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- W2078225504 abstract "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." @default.
- W2078225504 created "2016-06-24" @default.
- W2078225504 creator A5088504528 @default.
- W2078225504 date "2013-06-01" @default.
- W2078225504 modified "2023-09-25" @default.
- W2078225504 title "On computing gradients of potential field data in the space domain" @default.
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- W2078225504 doi "https://doi.org/10.1088/1742-2132/10/3/035007" @default.
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