Noise Cross-correlation Functions Research Articles

Optimal stacking of noise cross-correlation functions

SUMMARY Cross-correlations of ambient seismic noise are widely used for seismic velocity imaging, monitoring and ground motion analyses. A typical step in analysing noise cross-correlation functions (NCFs) is stacking short-term NCFs over longer time periods to increase the signal quality. Spurious NCFs could contaminate the stack, degrade its quality and limit its use. Many methods have been developed to improve the stacking of coherent waveforms, including earthquake waveforms, receiver functions and NCFs. This study systematically evaluates and compares the performance of eight stacking methods, including arithmetic mean or linear stacking, robust stacking, selective stacking, cluster stacking, phase-weighted stacking, time–frequency phase-weighted stacking, Nth-root stacking and averaging after applying an adaptive covariance filter. Our results demonstrate that, in most cases, all methods can retrieve clear ballistic or first arrivals. However, they yield significant differences in preserving the phase and amplitude information. This study provides a practical guide for choosing the optimal stacking method for specific research applications in ambient noise seismology. We evaluate the performance using multiple onshore and offshore seismic arrays in the Pacific Northwest region. We compare these stacking methods for NCFs calculated from raw ambient noise (referred to as Raw NCFs) and from ambient noise normalized using a one-bit clipping time normalization method (referred to as One-bit NCFs). We evaluate six metrics, including signal-to-noise ratios, phase dispersion images, convergence rate, temporal changes in the ballistic and coda waves, relative amplitude decays with distance and computational time. We show that robust stacking is the best choice for all applications (velocity tomography, monitoring and attenuation studies) using Raw NCFs. For applications using One-bit NCFs, all methods but phase-weighted and Nth-root stacking are good choices for seismic velocity tomography. Linear, robust and selective stacking methods are all equally appropriate choices when using One-bit NCFs for monitoring applications. For applications relying on accurate relative amplitudes, the linear, robust, selective and cluster stacking methods all perform well with One-bit NCFs. The evaluations in this study can be generalized to a broad range of time-series analysis that utilizes data coherence to perform ensemble stacking. Another contribution of this study is the accompanying open-source software package, StackMaster, which can be used for general purposes of time-series stacking.

Using the three-station interferometry method to improve urban DAS ambient noise tomography

Distributed acoustic sensing (DAS) is a novel seismological observation technology based on the fiber-optic sensing method, and can transform existing urban fiber-optic cables into ultra-dense array for urban seismological researches, thus opening abundant opportunities for resolving fine details of near surface structures. While high frequency ambient noise recorded on DAS has been applied in surface wave tomography, it is often difficult to extract a clear dispersion curve for the data recorded by urban internet cable because of the effect of precursor signals on noise correlation functions due to uneven distribution of noise sources, and weak coupling between the cable and the solid earth. In this study, we investigate the performance of the three-station interferometry method for improving the noise cross-correlation functions of the linear array. We applied this method to a DAS dataset acquired in an urban area, suppressed the precursor signal, improved the measurement of the dispersion curve, and constructed a 2D S-wave profile that reveals the hidden fault beneath the city. We also observed that the convergence of noise cross-correlation functions with weak coupling was significantly accelerated using this method. We employed this method to improve the signal quality of surface waves at far offset for the long segment, thus obtaining a more accurate dispersion curve. In conclusion, the three-station interferometry is an effective method to enhance the surface wave signal and suppress the precursor signal retrieved from the data recorded by urban internet cable, which could help in providing high resolution images of shallow structures in built-up areas.

Multimode dispersion measurement of surface waves extracted by multicomponent ambient noise cross-correlation functions

SUMMARY Cross-correlation functions of ambient seismic noise sometimes show multimode characteristics of surface waves, especially in observations in sedimentary areas and ocean areas. Multimode dispersion curves are useful for improving the depth resolution of subsurface imaging; nevertheless, measuring the multimode dispersion curves is not easy. Multimode interference of surface waves makes the cross-correlation functions complicated even without lateral heterogeneity of the subsurface structure, and the complex waveforms may result in unphysical dispersion measurement. We developed a method to determine multimode phase velocity dispersion curves based on the fitting of the synthetic cross-spectra to observed ones. The phase velocity in the synthetic cross-spectra is modelled as the function of a 1-D velocity structure, which achieves the measurement of physically realizable dispersion curves. The 1-D structures do not necessarily represent the Earth structure directly but act as model parameters of the dispersion curves within station pairs. The cross-spectral fitting has two steps, that is, array-based and single-pair fittings. The first step estimates the amplitude of each surface wave mode and the reference 1-D structure from the cross-spectral data within an array. The second step estimates the pair-dependent dispersion curves from the cross-spectra of a single station pair using the modal amplitudes and the reference structure estimated by the first step. The dispersion measurement based on the cross-spectral fitting can work even at short distances where the multimode inference is significant in the time-domain cross-correlation functions. We applied this method to synthetic and field data in seafloor observations. The synthetic and field applications show that the simultaneous use of multicomponent cross-correlation functions is effective to determine multimode dispersion curves. The multimode phase velocity dispersion curves in the ocean area are estimated stably even though the signal-to-noise ratio of cross-correlation functions is not high. The pair-dependent multimode dispersion curves estimated by the present method can serve as robust input data for high-resolution surface wave tomography.

Improvement of Frequency–Bessel Phase-Velocity Spectra of Multicomponent Cross-Correlation Functions from Seismic Ambient Noise

ABSTRACT The frequency–Bessel (F–J) transformation method is effective for the extraction of multimode surface wave dispersion data from ambient noise cross-correlation functions (CCFs). Recently, this method has been improved in terms of increasing resolution and reducing artifacts (or cycle skipping) in Rayleigh wave dispersion measurements. However, these advances are restricted to the ZZ-component F–J method, which is only applicable to Rayleigh waves. In contrast, they have not been extended to Love waves, which are fundamental for determining the horizontally polarized shear-wave velocity and the radial anisotropy associated with it. Furthermore, there is still a lack of a methodology for combining these advances. In this study, we propose a modified multicomponent F–J (MMFJ) method to extract high-quality dispersion data of both the Rayleigh and Love waves. To achieve high resolution, we derive formulas to optimize the MMFJ spectra. With synthetic ambient noise data and USArray data, we demonstrated the effectiveness of the MMFJ method in eliminating “crossed” artifacts and enhancing resolution. In particular, the “crossed” artifacts are greatly reduced using the MMFJ with small seismic arrays when the interstation distances in the seismic array are not dense enough. As such, the new MMFJ method has significant potential for handling seismic arrays with a limited number of receivers and the subsequent tomography of radial anisotropies at high precision.

Measuring the phase of ambient noise cross correlations: anisotropic Rayleigh and Love wave tomography across the Oman Mountains

SUMMARY Ambient seismic noise tomography has, over the last two decades, developed into a well-established tool for imaging seismic properties of the Earth’s crust. Fundamental mode Rayleigh and Love wave phase velocity dispersion curves can be measured from ambient noise cross-correlation functions (CCF) either using a high-frequency approximation theory, or by fitting the spectrum of the CCF to a Bessel function. Here, we advance the latter approach and present an automated algorithm that fits the phase of the Hankel function to the phase of the causal symmetric part of the CCF in order to determine phase velocity curves as continuous functions of frequency. Synthetic tests verify the reliability of the proposed method in the presence of low signal-to-noise ratio (SNR). Moreover, usage of the phase allows for robust phase velocity measurements at longer periods than when using the zero crossings of the Bessel function only and is, therefore, particularly useful at short inter-station distances. In the frequency domain, acceptable bandwidths of smooth phase velocity curves are obtained in an automated procedure using a set of fine-tuned quality criteria. We apply the method to 2.5 yr of continuous waveform data recorded by 58 temporary and permanent broad-band seismic stations in northern Oman. We obtain 1072 and 670 phase velocity curves for Rayleigh and Love waves, respectively, in the period range of 2–40 s. The data are inverted for isotropic and azimuthally anisotropic period-dependent phase velocity maps. Synthetic reconstruction tests show that the phase velocity maps have a lateral resolution of ∼30 km. The results suggest distinctly different middle to lower crustal architecture between the northern and eastern Oman Mountains. Azimuthal anisotropy shows contrasting fast propagation orientations in the shallow and deep crust, which we attribute to stress-induced and structural anisotropy in the upper crust and to lattice-preferred orientation in the lower crust.

The extended range phase shift method for broadband surface wave dispersion measurement from ambient noise and its application in ore deposit characterization

Surface wave tomography using seismic ambient noise has been applied widely in subsurface characterization, the depth of which ranges from a few meters in urban underground engineering to tens of kilometers in delineation of crustal heterogeneities. Currently, multichannel analysis of surface waves with active and passive sources together with some similar techniques has been widely applied to obtain fine near-surface structures. However, it is still difficult to retrieve accurate dispersion curves at low frequencies with those methods to constrain structures at greater depths. To better retrieve surface wave dispersion data at lower frequencies using ambient noise data acquired by dense linear arrays, we use the extended range phase shift (ERPS) method, which can extract broadband dispersions from the ambient noise crosscorrelation functions (CFs). A broadband dispersion curve is obtained by merging a dispersion curve of medium-to-high frequencies with a dispersion curve of low-to-medium frequencies measured using receivers with different combinations, whereas both curves reflect the local property of the subsurface structure under a subarray with a relatively small aperture. Thus, the horizontal resolution of the inverted models is not compromised, whereas the inverted depth is improved considerably. We first perform a synthetic test to validate the ERPS method, and then apply the method in characterizing the Woxi polymetallic deposit in Hunan, China, where eight 10 km linear arrays using 467 seismic nodes were deployed to record ambient noise. The dispersion data within 0.5–10 Hz are extracted from the CFs using ERPS and then used to invert for the [Formula: see text] models down to at least 2 km. The inverted structures are found to be consistent with the previous geologic studies and known structures from underground mining, and the proposed passive-source imaging method is considered to be economical and practical for ore deposit explorations.

Exploring surface source distributions for ocean ambient noise interferometry with airgun shots

Ambient noise interferometry utilizes the cross-correlations of ambient sound to estimate the time domain Green’s function (TDGF). We have previously shown that ambient noise interferometry can resolve multi-path arrivals between two bottom-mounted hydrophones separated by 3.2 km, at a depth of 1500 m, and located 470 km off the Oregon coast. In 2019, a seismic reflection survey was conducted directly over the two hydrophones for 28 days covering a 763 km2 area. The airgun shots occurred every 37.5 m while the ship moved at a speed of ∼4.5 knots, equivalent to a shooting interval of 16 s. The hydrophone recordings during this survey provide the unique opportunity to understand the effects of the surface source distribution on the noise cross correlation function (NCCF). In this talk, we show the sensitivity of the NCCF to the surface source locations using simulated and experimental data. Then, we use the image source method to analytically define the location of the sound sources that contribute to different delay times in the NCCF. [Work supported by ONR.]

Extracting reliable empirical Green's functions using weighted cross-correlation functions of ambient seismic noise in west-central and southern Brazil

SUMMARY Ambient seismic noise is now routinely used to study the Earth's interior. For an isotropic homogeneous medium, the basic assumption to extract seismic phases from a station pair is that the sources of seismic noise are distributed in such a way that there is a uniform energy flux around the station pair. In general, however, some particular azimuthal directions may dominate the energy flux, which directly affects the extracted interstation empirical Green's function (EGF). To solve this problem, we analysed synthetic cross-correlation functions (CCFs) from seismic pulses propagated in isotropic and anisotropic heterogeneous half-space media towards a station pair under the assumptions of uniformly and non-uniformly distributed sources of noise. A reliable EGF signal can be extracted by applying three processing steps: (1) normalizing the number of repeated stationary sources, (2) normalizing the energy of each excited source and (3) selecting coherent CCFs in the final stacking. In this way, three different classes of station pairs were identified based on the number of CCFs used in the stacking procedure. We introduced and applied a new method based on weighted root-mean-square stacking (WRMS) to the CCFs of more than 33 months of ambient noise recorded from January 2016 to September 2018 at 75 broad-band stations in West-Central Brazil. In the case of non-uniform distribution of source of noise, simple classical linear stacking of CCFs produces distorted EGFs. However, the waveform extracted by the WRMS method is very similar to the Rayleigh waves excited by an earthquake (on 2017 January 3) near one receiver observed at the other receiver. Moreover, synthetic tests and a comparison between extracted and earthquake signals show that although the WRMS method can extract the main part of the signal that is propagated on the shortest path, it cannot recover the energy parts propagated on multipath. Despite the N–W directionality in the geometry of the array, the rose-diagram results indicate no significant spatial variations in the energy level of EGFs extracted by the WRMS stacking, whereas the EGFs extracted by the classical linear stacking indicate the extreme directionality of energy flow in different period ranges. Rayleigh wave group and phase velocity tomographic maps resolved by the EGFs derived from the WRMS method indicate a clear boundary along the Asuncion and Rio Grande Arches between the Chaco-Paraná and the Paraná basins at the shorter period, while the tomographic maps in the same periods which were calculated by other stacking methods cannot clearly separate basins and arcs. Our tomographic maps at longer periods indicate variations of Moho depth and lithospheric velocities.

A Short-Period Surface-Wave Dispersion Dataset for Model Assessment of Africa’s Crust: ADAMA

Abstract We present the first in a series of dataset and model assessment products for investigating Africa’s lithosphere (ADAMA). This is a comprehensive catalog of short-period interstation surface-wave dispersion measurements and uncertainties. It is derived from processing continuous recordings of all publicly available three-component seismograms, spanning four decades, from ∼1372 stations, across 62 seismic networks deployed in and around the African continent. It includes Love- and Rayleigh-wave dispersion derived from frequency-domain ambient noise cross-correlation functions (NCFs). Phase and group dispersion, as well as their uncertainties, are then obtained with an iterative nonlinear waveform fitting of the NCFs, using a spectral element representation of a path-average a priori Earth model. Our catalog represents the following advances: (1) a large distribution of short period dispersion measurements: ∼114,000 interstation pairs at periods between 5 s and 40 s, (2) inclusion of uncertainties useful for regularization in continent-wide model building, (3) preliminary model assessments for different tectonic domains on the continent, and (4) an exemplary Love-wave phase velocity map obtained by Bayesian inversion revealing detailed features not previously detected. ADAMA will be used to prepare short-period, high-resolution dispersion maps, and for assessment and updates of widely used seismic velocity models of the crust across a diversity of terranes on the continent.

Using the Features Extracted From the Ambient Noise Cross-Correlation Function to Evaluate the Performance of Broadband Seismograph

Broadband seismographs are used to collect seismic data over an extended period. Temperature, pressure, and humidity are field variables that can have an impact on the broadband seismograph’s performance as well as the accuracy of observational data. Variations in performance, geological structure, and noise source will cause the cross-correlation function of seismic ambient noise to alter. To evaluate the effectiveness of seismographs, we propose to use the whole cross-correlation function as well as the positive and negative time waveforms for feature extraction. The cross-correlation function is decomposed to evaluate the phase variations using Local Mean Decomposition (LMD) and Variational Mode Decomposition (VMD). This is followed by the calculation of the Multivariate Multiscale Fuzzy Entropy Partial Mean (MMFEPM). Wavelet Packet Decomposition (WPD) and MMFEPM are used to evaluate phase variations in the positive and negative time waveforms. WPD combined with Wavelet Feature Scale Entropy (WFSE) is chosen to evaluate the amplitude variations of the cross-correlation function and its positive and negative waveforms. The results show that the proposed methods can identify time offsets within 0.025-2.5s and amplitude variations of 10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-16</sup> , which provide a new direction for evaluating the performance of seismographs using ambient noise.

Teleseismic body waves extracted from ambient noise cross correlation between F-net and ChinArray phase II

The vertical-vertical noise cross-correlation functions (NCFs) between two seismic arrays, the Japan F-net and ChinArray phase II, are calculated using continuous recordings during 2013–2016. After array interferometry to obtain bin stacked NCFs, clear body waves are retrieved at different period bands. Teleseismic direct P waves for distance 15–40 degrees are observed between short period 3–10 ​s while core reflected PcP/ScS waves are more obvious for longer period 30–60s. The signal-to-noise-ratio (SNR) of the short period P waves reaches its highest point with bin widths around 20 ​km while SNRs of PcP and ScS increase slowly with bin width. All those body waves demonstrate clear directivity with strong signals traveling from the east. The time-lapse SNR variations for the PcP and ScS show correlation with the occurrence of major earthquakes, while the P-wave SNR demonstrates seasonal variations with additional contribution from major earthquakes. The present results suggest teleseismic body waves can be retrieved through bin stacking, though further processing is still necessary to obtain finer waveforms such as P wave triplications.

Limits for leak noise detection in gas pipes using cross correlation

The cross correlation method is widely used in leak detection and location for pipes. The model of the cross correlation function of the leak noise for water pipes has been established in an earlier study, while there is no such model for gas pipes. In this study, a model of the correlation function of the leak noise in gas pipes is developed. The characteristics of wave propagation in gas pipes, combined with the leak noise spectrum, are incorporated into the model to consider the effects of physical parameters, i.e., turbulence parameters, pipe parameters and flow parameters, on the cross correlation function. This model is capable of describing the main features of the correlation results in gas pipes. Moreover, the model gives an estimation of the detection limits of the leak noise in the absence of noise, which is crucial to the deployment of sensors in real gas pipelines. The findings of this study provide theoretical insight and experimental evidence for optimizing the cross correlation method when conducting leak detection and location in gas pipes.

Sensing Shallow Structure and Traffic Noise with Fiber-optic Internet Cables in an Urban Area

Distributed acoustic sensing (DAS) is a novel seismic observation system developed in recent years that can realize ultrahigh density observations and has attracted extensive attention in the field of seismology. DAS uses fiber-optic cables as sensing units, which are easy to incorporate with urban telecommunication fiber-optic cables for seismological observations. Compared with seismometers, DAS has the advantages of being rapidly deployed and recyclable, being able to acquire dense observations at low cost, and convenient data collection. In this study, a 5.2 km long telecom fiber-optic internet cable was utilized as a DAS array in an urban area to record ambient noise, and the noise cross-correlation function (NCF) was calculated. There are two different distribution types of ambient noise sources along the cable, regular along-road trucks (Taihe Road) and complex ambient noise, including human activities and traffic sources along and across the Jinniu road. In the first case, we constructed a 2D S-wave velocity model down to 100 m depth and a low-velocity zone was revealed. The S-wave model well explained the traffic signal along the Taihe road and the low-velocity zone is also consistent with the results obtained from co-located geophone arrays. In the second case, due to the complexity of the traffic noise distribution, empirical Green’s functions were barely achieved. Therefore, we performed a synthetic test obtaining different NCFs with different source distributions, and two specific cases that dominate the NCF results were matched. Finally, we obtained the traffic noise distribution along the road, which is consistent with the power spectra density of the ambient noise. In conclusion, by combining DAS and urban fiber-optic internet cables with urban traffic noise, we can effectively reveal the traffic activities and image shallow structures with high resolution, which could offer a reference for urban construction and disaster prevention.Article Highlights DAS turns the urban fiber-optic internet cables into ultra-dense permanent seismic observation arraysWe revealed a high-resolution shallow structure using urban fiber-optic internet cablesWe obtained the distribution of traffic activities along the road

Estimating ocean variables using ambient noise interferometry

Ambient noise interferometry is a method of estimating the time domain Greene's function (TDGF) by correlating and averaging sound from adjacent hydrophones. These averaged cross correlations are called noise cross correlation functions (NCCFs). Noise interferometry has been used in ocean acoustics to estimate ocean variables such as water temperature by measuring propagation times. In this talk, a 6-year NCCF stack between two Ocean Observatories Initiative cabled array hydrophones is investigated. The hydrophones are separated by 3.2 km, and are bottom mounted at a depth of 1500 meters. They are located in the caldera of the Axial Seamount volcano approximately 470 km off the Oregon coast. The TDGF estimate from the NCCF stack contains clear, multipath arrivals. Fluctuations in the arrival time over the six years are on the order of a single time bin. However, if the signal to noise ratio is high enough, it is possible to measure the arrival times with more accuracy than a single time bin. In this presentation, signal processing methods to accurately estimate the propagation time will be explored, as well as the viability of inverting these multipath arrival times to estimate ocean variables such as water temperature. [Work supported by ONR.]

Fault detection by reflected surface waves based on ambient noise interferometry

Detecting subsurface fault structure is important for evaluating potential earthquake risks associated with active faults. In this study, we propose a new method to detect faults using reflected surface waves observed in ambient noise cross correlation functions. Ambient noise tomography using direct surface waves obtained from ambient noise interferometry has been widely used to characterize active fault zones. In cases where a strong velocity contrast exists across the fault interface, fault-reflected surface waves are expected. We test this idea using a linear array deployed in the Suqian segment of Tanlu fault zone in Eastern China. The fault-reflected surface waves can be clearly seen in the cross-correlation functions of the ambient noise data, and the spatial position of the fault on the surface is close to the stations where the reflected signals first appear. Potentially reflected surface waves could also be used to infer the dip angle, fault zone thickness and the degree of velocity contrast across the fault by comparing synthetic and observed waveforms.

Distribution of Rayleigh Wave Microseisms Constrained by Multiple Seismic Arrays

AbstractMicroseisms are the most energetic signals of Earth's ambient noise field. Locating the sources of microseisms helps us to understand arrivals on noise cross‐correlation functions (NCFs) and the asymmetric amplitude of Rayleigh waves on the positive and negative parts of the NCFs. Using a dense broadband seismic array in eastern China, we investigated temporal and spatial characteristics of Rayleigh wave microseisms in the frequency range of 45–155 mHz by conducting beamforming and Rayleigh wave amplitude‐azimuth variation analyses. Seasonal variations of incident direction are clearly observable at the primary microseisms frequency band (45–95 mHz) but are less prominent at the secondary microseisms frequency band (95–155 mHz). The beamforming and amplitude‐azimuth variation analyses also indicated that microseisms arriving at the array are dominantly from five back azimuthal bands. To locate the source areas of the observed microseisms, we combined noise data from two additional arrays in southern California and employed a multi‐array beamforming technique to constrain plausible microseisms' source areas. We found that microseisms of the five azimuthal bands were excited at the Southern Ocean, western coast of Europe, coastal areas of the North Pacific Ocean, the Kerguelen Islands in the southern Indian Ocean, and the Polynesia islands in the South Pacific Ocean, respectively.

Improving the retrieval of high-frequency surface waves from ambient noise through multichannel-coherency-weighted stack

SUMMARY Seismic interferometry is becoming increasingly popular in urban areas due to its ability to retrieve high-frequency surface waves from abundant anthropogenic seismic noise, hence the need for advanced processing schemes in resolving complex environments. Stacking noise cross-correlation functions is an essential step for the successful retrieval of surface waves and some nonlinear methods are developed for attenuating incoherent noise; however, these methods are susceptible to waveform distortions. In addition, a lot of attention has been focused on the improvement of the pairwise noise cross-correlation functions, while the spatial coherency of waves is less utilized. We obtain the multichannel coherency by summing the local phase coherencies in a time window and propose the multichannel-coherency-weighted stack method for accelerating the retrieval of high-frequency surface waves. A synthetic test and a real-world three-component example demonstrate the superiority of the proposed method over both the linear stack and the phase-weighted stack methods in obtaining cleaner surface waves and more accurate dispersion measurements. Our method is not limited by waveform distortions owing to its linearity. Furthermore, the proposed method has the potential to be extended to body wave retrieval from ambient noise by adjusting its parameters.

Temporal Variation in Cultural Seismic Noise and Noise Correlation Functions during COVID-19 Lockdown in Canada

AbstractThe COVID-19 pandemic of 2020 led to a widespread lockdown that restricted human activities, particularly land, air, and maritime traffic. The “quietness” on land and ocean that followed presents an opportunity to measure an unprecedented reduction in human-related seismic activities and study its effect on the short-period range of ambient noise cross-correlation functions (NCFs). We document the variations in seismic power levels and signal quality of short-period NCFs measured by four seismographs located near Canadian cities across the pandemic-defined timeline. Significant drops in seismic power levels are observed at all the locations around mid-March. These drops coincide with lockdown announcements by the various Canadian provinces where the stations are located. Mean seismic power reductions of ∼24% and ∼17% are observed near Montreal and Ottawa, respectively, in eastern Canada. Similar reductions of ∼27% and 17% are recorded in western Canada near Victoria and Sidney, respectively. None of the locations show full recovery in seismic power back to the pre-lockdown levels by the end of June, when the provinces moved into gradual reopening. The overall levels of seismic noise during lockdown are a factor of 5–10 lower at our study locations in western Canada, relative to the east. Signal quality of NCF measured in the secondary microseism frequency band for the station pair in western Canada is maximum before lockdown (late February–early March), minimum during lockdown (mid–late March), and increased to intermediate levels in the reopening phase (late May). A similar pattern is observed for the signal quality of the eastern Canada station pair, except for a jump in levels at similar periods during the lockdown phase. The signal quality of NCF within the secondary microseism band is further shown to be the lowest for the western Canada station pair during the 2020 lockdown phase, when compared with similar time windows in 2018 and 2019.

Passive imaging of water pipelines using ambient turbulence noise

Ambient noise generated by flowing water turbulence is harnessed as a signal source for imaging key parameters and fault detection in water pipelines. This approach is important because it can aid in the estimation of wave speed or detection of water pipeline defects such as blockages and leakages. More importantly it overcomes the challenging problem of generating a signal source of sufficient power to provide the necessary signal-to-noise ratios for conventional water pipeline imaging and fault detection techniques. In this paper, the expressions of the auto- and cross-correlation functions of the ambient noise between sensors are derived using wave theory. It is shown that the time-domain Green’s functions can be extracted from the correlation functions. Experimental and numerical examples are provided for water pipelines to demonstrate that wave speed can be estimated from the time-domain Green’s functions. A method for extending the technique, by using straightforward but accurate approximations of the correlation functions, to detect the presence of defects in the profile of the water pipeline is also proposed.

Time Correction of Ocean-Bottom Seismometers Using Improved Ambient Noise Cross Correlation of Multicomponents and Dual-Frequency Bands

Abstract An effective approach was developed for identifying and correcting ocean-bottom seismometer (OBS) time errors through improving ambient noise cross-correlation function (NCCF) analysis and combination with other methods. Significant improvements were illustrated through analyzing data from a passive-source seismic experiment in the southwestern sub-basin of the South China Sea. A novel method was first developed that can effectively identify errors in the sampling frequency of the OBS instruments. The traditional NCCF method was then expanded by increasing the analyzed data spectrum from a single-frequency band to dual-frequency band pairs, thus doubling the number of available data points and substantially improving the time correction quality. For data with relatively low signal-to-noise ratios, the average time errors were reduced from the original average values of 60–80 ms by the conventional methods to &amp;lt;40 ms using the improved approaches. The new multistep procedure developed in this study has general applicability to analysis of other OBS experiments. The demonstrated significant improvements in the data quality are critical for advancing seismic tomography and other modern marine geophysical studies that require high accuracy in the OBS data.