Over the past several decades, a wide range of complex structures or phenomena of interest
to geologists and geochemists has been quantitatively characterized using …

Data-driven mineral prospectivity map** (MPM) based on deep learning methods has
become a powerful tool for mineral exploration targeting in the past years. Convolutional …

This study aims to differentiate between Cu-Mo and Cu-Au porphyry deposits within Iran
through fractal modeling, utilizing the Mo/Au geochemical index as a primary determinant …

Fractal/multifractal classification models applied to regional geochemical data are typically
based on relationships between geochemical concentrations and mathematical, statistical or …

The separation, identification and assessment of high-grade ore zones from low-grade ones
are extremely important in mining of metalliferous deposits. A technique that provides …

Various statistical methods, including fractal/multifractal techniques, have been applied to
clustering of geochemical samples based on their elemental concentrations. Most …

Determining indicator element association for mineralization can not only improve mineral
exploration efficiency but also reduce the cost of unnecessary element analysis during …

Parent lithology exerts a major influence on the associated regolith geochemistry and affects
the setting of population or domain boundaries. In regional geochemical map** and …

Regional mineral exploration is based on geochemical data of which the nature is
compositional and frequently involves a large number of components. Consequently, it …

Dispersion pattern of geochemical elements in stream sediment data of a study area is
affected by several factors, eg, geological and geomorphological characteristics of the area …