H. Mahdiyanfar
Abstract
Over the past two decades, the frequency domain (FD) of the geochemical data has been studied by some researchers. Metal zoning is one of the challenging subjects in the mining exploration, where a new scenario has been proposed for solving this problem in FD. Three mineralization areas including the ...
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Over the past two decades, the frequency domain (FD) of the geochemical data has been studied by some researchers. Metal zoning is one of the challenging subjects in the mining exploration, where a new scenario has been proposed for solving this problem in FD. Three mineralization areas including the Dalli (Cu-Au), Zafarghand (Cu-Mo), and Tanurcheh (Au-Cu) mineralization areas are selected for this investigation. After transferring the surface geochemical data to FD, the geochemical signals obtained are filtered using the wavenumber-based filters. The high and moderate frequency signals are removed, and the residual signals are interpreted by the statistical method of principal component analysis (PCA). In order to discriminate the deep metal ore deposits, the principal factors of elemental power spectrum extracted by PCA are depicted in a novel diagram (PC1 vs. PC2). This approach indicates that the geochemical data in the Dalli and Zafarghand deep ore deposits have similar frequency behaviors. The Au, Mo, and Cu elements in these two areas are discriminated from the Au, Mo, and Cu mineralization elements of the Tanurcheh area as a deep non-mineralization zone in this diagram. This new criterion used for distinguishing the buried ore deposits and deep non-mineralization zones is properly confirmed by the exploratory deep drilled boreholes. The geochemical anomaly filtering demonstrates that the strong signatures of deep mineralization are associated with the low frequency geochemical signals at the surface, and the buried mineralization areas with weak surface anomaly can be identified using the geochemical FD data.
A. Khojamli; F. Doulati Ardejani; A. Moradzadeh; A. Nejati Kalateh; A. Roshandel Kahoo; S. Porkhial
Abstract
The Ardabil geothermal area is located in the northwest of Iran, which hosts several hot springs. It is situated mostly around the Sabalan Mountain. The Sabalan geothermal area is now under investigation for the geothermal electric power generation. It is characterized by its high thermal gradient and ...
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The Ardabil geothermal area is located in the northwest of Iran, which hosts several hot springs. It is situated mostly around the Sabalan Mountain. The Sabalan geothermal area is now under investigation for the geothermal electric power generation. It is characterized by its high thermal gradient and high heat flow. In this study, our aim is to determine the fractal parameter and top and bottom depths of the magnetic sources. A modified spectral analysis technique named “de-fractal spectral depth method” is developed and used to estimate the top and bottom depths of the magnetized layer. A mathematical relationship is used between the observed power spectrum (due to fractal magnetization) and an equivalent random magnetization power spectrum. The de-fractal approach removes the effect of fractal magnetization from the observed power spectrum, and estimates the parameters of the depth to top and depth to bottom of the magnetized layer using the iterative forward modelling of the power spectrum. This approach is applied to the aeromagnetic data of the Ardebil province. The results obtained indicated variable magnetic bottom depths ranging from 10.4 km in the northwest of Sabalan to about 21.1 km in the north of the studied area. In addition, the fractal parameter was found to vary from 3.7 to 4.5 within the studied area.