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Conder, Australia

Roy I.G.,Spaceage Geoconsulting
Geophysics | Year: 2013

We developed a novel technique of robust estimation of the discrete Hilbert transform (DHT) of noisy geophysical data. The technique used the sinc method, in which the data were transformed via conformal mapping and the sinc bases were determined by solving a linear matrix equation. A transformation rule was presented for selecting a suitable conformal mapping function that would transform the class of geophysical data set in an appropriate interval range. A novel regularization technique was designed to obtain a robust solution of sinc bases when the data contained noise, in which an optimal regularization parameter was obtained in an automated way using a 1D optimization scheme. The technique of selecting the optimal value of the regularization parameter required no a priori knowledge about the level of noise contamination in the data. Numerical experiments were conducted on synthetically generated and published field data sets with a varying level of noise contamination to test the performance of the scheme. The results obtained using the proposed technique of DHT and those obtained by a standard Fourier domain technique were compared, and it was established that the proposed scheme of discrete Hilbert transformation performed better than that of the standard Fourier domain technique, for noise free and noisy data. The scheme was applied successfully on potential field and infrasound waveform data and also in estimating instantaneous frequency of nonstationary ultrasonic waveform data, which suggested applicability of the scheme to a wide class of geophysical data. © 2013 Society of Exploration Geophysicists. Source

Roy I.G.,Spaceage Geoconsulting
Journal of Applied Geophysics | Year: 2013

The interpretation of tilt angle transformed total magnetic intensity data for a dipping contact model is studied, where it is shown that if the trace of a dipping contact on a horizontal surface is determined then other source parameters, such as the dip and the depth of burial of the contact can be estimated using simple formulas. The trace of the dipping contact can be obtained from the location of the peak of a profile of the first order horizontal derivative of a tilt angle. The tilt angle response and its horizontal derivative are found to be sensitive to noise; however, it is shown that upward continuation operation which does not alter the location of the trace of the contact can improve the tilt angle interpretation for the measured noisy data. Use on synthetic model studies and subsequently on field examples on an aeromagnetic profile across the San Ysidro Fault in the Rio Grande Ridge, U.S.A., and also on an extracted profile from 2D ground magnetic data across Son-Narmada Fault in India demonstrates the applicability of the tilt angle interpretation to delineate the subsurface architecture. © 2013 Elsevier B.V. Source

Roy I.G.,Spaceage Geoconsulting
Journal of Computational Physics | Year: 2015

Enhancing resolution in spectral response and an ability to differentiate spectral mixing in delineating the endmembers from the spectral response are central to the spectral data analysis. First and higher order derivatives analysis of absorbance and reflectance spectral data is commonly used techniques in differentiating the spectral mixing. But high sensitivity of derivative to the noise in data is a major problem in the robust estimation of derivative of spectral data. An algorithm of robust estimation of first and second order derivative spectra from evenly spaced noisy normal spectral data is proposed. The algorithm is formalized in the framework of an inverse problem, where based on the fundamental theorem of calculus a matrix equation is formed using a Volterra type integral equation of first kind. A regularization technique, where the balancing principle is used in selecting a posteriori optimal regularization parameter is designed to solve the inverse problem for robust estimation of first order derivative spectra. The higher order derivative spectra are obtained while using the algorithm in sequel. The algorithm is tested successfully with synthetically generated spectral data contaminated with additive white Gaussian noise, and also with real absorbance and reflectance spectral data for fresh and sea water respectively. © 2015 Elsevier Inc. Source

Multiscale analysis of high resolution total magnetic intensity (TMI) aeromagnetic data over a regional scale is investigated to delineate structural framework suitable for groundwater exploration in an arid region of South Australia. An innovative workflow in processing TMI data is designed, which aids in the multiscale analysis of TMI data in tilt angle domain. The rationale in considering multiscale analysis in the tilt angle domain is discussed in the paper. Each processing module of the workflow of multiscale analysis has been analyzed and the interim output in each processing step is used in the image based interpretation. An interpretation mechanism is formalized by collating digital elevation model (DEM) and geological data with the multiscale images of tilt angle anomalies of high resolution TMI data. The image based interpretation technique with multiscale analysis of high resolution aeromagnetic data has been tested successfully for groundwater resource targeting in an arid region of western Gawler Craton, South Australia. The method has been found to be an important aid in delineating structural trends, in identifying paleovalley or paleochannels and in understanding hydrogeomorphological setup of the study area. © 2014 Elsevier B.V. Source

Roy I.G.,Spaceage Geoconsulting
Journal of Geophysics and Engineering | Year: 2013

Accurate and robust computation of gradients of potential field data are crucial in potential field-data processing and also in data-based interpretation. The standard Fourier domain approach in gradient computation, although computationally efficient, is flawed due to its sensitivity to noise in the data. A robust space domain technique in computing both the horizontal and vertical gradients of equally spaced 2D potential field data is formalized. The method uses moving polynomial interpolation in 2D to compute the x- and y-components of the horizontal gradient of the 2D data, and provides optimal low-pass filtering to the noisy data as well. The amount of filtering depends on the order of polynomial and the dimension of the filter window. The vertical gradient is computed through a Hilbert transform of the x- and y-components of the horizontal gradient in the space domain using a sinc interpolation method, where a regularization technique and a conjugate gradient solver are used to determine the sinc bases which are used to compute the Hilbert transform. Numerical experiments on synthetically generated 2D data contaminated with varied levels of random noise were carried out and a comparison of the present technique with the standard Fourier domain technique was also made. The applicability of the method to the field data was also tested. © 2013 Sinopec Geophysical Research Institute. Source

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