Packets Wavelets and Stockwell Transform Analysis of Femoral Doppler Ultrasound Signals

Ultrasonic Doppler signals are widely used in the detection of cardiovascular pathologies or the evaluation of the degree of stenosis in the femoral arteries. The presence of stenosis can be indicated by disturbing the blood flow in the femoral arteries, causing spectral broadening of the Doppler signal. To analyze these types of signals and determine stenosis index, a number of time-frequency methods have been developed, such as the short-time Fourier transform, the continuous wavelets transform, the wavelet packet transform, and the S-transform

Automatic classification of power quality disturbances: a review

The development of intelligent power quality (PQ) disturbances classification and analysis tools exploited various digital signal-processing techniques to extract important features from the PQ signals. The purpose of this paper is to present a comprehensive review and discussion of the advanced tools for the automatic classification of PQ disturbances. The digital signal-processing tools applied for feature extraction include Fourier-transform, Wavelet-transform, Stockwell-transform etc. For the classification of PQ disturbances, the artificial intelligence techniques such as artificial neural networks, fuzzy logic and support vector machine are reviewed here. A large number of features used as inputs to the classifiers may affect the accuracy rate and requires a large memory space. The optimization techniques have been used in literature for optimal feature selection, which include genetic algorithm, simulated annealing, particle swarm optimization and ant colony optimization. An extensive review provides to the researchers a clear perspective on various techniques of PQ disturbances classification

Analysis of Multi-Component Seismic Data in the Shallow Water Environment of the Arabian Gulf

The quality of the seismic data is essential to quantitative reservoir characterization of rock properties and geological structure interpretation. Although marine multi-component seismic data hold a wealth of information about both compressional and shear velocities, the acquisition suffers from high levels of noise, which make the processing a challenging task and drastically decreases optimal value extraction. This dissertation employs a four component (4C) processing workflow via advanced time-frequency-wavenumber filtering and polarization methods to improve data quality for further interpretation and reservoir characterization. The proposed workflow is used to enhance seismic reflected energy and explore the shear wave information in the horizontal components. This study makes use of one 2D seismic line and well log dataset from one offshore in the southern Arabian Gulf (Abu Dhabi, United Arab Emirates). A combination of strong lateral seafloor heterogeneities, shallow water depths (~10m), and hard sea bottom results in highly interfering and complex wave-fields and seemingly noisy seismic data acquired in this shallow water environment. Meanwhile, we expect converted wave modes (PS-S waves) due to the strong reflector at hard sea bottom. In this work, we first propose sophisticated filtering algorithms to attenuate surface waves, and then designed advanced processing sequence combined with existing techniques for converted waves detection. Compared to body waves, surface waves are characterized by low velocity, low frequency and high polarization. First, we utilize the variable factor S transform to transform the seismic data from time domain to time-frequency-wavenumber(TFK) domain. This designed transform provides better resolution control on both time and frequency by adjusting the shape of Gaussian window function through additional parameters. Second, we estimate the impacts of residual surface waves on rotation and suppress those waves using TFK dependent polarization analysis. Polarization attributes, ellipticity and rise angle, are calculated through a developed 3D covariance matrix analysis that exploits the joint relationship of wavenumber, time, frequency and polarization. Those computed attributes are used for attenuating the surface waves and determining radial and transverse components. Third, we introduce the new 4C ocean bottom cable (OBC) processing strategy using both compressional and shear waves to recover the image of the subsurface from noisy seismic data. Comparing the time slices and gathers before and after using the strategy, it is observed that the method, described here, attenuates surface waves and remnant surface waves effectively and improves the signal to noise ratio without weakening the desired reflected signals. The results from this dissertation will find application in reservoir characterization from shear wave and converted wave analysis

On the estimation of the evolutionary power spectral density

Two popular spectral-based approaches for estimating the evolutionary power spectral density (EPSD) function from the samples of the evolutionary process are based on the short-time Fourier transform (STFT) and the continuous wavelet transform. Both rely on the concept of slowly varying modulation or EPSD function, although the quantification of the effect of the 'slow' variation in the estimated EPSD is elusive. We propose, in the present study, to use the derivatives of the EPSD function to quantify the smoothness of the EPSD function in the context of estimating the EPSD function. We derive equations for estimating EPSD by using the S-transform and continuous wavelet transform. These equations are as simple to use as that derived based on STFT. We also derive the corresponding equations for assessing the residual for the estimated EPSD by using these transforms, including STFT. The residual provides an approach for identifying or quantifying, in the context of its estimation, the 'slow' variation of the EPSD function. The derived equations and numerical results indicate that the residual depends on both the derivatives of the EPSD function with respect to time and frequency as well as the adopted transform