Seismic Wave Gradiometry Using the Wavelet Transform: Application to the Analysis of Complex Surface Waves Recorded at the Glendora Array, Sullivan, Indiana, USA

2010 ◽  
Vol 100 (3) ◽  
pp. 1211-1224 ◽  
Author(s):  
C. Poppeliers
Keyword(s):  
Wavelet Transform ◽  
Surface Waves ◽  
Seismic Wave ◽  
Complex Surface ◽  
Wave Gradiometry

The Effects of Measurement Uncertainties in Seismic-Wave Gradiometry

2015 ◽  
Vol 105 (6) ◽  
pp. 3143-3155 ◽  
Author(s):  
Christian Poppeliers ◽  
Elizabeth V. Evans
Keyword(s):  
Seismic Wave ◽  
Measurement Uncertainties ◽  
Wave Gradiometry

scholarly journals Application of an Automatic Noise or Signal Removal Algorithm Based on Synchrosqueezed Continuous Wavelet Transform of Passive Surface Wave Imaging: A Case Study in Sichuan, China

2021 ◽  
Vol 11 (24) ◽  
pp. 11718
Author(s):  
Jie Fang ◽  
Guofeng Liu ◽  
Yu Liu
Keyword(s):  
Wavelet Transform ◽  
Surface Wave ◽  
Surface Waves ◽  
Continuous Wavelet Transform ◽  
Cross Correlation ◽  
Underground Structure ◽  
Inversion Method ◽  
Continuous Wavelet ◽  
Dispersion Measurement ◽  
Wave Imaging

Passive surface wave imaging based on noise cross-correlation has been a research hotspot in recent years. However, because randomness of noise is difficult to achieve in reality, prominent noise sources will inevitably affect the dispersion measurement. Additionally, in order to recover high-fidelity surface waves, the time series input during cross-correlation calculation is usually very long, which greatly limits the efficiency of passive surface wave imaging. With an automatic noise or signal removal algorithm based on synchrosqueezed continuous wavelet transform (SS-CWT), these problems can be alleviated. We applied this method to 1-h passive datasets acquired in Sichuan province, China; separated the prominent noise events in the raw field data, and enhanced the cross-correlation reconstructed surface waves, effectively improving the accuracy of the dispersion measurement. Then, using the conventional surface wave inversion method, the shear wave velocity profile of the underground structure in this area was obtained.

Exploiting surface consistency for surface-wave characterization and mitigation — Part 1: Theory and 2D examples

Geophysics ◽  
2017 ◽  
Vol 82 (1) ◽  
pp. V21-V37 ◽  
Author(s):  
Christine E. Krohn ◽  
Partha S. Routh
Keyword(s):  
Surface Wave ◽  
Surface Waves ◽  
Single Mode ◽  
Complex Surface ◽  
Companion Paper ◽  
Inversion Method ◽  
Earth Model ◽  
Model Parameters ◽  
Quality Factors ◽  
Near Surface

We have developed a new tomographic inversion method that is able to determine the properties of complex surface waves, which are multimodal and heterogeneous. These properties can be used to generate a detailed near-surface earth model or to predict and remove the surface waves, while protecting reflection signals even with aliased data. The inversion assumes plane-wave physics and generates surface-consistent model parameters as a function of frequency. In this paper, we validate our method with 2D models and data. In a companion paper, we demonstrate its application to 3D data. Inversion for a single mode is linear, but the linearity does not hold at higher frequencies, where multiple modes interfere. However, single-mode inversion results can be used to create a starting model for the subsequent nonlinear multimode tomography. The resulting velocity-frequency grid has greater resolution compared with a beam-forming method. The dispersion curves can be used as input to a subsequent standard 1D surface-wave inversion to generate a velocity-depth model. The tomographic method also determines a grid of attenuation quality factors and variations in the source amplitude and bandwidth, which correlate with the near-surface elevation changes. The amplitude and phase properties can be used together to predict the surface-wave waveforms, which can then be adaptively subtracted from the data on a trace-to-trace basis.

scholarly journals Imaging Seismic Wave-Fields with AlpArray and Neighboring European Networks

2020 ◽  
Author(s):  
Marcel Tesch ◽  
Johannes Stampa ◽  
Thomas Meier ◽  
Edi Kissling ◽  
György Hetényi ◽  
...  
Keyword(s):  
Surface Waves ◽  
Wave Field ◽  
Seismic Wave ◽  
Time Window ◽  
Deep Structure ◽  
Body Wave ◽  
Broad Band ◽  
Wave Fields ◽  
Short Period ◽  
Spatio Temporal

Abstract. The modern-day coverage and availability of broad-band stations in the greater Alpine area offered by AlpArray, Swath-D and the European seismological networks allows for imaging seismic wave-fields at yet unprecedented resolution. In the AlpArray area and in Italy, the distance of any point to the nearest station is less than 30 km, resulting in an average inter-station distance of about 45 km. With a much denser deployment in a smaller region of the Alps (320 km in length and 140 km wide), the Swath-D network possesses an average inter-station distance of about 15 km. We provide single event seismogram sections, time slices of teleseismic and regional wave-fields, and wave-field animations to reveal both the resolution capabilities of this dense station distribution as well as the enormous spatio-temporal complexity of seismic wave propagation. The time slices and wave-field animations demonstrate the need for dense regional arrays of broad-band stations, such as provided by AlpArray and neighboring networks, to resolve properties of teleseismic wave-fields. Here we present the images of coherent arrivals of direct body and surface waves, multiple body wave reflections, and multi-orbit phases for teleseismic and regional events with moment magnitudes larger than 6 over a time window of at least 2:45 hours. Spatial observations of the wave-fields illustrate e.g. the decrease in horizontal wavelength from P to S to surface waves and the way in which they considerably deviate from plane waves, due to heterogeneous earth structures along the path from the source to the array and beneath the regional array itself. Tomographic imaging techniques for the deep structure beneath the regional array have to take this spatio-temporal variability into account and correct for it. The lateral resolution of the regional broad-band array is however dependent on station density, in this case limited to about 100 km. Only even denser station distributions like those provided by Swath-D suffice to recover wave-fields of short period body and surface waves.

Signal reconstruction of surface waves on SASW measurement using Gaussian Derivative wavelet transform

2009 ◽  
Vol 57 (3) ◽  
pp. 616-635 ◽  
Author(s):  
Sri Atmaja P. Rosyidi ◽  
Mohd Raihan Taha ◽  
Zamri Chik ◽  
Amiruddin Ismail
Keyword(s):  
Wavelet Transform ◽  
Surface Waves ◽  
Signal Reconstruction ◽  
Gaussian Derivative

Multiwavelet Seismic-Wave Gradiometry

2011 ◽  
Vol 101 (5) ◽  
pp. 2108-2121 ◽  
Author(s):  
C. Poppeliers
Keyword(s):  
Seismic Wave ◽  
Wave Gradiometry
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