Broadband Signal Enhancement of Seismic Array Data: Application to Long-Period Surface Waves & High Frequency Wavefields

1998 ◽  
Author(s):  
Frank L. Vernon ◽  
Robert J. Mellors ◽  
David J. Thomson
Keyword(s):  
Surface Waves ◽  
High Frequency ◽  
Signal Enhancement ◽  
Seismic Array ◽  
Array Data ◽  
Long Period ◽  
Data Application ◽  
Broadband Signal

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.

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.

scholarly journals Combination of Spectral Representation and Wavelet Packets for Generating Long-Period Ground Motions

2020 ◽  
Vol 2020 ◽  
pp. 1-24
Author(s):  
Minghui Dai ◽  
Yingmin Li
Keyword(s):  
Surface Waves ◽  
High Frequency ◽  
Spectral Representation ◽  
Response Spectrum ◽  
Ground Motions ◽  
Time History ◽  
Wavelet Packets ◽  
Velocity Spectrum ◽  
Long Period ◽  
Frequency Components

Far-field long-period ground motions (hereafter long-period ground motions) featuring low-frequency components are responsible for the resonant responses of high-rise buildings. In this context, it is beneficial to assess the dynamic performance of these buildings under long-period ground motions with the aid of time history analysis. This paper proposes a method for generating long-period motions by combining long-period components synthesized by spectral representation with high-frequency components simulated by wavelet packets. Later-arriving long-period surface waves (LALP surface waves), which are determined on the grounds of phase dispersion, represent the main long-period properties in sense of velocity spectrum at longer periods of interest. An analytical expression for power spectrum density is employed to capture the narrowband properties of LALP velocity surface waves. Meanwhile, modification of the Gaussian random process is performed in time and frequency domains to attain a modulated initial seed motion, which shows the variability of the targeted ground motion. A simulation of high-frequency components is accomplished by means of iteration, in which wavelet coefficients of the modulated seed motion are adjusted to match the targeted response spectrum and cumulative energy plot. Furthermore, comparisons between an ensemble of realizations and target motions demonstrate the feasibility of the proposed method to generate long-period simulations sharing similar properties to target motions.

scholarly journals Statistical analysis of Stromboli VLP tremor in the band [0.1–0.5] Hz: some consequences for vibrating structures

2006 ◽  
Vol 13 (4) ◽  
pp. 393-400 ◽  
Author(s):  
E. De Lauro ◽  
S. De Martino ◽  
M. Falanga ◽  
M. Palo
Keyword(s):  
Frequency Band ◽  
High Frequency ◽  
Noise Source ◽  
Volcanic Tremor ◽  
Large Data ◽  
Musical Instruments ◽  
Data Set ◽  
Long Period ◽  
Vibrating Structures ◽  
Analyze Time Series

Abstract. We analyze time series of Strombolian volcanic tremor, focusing our attention on the frequency band [0.1–0.5] Hz (very long period (VLP) tremor). Although this frequency band is largely affected by noise, we evidence two significant components by using Independent Component Analysis with the frequencies, respectively, of ~0.2 and ~0.4 Hz. We show that these components display wavefield features similar to those of the high frequency Strombolian signals (>0.5 Hz). In fact, they are radially polarised and located within the crater area. This characterization is lost when an enhancement of energy appears. In this case, the presence of microseismic noise becomes relevant. Investigating the entire large data set available, we determine how microseismic noise influences the signals. We ascribe the microseismic noise source to Scirocco wind. Moreover, our analysis allows one to evidence that the Strombolian conduit vibrates like the asymmetric cavity associated with musical instruments generating self-sustained tones.

scholarly journals Comparison of fluid tiltmeter data with long-period seismograms: Surface waves and Earth's free oscillations

2006 ◽  
Vol 111 (B11) ◽  
pp. n/a-n/a ◽  
Author(s):  
A. M. G. Ferreira ◽  
N. F. d'Oreye ◽  
J. H. Woodhouse ◽  
W. Zürn
Keyword(s):  
Surface Waves ◽  
Free Oscillations ◽  
Long Period ◽  
Earth’S Free Oscillations

Bayesian deconvolution of gamma‐ray logs

Geophysics ◽  
1987 ◽  
Vol 52 (11) ◽  
pp. 1535-1546 ◽  
Author(s):  
Ping Sheng ◽  
Benjamin White ◽  
Balan Nair ◽  
Sandra Kerford
Keyword(s):  
High Frequency ◽  
Gamma Ray ◽  
Simulated Data ◽  
Field Measurements ◽  
Bayesian Optimization ◽  
Frequency Noise ◽  
High Frequency Noise ◽  
Data Application ◽  
Gamma Ray Detector ◽  
Gamma Ray Log

The spatial resolution of gamma‐ray logs is defined by the length 𝓁 of the gamma‐ray detector. To resolve thin beds whose thickness is less than 𝓁, it is generally desirable to deconvolve the data to reduce the averaging effect of the detector. However, inherent in the deconvolution operation is an amplification of high‐frequency noise, which can be a detriment to the intended goal of increased resolution. We propose a Bayesian statistical approach to gamma‐ray log deconvolution which is based on optimization of a probability function which takes into account the statistics of gamma‐ray log measurements as well as the empirical information derived from the data. Application of this method to simulated data and to field measurements shows that it is effective in suppressing high‐frequency noise encountered in the deconvolution of gamma‐ray logs. In particular, a comparison with the least‐squares deconvolution approach indicates that the incorporation of physical and statistical information in the Bayesian optimization process results in optimal filtering of the deconvolved results.

Application Of Elastic Layers To Register Pressure Field On The Model Surface In Supersonic Flow

2016 ◽  
Vol 11 (1) ◽  
pp. 23-33
Author(s):  
Maxim Golubev ◽  
Andrey Shmakov
Keyword(s):  
Surface Waves ◽  
High Frequency ◽  
High Speed ◽  
Pressure Pulsation ◽  
Pressure Field ◽  
Leading Edge ◽  
Supersonic Wind Tunnel ◽  
Register Pressure ◽  
Elastic Layers ◽  
Sharp Leading Edge

The work presents the results of application of panoramic interferential technique which is based on elastic layers (sensors) usage to obtain pressure distribution on the flat plate having sharp leading edge. Experiments were done in supersonic wind tunnel at Mach number M = 4. Sensitivity and response time are shown to be enough to register pressure pulsation against standing and traveling sensor surface waves. Applying high-frequency image acquiring is demonstrated to make possible to distinguish at visualization images high-speed disturbances propagating in the boundary layer from low-speed surface waves

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