the area is located 20 km northwest of kashmar and about 4 km of kalateh taimour in khorasan razavi province. the study area is part of tertiary volcanic-plutonic belt north of daruneh fault and its situation in tectonic inliers between two important active faults, doruneh and taknar. volcanic rocks are mainly intermediate to acid pyroclastic type. they formed during early tertiary. the volcani...

Three-dimensional (3D) geological models are typical data sources in 3D mineral prospectivity modeling. However, identifying prospectivity-informative predictor variables from is a challenging and work-intensive task. Motivated by the ability of convolutional neural networks (CNNs) to learn intrinsic features, this paper, we present novel method that leverages CNNs models. By exploiting learnin...

in order to assess the potential of copper mineralization and its associated elements in soltan meydan basaltic formation situated in the north of shahrud, the method of stream sediment and heavy mineral has been used. to achieve this aim, totally 68 samples of sediments (-80 mesh in particle size) and 6 samples of heavy minerals (-20 mesh in particle size) have been collected in an optimized n...

the tajroud vein system is located 190 km southwest of mashhad, and in the southern part of the sabzevar zone. the vein host rocks consist of eocene intermediate to silicic volcanic rocks. the mineralization occurs as open space filling, taking place as veins, veinlets and hydrothermal breccias. based on field geology and textural evidence, three main stages of mineralization were identified. s...

In this work, the concentration gradient (CG) analysis of local-scale exploration for Porphyry-Cu deposits is applied in two zones using the G(Vz) index (CG(Zn*Pb)/CG(Cu*Mo)). The first zone is covered by a 1:2000 map of the Sungun and Astamal areas in NW Iran and the second one in the Inza area in British Columbia, Canada. The rock samples are taken from Sungun and Astamal and the soil samples...

The classification of mineralized areas into different groups based on mineral grade and prospectivity is a practical problem in the area of optimal risk, time, and cost management of exploration projects. The purpose of this paper was to present a new approach for optimizing the grade classification model of an orebody. That is to say, through hybridizing machine learning with a metaheuristic ...