due to substantial effect of classification of resource models on future mine planning, one should come with an accurate method of estimation to guarantee that the minimum error is acquired in the estimation process. the known world class cu-mo deposit, sarcheshmeh porphyry deposit (central iran) selected as the study area. the hypogene zone of the deposit was chosen as the space in which estim...

due to substantial effect of classification of resource models on future mine planning, one should come with an accurate method of estimation to guarantee that the minimum error is acquired in the estimation process. the known world class cu-mo deposit, sarcheshmeh porphyry deposit (central iran) selected as the study area. the hypogene zone of the deposit was chosen as the space in which estim...

Hyperspectral remote sensing records reflectance or emittance data in a large sum of contiguous and narrow spectral bands, and thus has many information in detecting and mapping the mineral zones. On the other hand, the geological and geophysical data gives us some other fruitful information about the physical characteristics of soil and minerals that have been recorded from the surface. ...

Abstract A current mineral exploration focus is the development of tools to identify magmatic districts predisposed host porphyry copper deposits. In this paper, we train and test four, common, supervised machine learning algorithms: logistic regression, support vector machines, artificial neural networks (ANN) Random Forest classify metallogenic ‘fertility’ in arc magmas based on whole-rock ge...

Porphyry copper (Cu) systems occur along magmatic belts derived in subduction zones. Our current understanding of their formation is restricted to observations from the overriding plate, resulting a knowledge gap terms processes occurring convergence zones through time. An association between key tectonic and timing location porphyry Cu requires linking geological plate models. We connect evolu...

The purpose of this study is to identify the enriched zones of Cu, Mo and Re in Nowchun Mo-Cu porphyry deposit (SE Iran) based on subsurface data and using of concentration–volume (C–V) fractal model. The C-V model illustrates four and five geochemical zones based on Mo and Cu distributions respectively and there are three geochemical populations for Re. The main mineralization for Mo, Cu and R...