M. Babaei; M. Abedi; Gh. H. Norouzi; S. Kazem Alilou
Abstract
This work presents the application of a geostatistical-based modeling approach for building up electrical properties acquired from a geophysical electrical tomography survey deployed for the purpose of porphyry Cu exploration at the Takht-e-Gonbad deposit, in the central domain of Iran. Electrical data ...
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This work presents the application of a geostatistical-based modeling approach for building up electrical properties acquired from a geophysical electrical tomography survey deployed for the purpose of porphyry Cu exploration at the Takht-e-Gonbad deposit, in the central domain of Iran. Electrical data were inverted in 2D along several profiles across the main favorable zones of Cu-bearing mineralization to image electrical resistivity and chargeability properties. Upon tight spatial correlation of these geophysical properties and Cu mineralization (i.e. Cu grade), electrical models were constructed in 3D through geostatistical interpolation of 2D inverted data to provide insights into the geometry of probable ore mineralization. Anomalous geophysical zone that was coincident simultaneously with higher values of electrical chargeability and resistivity, was in accordance with the main body of high Cu grades generated from exploratory drillings. It reveals that the porphyry-type Cu mineralization system in this area has strong geophysical footprints controlled mainly by rock types and alterations. Note that these physical models supply valuable pieces of information for designing the layout of further exploratory drillings, constructing geological characteristics, separating non-mineralized form mineralized zones, and resource modeling.
M. Rezaie; S. Moazam
Abstract
Inversion of magnetic data is an important step towards interpretation of the practical data. Smooth inversion is a common technique for the inversion of data. Physical bound constraint can improve the solution to the magnetic inverse problem. However, how to introduce the bound constraint into the inversion ...
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Inversion of magnetic data is an important step towards interpretation of the practical data. Smooth inversion is a common technique for the inversion of data. Physical bound constraint can improve the solution to the magnetic inverse problem. However, how to introduce the bound constraint into the inversion procedure is important. Imposing bound constraint makes the magnetic data inversion a non-linear inverse problem. In this work, a new algorithm is developed for the 3D inversion of magnetic data, which uses an efficient penalization function for imposing the bound constraint and Gauss Newton method to achieve the solution. An adaptive regularization method is used in order to choose the regularization parameter in this inversion approach. The inversion results of synthetic data show that the new method can produce models that adequately match the real location and shape of the synthetic bodies. The test carried out on the field data from Mt. Milligan copper-gold porphyry deposit shows that the new inversion approach can produce the magnetic susceptibility models consistent with the true structures.
Ali Nejati Kalateh; Amin Roshandel kahoo
Abstract
We inverse the surface gravity data to recover subsurface 3D density distribution with two strategy. In the first strategy, we assumed wide density model bound for inverting gravity data and In the second strategy, the inversion procedure have been carried out by limited bound density. Wediscretize the ...
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We inverse the surface gravity data to recover subsurface 3D density distribution with two strategy. In the first strategy, we assumed wide density model bound for inverting gravity data and In the second strategy, the inversion procedure have been carried out by limited bound density. Wediscretize the earth model into rectangular cells of constant andunidentified density. The number of cells is often greater than the number of observation points thus we have an underdetermined inverse problem. The densities are estimated by minimizing a cost function subject to fitting the observed data. The synthetic results show that the recovered model from the first strategy is characterized by broad density distribution around the true model, butthat of the second strategy is closer to true models.We carry out inversion of gravity data taken over chromite deposit located at Hormozgan providence of Iran for estimating of subsurface density distribution. The recovered model obtained from second strategy has appropriate agreement with previous study.
