scholarly journals Passive seismic monitoring with nonstationary noise sources

Geophysics ◽  
2017 ◽  
Vol 82 (4) ◽  
pp. KS57-KS70 ◽  
Author(s):  
Evan Delaney ◽  
Laura Ermert ◽  
Korbinian Sager ◽  
Alexander Kritski ◽  
Sascha Bussat ◽  
...  
Keyword(s):  
Field Experiments ◽  
Noise Source ◽  
Model Space ◽  
Real Data ◽  
Seismic Monitoring ◽  
Time Dependent ◽  
Source Distribution ◽  
False Alarms ◽  
Apparent Velocity ◽  
Noise Sources

Heterogeneous, nonstationary noise sources can cause traveltime errors in noise-based seismic monitoring. The effect worsens with increasing temporal resolution. This may lead to costly false alarms in response to safety concerns and limit our confidence in the results when these systems are used for quasi-real-time monitoring of subsurface changes. Therefore, we have developed a new method to quantify and correct these traveltime errors to more accurately monitor subsurface conditions at daily or even hourly timescales. It is based on the inversion of noise correlation asymmetries for the time-dependent distribution of noise sources. The source model is then used to simulate time-dependent ambient noise correlations. The comparison with correlations computed for homogeneous noise sources yields traveltime errors that translate into spurious changes of the subsurface. The application of our method to data acquired at Statoil’s SWIM array, a permanent seismic installation at the Oseberg field, demonstrates that fluctuations in the noise source distribution may induce apparent velocity changes of 0.25% within one day. Such biases thereby likely mask realistic subsurface variations expected on these timescales. These errors are systematic, being primarily dependent on the noise source location and strength, and not on the interstation distance. Our method can then be used to correct for source-induced traveltime errors by subtracting these quantified biases in either the data or model space. It can furthermore establish a minimum threshold for which we may reliably attribute traveltime changes to actual subsurface changes, should we not correct for these errors. In addition to the aforementioned real data scenario, we apply our method to a synthetic case for a daily passive monitoring overburden feasibility study. Synthetics and field experiments validated the method’s theory and application.

Rapid Global Finite-Frequency Ambient Noise Source Inversion

2020 ◽  
Author(s):  
Jonas Igel ◽  
Laura Ermert ◽  
Andreas Fichtner
Keyword(s):  
Ambient Noise ◽  
Noise Source ◽  
Computational Cost ◽  
User Interaction ◽  
Real Data ◽  
Source Distribution ◽  
Source Inversion ◽  
Finite Frequency ◽  
Noise Sources ◽  
Cross Correlations

<p>Common assumptions in ambient noise seismology such as Green’s function retrieval and equipartitioned wavefields are often not met in the Earth. Full waveform ambient noise tomography methods are free of such assumptions, as they implement knowledge of the time- and space-dependent ambient noise source distribution, whilst also taking finite-frequency effects into account. Such methods would greatly simplify near real-time monitoring of the sub-surface. Additionally, the distribution of the secondary microseisms could act as a new observable of the ocean state since its mechanism is well understood (e.g. Ardhuin et al., 2011).</p><p>To efficiently forward-model global noise cross-correlations we implement (1) pre-computed high-frequency wavefields obtained using, for example, AxiSEM (Nissen-Meyer et al., 2014), and (2) spatially variable grids, both of which greatly reduce the computational cost. Global cross-correlations for any source distribution can be computed within a few seconds in the microseismic frequency range (up to 0.2 Hz). Similarly, we can compute the finite-frequency sensitivity kernels which are then used to perform a gradient-based iterative inversion of the power-spectral density of the noise source distribution. We take a windowed logarithmic energy ratio of the causal and acausal branches of the cross-correlations as measurement, which is largely insensitive to unknown 3D Earth structures.</p><p>Due to its parallelisation on a cluster, our inversion tool is able to rapidly invert for the global microseismic noise source distribution with minimal required user interaction. Synthetic and real data inversions show promising results for noise sources in the North Atlantic with the structure and spatial distribution resolved at scales of a few hundred kilometres. Finally, daily noise sources maps could be computed by combining our inversion tool with a daily data download and processing toolkit.</p>

scholarly journals Noise-based ballistic wave passive seismic monitoring. Part 1: body waves

2020 ◽  
Vol 221 (1) ◽  
pp. 683-691 ◽  
Author(s):  
F Brenguier ◽  
R Courbis ◽  
A Mordret ◽  
X Campman ◽  
P Boué ◽  
...  
Keyword(s):  
Seismic Velocity ◽  
Noise Source ◽  
Seismic Monitoring ◽  
Body Waves ◽  
P Wave ◽  
New Technique ◽  
Apparent Velocity ◽  
Near Surface ◽  
Velocity Increase ◽  
Passive Seismic

SUMMARY Unveiling the mechanisms of earthquake and volcanic eruption preparation requires improving our ability to monitor the rock mass response to transient stress perturbations at depth. The standard passive monitoring seismic interferometry technique based on coda waves is robust but recovering accurate and properly localized P- and S-wave velocity temporal anomalies at depth is intrinsically limited by the complexity of scattered, diffracted waves. In order to mitigate this limitation, we propose a complementary, novel, passive seismic monitoring approach based on detecting weak temporal changes of velocities of ballistic waves recovered from seismic noise correlations. This new technique requires dense arrays of seismic sensors in order to circumvent the bias linked to the intrinsic high sensitivity of ballistic waves recovered from noise correlations to changes in the noise source properties. In this work we use a dense network of 417 seismometers in the Groningen area of the Netherlands, one of Europe's largest gas fields. Over the course of 1 month our results show a 1.5 per cent apparent velocity increase of the P wave refracted at the basement of the 700-m-thick sedimentary cover. We interpret this unexpected high value of velocity increase for the refracted wave as being induced by a loading effect associated with rainfall activity and possibly canal drainage at surface. We also observe a 0.25 per cent velocity decrease for the direct P-wave travelling in the near-surface sediments and conclude that it might be partially biased by changes in time in the noise source properties even though it appears to be consistent with complementary results based on ballistic surface waves presented in a companion paper and interpreted as a pore pressure diffusion effect following a strong rainfall episode. The perspective of applying this new technique to detect continuous localized variations of seismic velocity perturbations at a few kilometres depth paves the way for improved in situ earthquake, volcano and producing reservoir monitoring.

Heterogeneous cloud-supercomputing framework for daily seismic noise source inversion

2020 ◽  
Author(s):  
Alexey Gokhberg ◽  
Laura Ermert ◽  
Jonas Igel ◽  
Andreas Fichtner
Keyword(s):  
Real Time ◽  
Seismic Noise ◽  
Cross Correlation ◽  
Noise Source ◽  
Workflow Management ◽  
Source Distribution ◽  
Ambient Seismic Noise ◽  
Source Inversion ◽  
Finite Frequency ◽  
Noise Sources

<p>The study of ambient seismic noise sources and their time- and space-dependent distribution is becoming a crucial component of the real-time monitoring of various geosystems, including active fault zones and volcanoes, as well as geothermal and hydrocarbon reservoirs. In this context, we have previously implemented a combined cloud - HPC infrastructure for production of ambient source maps with high temporal resolution. It covers the entire European continent and the North Atlantic, and is based on seismic data provided by the ORFEUS infrastructure. The solution is based on the Application-as-a-Service concept and includes (1) acquisition of data from distributed ORFEUS data archives, (2) noise source mapping, (3) workflow management, and (4) front-end Web interface to end users.</p><p>We present the new results of this ongoing project conducted with support of the Swiss National Supercomputing Centre (CSCS). Our recent goal has been transitioning from mapping the seismic noise sources towards modeling them based on our new method for near real-time finite-frequency ambient seismic noise source inversion. To invert for the power spectral density of the noise source distribution of the secondary microseisms we efficiently forward model global cross-correlation wavefields for any noise distribution. Subsequently, a gradient-based iterative inversion method employing finite-frequency sensitivity kernels is implemented to reduce the misfit between synthetic and observed cross correlations.</p><p>During this research we encountered substantial challenges related to the large data volumes and high computational complexity of involved algorithms. We handle these problems by using the CSCS massively parallel heterogeneous supercomputer "Piz Daint". We also apply various specialized numeric techniques which include: (1) using precomputed Green's functions databases generated offline with Axisem and efficiently extracted with Instaseis package and (2) our previously developed high performance package for massive cross correlation of seismograms using GPU accelerators. Furthermore, due to the inherent restrictions of supercomputers, some crucial components of the processing pipeline including the data acquisition and workflow management are deployed on the OpenStack cloud environment. The resulting solution combines the specific advantages of the supercomputer and cloud platforms thus providing a viable distributed platform for the large-scale modeling of seismic noise sources.</p>

scholarly journals The sources of jet noise: experimental evidence

2008 ◽  
Vol 615 ◽  
pp. 253-292 ◽  
Author(s):  
CHRISTOPHER K. W. TAM ◽  
K. VISWANATHAN ◽  
K. K. AHUJA ◽  
J. PANDA
Keyword(s):  
High Speed ◽  
Noise Source ◽  
Jet Noise ◽  
Polar Angle ◽  
Sound Field ◽  
Source Distribution ◽  
Far Field ◽  
Noise Sources ◽  
Directional Information ◽  
Jet Mixing

The primary objective of this investigation is to determine experimentally the sources of jet mixing noise. In the present study, four different approaches are used. It is reasonable to assume that the characteristics of the noise sources are imprinted on their radiation fields. Under this assumption, it becomes possible to analyse the characteristics of the far-field sound and then infer back to the characteristics of the sources. The first approach is to make use of the spectral and directional information measured by a single microphone in the far field. A detailed analysis of a large collection of far-field noise data has been carried out. The purpose is to identify special characteristics that can be linked directly to those of the sources. The second approach is to measure the coherence of the sound field using two microphones. The autocorrelations and cross-correlations of these measurements offer not only valuable information on the spatial structure of the noise field in the radial and polar angle directions, but also on the sources inside the jet. The third approach involves measuring the correlation between turbulence fluctuations inside a jet and the radiated noise in the far field. This is the most direct and unambiguous way of identifying the sources of jet noise. In the fourth approach, a mirror microphone is used to measure the noise source distribution along the lengths of high-speed jets. Features and trends observed in noise source strength distributions are expected to shed light on the source mechanisms. It will be shown that all four types of data indicate clearly the existence of two distinct noise sources in jets. One source of noise is the fine-scale turbulence and the other source is the large turbulence structures of the jet flow. Some of the salient features of the sound field associated with the two noise sources are reported in this paper.

scholarly journals Optimal processing for seismic noise correlations

2020 ◽  
Vol 223 (3) ◽  
pp. 1548-1564
Author(s):  
Andreas Fichtner ◽  
Daniel Bowden ◽  
Laura Ermert
Keyword(s):  
Seismic Noise ◽  
Wide Spectrum ◽  
Real Data ◽  
Seismic Wave Propagation ◽  
Small Time ◽  
Time Dependent ◽  
Noise Sources ◽  
Optimal Processing ◽  
Accelerate Convergence ◽  
Correlation Process

SUMMARY A wide spectrum of processing schemes is commonly applied during the calculation of seismic noise correlations. This is intended to suppress large-amplitude transient and monochromatic signals, to accelerate convergence of the correlation process or to modify raw correlations into more plausible approximations of interstation Green’s functions. Many processing schemes, such as one-bit normalization or various other nonlinear normalizations, clearly break the linear physics of seismic wave propagation. This naturally raises the question: To what extent are the resulting noise correlations physically meaningful quantities? In this contribution, we demonstrate that commonly applied processing methods may indeed introduce an unphysical component into noise correlations. This affects not only noise correlation amplitudes but also, to a lesser extent, time-dependent phase information. The profound consequences are that most processed correlations cannot be entirely explained by any combination of Earth structure and noise sources, and that inversion results may thus be polluted. The positive component of our analysis is a new and easily applicable method that allows us to modify any existing processing such that it becomes optimal in the sense of (1) completely avoiding the unphysical component while (2) approximating the result of the original processing as closely as possible. The resulting optimal schemes can be derived purely on the basis of observed noise, without any knowledge of or assumptions on the nature of noise sources. In addition to the theoretical analysis, we present illustrative real-data examples from the Irish National Seismic Network and the Lost Hills array in Central California. We anticipate that optimal processing schemes may be most useful in applications that exploit complete correlation waveforms, amplitudes and weak arrivals, or small (time-dependent) phase shifts.

Imaging noise sources: comparing and combining a matched-field processing technique with finite-frequency noise source inversions

2021 ◽  
Author(s):  
Jonas Igel ◽  
Daniel Bowden ◽  
Korbinian Sager ◽  
Andreas Fichtner
Keyword(s):  
Noise Source ◽  
Time Window ◽  
Waveform Inversion ◽  
Temporal Variations ◽  
Source Distribution ◽  
Frequency Noise ◽  
Finite Frequency ◽  
Noise Sources ◽  
Matched Field Processing ◽  
Full Waveform

<p>Imaging the spatio-temporal variations of ambient seismic noise sources can provide important information to improve near real-time monitoring and noise tomography. Various methods have been developed to tackle this problem. For example, Matched-Field Processing (MFP) offers an efficient data-driven approach by testing different noise source locations and subsequently correlating and stacking. A more rigorous approach is treating it as a finite-frequency full-waveform inversion problem. In contrast to the MFP technique, an inversion framework allows for the incorporation of prior information and subsequent iterative updates of the noise source distribution by numerically modelling correlations and source sensitivity kernels. Bowden et al. (2020) discuss the similarities between these two methods and how one can be derived from the other. </p><p>We aim to compare and contrast the two methods using real data from a regional to a global scale to locate the secondary microseismic sources in the ocean. Igel et al. (2021, in prep) use a logarithmic energy ratio as measurement for the sensitivity kernels, which is chosen due to its robustness with respect to unknown 3D Earth structures. However, some disadvantages of this type of measurement are not considering absolute amplitudes and discarding information outside of the expected surface wave arrival time window. By combining the two methods and first using MFP to create an initial model for the inversion, we are able to steer the inversion in the right direction, allowing us to use a more elaborate full-waveform measurement in the inversion and hence increasing the resolution and quality of the final model. </p><p>Results for noise source inversions in the ocean on a daily basis using the combination of the two methods will be presented. This work paves the way for publicly available, daily, multi-scale ambient noise source maps.</p>

The Research of Cylindrical Noise Source Distribution Using Near-Field High-Resolution Location Methods Based on MVDR Algorithm

2012 ◽  
Vol 226-228 ◽  
pp. 487-492 ◽  
Author(s):  
Huan Chen ◽  
Feng Xu ◽  
Shuai Su
Keyword(s):  
High Resolution ◽  
Source Localization ◽  
Noise Source ◽  
Near Field ◽  
Source Distribution ◽  
Beam Forming ◽  
Noise Sources ◽  
Cylinder Model ◽  
Measurement Surface ◽  
Focused Beam

According to the lack of cylinder-model noise source localization technology based on near-field focused beam-forming, the paper aimed to find a near-field high-resolution method of the cylindrical noise source which is applied to measure the model as cylinder-models. This method established a near-field measurement model of noise sources using cylindrical measurement surface, and applied MVDR algorithm to noise sources localization. Reconstruct the cylinder measurement surface through the joint amplitude-phase compensation to achieve the noise source high-resolution localization and relative intensity estimates in the near-field. Verify the availability of this method through the simulations, which provided a theoretical basis for the next practical engineering application of the cylinder-model noise source localization based on near-field focused beam-forming.

COVID-19: Time-Dependent Effective Reproduction Number and Sub-notification Effect Estimation Modeling (Preprint)

2020 ◽  
Author(s):  
Eduardo Atem De Carvalho ◽  
Rogerio Atem De Carvalho
Keyword(s):  
New York ◽  
Reproduction Number ◽  
Moving Average ◽  
Real Data ◽  
Time Dependent ◽  
Initial Value ◽  
Health Authorities ◽  
Reproduction Numbers ◽  
Effect Estimation ◽  
The Impact

BACKGROUND Since the beginning of the COVID-19 pandemic, researchers and health authorities have sought to identify the different parameters that govern their infection and death cycles, in order to be able to make better decisions. In particular, a series of reproduction number estimation models have been presented, with different practical results. OBJECTIVE This article aims to present an effective and efficient model for estimating the Reproduction Number and to discuss the impacts of sub-notification on these calculations. METHODS The concept of Moving Average Method with Initial value (MAMI) is used, as well as a model for Rt, the Reproduction Number, is derived from experimental data. The models are applied to real data and their performance is presented. RESULTS Analyses on Rt and sub-notification effects for Germany, Italy, Sweden, United Kingdom, South Korea, and the State of New York are presented to show the performance of the methods here introduced. CONCLUSIONS We show that, with relatively simple mathematical tools, it is possible to obtain reliable values for time-dependent, incubation period-independent Reproduction Numbers (Rt). We also demonstrate that the impact of sub-notification is relatively low, after the initial phase of the epidemic cycle has passed.

Noise source location and scaling of subsonic upper-surface blowing

2020 ◽  
Vol 19 (3-5) ◽  
pp. 191-206
Author(s):  
Trae L Jennette ◽  
Krish K Ahuja
Keyword(s):  
Strouhal Number ◽  
Noise Source ◽  
Low Frequency ◽  
Directivity Pattern ◽  
Source Location ◽  
Dipole Source ◽  
Frequency Noise ◽  
Noise Sources ◽  
Trailing Edge ◽  
Trailing Edge Noise

This paper deals with the topic of upper surface blowing noise. Using a model-scale rectangular nozzle of an aspect ratio of 10 and a sharp trailing edge, detailed noise contours were acquired with and without a subsonic jet blowing over a flat surface to determine the noise source location as a function of frequency. Additionally, velocity scaling of the upper surface blowing noise was carried out. It was found that the upper surface blowing increases the noise significantly. This is a result of both the trailing edge noise and turbulence downstream of the trailing edge, referred to as wake noise in the paper. It was found that low-frequency noise with a peak Strouhal number of 0.02 originates from the trailing edge whereas the high-frequency noise with the peak in the vicinity of Strouhal number of 0.2 originates near the nozzle exit. Low frequency (low Strouhal number) follows a velocity scaling corresponding to a dipole source where as the high Strouhal numbers as quadrupole sources. The culmination of these two effects is a cardioid-shaped directivity pattern. On the shielded side, the most dominant noise sources were at the trailing edge and in the near wake. The trailing edge mounting geometry also created anomalous acoustic diffraction indicating that not only is the geometry of the edge itself important, but also all geometry near the trailing edge.

scholarly journals Innovative techniques for the improvement of industrial noise sources identification by beamforming

Noise Mapping ◽  
2021 ◽  
Vol 8 (1) ◽  
pp. 129-137
Author(s):  
Giorgio Baldinelli ◽  
Francesco Bianchi ◽  
Danilo Costarelli ◽  
Francesco D’Alessandro ◽  
Flavio Scrucca ◽  
...  
Keyword(s):  
Image Processing ◽  
Noise Source ◽  
Focal Length ◽  
Noise Sources ◽  
Geometric Information ◽  
Industrial Noise ◽  
Sources Identification ◽  
Innovative Technique ◽  
Innovative Techniques

Abstract An innovative technique based on beamforming is implemented, at the aim of detecting the distances from the observer and the relative positions among the noise sources themselves in multisource noise scenarios. By means of preliminary activities to assess the optical camera focal length and stereoscopic measurements followed by image processing, the geometric information in the source-microphone direction is retrieved, a parameter generally missed in classic beamforming applications. A corollary of the method consists of the possibility of obtaining also the distance among different noise sources which could be present in a multisource environment. A loss of precision is found when the effect of the high acoustic reflectivity ground interferes with the noise source.

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