Separating the gravity field of Iraq by using bidimensional empirical mode decomposition technique
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ORIGINAL PAPER
Separating the gravity field of Iraq by using bidimensional empirical mode decomposition technique Ali M. Al-Rahim 1
Received: 26 November 2014 / Accepted: 18 September 2015 # Saudi Society for Geosciences 2015
Abstract Potential field is nonstationary and nonlinear data. The empirical mode decomposition (EMD) is considered as new data analysis method suitable for processing such type of data. EMD is a fully data driven technique to decompose signals into their natural scale components. It expresses the original signal as a sum of intrinsic mode functions (IMFs) whose characteristics are a reflection of the intrinsic physical meanings of the original signal. This research proposes the bidimensional empirical mode decomposition (BEMD) based on the calculation principle of empirical mode decomposition to be applied for separating the gravity field of Iraq. The method is compared with polynomial method to separate the same field. BEMD method shows a preference on the polynomial method in separating the gravity field into multi-scale components which reflects the anomaly source form from shallow to deep. Keywords Bidimensional empirical mode decomposition (BEMD) . Intrinsic mode functions (IMFs) . Potential field separation . Gravity field of Iraq
Introduction Gravity anomaly separation into the regional and residual is considered an essential step before any qualitative and quantitative interpretation process. The reason is because the observed gravity anomalies represent the combined effects of
* Ali M. Al-Rahim [email protected] 1
College of Science, University of Baghdad, Baghdad, Iraq
sources under different depth and/or density variation. Usually, the regional Bouguer gravity anomaly is the longer wavelength field due to deep sources, whereas the residual Bouguer gravity anomaly stands for short wavelength fields of shallower bodies. Normally, the short wavelength fields disappear gradually with depth. For that purpose (anomalies separation), several techniques are applied and developed for more than seven decades but none may be taken for granted as the most effective one. These techniques may be classified into two probable categories: (1) intuitive graphical which is highly flexible and requires considerable expertise (Nettleton 1976; Li and Oldenburg 1998) and (2) mathematical techniques, which are least squares polynomial (Simpson 1954; Abdelrahman et al. 1985; Zeng 1989; Abokhodair 2011). orthogonal polynomial (Oldham and Sutherland 1955). two-dimensional frequency analysis and design of grid operators (Fuller 1967). relaxation technique (Paul 1967; Skeels 1967). statistical models (Spector and Grant 1970; Spector 1975). Fourier method (Syberg 1972). minimum curvature technique (Mickus et al. 1991). wavelet analysis (Fedi and Quarta 1998). finite element method (Mallick and Sharma 1999; Kannan and Mallick 2003; Kaftan et al. 2005). differential Markov random field (Ucan et al. 2000). and many others. The Fourier transform (FFT) is designed to work with linear and stationary signals
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