHOR]

The variations of the seismic energy absorption of the various nonlinear hysteretic models in different structural systems need to great study for proposing adequate energy-based design criteria. In this study, variations of the energy absorption with respect to the structural characteristics are investigated in two different strength levels of structures, in both 2D and 3D states by using different nonlinear hysteretic models, such as Bilinear, Clough, Takeda, Elasto-plastic and Wen models. Various earthquake records with different frequency contents and peak ground acceleration values are used in nonlinear time history analyses. According to the results, the amounts of energy absorption, nonlinear displacement and base shear vary considerably with the hysteretic characteristics of the structure. Also, it can be concluded that the hysteretic characteristics can be considered as criteria to limit the amount of earthquake energy absorption, and consequently the level of general damage to the structures. [ABSTRACT FROM AUTHOR]

Many field investigations have proven that the stoping speed of mining face is closely related to the amount of energy released from hard roof fracturing. Taking the Dongtan Coal Mine as the engineering background, we first analyze the relationship between the stoping speed and the microseismic activity. Then, the effect of the variable loading rate on the mechanical behavior of rock or coal is studied using PFC2D simulation. Finally, the occurrence mechanism of rock burst induced by the stoping speed variation under the hard roof condition is revealed. The stoping speed variation is not advantageous for the slow release of elastic energy stored in the roof and coal seam, and it can easily induce high energy events, which can reach 2.88–6.81 × 106 J. Under a variable loading rate condition, the energy storage capacity of coal and the released kinetic energy increase. When the stoping speed increases, the energy stored in the coal seam simultaneously increases, which implies that the dynamic balanced system is disturbed, and a rock burst may occur. When the stoping speed decreases, the new dynamic balanced system cannot absorb the entire pre-stored energy, and some of that energy will be released, which may also induce a rock burst. [ABSTRACT FROM AUTHOR]

Random noise suppression is of great importance in seismic processing and interpretation, and time–frequency peak filtering (TFPF) is a classic denoising approach. In TFPF, pseudo Wigner–Ville distribution (PWVD) is used to linearise the given signal for an unbiased estimation of the instantaneous frequency. However, window length is a trade-off parameter for preserving valid signals and attenuating random noise. A long window length may cause loss of the desired signal, whereas a short window length may be inadequate to suppress noise. To ensure a good trade-off between signal preservation and noise reduction, empirical mode decomposition (EMD) has been introduced into the TFPF method. Although the EMD-TFPF method can achieve good results, the mode mixing problem in EMD is non-negligible. In this article, we introduce variational mode decomposition (VMD) to overcome the mode mixing problem. VMD decomposes a signal into an ensemble of modes that own their respective centre frequencies. Thus, the modes obtained by VMD contain less noise, which simplifies selection of the window width of TFPF. Therefore, we propose the VMD-based TFPF (VMD-TFPF) method to suppress random noise. Synthetic and field seismic data examples are employed to illustrate the superior performance of the proposed method in attenuating random noise and preserving the desired signal. [ABSTRACT FROM AUTHOR]

Impedance inversion performed on post-stack seismic data is one approach to reservoir prediction. Conventional post-stack seismic data inversion has two main stages. Stage one involves deconvolution to estimate reflectivities and stage two is estimation of the impedance section from these reflectivities. These two stages are ill-posed inverse problems due to the nature of seismic inversion. An alternative method has been proposed that combines the two stages to estimate seismic impedance directly. Because it is less sensitive to noise in the seismic data, the proposed method decreases the inherent ill-posedness of impedance inversion. To regularise this merged inverse problem, L0 gradient minimisation of impedance has been used. L0 gradient minimisation regularisation provides a blocky impedance solution that makes formation interfaces and geological edges more precise and keeps the inversion procedure robust even if random noise exists in the seismic data. A split-Bregman-like algorithm has been used to solve the L0 gradient minimisation problem. The results of numerical examples show that the proposed inversion method can generate more accurate impedance models compared with conventional methods. Finally, the proposed method is applied to real seismic data from east China to test its applicability in practice. The inversion results confirm that the proposed method is effective at inverting real seismic data. [ABSTRACT FROM AUTHOR]

In this study, a data-driven linear filtering method is proposed to recover microseismic signals from noisy data/observations. The proposed method is based on the statistics of the background noise and the observation, which are directly extracted from the recorded data, obviating prior statistical knowledge of the microseismic source signal. The proposed method does not depend on any specific underlying noise statistics; therefore, it works for any type of noise, e.g. uncorrelated (random/white Gaussian), temporally correlated and spatially correlated noises. Consequently, the proposed method is suitable for microquake data sets that are recorded in contrastive noise environments. A mathematical analysis is presented to interpret the proposed method in two different ways. Furthermore, a number of practical concerns are discussed and their corresponding solutions are introduced. Finally, the proposed scheme is evaluated using both field and synthetic data sets and the experimental results show a reasonable and robust performance. [ABSTRACT FROM AUTHOR]

Sichuan-Tibet Railway plays a vital role in China’s transportation system by connecting Tibet and Central China, whose design and construction are extremely difficult due to numerous seismic zones and deep valleys along the railway line. This paper systematically presents a framework to control seismic vibration of T-beam bridges with high-piers in Sichuan-Tibet Railway using tuned mass dampers (TMDs). Firstly, a finite element model of the widely used high-pier bridge is established to reveal its vibration modes subject to earthquakes. On this basis, optimal installation locations and optimal parameters of the TMDs are determined. Then, vibration reduction effects of the designed TMDs on the high-pier bridge subject to actual earthquake samples are investigated and compared with that of using some other vibration absorption measures. Finally, a detailed train-track-bridge dynamic model with attached TMDs is established to study the effects of the designed TMDs on the seismic responses of the running trains. The results indicate that, for the high-pier T-beam bridges, the first bending vibration mode of the high-pier is most likely to be excited by earthquakes, which should be restrained. With the designed optimal parameters, the attached TMDs are effective to control seismic vibrations of the concerned high-pier bridges. Tuned mass damper is the best one among all the investigated measures to absorb vibrations subject to earthquakes from the perspective of vibration absorption performance, installation and maintenance. [ABSTRACT FROM AUTHOR]

Rock wedge parting is an important factor that can induce coal burst. In this study, a physical model for the stick-slip model was developed to investigate coal burst induced by rock wedge parting. The Maxwell model was used to explain the stick-slip motion of the rock wedge parting. The evolution of microseismic source locations in the coal face was also obtained to correlate rock wedge parting with coal burst. It was found that superposition of the high static stress concentration and the dynamic stress from the fracture and caving of key stratum induced the coal burst. [ABSTRACT FROM AUTHOR]

This paper is the first to address the environmental legal issues that could arise from the conduct of unilateral seismic operations in disputed maritime areas. And that should be surprising: such operations are ongoing in many places across the globe as states seek to enhance their domestic natural resource potentials and establish their sovereign control in the areas under dispute. But, the lack of previous legal scholarship on the topic is even more surprising when one realises the serious and multifaceted risks posed by seismic surveys on the marine environment. As this paper discusses, there are known environmental risks that include permanent injuries to marine organisms or even immediate death. Other effects may include temporary injuries that may or may not directly result in death but that may make marine organisms less fit, resulting in lower chances of survival. These risks are in addition to less well understood but nonetheless plausible risks to marine ecosystems, such as the potential for noise-derived behavioural disturbance. This could have an impact on animals’ feeding, movement and reproduction, and might also have short- or long-term effects on catch success rates. The paper examines the possible application of provisional measures of protection under Article 290 of the United Nations Convention on the Law of the Sea (UNCLOS). This provision enables a court or tribunal exercising jurisdiction under UNCLOS to prescribe provisional measures not only to preserve the rights of the disputants, but also, or even solely, to prevent serious harm to the marine environment. The analysis explores the foreseeable risks posed by unilateral seismic surveys and examines if Article 290 of UNCLOS provides adequate protection to the complainant state against such operations, pending the final settlement of the dispute. The paper reviews the existing environmental jurisprudence of the International Tribunal for the Law of the Sea (ITLOS) on provisional measures and comments on the potential to respond meaningfully to unilateral seismic exploration activities in disputed maritime areas through recourse to provisional measures of protection. [ABSTRACT FROM AUTHOR]

The seismic background noise is studied at newly constructed sites of the Eastern Ghat Mobile Belts (EGMB), in Orissa. Ten broadband stations have been deployed along two profiles. The area has not been previously attempted for any broadband experiment. To assess the performance of the stations, we investigate the characteristics of different types of noises dominated at those sites. The power spectral densities of ambient background noise for each site are calculated and compared with the global noise model. The results suggest that the noise levels at all stations that belong to profile-1 are within the global high and low bounds. Along profile-2, the station PATN stabilizes after some time post-deployment while noise levels at other two stations are within the proposed limits. Results show that profile-1 is predominated by cultural noise, and the microseismic noise levels are observed to be low in both the profiles. Assessment of the temporal and seasonal variation of the noise has also been done, along with the calculation of the power spectral densities in the East and North components of the seismometer for this station. Overall, our observations suggest that installation of the seismometers have been successful in all the sites. [ABSTRACT FROM AUTHOR]

Current understanding of the Auckland Volcanic Field is predominantly based on geological and geochemical observations from the surface. Low local seismicity hinders passive seismic imaging efforts, whereas strong shallow heterogeneity reduces the resolution and penetration of active seismic models. To overcome these difficulties, we have estimated crustal shear-wave velocity profiles beneath the Auckland Volcanic Field from the ocean-generated ambient seismic noise. Variations in seismic velocity in the shallow crust correlate with variations in surface geology. In addition, our results highlight a contrast between oceanic and continental features in the Auckland Volcanic Field. Velocity models associated with the Waipapa Terrane (relative juvenile continental crust) tend to show a mid-crustal low-velocity anomaly, whereas a monotonic increase in velocity is associated with including the oceanic rocks in the ophiolite belt of the Dun Mountain–Maitai Terrane. [ABSTRACT FROM PUBLISHER]

In the current work, we constructed new comprehensive standard seismic noise models and 3D temporalspatial seismic noise level cubes for Morocco in north-west Africa to be used for seismological and engineering purposes. Indeed, the original global standard seismic noise models published by Peterson (1993) and their following updates by Astiz and Creager (1995), Ekström (2001) and Berger et al. (2003) had no contributing seismic stations deployed in North Africa. Consequently, this preliminary study was conducted to shed light on seismic noise levels specific to north-west Africa. For this purpose, 23 broadband seismic stations recently installed in different structural domains throughout Morocco are used to study the nature and characteristics of seismic noise and to create seismic noise models for Morocco. Continuous data recorded during 2009, 2010 and 2011 were processed and analysed to construct these new noise models and 3D noise levels from all stations. We compared the Peterson new high-noise model (NHNM) and low-noise model (NLNM) with theMoroccan high-noise model (MHNM) and low-noise model (MLNM). These new noise models are comparable to the United States Geological Survey (USGS) models in the short period band; however, in the period range 1.2 s to 1000 s for MLNM and 10 s to 1000 s for MHNM display significant variations. This variation is attributed to differences in the nature of seismic noise sources that dominate Morocco in these period bands. The results of this study have a new perception about permanent seismic noise models for this spectacular region and can be considered a significant contribution because it supplements the Peterson models and can also be used to site future permanent seismic stations in Morocco. [ABSTRACT FROM AUTHOR]

Microseismic (MS) technology has been widely adopted for monitoring coal and rock dynamic disasters. Insights into MS wave characteristics contribute to the accurate prediction of these disasters. In this study, MS wave characteristics were analysed from three aspects: the signal spectra, wavelet packet energy and fractal features. It is shown that prior to the rock burst, the MS wave main frequency decreased following a power law, the amplitude linearly increased, the wavelet packet energy tended to become concentrated on the low frequency bands, and the correlation dimension decreased. When the rock burst occurred, the MS wave main frequency, wavelet packet energy and correlation dimension declined to their lowest levels. Meanwhile, the amplitude rose to a maximum. Therefore, the MS wave characteristics in this study were found to effectively identify and extract precursor information of value for predicting rock dynamic disasters. [ABSTRACT FROM PUBLISHER]

Borehole–surface microseismic monitoring is a new approach for monitoring artificially induced hydraulic fracturing in an oil or gas field. However, ineffective communication links and incompatible data formats between current borehole- and surface-based monitoring systems mean that borehole–surface monitoring cannot be reported in real time. To solve this problem, the borehole–surface microseismic monitoring system reported here allows fracturing points through inversion and the development of fractures to be viewed in real time. Private cloud technology is used to control the instruments, manage the borehole and the surface database, and process the data. This system ensures high performance and availability of the system. The data acquisition modules and the geophones used in the borehole and surface instruments were calibrated in the laboratory to ensure the consistency of the acquired microseismic signals. The monitoring system located 82 microseismic events with a fracture azimuth of N84°E during fracture production in the Daqing Oilfield. Subsequent analysis showed that the locations of the fractures and their strike directions were consistent with the theory of hydraulic fracture propagation and the local crustal stress field. The results demonstrate that the monitoring system effectively and promptly processed data, thus enabling real-time borehole–surface microseismic monitoring. [ABSTRACT FROM AUTHOR]

We utilise seismic data from the central section of the Alpine Fault to locate earthquakes and image crustal structure in three dimensions. Tomography results from c. 6500 sources reveal the fault as either a southeast-dipping low-velocity zone or a marked velocity contrast in different parts of the study region. Where our model is best resolved, we interpret the Alpine Fault to be listric in nature, dipping steeply in the upper crust (50–60°) and flattening to 25–30° in the lower crust. The base of the seismogenic zone shallows from c. 15 km beneath the footwall and Alpine Fault to c. 6 km beneath the Southern Alps Main Divide, and then deepens to c. 15 km by c. 10 km further southeast. The shallow brittle–ductile transition overlies a broad low-velocity zone, which together likely result from the presence of fluids and elevated temperatures brought about by enhanced exhumation rate in this section of the Alpine Fault. [ABSTRACT FROM PUBLISHER]

An intertidal rocky platform tucked in behind a rocky headland on open-ocean Gibson Beach, near Raglan, supports an agglomeration of cobble- to large-boulder-sized clasts of Cenozoic sandstone and limestone. Rather than exhibiting just point contacts, many larger clasts are tightly interlocked and fitted with their neighbours and/or the underlying platform bedrock. Clast interface geometry relates to the strength contrast between adjacent rock types, linked to their calcite (cement) content. The end-product is an armoured, highly stable framework of boulder clasts resembling a giant three-dimensional jigsaw puzzle. While the direct impact of breaking waves likely plays a role in in situ jostling of boulders, we speculate that mechanical abrasion and fitting between larger clasts may also be promoted and maintained by in situ microvibration of the boulders as a consequence of wave-induced microseismic shaking within the cliff-backed rocky platform and headland, especially during major storm wave assault from the southwest. [ABSTRACT FROM PUBLISHER]

The Gujarat state seismic network (GSNet), comprising of 50 broadband seismograph (BBS) stations and 40 strong motion accelerographs (SMAs), has been operated and maintained by the Institute of Seismological Research (ISR) since 2006. Nineteen permanent BBS stations are connected through VSAT and the rest are kept in an offline mode. The local geology beneath seismic stations varies from Mesozoic to Quaternary formations. The seismic background noise (SBN) at these stations was calculated and found that it varies widely as a function of period, time and geographic location. We have studied the SBN variation along these three parameters for 14 online BBS stations of the GSNet. It was found that the stations located on the Deccan trap and Mesozoic formations are good sites with low SBN while stations on Quaternary, Tertiary and soft soil are noisy. The comparison between day and night noise spectra shows that SBN increases during the daytime at most of the stations. Three typical noisy peaks at three different periods were recorded at all of the stations, which is a global phenomenon. The results of this study will be helpful in selecting sites for future earthquake observations. [ABSTRACT FROM AUTHOR]

The noise level of the Romanian broadband stations operating since 2006 has been studied in order to identify the variations in background seismic noise as a function of time of day, season, and particular conditions at the stations. Power spectral densities and their corresponding probability density functions are used in this paper to characterize the background seismic noise. At high frequencies (> 1 Hz), seismic noise seems to have cultural origin, since significant variations (up to 55 dB) between daytime and nighttime noise levels are observed at almost all of the stations. However, this variability appears not to influence the detection capabilities of the Romanian Seismic Network in case of intermediate-depth earthquakes and earthquakes with magnitude over 3.0. For smaller magnitude events (Mw < 3), we showed that the number of stations detecting an event decreases during daytime. We studied the seasonal variation of the seismic noise for primary and secondary microseisms (with emphasize for the latter) and we demonstrated that the noise levels are higher in winter than in summer. We also observed a shift of the double-frequency peak from lower periods in summer to longer periods in winter. The polarization analysis indicated that the main sources of secondary microseisms for stations close to the Black Sea are coming from the Black Sea, while for the others the main sources are found in the Mediterranean Sea and Atlantic Ocean. Finally, the analysis of the probability density functions for stations located in different geologic conditions has pointed out that the noise level is higher for stations sited on softer formations than those sited on hard rocks. [ABSTRACT FROM AUTHOR]

Whales living within seismically active regions are subject to intense disturbances from strong sounds produced by earthquakes that can kill or injure individuals. Nishimura & Clark (1993) relate the possible effects of underwater earthquake noise levels in marine mammals, adducing that T-phase source signal level (10- to 30- Hz range) can exceed 200 dB re: 1 μPa at 1 m, for a magnitude 4-5 earthquake, sounds audible to fin whales which produce low frequency sounds of 16-20/25-44 Hz over 0.5-is, typically of 183 dB re: 1 μPa at 1 m. Here we present the response of a fin whale to a 5.5 Richter scale earthquake that took place on 22 February 2005, in the Gulf of California. The whale covered 13 km in 26 mm (mean speed = 30.2 km/ h). We deduce that the sound heard by this whale might have triggered the costly energy expenditure of high speed swimming as a seismic-escape response. These observations support the hypothesis of Richardson et al. (1995) that cetaceans may flee from loud sounds before they are injured, when exposed to noise in excess of 140 dB re: 1 μPa 1 m. [ABSTRACT FROM AUTHOR]

This study shows three-component particle vibration records from a number of Ø165 mm blast holes, single or double, of different depths and with varying charge contents. In this concept, effects of (1) hole-depth, (2) surface delays, (3) inter-hole delays and (4) free-face on the seismic signal were investigated. The pulse from one hole or charge was used as a signature and by linear superposition the composite signal from two holes or charges were constructed and compared with the measured signal. From these comparisons, a number of conclusions were drawn. Those conclusions provide the way for better mining solutions in terms of good fragmentation and minimum vibration. [ABSTRACT FROM AUTHOR]

An approach devoted to quickly assess the thickness of soft sedimentary cover in areas of unknown subsurface morphology is applied in this study. In particular, soil thickness (h) is derived by combining estimates of the resonance frequency (fr) relative to soft sediments with the local shear-wave velocity (Vs) profile. For this purpose, fr values are assessed from horizontal to vertical (H/V) spectral ratios of seismic noise recordings and the Vs profile is obtained by considering information from shallow seismic surveys. Results obtained for a Quaternary sedimentary basin in Southern Italy are discussed. Since in the investigated area only weak independent constraints are available, special emphasis is given to the assessment of uncertainties involved in this estimate of soil thickness. [ABSTRACT FROM AUTHOR]