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.

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.

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.

scholarly journals Imaging near-surface heterogeneities by natural migration of backscattered surface waves: Field data test

Geophysics ◽  
2017 ◽  
Vol 82 (3) ◽  
pp. S197-S205 ◽  
Author(s):  
Zhaolun Liu ◽  
Abdullah AlTheyab ◽  
Sherif M. Hanafy ◽  
Gerard Schuster
Keyword(s):  
Surface Waves ◽  
Field Data ◽  
Synthetic Data ◽  
Data Sets ◽  
Data Set ◽  
Near Surface ◽  
3D Data ◽  
Strong Surface ◽  
Migration Method ◽  
Recorded Data

We have developed a methodology for detecting the presence of near-surface heterogeneities by naturally migrating backscattered surface waves in controlled-source data. The near-surface heterogeneities must be located within a depth of approximately one-third the dominant wavelength [Formula: see text] of the strong surface-wave arrivals. This natural migration method does not require knowledge of the near-surface phase-velocity distribution because it uses the recorded data to approximate the Green’s functions for migration. Prior to migration, the backscattered data are separated from the original records, and the band-passed filtered data are migrated to give an estimate of the migration image at a depth of approximately one-third [Formula: see text]. Each band-passed data set gives a migration image at a different depth. Results with synthetic data and field data recorded over known faults validate the effectiveness of this method. Migrating the surface waves in recorded 2D and 3D data sets accurately reveals the locations of known faults. The limitation of this method is that it requires a dense array of receivers with a geophone interval less than approximately one-half [Formula: see text].

A method for relocating seismic events using surface waves

1973 ◽  
Vol 63 (4) ◽  
pp. 1305-1313
Author(s):  
S. T. Crough ◽  
R. Van der Voo
Keyword(s):  
Surface Wave ◽  
Surface Waves ◽  
Group Velocity ◽  
Group Velocity Dispersion ◽  
Body Wave ◽  
Test Site ◽  
Seismic Events ◽  
Computer Technique ◽  
Nuclear Explosions ◽  
Reference Event

abstract Seismic events can be relocated relative to a reference event by using the group-velocity dispersion curves of surface waves. Since group velocity is a function of the travel path, surface waves from two events in the same locale should show identical group velocities when viewed at any one seismograph station. A computer technique has been developed for comparing the group-velocity curves of any event with the curves of a reference event and for determining the relocation which causes the curves to best coincide. The method is evaluated by relocating eight intermediate-size nuclear explosions of the Nevada Test Site series. With precise curve fitting, the surface-wave locations are slightly more accurate in southern Nevada than the standard body-wave determinations. The surface-wave origin times are considerably more accurate. In areas of sparse station coverage or of many small earthquakes, the surface-wave method can be expected to improve seismic locations significantly.

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.

An elastodynamic inverse scattering method for removing scattered surface waves from field data

Geophysics ◽  
1995 ◽  
Vol 60 (6) ◽  
pp. 1897-1905 ◽  
Author(s):  
Bastian Blonk ◽  
Gerard C. Herman ◽  
Guy G. Drijkoningen
Keyword(s):  
Surface Waves ◽  
Inverse Scattering ◽  
Seismic Data ◽  
Field Data ◽  
Inverse Scattering Method ◽  
Scattering Method ◽  
Data Sets ◽  
Propagation Characteristics ◽  
Fitting Procedure ◽  
Separate Source

In an earlier paper, we introduced a 3-D inverse scattering method for removing scattered surface waves from seismic data that was based on a tomographic imaging of the scattered surface waves by a data‐fitting procedure that used as much of the seismic data as possible. After this imaging step, the scattered surface waves can be computed and removed for each separate source‐receiver pair. We now apply the method to two field‐data sets. The method requires a knowledge of the source waveform and shallow propagation characteristics, and these input requirements are estimated from the direct surface wave. We conclude that the method effectively attenuates crossline scattered surface waves without affecting deeper reflections.

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.

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