Near-surface imaging using ambient-noise body waves

2016 ◽  
Vol 4 (3) ◽  
pp. SJ55-SJ65 ◽  
Author(s):  
Pascal Edme ◽  
David F. Halliday
Keyword(s):  
Ambient Noise ◽  
Body Wave ◽  
Synthetic Data ◽  
Real Data ◽  
Body Waves ◽  
Seismic Survey ◽  
Subsurface Imaging ◽  
Near Surface ◽  
Deconvolution Technique ◽  
Zero Offset

We have introduced a workflow that allows subsurface imaging using upcoming body-wave arrivals extracted from ambient-noise land seismic data. Rather than using the conventional seismic interferometry approach based on correlation, we have developed a deconvolution technique to extract the earth response from the observed periodicity in the seismic traces. The technique consists of iteratively applying a gapped spiking deconvolution, providing multiple-free images with higher resolution than conventional correlation. We have validated the workflow for zero-offset traces with simple synthetic data and real data recorded during a small point-receiver land seismic survey.

scholarly journals Automatic 3D illumination-diagnosis method for large-N arrays: Robust data scanner and machine-learning feature provider

Geophysics ◽  
2019 ◽  
Vol 84 (3) ◽  
pp. Q13-Q25 ◽  
Author(s):  
Michał Chamarczuk ◽  
Michał Malinowski ◽  
Yohei Nishitsuji ◽  
Jan Thorbecke ◽  
Emilia Koivisto ◽  
...  
Keyword(s):  
Ambient Noise ◽  
Body Wave ◽  
Synthetic Data ◽  
Large Data ◽  
Body Waves ◽  
Support Vector ◽  
Full Data ◽  
Noise Sources ◽  
Data Set ◽  
Receiver Array

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.

Regularization and datuming of seismic data by weighted, damped least squares

Geophysics ◽  
2006 ◽  
Vol 71 (5) ◽  
pp. U67-U76 ◽  
Author(s):  
Robert J. Ferguson
Keyword(s):  
Least Squares ◽  
Seismic Data ◽  
Synthetic Data ◽  
Real Data ◽  
Structural Data ◽  
Irregular Sampling ◽  
Data Set ◽  
Near Surface ◽  
Damped Least Squares ◽  
Wavefield Extrapolation

The possibility of improving regularization/datuming of seismic data is investigated by treating wavefield extrapolation as an inversion problem. Weighted, damped least squares is then used to produce the regularized/datumed wavefield. Regularization/datuming is extremely costly because of computing the Hessian, so an efficient approximation is introduced. Approximation is achieved by computing a limited number of diagonals in the operators involved. Real and synthetic data examples demonstrate the utility of this approach. For synthetic data, regularization/datuming is demonstrated for large extrapolation distances using a highly irregular recording array. Without approximation, regularization/datuming returns a regularized wavefield with reduced operator artifacts when compared to a nonregularizing method such as generalized phase shift plus interpolation (PSPI). Approximate regularization/datuming returns a regularized wavefield for approximately two orders of magnitude less in cost; but it is dip limited, though in a controllable way, compared to the full method. The Foothills structural data set, a freely available data set from the Rocky Mountains of Canada, demonstrates application to real data. The data have highly irregular sampling along the shot coordinate, and they suffer from significant near-surface effects. Approximate regularization/datuming returns common receiver data that are superior in appearance compared to conventional datuming.

Large‐scale three‐dimensional seismic models and their interpretive significance

Geophysics ◽  
1990 ◽  
Vol 55 (9) ◽  
pp. 1166-1182 ◽  
Author(s):  
Irshad R. Mufti
Keyword(s):  
Finite Difference ◽  
Wave Field ◽  
Large Scale ◽  
Three Dimensional ◽  
Synthetic Data ◽  
Real Data ◽  
The Real ◽  
Need To Evaluate ◽  
Zero Offset ◽  
Seismic Models

Finite‐difference seismic models are commonly set up in 2-D space. Such models must be excited by a line source which leads to different amplitudes than those in the real data commonly generated from a point source. Moreover, there is no provision for any out‐of‐plane events. These problems can be eliminated by using 3-D finite‐difference models. The fundamental strategy in designing efficient 3-D models is to minimize computational work without sacrificing accuracy. This was accomplished by using a (4,2) differencing operator which ensures the accuracy of much larger operators but requires many fewer numerical operations as well as significantly reduced manipulation of data in the computer memory. Such a choice also simplifies the problem of evaluating the wave field near the subsurface boundaries of the model where large operators cannot be used. We also exploited the fact that, unlike the real data, the synthetic data are free from ambient noise; consequently, one can retain sufficient resolution in the results by optimizing the frequency content of the source signal. Further computational efficiency was achieved by using the concept of the exploding reflector which yields zero‐offset seismic sections without the need to evaluate the wave field for individual shot locations. These considerations opened up the possibility of carrying out a complete synthetic 3-D survey on a supercomputer to investigate the seismic response of a large‐scale structure located in Oklahoma. The analysis of results done on a geophysical workstation provides new insight regarding the role of interference and diffraction in the interpretation of seismic data.

A linear algorithm for ambient seismic noise double beamforming without explicit crosscorrelations

Geophysics ◽  
2021 ◽  
Vol 86 (1) ◽  
pp. F1-F8
Author(s):  
Eileen R. Martin
Keyword(s):  
Correlation Functions ◽  
Seismic Noise ◽  
Ambient Noise ◽  
Computational Cost ◽  
Body Waves ◽  
Ambient Seismic Noise ◽  
Noise Correlation ◽  
Dense Array ◽  
Near Surface ◽  
Noise Interferometry

Geoscientists and engineers are increasingly using denser arrays for continuous seismic monitoring, and they often turn to ambient seismic noise interferometry for low-cost near-surface imaging. Although ambient noise interferometry greatly reduces acquisition costs, the computational cost of pair-wise comparisons between all sensors can be prohibitively slow or expensive for applications in engineering and environmental geophysics. Double beamforming of noise correlation functions is a powerful technique to extract body waves from ambient noise, but it is typically performed via pair-wise comparisons between all sensors in two dense array patches (scaling as the product of the number of sensors in one patch with the number of sensors in the other patch). By rearranging the operations involved in the double beamforming transform, I have developed a new algorithm that scales as the sum of the number of sensors in two array patches. Compared to traditional double beamforming of noise correlation functions, the new method is more scalable, easily parallelized, and it does not require raw data to be exchanged between dense array patches.

Walk‐away VSP using drill noise as a source

Geophysics ◽  
1995 ◽  
Vol 60 (4) ◽  
pp. 978-997 ◽  
Author(s):  
Jacob B. U. Haldorsen ◽  
Douglas E. Miller ◽  
John J. Walsh
Keyword(s):  
Seismic Profile ◽  
Drill String ◽  
Seismic Survey ◽  
Effective Bandwidth ◽  
Walk Away ◽  
Data Set ◽  
Deconvolution Technique ◽  
Noise Data ◽  
Zero Offset ◽  
Noise Signature

We describe a method for extracting and deconvolving a signal generated by a drill bit and collected by an array of surface geophones. The drill‐noise signature is reduced to an effective impulse by means of a multichannel Wiener deconvolution technique, producing a walk‐away reverse vertical seismic profile (VSP) sampled almost continuously in depth. We show how the multichannel technique accounts for noise and for internal drill‐string reflections, automatically limiting the deconvolved data to frequencies containing significant energy. We have acquired and processed a data set from a well in Germany while drilling at a depth of almost 4000 m. The subsurface image derived from these data compares well with corresponding images from a 3-D surface seismic survey, a zero‐offset VSP survey, and a walk‐away VSP survey acquired using conventional wireline techniques. The effective bandwidth of the deconvolved drill‐noise data is comparable to the bandwidth of surface seismic data but significantly smaller than what can be achieved with wireline VSP techniques. Although the processing algorithm does not require the use of sensors mounted on the drill string, these sensors provide a very economic way to compress the data. The sensors on the drill string were also used for accurate timing of the deconvolved drill‐noise data.

Extracting subsurface information from ambient seismic noise — A case study from Germany

Geophysics ◽  
2012 ◽  
Vol 77 (4) ◽  
pp. KS13-KS31 ◽  
Author(s):  
Alexander Goertz ◽  
Barbara Schechinger ◽  
Benjamin Witten ◽  
Matthias Koerbe ◽  
Paul Krajewski
Keyword(s):  
Seismic Noise ◽  
Body Wave ◽  
Source Region ◽  
Low Frequency ◽  
Spectral Ratio ◽  
Velocity Model ◽  
Body Waves ◽  
Seismic Survey ◽  
Ambient Seismic Noise ◽  
Oil Reservoir

We analyzed ambient seismic noise from a broadband passive seismic survey acquired in an urban area in Germany. Despite a high level of anthropogenic noise, we observe lateral variations in the quasi-stationary spectra that are of natural origin and indicative of the subsurface in the survey area. The best diagnostic is the ellipticity spectrum which is the spectral ratio of the vertical over the horizontal components. Deviations of the observed spectra from a pure Rayleigh-wave ellipticity allow an approximate separation of surface-wave from body-wave components in the analyzed frequency range, distinguishing shallow (upper tens of meters) from deeper (upper three kilometers) subsurface effects. We observe an increase of vertically polarized body waves between 1 and 4 Hz that is correlated to a subsurface structure that contains an oil reservoir at about 2-km depth. We located the source of the observed body wave microtremor in depth by applying an elastic wavefield back projection and imaging technique. The method includes normalization by the impulse response of the velocity model, effects of the receiver geometry, and lateral variation of incoherent noise. The source region of the low-frequency body wave microtremor is centered above the location of the oil reservoir. Two possible explanations for the deep microtremor are elastic body-wave scattering due to the impedance contrast of the structural trap, and viscoelastic scattering due to poroelastic effects in the partially saturated reservoir.

Seismoelectric Surface-Wave Analysis for Characterization of Formation Properties, using Dispersive Relative Spectral Amplitudes

Geophysics ◽  
2021 ◽  
pp. 1-25
Author(s):  
N. Grobbe ◽  
S. A. L. de Ridder
Keyword(s):  
Surface Wave ◽  
Body Wave ◽  
Electrical Potential ◽  
Relative Strength ◽  
Body Waves ◽  
Fluid Viscosity ◽  
Near Surface ◽  
Em Field ◽  
Seismic Body Waves

We study seismoelectric (SE) surface-wave signals and find that they can be used to infer changes in the SE coupling properties at depth. Seismoelectric surface-wave signals have much higher amplitudes than seismoelectric body-wave signals. We propose to measure both the seismic and the electrical potential or electromagnetic (EM) field along the surface of the Earth. We use Dispersive Relative Spectral Amplitudes (DRSA) that measure the frequency-dependent relative strength of electrical signals versus seismic signals associated with seismoelectric surface-wave signals. We show that the DRSA have sensitivity to contrasts in the electrokinetic coupling coefficient and other relevant petrophysical properties at depth. Our discovery can mitigate the major limitation that plagues body wave-based SE methods: the relative weakness of the converted, EM signals from seismic body waves. We envision applications to characterize subsurface rock, fluid and fluid-flow properties (e.g. porosity, permeability, and dynamic fluid viscosity, salinity) in the near surface, for aquifers, and shallow geothermal reservoirs.

scholarly journals Synthetic Modeling of Ambient Seismic Noise Tomography Data

2021 ◽  
Vol 873 (1) ◽  
pp. 012096
Author(s):  
Firman Syaifuddin ◽  
Andri Dian Nugraha ◽  
Zulfakriza ◽  
Shindy Rosalia
Keyword(s):  
Seismic Noise ◽  
Ambient Noise ◽  
Noise Analysis ◽  
Reference Signal ◽  
Synthetic Data ◽  
Data Modeling ◽  
The United States ◽  
Ambient Seismic Noise ◽  
Near Surface ◽  
Tomography Method

Abstract Ambient seismic noise tomography is one of the most widely used methods in seismological studies today, especially after a comprehensive Earth noise model was published and noise analysis was performed on the IRIS Global Seismographic Network. Furthermore, the Power Spectral Density technique was introduced to identify background seismic noise in the United States. Many studies have been carried out using the ambient seismic noise tomography method which can be broadly grouped into several groups based on the objectives and research targets, such as to determine the structure of the earth’s crust and the upper mantle, to know the thickness of the sedimentary basins, to know the tectonic settings and geological structures, to know volcanic systems and geothermal systems, knowing near-surface geological features and as a monitoring effort the Ambient Noise Tomography method carried out by repeated measurements or time lapse. In this study, we investigate the characteristics of the ambient noise seismic tomography method, both its advantages and limitations of the method by utilizing synthetic data modeling using a simple geological model. Synthetic data is generated based on 1D dispersion curve forward modelling and the forward modeling of surface waves travel time for each period, which is then convoluted with the wavelets of each periods, then doing reverse correlation using a reference signal to produce synthetic recording data. We found that the estimate target depth and vertical resolution depend on the recorded data periods and the synthetic data modeling can be used as a basis in determining the acquisition design.

scholarly journals Seismic Characterization of the Nevada National Security Site Using Joint Body Wave, Surface Wave, and Gravity Inversion

2019 ◽  
Vol 110 (1) ◽  
pp. 110-126
Author(s):  
Leiph Preston ◽  
Christian Poppeliers ◽  
David J. Schodt
Keyword(s):  
Surface Wave ◽  
National Security ◽  
Surface Waves ◽  
Body Wave ◽  
Wave Dispersion ◽  
The Body ◽  
Body Waves ◽  
Gravity Inversion ◽  
Surface Wave Dispersion ◽  
Near Surface

ABSTRACT As a part of the series of Source Physics Experiments (SPE) conducted on the Nevada National Security Site in southern Nevada, we have developed a local-to-regional scale seismic velocity model of the site and surrounding area. Accurate earth models are critical for modeling sources like the SPE to investigate the role of earth structure on the propagation and scattering of seismic waves. We combine seismic body waves, surface waves, and gravity data in a joint inversion procedure to solve for the optimal 3D seismic compressional and shear-wave velocity structures and earthquake locations subject to model smoothness constraints. Earthquakes, which are relocated as part of the inversion, provide P- and S-body-wave absolute and differential travel times. Active source experiments in the region augment this dataset with P-body-wave absolute times and surface-wave dispersion data. Dense ground-based gravity observations and surface-wave dispersion derived from ambient noise in the region fill in many areas where body-wave data are sparse. In general, the top 1–2 km of the surface is relatively poorly sampled by the body waves alone. However, the addition of gravity and surface waves to the body-wave dataset greatly enhances structural resolvability in the near surface. We discuss the methodology we developed for simultaneous inversion of these disparate data types and briefly describe results of the inversion in the context of previous work in the region.

Retrieval of amplitude and attenuation from ambient seismic noise: synthetic data and practical considerations

2020 ◽  
Vol 222 (1) ◽  
pp. 544-559
Author(s):  
Lianqing Zhou ◽  
Xiaodong Song ◽  
Richard L Weaver
Keyword(s):  
Numerical Simulation ◽  
Seismic Data ◽  
Seismic Noise ◽  
Ambient Noise ◽  
Linear Array ◽  
Noise Source ◽  
Synthetic Data ◽  
Real Data ◽  
Noise Correlation ◽  
Theoretical Derivation

SUMMARY Ambient noise correlation has been used extensively to retrieve traveltimes of surface waves. However, studies of retrieving amplitude information and attenuation from ambient noise are limited. In this study, we develop methods and strategies to extract Rayleigh wave amplitude and attenuation from ambient noise correlation, based on theoretical derivation, numerical simulation, and practical considerations of real seismic data. The synthetic data included a numerical simulation of a highly anisotropic noise source and Earth-like temporally varying strength. Results from synthetic data validate that amplitudes and attenuations can indeed be extracted from noise correlations for a linear array. A temporal flattening procedure is effective in speeding up convergence while preserving relative amplitudes. The traditional one-bit normalization and other types of temporal normalization that are applied to each individual station separately are problematic in recovering attenuation and should be avoided. In this study, we propose an ‘asynchronous’ temporal flattening procedure for real data that does not require all stations to have data at the same time. Furthermore, we present the detailed procedure for amplitude retrieval from ambient noise. Tests on real data suggest attenuations extracted from our noise-based methods are comparable with those from earthquakes. Our study shows an exciting promise of retrieving amplitude and attenuation information from ambient noise correlations and suggests practical considerations for applications to real data.

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