Exploitation
S. Salarian; O. Asghari; M. Abedi; S. K. Alilou
Abstract
This work aims at figuring out the spatial relationships between the geophysical and geological models in a case study pertaining to copper-sulfide mineralization through an integrated 3D analysis of favorable target. The Ghalandar Skarn-Porphyry Cu Deposit, which is located in NW Iran, is selected for ...
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This work aims at figuring out the spatial relationships between the geophysical and geological models in a case study pertaining to copper-sulfide mineralization through an integrated 3D analysis of favorable target. The Ghalandar Skarn-Porphyry Cu Deposit, which is located in NW Iran, is selected for this research work. Three geophysical surveys of direct current electrical resistivity and induced polarization tomography along with magnetometry are performed to construct the physical properties of electrical resistivity, chargeability, and magnetic susceptibility, respectively. Inverse modeling and geostatistical interpolation are utilized to generate the physical 3D models. A 3D model of Cu grade is generated using ordinary kriging; however, the indicator kriging method is run to design a 3D model of rock types through incorporating the drilling results. Block models of geophysical and geological characteristics are cast in a similar 3D mesh to investigate their relationships in copper mineralization. A concentration-volume multi-fractal method is utilized to divide each model into its sub-sets, where the most productive portions in association with Cu-bearing mineralization are distinguished. Note that sub-sets of geophysical models are spatially matched with geological models of Cu grade and rock types. The zones with low electrical resistivity, high chargeability, and low magnetic susceptibility correspond to the main source of Cu mineralization in a dominated skarn rock type setting.
Maysam Abedi; Gholam-Hossain Norouzi; Nader Fathianpour; Ali Gholami
Abstract
This paper describes the application of approximate methods to invert airborne magnetic data as well as helicopter-borne frequency domain electromagnetic data in order to retrieve a joint model of magnetic susceptibility and electrical resistivity. The study area located in Semnan province of Iran consists ...
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This paper describes the application of approximate methods to invert airborne magnetic data as well as helicopter-borne frequency domain electromagnetic data in order to retrieve a joint model of magnetic susceptibility and electrical resistivity. The study area located in Semnan province of Iran consists of an arc-shaped porphyry andesite covered by sedimentary units which may have potential of mineral occurrences, especially porphyry copper. Based on previous studies, which assume a homogenous half-space earth model, two approximate methods involving the Siemon and the Mundry approaches are used in this study to generate a resistivity-depth image of underground geologically plausible porphyry unit derived from airborne electromagnetic data. The 3D visualization of the 1D inverted resistivity models along all flight lines provides a resistive geological unit which corresponds to the desired porphyry andesite. To reduce uncertainty arising from single geophysical model, i.e., the resistivity model acquired from the frequency domain electromagnetic data, a fast implementable approach for 3D inversion of magnetic data called the Lanczos bidiagonalization method is also applied to the large scale airborne magnetic data in order to construct a 3D distribution model of magnetic susceptibility, by which the obtained model consequently confirms the extension of an arc-shaped porphyry andesite at depth. The susceptible-resistive porphyry andesite model provided by integrated geophysical data indicates a thicker structure than what is shown on the geological map while extends down at depth. As a result, considering simultaneous interpretation of airborne magnetic and frequency domain electromagnetic data certainly yield lower uncertainty in the modeling of andesite unit as a potential source of copper occurrences.