Interpretation of the magnetic data from Shavaz iron ore using enhanced local wavenumber (ELW) and comparison with Euler
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ORIGINAL PAPER
Interpretation of the magnetic data from Shavaz iron ore using enhanced local wavenumber (ELW) and comparison with Euler deconvolution method K. Alamdar 1
Received: 15 December 2014 / Accepted: 1 August 2016 # Saudi Society for Geosciences 2016
Abstract This paper presents an inversion method for the interpretation of 2D magnetic anomaly data, in which uses the enhanced local wavenumber function to estimate the depth and the nature (structural index) of an isolated magnetic source. However, the method is sensitive to noise. In order to lower the effect of noise, I applied upward continuation technique to smooth the anomaly. Tests on synthetic noisefree and noise-corrupted magnetic data show that the method can successfully estimate the depth and the nature of the causative source. The practical application of the technique is applied to measured magnetic anomaly data from Shavaz Iron Ore, center of Iran, and the inversion results are in agreement with the inversion results from Euler deconvolution of the analytic signal and exploratory drilling. Keywords Euler deconvolution . Wavenumber . Structural index . Upward continuation . Shavaz
Introduction Nowadays, a large amount of magnetic data is collected for environmental and geological applications, including mineral and oil exploration and groundwater investigations. Many experts have developed manual or automatic techniques to interpret the large amount of data acquired from these surveys. The common parameter sought for by all methods is undoubtedly the location of the magnetic source bodies and their depths. A * K. Alamdar [email protected]; [email protected] 1
Department of the Mining and Metallurgical Engineering, Yazd University, Yazd, Iran
reliable depth estimate of the causative source helps in planning drill holes to test the magnetic targets. If the thickness of non-mineralized cover rocks could be estimated with reasonable accuracy, the budgeting and planning of exploitation program can be improved (Agarwal and Srivastava 2008). There are various techniques used for interpretation of magnetic data, viz., slope method (Peters 1949), decomposition in even and odd functions (Naudy 1971), analytical signal (Nabighian 1972), Euler deconvolution (Thompson 1982), Werner deconvolution (Ku and Sharp 1983), source parameter imaging (SPI) or local wavenumber technique (Thurston and Smith 1997; Salem and Smith 2005), continuous wavelet transform (Ridsdill-Smith 1998), and Euler deconvolution of the analytical signal (Keating and Pilkington 2004). Each of these techniques has its own advantages and disadvantages in accurate estimation of depth and location and geometry of the causative source. Approximately, all the interpretation methods suffer from an inherent ambiguity due to a lesser number of known quantities than the number of unknown parameters describing the geological model. For example, in the conventional Euler deconvolution (CED) method, the structural index must be known and inserted into the equation before solving for
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