scholarly journals Seismic interferometry from correlated noise sources

Author(s):  
Daniella Ayala ◽  
Andrew Curtis ◽  
Michal Branicki

<p>It is a well-established principle that cross-correlating seismic observations at different receiver locations yields new seismic responses that, under certain conditions, provide a useful estimate of the Green's function between the given receiver locations (that is, the medium response at one receiver location, had there been an impulsive source located at the other receiver). This principle, known as seismic interferometry, is a powerful technique that transforms previously discarded data such as seismic codas or background noise into useful signals that allow us to remotely illuminate subsurface Earth structures.</p><p> </p><p>In practice it is often necessary and even desirable to rely on noise already present in the environment, since this type of seismic energy is freely and widely available in many regions around the globe.  Across many applications of ambient noise interferometry there exists a persistent assumption that the noise sources in question are uncorrelated in space and time, and that energy arrives at the receiver array more-less equally from all directions. That this assumption is so tenaciously made comes as no surprise since the underlying theory unambiguously requires that the noise sources be uncorrelated for interferometry to work.</p><p> </p><p>However, many real-world noise sources such as trains or highway traffic are inherently correlated both in space and time, in direct contradiction to these theoretical foundations. Violating the uncorrelatedness condition makes the Green’s function and associated phases liable to estimation errors that so far have not been accounted for. We show that these errors are indeed significant for commonly used noise sources, in some cases completely obscuring the phase one wishes to retrieve. Furthermore, we perform analysis that explains why stacking has the potential to reduce these errors in the interferometric estimate, as well as some limitations of this approach. This analytical insight allowed us to develop a novel workflow that mitigates or even completely removes the spurious effects arising from the use of correlated noise sources. Our methodology can be used in conjunction with already existing approaches, and hence we expect it to be widely applicable in real life ambient noise studies.</p>

2021 ◽  
Vol 13 (14) ◽  
pp. 2703
Author(s):  
Daniella Ayala-Garcia ◽  
Andrew Curtis ◽  
Michal Branicki

It is a well-established principle that cross-correlating seismic observations at different receiver locations can yield estimates of band-limited inter-receiver Green’s functions. This principle, known as Green’s function retrieval or seismic interferometry, is a powerful technique that can transform noise into signals which enable remote interrogation and imaging of the Earth’s subsurface. In practice it is often necessary and even desirable to rely on noise already present in the environment. Theory that underpins many applications of ambient noise interferometry assumes that the sources of noise are uncorrelated in time. However, many real-world noise sources such as trains, highway traffic and ocean waves are inherently correlated in space and time, in direct contradiction to the these theoretical foundations. Applying standard interferometric techniques to recordings from correlated energy sources makes the Green’s function liable to estimation errors that so far have not been fully accounted for theoretically nor in practice. We show that these errors are significant for common noise sources, always perturbing or entirely obscuring the phase one wishes to retrieve. Our analysis explains why stacking may reduce the phase errors, but also shows that in commonly encountered circumstances stacking will not remediate the problem. This analytical insight allowed us to develop a novel workflow that significantly mitigates effects arising from the use of correlated noise sources. Our methodology can be used in conjunction with already existing approaches, and improves results from both correlated and uncorrelated ambient noise. Hence, we expect it to be widely applicable in ambient noise studies.


Geophysics ◽  
2020 ◽  
Vol 85 (1) ◽  
pp. KS29-KS38 ◽  
Author(s):  
Guoli Wu ◽  
Hefeng Dong ◽  
Ganpan Ke ◽  
Junqiang Song

Accurate approximations of Green’s functions retrieved from the correlations of ambient noise require a homogeneous distribution of random and uncorrelated noise sources. In the real world, the existence of highly coherent, strong directional noise generated by ships, earthquakes, and other human activities can result in biases in the ambient-noise crosscorrelations (NCCs). We have developed an adapted eigenvalue-based filter to attenuate the interference of strong directional sources. The filter is based on the statistical model of the sample covariance matrix and can separate different components of the data covariance matrix in the eigenvalue spectrum. To improve the effectiveness and make it adaptable for different data sets, a weight is introduced to the filter. Then, the NCCs can be calculated directly from the filtered data covariance matrix. This approach is applied to a 1.02 h data set of ambient noise recorded by a permanent reservoir monitoring receiver array installed on the seabed. The power spectral density indicates that the noise recordings were contaminated by strong directional noise over nearly half of the whole observation period. Beamforming and crosscorrelation results indicate that the interference still exists even after applying traditional temporal and spectral normalization techniques, whereas the adapted eigenvalue-based filter can significantly attenuate it and help to obtain improved crosscorrelations. The approach makes it possible to retrieve reliable approximations of Green’s functions over a much shorter recording time.


Geophysics ◽  
2019 ◽  
Vol 84 (3) ◽  
pp. B195-B203
Author(s):  
Sergey Yaskevich ◽  
Anton A. Duchkov ◽  
Artem Myasnikov

For downhole microseismic monitoring of hydraulic fracturing, the acquisition is performed using a set of three-component (3C) seismic receivers attached firmly to the borehole wall by a clamping mechanism. Such an acquisition cannot be repeated, and it is focused on recording weak signals. Thus, proper installation of the receivers is especially crucial for microseismic applications. We have developed a case study of using a seismic-interferometry approach for assessing the receiver’s installation quality from ambient-noise records. Crosscorrelation of one vertical receiver noise records with the others allows us to retrieve the direct body wave propagating along the receiver array. Our observations indicate that the inability to retrieve the direct body wave is an indicator of clamping issues. Our case study does not support the emergence-frequency hypothesis reported in the literature (that higher frequencies present in the retrieved body-wave spectrum imply better clamping quality). Another conclusion is that seismic-interferometry processing provides a stable assessment of the clamping quality only for the vertical receivers. Thus, one gets only partial diagnostics of the clamping quality for the 3C downhole tool. This is important because the horizontal components may be affected more by the clamping issues compared with the vertical components. The overall conclusion is that seismic-interferometry processing of noise records is recommended for the assessment of the downhole receiver installation prior to microseismic monitoring. It does not provide complete diagnostics but comes for free (does not need any additional technological operations or extra time).


Geophysics ◽  
2019 ◽  
Vol 84 (3) ◽  
pp. Q13-Q25 ◽  
Author(s):  
Michał Chamarczuk ◽  
Michał Malinowski ◽  
Yohei Nishitsuji ◽  
Jan Thorbecke ◽  
Emilia Koivisto ◽  
...  

The main issues related to passive-source reflection imaging with seismic interferometry (SI) are inadequate acquisition parameters for sufficient spatial wavefield sampling and vulnerability of surface arrays to the dominant influence of the omnipresent surface-wave sources. Additionally, long recordings provide large data volumes that require robust and efficient processing methods. We address these problems by developing a two-step wavefield evaluation and event detection (TWEED) method of body waves in recorded ambient noise. TWEED evaluates the spatiotemporal characteristics of noise recordings by simultaneous analysis of adjacent receiver lines. We test our method on synthetic data representing transient ambient-noise sources at the surface and in the deeper subsurface. We discriminate between basic types of seismic events by using three adjacent receiver lines. Subsequently, we apply TWEED to 600 h of ambient noise acquired with an approximately 1000-receiver array deployed over an active underground mine in Eastern Finland. We develop the detection of body-wave events related to mine blasts and other routine mining activities using a representative 1 h noise panel. Using TWEED, we successfully detect 1093 body-wave events in the full data set. To increase the computational efficiency, we use slowness parameters derived from the first step of TWEED as input to a support vector machine (SVM) algorithm. Using this approach, we detect 94% of the TWEED-evaluated body-wave events indicating the possibility to limit the illumination analysis to only one step, and therefore increase the time efficiency at the price of lower detection rate. However, TWEED on a small volume of the recorded data followed by SVM on the rest of the data could be efficiently used for a quick and robust (real-time) scanning for body-wave energy in large data volumes for subsequent application of SI for retrieval of reflections.


Geophysics ◽  
2015 ◽  
Vol 80 (1) ◽  
pp. Q1-Q13 ◽  
Author(s):  
Boris Boullenger ◽  
Arie Verdel ◽  
Bob Paap ◽  
Jan Thorbecke ◽  
Deyan Draganov

Seismic interferometry applied to ambient-noise measurements allows the retrieval of the seismic response between pairs of receivers. We studied ambient-noise seismic interferometry (ANSI) to retrieve time-lapse reflection responses from a reservoir during [Formula: see text] geologic sequestration, using the case of the experimental site of Ketzin, Germany. We applied ANSI to numerically modeled data to retrieve base and repeat reflection responses characterizing the impedances occurring at the reservoir both with and without the injection of [Formula: see text]. The modeled data represented global transmission responses from band-limited noise sources randomly triggered in space and time. We found that strong constraints on the spatial distribution of the passive sources were not required to retrieve the time-lapse signal as long as sufficient source-location repeatability was observed between the base and the repeat passive survey. To illustrate the potential of the technique, ANSI was applied to three days of passive field data recorded in 2012 at Ketzin. Comparison with the modeled results illustrated the potential to retrieve key reflection events using ANSI on field data from Ketzin. This study supports the idea that the geologic setting and characteristics of ambient noise at Ketzin may be opportune to monitor [Formula: see text] sequestration.


2018 ◽  
Vol 26 (02) ◽  
pp. 1850007 ◽  
Author(s):  
Qiulong Yang ◽  
Kunde Yang ◽  
Shunli Duan

Sea-surface wind agitation can be considered the dominant noise sources whose intensity relies on local wind speed during typhoon period. Noise source levels in previous researches may be unappreciated for all oceanic regions and should be corrected for modeling typhoon-generated ambient noise fields in deep ocean. This work describes the inversion of wind-driven noise source level based on a noise field model and experimental measurements, and the verification of the inverted noise source levels with experimental results during typhoon period. A method based on ray approach is presented for modeling underwater ambient noise fields generated by typhoons in deep ocean. Besides, acoustic field reciprocity is utilized to decrease the calculation amount in modeling ambient noise field. What is more, the depth dependence and the vertical directionality of noise field based on the modeling method and the Holland typhoon model are evaluated and analyzed in deep ocean. Furthermore, typhoons named “Soulik” in 2013 and “Nida” in 2016 passed by the receivers deployed in the western Pacific (WP) and the South China Sea (SCS). Variations in sound speed profile, bathymetry, and the related oceanic meteorological parameters are analyzed and taken into consideration for modeling noise field. Boundary constraint simulated annealing (SA) method is utilized to invert the three parameters of noise source levels and to minimize the objective function value. The prediction results with the inverted noise source levels exhibit good agreement with the measured experiment data and are compared with predicted results with other noise sources levels derived in previous researches.


2018 ◽  
Vol 23 (1) ◽  
pp. 32-38 ◽  
Author(s):  
Jantien L. Vroegop ◽  
Nienke C. Homans ◽  
André Goedegebure ◽  
J. Gertjan Dingemanse ◽  
Teun van Immerzeel ◽  
...  

Although the benefit of bimodal listening in cochlear implant users has been agreed on, speech comprehension remains a challenge in acoustically complex real-life environments due to reverberation and disturbing background noises. One way to additionally improve bimodal auditory performance is the use of directional microphones. The objective of this study was to investigate the effect of a binaural beamformer for bimodal cochlear implant (CI) users. This prospective study measured speech reception thresholds (SRT) in noise in a repeated-measures design that varied in listening modality for static and dynamic listening conditions. A significant improvement in SRT of 4.7 dB was found with the binaural beamformer switched on in the bimodal static listening condition. No significant improvement was found in the dynamic listening condition. We conclude that there is a clear additional advantage of the binaural beamformer in bimodal CI users for predictable/static listening conditions with frontal target speech and spatially separated noise sources.


2021 ◽  
Author(s):  
Alexandru Tiganescu ◽  
Bogdan Grecu ◽  
Iolanda-Gabriela Craifaleanu ◽  
Dragos Toma-Danila ◽  
Stefan-Florin Balan

<p>The impact of natural hazards on structures and infrastructures is a critical issue that needs to be properly addressed by both public and private entities. To better cope with seismic hazard and to mitigate the risk, long-term multi-sensor infrastructure monitoring represents a useful tool for acquiring information on their condition and vulnerability. However, the current increasing data volume collected using sensors is not suitable to be processed with classical standalone methods. Thus, automatic algorithms and decision-making frameworks should be developed to use this data, with minimum intervention from human operators. A case-study for the application of advanced methods is focused on the headquarters of the Institute for Atomic Physics, a 11-story reinforced concrete building, located near Bucharest, Romania. The instrumentation scheme consists of accelerometers installed at the basement, at an intermediate floor and at the top of the structure. The data were continuously recorded, starting with December 2013. More than 80 seismic events with moment magnitude, M<sub>W</sub>, larger than 3.8 were recorded during the monitoring period. The current study covers the long-term evolution and variation of dynamic parameters (one value per hour), based on both ambient noise sources and small and medium magnitude seismic events. The seasonal variation of these parameters will be determined, as well as their daily variation and the differences between values obtained from ambient noise and from earthquake-induced vibrations. Other atmospheric parameters (e.g. temperature, precipitation, wind speed) will be considered in future studies. The goal of the PREVENT project, in the framework of which the research is performed, is to collect multi-disciplinary data and to integrate them into a complex monitoring system. The current study achieved the first step, focusing on data from the seismic sensors and setting up the premises for a multi-sensor, multi-parameter, more reliable infrastructure monitoring system.  </p>


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