Application of constrained polarization filtering for surface-wave mitigation: Three case studies

Geophysics ◽  
2012 ◽  
Vol 77 (5) ◽  
pp. V169-V181 ◽  
Author(s):  
Mamadou S. Diallo ◽  
Warren S. Ross ◽  
Andrew P. Shatilo ◽  
Inmaculada Dura-Gomez ◽  
Gary C. Szurek
Keyword(s):  
Surface Wave ◽  
Surface Waves ◽  
Case Studies ◽  
Data Sets ◽  
Velocity Amplitude ◽  
Time Frequency ◽  
Frequency Information ◽  
Straightforward Application ◽  
F Region ◽  
Polarization Filtering

We applied constrained polarization filtering (CPF) to surface-wave mitigation on data sets from different geologic settings. The method derives from the application of polarization filtering in the time-frequency (t-f) domain and introduces new constraints to effectively detect and mitigate surface waves while protecting the signal. We use these constraints that we derive from velocity, amplitude, time, and frequency information to delineate the t-f region dominated by surface-wave noises. Then, we restrict the application of polarization filtering to this region to avoid damaging the signal. Straightforward application of polarization filtering without these constraints results in ineffective filtering or damage to the signal, due to the complexity of surface-wave wavetrains. The performance of CPF with these various data sets is demonstrably superior compared to the unconstrained approach. There are some of the issues that may affect performance of the CPF, but they can be overcome.

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.

Multi-Window Weighted Stacking of Surface-Wave Dispersion

Geophysics ◽  
2020 ◽  
pp. 1-53
Author(s):  
Sylvain Pasquet ◽  
Wei Wang ◽  
Po Chen ◽  
Brady A. Flinchum
Keyword(s):  
Surface Wave ◽  
Surface Waves ◽  
Real Data ◽  
Wave Dispersion ◽  
Lateral Resolution ◽  
Data Sets ◽  
S Wave ◽  
Surface Wave Dispersion ◽  
Shallow Subsurface ◽  
Depth Of Investigation

Surface wave (SW) methods are classically used to characterize shear (S-) wave velocities ( VS) of the shallow subsurface through the inversion of dispersion curves. When targeting 2D shallow structures with sharp lateral heterogeneity, windowing and stacking techniques can be implemented to provide a better description of VS lateral variations. These techniques, however, suffer from the trade-off between lateral resolution and depth of investigation, well-known when using multichannel analysis of surface waves (MASW). We propose a novel methodology aimed at enhancing both lateral resolution and depth of investigation of MASW results through the use of multi-window weighted stacking of surface waves (MW-WSSW). MW-WSSW consists in stacking dispersion images obtained from data segments of different sizes, with a wavelength-based weight that depends on the aperture of the data selection window. In that sense, MW-WSSW provides additional weight to short wavelengths in smaller windows so as to better inform shallow parts of the subsurface, and vice versa for deeper velocities. Using multiple windows improves the depth of investigation, while applying wavelength-based weights enhances shallow lateral resolution. MW-WSSW was implemented within the open-source package SWIP, and applied to the processing of synthetic and real data sets. In both cases we compared it with standard windowing and stacking procedures that are already implemented in SWIP. MW-WSSW provided convincing results with optimized lateral extent, improved shallow resolution, and increased depth of investigation.

Ground roll: Rejection using adaptive phase‐matched filters

Geophysics ◽  
1990 ◽  
Vol 55 (6) ◽  
pp. 776-781 ◽  
Author(s):  
R. B. Herrmann ◽  
D. R. Russell
Keyword(s):  
Surface Wave ◽  
Surface Waves ◽  
Iterative Process ◽  
Spatial Sampling ◽  
Matched Filtering ◽  
Data Sets ◽  
Matched Filters ◽  
Wide Range ◽  
Ground Roll ◽  
Band Pass

The technique of phase‐matched filtering dispersive surface waves is extended to permit an adaptive, iterative process by which the signal itself in a seismic trace designs a filter to remove the surface wave. The technique is robust and well‐behaved and requires the specification of only simple parameters for its operation. The technique is applied to data sets from three regions, representing a wide range in the ratio of surface‐wave noise to exploration signal. The technique works very well with poor data sets and also improves good data sets. Since the technique is applied to individual traces, it works in situations for which f‐k filtering might not be feasible due to poor spatial sampling. The technique is computationally more intensive than recursive digital band‐pass filtering of individual traces, but is less intensive than filtering in the f‐k domain.

Adaptive wavelets for analyzing dispersive seismic waves

Geophysics ◽  
2007 ◽  
Vol 72 (1) ◽  
pp. V1-V11 ◽  
Author(s):  
A. Kritski ◽  
A. P. Vincent ◽  
D. A. Yuen ◽  
T. Carlsen
Keyword(s):  
Surface Wave ◽  
Surface Waves ◽  
Shear Wave ◽  
Primary Objective ◽  
Sediment Surface ◽  
Horizontal Distance ◽  
Time Frequency ◽  
Interface Waves ◽  
Adaptive Wavelets ◽  
Wave Modes

Our primary objective is to develop an efficient and accurate method for analyzing time series with a multiscale character. Our motivation stems from the studies of the physical properties of marine sediment (stiffness and density) derived from seismic acoustic records of surface/interface waves along the water-seabed boundary. These studies depend on the dispersive characteristics of water-sediment surface waves. To obtain a reliable retrieval of the shear-wave velocities, we need a very accurate time-frequency record of the surface waves. Such a time-frequency analysis is best carried out by a wavelet-transform of the seismic records. We have employed the wavelet crosscorrelation technique for estimating the shear-wave propagational parameters as a function of depth and horizontal distance. For achieving a greatly improved resolution in time-frequency space, we have developed a new set of adaptive wavelets, which are driven by the data. This approach is based on a Karhunen-Loeve (KL) decomposition of the seismograms. This KL decomposition allows us to obtain a set of wavelet functions that are naturally adapted to the scales of the surface-wave modes. We demonstrate the superiority of these adaptive wavelets over standard wavelets in their ability to simultaneously discriminate the different surface-wave modes. The results can also be useful for imaging and statistical data analysis in exploration geophysics and in other disciplines in the environmental sciences.

Ground roll extraction using the Karhunen-Loeve transform in the time-frequency domain

Geophysics ◽  
2021 ◽  
pp. 1-22
Author(s):  
Aleksander S. Serdyukov
Keyword(s):  
Surface Wave ◽  
Data Processing ◽  
Surface Waves ◽  
Frequency Domain ◽  
Band Frequency ◽  
Time Frequency ◽  
S Transform ◽  
Ground Roll ◽  
Karhunen Loeve Transform ◽  
Complex Valued

Ground roll suppression is critical for seismic reflection data processing. Many standard methods, i.e., FK filtering, fail when spatially aliased surface wave interference is present in the data. Spatial aliasing is a common problem; receiver spacing is often not dense enough to extract wavenumbers of low-velocity surface waves. It has long been known that the Karhunen-Loeve transform can be used to suppress aliased ground roll. However, the ground roll should be flattened before suppression, which is challenging due to the dispersion of surface wave velocities. I propose to solve this problem via the time-frequency domain. I apply the S-transform, which was previously shown to perform well in the multichannel analysis of surface waves. A simple complex-valued constant phase shift is a suitable model of surface wave propagation in common-frequency S-transform gathers. Therefore, it is easy to flatten the corresponding S-transform narrow-band frequency surface wave packet and extract it from the data by principal component analysis of the corresponding complex-valued data-covariance matrix. As the result, the proposed S-transform Karhunen-Loeve (SKL) method filters the aliased ground roll without damaging the reflection amplitudes. The advantages of SKL filtering have been confirmed by synthetic- and field-data processing.

scholarly journals Polarization Filtering Method for Suppressing Surface Wave in Time-Frequency Domain

2019 ◽  
Vol 10 (04) ◽  
pp. 481-490
Author(s):  
Xiaoming Yang ◽  
Yang Gao ◽  
Wenzhong Zhang ◽  
Yanchun Wang ◽  
Meihua Lan
Keyword(s):  
Surface Wave ◽  
Frequency Domain ◽  
Time Frequency ◽  
Filtering Method ◽  
Polarization Filtering

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.

scholarly journals The appearance of boundary layers and drift flows due to high-frequency surface waves

2012 ◽  
Vol 707 ◽  
pp. 482-495 ◽  
Author(s):  
Ofer Manor ◽  
Leslie Y. Yeo ◽  
James R. Friend
Keyword(s):  
Boundary Layer ◽  
Surface Waves ◽  
High Frequency ◽  
Slip Boundary Condition ◽  
Inertial Effects ◽  
Velocity Amplitude ◽  
Slip Boundary ◽  
Long Period ◽  
Bulk Waves ◽  
Schlichting Streaming

AbstractThe classical Schlichting boundary layer theory is extended to account for the excitation of generalized surface waves in the frequency and velocity amplitude range commonly used in microfluidic applications, including Rayleigh and Sezawa surface waves and Lamb, flexural and surface-skimming bulk waves. These waves possess longitudinal and transverse displacements of similar magnitude along the boundary, often spatiotemporally out of phase, giving rise to a periodic flow shown to consist of a superposition of classical Schlichting streaming and uniaxial flow that have no net influence on the flow over a long period of time. Correcting the velocity field for weak but significant inertial effects results in a non-vanishing steady component, a drift flow, itself sensitive to both the amplitude and phase (prograde or retrograde) of the surface acoustic wave propagating along the boundary. We validate the proposed theory with experimental observations of colloidal pattern assembly in microchannels filled with dilute particle suspensions to show the complexity of the boundary layer, and suggest an asymptotic slip boundary condition for bulk flow in microfluidic applications that are actuated by surface waves.

LFM Signal Detection Method Based on Fractional Fourier Transform

2014 ◽  
Vol 989-994 ◽  
pp. 4001-4004 ◽  
Author(s):  
Yan Jun Wu ◽  
Gang Fu ◽  
Yu Ming Zhu
Keyword(s):  
Fourier Transform ◽  
Signal Detection ◽  
Frequency Analysis ◽  
Experimental Analysis ◽  
Fractional Fourier Transform ◽  
Detection Method ◽  
Time Frequency Analysis ◽  
Time Frequency ◽  
Frequency Information ◽  
Strong Impulse

As a generalization of Fourier transform, the fractional Fourier Transform (FRFT) contains simultaneity the time-frequency information of the signal, and it is considered a new tool for time-frequency analysis. This paper discusses some steps of FRFT in signal detection based on the decomposition of FRFT. With the help of the property that a LFM signal can produce a strong impulse in the FRFT domain, the signal can be detected conveniently. Experimental analysis shows that the proposed method is effective in detecting LFM signals.

Improving surface‐wave group velocity measurements by energy reassignment

Geophysics ◽  
2003 ◽  
Vol 68 (2) ◽  
pp. 677-684 ◽  
Author(s):  
Helle A. Pedersen ◽  
Jérôme I. Mars ◽  
Pierre‐Olivier Amblard
Keyword(s):  
Surface Waves ◽  
Dispersion Curve ◽  
Group Velocity ◽  
Shear Wave ◽  
Group Velocity Dispersion ◽  
Seismic Survey ◽  
Earth Model ◽  
Velocity Measurements ◽  
Time Frequency ◽  
Shallow Seismic

Surface waves are increasingly used for shallow seismic surveys—in particular, in acoustic logging, environmental, and engineering applications. These waves are dispersive, and their dispersion curves are used to obtain shear velocity profiles with depth. The main obstacle to their more widespread use is the complexity of the associated data processing and interpretation of the results. Our objective is to show that energy reassignment in the time–frequency domain helps improve the precision of group velocity measurements of surface waves. To show this, full‐waveform seismograms with added white noise for a shallow flat‐layered earth model are analyzed by classic and reassigned multiple filter analysis (MFA). Classic MFA gives the expected smeared image of the group velocity dispersion curve, while the reassigned curve gives a very well‐constrained, narrow dispersion curve. Systematic errors from spectral fall‐off are largely corrected by the reassignment procedure. The subsequent inversion of the dispersion curve to obtain the shear‐wave velocity with depth is carried out through a procedure combining linearized inversion with a nonlinear Monte Carlo inversion. The diminished uncertainty obtained after reassignment introduces significantly better constraints on the earth model than by inverting the output of classic MFA. The reassignment is finally carried out on data from a shallow seismic survey in northern Belgium, with the aim of determining the shear‐wave velocities for seismic risk assessment. The reassignment is very stable in this case as well. The use of reassignment can make dispersion measurements highly automated, thereby facilitating the use of surface waves for shallow surveys.

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