scholarly journals Application of Seismic Interferometry by Multidimensional Deconvolution to Earthquake Data Recorded in Malargüe, Argentina

2021 ◽  
Vol 13 (23) ◽  
pp. 4818
Author(s):  
Faezeh Shirmohammadi ◽  
Deyan Draganov ◽  
Mohammad Reza Hatami ◽  
Cornelis Weemstra
Keyword(s):  
Surface Wave ◽  
Surface Waves ◽  
Power Spectra ◽  
Site Amplification ◽  
Seismic Array ◽  
Seismic Interferometry ◽  
Seismic Responses ◽  
Central Chile ◽  
Earthquake Data

Seismic interferometry (SI) refers to the principle of generating new seismic responses using crosscorrelations of existing wavefield recordings. In this study, we report on the use of a specific interferometric approach, called seismic interferometry by multidimensional deconvolution (SI by MDD), for the purpose of retrieving surface-wave responses. In theory, SI by MDD suffers less from irregularities in the distribution of (passive) sources than conventional SI. Here, we confirm this advantage for the application to surface waves originating from regional earthquakes close to Central Chile. For that purpose, we use the Malargüe seismic array in Argentina. This T-shaped array consists of two perpendicular lines of stations, which makes it rather suitable for the application of SI by MDD. Comparing the responses retrieved through SI by MDD to the responses retrieved using conventional SI, we find that the application of SI by MDD results in surface-wave responses that are both more accurate and more stable than surface-wave responses that are retrieved using conventional SI. That is, our results demonstrate that SI by MDD suffers less from non-uniformly distributed earthquakes and differences in the power spectra of earthquake responses. In addition, we show that SI by MDD mitigates the effect of site amplification on the retrieved surface waves.

LONG‐PERIOD SIGNAL PROCESSING RESULTS FOR THE LARGE APERTURE SEISMIC ARRAY

Geophysics ◽  
1969 ◽  
Vol 34 (3) ◽  
pp. 305-329 ◽  
Author(s):  
J. Capon ◽  
R. J. Greenfield ◽  
R. T. Lacoss
Keyword(s):  
Signal Processing ◽  
Surface Wave ◽  
Maximum Likelihood ◽  
Surface Waves ◽  
Body Wave ◽  
Seismic Array ◽  
Seismic Events ◽  
Long Period ◽  
Large Aperture ◽  
Period Data

The results of a series of off‐line signal processing experiments are presented for long‐period data obtained from the Large Aperture Seismic Array (LASA) located in eastern Montana. The signal‐to‐noise ratio gains obtained with maximum‐likelihood processing, as well as other simpler forms of processing, are presented for body‐wave as well as surface‐wave phases. A discussion of the frequency‐wavenumber characteristics of the noise which led to these results is also given. On the basis of these experiments, several recommendations are made concerning optimum long‐period array configurations and on‐line or off‐line processing methods. The usefulness of maximum‐likelihood processing in suppressing an interfering teleseism is demonstrated. An experiment is given in which maximum‐likelihood processing achieved about 20 db suppression of an interfering teleseism, while simpler forms of processing such as beam‐forming obtained about 11 db. The matched filtering of surface waves using chirp waveforms is shown to be highly effective. A useful discriminant for distinguishing between natural seismic events and underground nuclear explosions, using both the long‐period and short‐period data, was found to be the relationship between the surface‐wave and body‐wave magnitudes. Measurements of this discriminant made on events from four tectonic regions of the earth are presented. It is shown that 60 and 100 percent detectability of surface waves for natural seismic events from the Central Asian‐Kurile Islands‐Kamchatka region occurs at about LASA body‐wave magnitudes 4.5 and 4.9, respectively.

A comprehensive comparison between the refraction microtremor and seismic interferometry methods for phase-velocity estimation

Geophysics ◽  
2017 ◽  
Vol 82 (6) ◽  
pp. EN99-EN108 ◽  
Author(s):  
Zongbo Xu ◽  
T. Dylan Mikesell ◽  
Jianghai Xia ◽  
Feng Cheng
Keyword(s):  
Surface Wave ◽  
Surface Waves ◽  
Wave Velocity ◽  
Velocity Estimation ◽  
Seismic Interferometry ◽  
S Wave ◽  
Noise Sources ◽  
Surface Wave Dispersion ◽  
Near Surface ◽  
Refraction Microtremor

Passive-source seismic-noise-based surface-wave methods are now routinely used to investigate the near-surface geology in urban environments. These methods estimate the S-wave velocity of the near surface, and two methods that use linear recording arrays are seismic interferometry (SI) and refraction microtremor (ReMi). These two methods process noise data differently and thus can yield different estimates of the surface-wave dispersion, the data used to estimate the S-wave velocity. We have systematically compared these two methods using synthetic data with different noise source distributions. We arrange sensors in a linear survey grid, which is conveniently used in urban investigations (e.g., along roads). We find that both methods fail to correctly determine the low-frequency dispersion characteristics when outline noise sources become stronger than inline noise sources. We also identify an artifact in the ReMi method and theoretically explain the origin of this artifact. We determine that SI combined with array-based analysis of surface waves is the more accurate method to estimate surface-wave phase velocities because SI separates surface waves propagating in different directions. Finally, we find a solution to eliminate the ReMi artifact that involves the combination of SI and the [Formula: see text]-[Formula: see text] transform, the array processing method that underlies the ReMi method.

scholarly journals Interferometric ground-roll removal: Attenuation of scattered surface waves in single-sensor data

Geophysics ◽  
2010 ◽  
Vol 75 (2) ◽  
pp. SA15-SA25 ◽  
Author(s):  
David F. Halliday ◽  
Andrew Curtis ◽  
Peter Vermeer ◽  
Claudio Strobbia ◽  
Anna Glushchenko ◽  
...  
Keyword(s):  
Surface Wave ◽  
Surface Waves ◽  
Seismic Data ◽  
Sensor Data ◽  
Seismic Survey ◽  
Seismic Interferometry ◽  
Near Surface ◽  
Reflection Data ◽  
Ground Roll ◽  
Single Sensor

Land seismic data are contaminated by surface waves (or ground roll). These surface waves are a form of source-generated noise and can be strongly scattered by near-surface heterogeneities. The resulting scattered ground roll can be particularly difficult to separate from the desired reflection data, especially when this scattered ground roll propagates in the crossline direction. We have used seismic interferometry to estimate scattered surface waves, recorded during an exploration seismic survey, between pairs of receiver locations. Where sources and receivers coincide, these interreceiver surface-wave estimates were adaptively subtracted from the data. This predictive-subtraction process can successfully attenuate scattered surface waves while preserving the valuable reflected arrivals, forming a new method of scattered ground-roll attenuation. We refer to this as interferometric ground-roll removal.

scholarly journals Interferometric surface-wave isolation and removal

Geophysics ◽  
2007 ◽  
Vol 72 (5) ◽  
pp. A69-A73 ◽  
Author(s):  
David F. Halliday ◽  
Andrew Curtis ◽  
Johan O. A. Robertsson ◽  
Dirk-Jan van Manen
Keyword(s):  
Surface Wave ◽  
Data Quality ◽  
Surface Waves ◽  
Survey Data ◽  
Seismic Data ◽  
Body Wave ◽  
Seismic Survey ◽  
Seismic Interferometry ◽  
Wave Component ◽  
Ground Roll

The removal of surface waves (ground roll) from land seismic data is critical in seismic processing because these waves tend to mask informative body-wave arrivals. Removal becomes difficult when surface waves are scattered, and data quality is often impaired. We apply a method of seismic interferometry, using both sources and receivers at the surface, to estimate the surface-wave component of the Green’s function between any two points. These estimates are subtracted adaptively from seismic survey data, providing a new method of ground-roll removal that is not limited to nonscattering regions.

Guided Surface Waves on an Elastic Half Space

1971 ◽  
Vol 38 (4) ◽  
pp. 899-905 ◽  
Author(s):  
L. B. Freund
Keyword(s):  
Wave Propagation ◽  
Surface Wave ◽  
Surface Waves ◽  
Half Space ◽  
Body Wave ◽  
Three Dimensional ◽  
Elastic Half Space ◽  
Normal Displacement ◽  
Rigid Barrier ◽  
Wave Disturbances

Three-dimensional wave propagation in an elastic half space is considered. The half space is traction free on half its boundary, while the remaining part of the boundary is free of shear traction and is constrained against normal displacement by a smooth, rigid barrier. A time-harmonic surface wave, traveling on the traction free part of the surface, is obliquely incident on the edge of the barrier. The amplitude and the phase of the resulting reflected surface wave are determined by means of Laplace transform methods and the Wiener-Hopf technique. Wave propagation in an elastic half space in contact with two rigid, smooth barriers is then considered. The barriers are arranged so that a strip on the surface of uniform width is traction free, which forms a wave guide for surface waves. Results of the surface wave reflection problem are then used to geometrically construct dispersion relations for the propagation of unattenuated guided surface waves in the guiding structure. The rate of decay of body wave disturbances, localized near the edges of the guide, is discussed.

Surface wave attenuation of seismic records with the co-core trace transform filter

Geophysics ◽  
2011 ◽  
Vol 76 (6) ◽  
pp. V115-V128 ◽  
Author(s):  
Ning Wu ◽  
Yue Li ◽  
Baojun Yang
Keyword(s):  
Surface Wave ◽  
Surface Waves ◽  
Field Data ◽  
Wave Attenuation ◽  
Seismic Events ◽  
Data Sets ◽  
Transform Domain ◽  
Recent Developments ◽  
Seismic Records ◽  
Trace Transform

To remove surface waves from seismic records while preserving other seismic events of interest, we introduced a transform and a filter based on recent developments in image processing. The transform can be seen as a weighted Radon transform, in particular along linear trajectories. The weights in the transform are data dependent and designed to introduce large amplitude differences between surface waves and other events such that surface waves could be separated by a simple amplitude threshold. This is a key property of the filter and distinguishes this approach from others, such as conventional ones that use information on moveout ranges to apply a mask in the transform domain. Initial experiments with synthetic records and field data have demonstrated that, with the appropriate parameters, the proposed trace transform filter performs better both in terms of surface wave attenuation and reflected signal preservation than the conventional methods. Further experiments on larger data sets are needed to fully assess the method.

Estimates of Surface Waves Using Subsurface EM-APEX Floats under Typhoon Fanapi 2010

2018 ◽  
Vol 35 (5) ◽  
pp. 1053-1075 ◽  
Author(s):  
Je-Yuan Hsu ◽  
Ren-Chieh Lien ◽  
Eric A. D’Asaro ◽  
Thomas B. Sanford
Keyword(s):  
Surface Wave ◽  
Surface Waves ◽  
Wave Spectrum ◽  
Nonlinear Least Squares ◽  
Peak Frequency ◽  
Wave Propagation Direction ◽  
Model Studies ◽  
Surface Wave Propagation ◽  
Left Quadrant ◽  
Field Inclination

AbstractSeven subsurface Electromagnetic Autonomous Profiling Explorer (EM-APEX) floats measured the voltage induced by the motional induction of seawater under Typhoon Fanapi in 2010. Measurements were processed to estimate high-frequency oceanic velocity variance associated with surface waves. Surface wave peak frequency fp and significant wave height Hs are estimated by a nonlinear least squares fitting to , assuming a broadband JONSWAP surface wave spectrum. The Hs is further corrected for the effects of float rotation, Earth’s geomagnetic field inclination, and surface wave propagation direction. The fp is 0.08–0.10 Hz, with the maximum fp of 0.10 Hz in the rear-left quadrant of Fanapi, which is ~0.02 Hz higher than in the rear-right quadrant. The Hs is 6–12 m, with the maximum in the rear sector of Fanapi. Comparing the estimated fp and Hs with those assuming a single dominant surface wave yields differences of more than 0.02 Hz and 4 m, respectively. The surface waves under Fanapi simulated in the WAVEWATCH III (ww3) model are used to assess and compare to float estimates. Differences in the surface wave spectra of JONSWAP and ww3 yield uncertainties of <5% outside Fanapi’s eyewall and >10% within the eyewall. The estimated fp is 10% less than the simulated before the passage of Fanapi’s eye and 20% less after eye passage. Most differences between Hs and simulated are <2 m except those in the rear-left quadrant of Fanapi, which are ~5 m. Surface wave estimates are important for guiding future model studies of tropical cyclone wave–ocean interactions.

Azimuthal multiple signal classification of dispersive and aliased surface waves recorded in 3D seismic acquisition

Geophysics ◽  
2021 ◽  
pp. 1-84
Author(s):  
Chunying Yang ◽  
Wenchuang Wang
Keyword(s):  
Surface Wave ◽  
Surface Waves ◽  
Body Waves ◽  
Signal Classification ◽  
Dispersion Pattern ◽  
Velocity Spectrum ◽  
Low Velocity ◽  
Surface Wave Dispersion ◽  
Multiple Signal Classification ◽  
Multiple Signal

Irregular acquisition geometry causes discontinuities in the appearance of surface wave events, and a large offset causes seismic records to appear as aliased surface waves. The conventional method of sampling data affects the accuracy of the dispersion spectrum and reduces the resolution of surface waves. At the same time, ”mode kissing” of the low-velocity layer and inhomogeneous scatterers requires a high-resolution method for calculating surface wave dispersion. This study tested the use of the multiple signal classification (MUSIC) algorithm in 3D multichannel and aliased wavefield separation. Azimuthal MUSIC is a useful method to estimate the phase velocity spectrum of aliased surface wave data, and it represent the dispersion spectra of low-velocity and inhomogeneous models. The results of this study demonstrate that mode-kissing affects dispersion imaging, and inhomogeneous scatterers change the direction of surface-wave propagation. Surface waves generated from the new propagation directions are also dispersive. The scattered surface wave has a new dispersion pattern different to that of the entire record. Diagonal loading was introduced to improve the robustness of azimuthal MUSIC, and numerical experiments demonstrate the resultant effectiveness of imaging aliasing surface waves. A phase-matched filter was applied to the results of azimuthal MUSIC, and phase iterations were unwrapped in a fast and stable manner. Aliased surface waves and body waves were separated during this process. Overall, field data demonstrate that azimuthal MUSIC and phase-matched filters can successfully separate aliased surface waves.

Errors Introduced in Estimation of Surface Wave Phase and Group Velocities Due to Wrong Assumptions: An Assessment Using a Simple Model For Love Wave

2021 ◽  
Author(s):  
Akash Kharita ◽  
Sagarika Mukhopadhyay
Keyword(s):  
Surface Wave ◽  
Surface Waves ◽  
Love Wave ◽  
Arrival Time ◽  
Epicentral Distance ◽  
Horizontal Distance ◽  
Wave Analysis ◽  
Time Period ◽  
Phase And Group Velocities ◽  
Group Velocities

&lt;p&gt;The surface wave phase and group velocities are estimated by dividing the epicentral distance by phase and group travel times respectively in all the available methods, this is based on the assumptions that (1) surface waves originate at the epicentre and (2) the travel time of the particular group or phase of the surface wave is equal to its arrival time to the station minus the origin time of the causative earthquake; However, both assumptions are wrong since surface waves generate at some horizontal distance away from the epicentre. We calculated the actual horizontal distance from the focus at which they generate and assessed the errors caused in the estimation of group and phase velocities by the aforementioned assumptions in a simple isotropic single layered homogeneous half space crustal model using the example of the fundamental mode Love wave. We took the receiver locations in the epicentral distance range of 100-1000 km, as used in the regional surface wave analysis, varied the source depth from 0 to 35 Km with a step size of 5 km and did the forward modelling to calculate the arrival time of Love wave phases at each receiver location. The phase and group velocities are then estimated using the above assumptions and are compared with the actual values of the velocities given by Love wave dispersion equation. We observed that the velocities are underestimated and the errors are found to be; decreasing linearly with focal depth, decreasing inversely with the epicentral distance and increasing parabolically with the time period. We also derived empirical formulas using MATLAB curve fitting toolbox that will give percentage errors for any realistic combination of epicentral distance, time period and depths of earthquake and thickness of layer in this model. The errors are found to be more than 5% for all epicentral distances lesser than 500 km, for all focal depths and time periods indicating that it is not safe to do regional surface wave analysis for epicentral distances lesser than 500 km without incurring significant errors. To the best of our knowledge, the study is first of its kind in assessing such errors.&lt;/p&gt;

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