gold

This study reports the application of remote sensing data and knowledge-driven GIS modeling to provide favorability maps for gold and copper mineralized areas. The South Gabal Um Monqul (SGUM) and the Gabal Al Kharaza (GKZ) prospects located in the northern Eastern Desert of Egypt are the targets for the present study. Four thematic layers (lithology maps, old trenches buffer analysis, lineament density maps, and alteration zone maps) were prepared and used as inputs for a weighted overlay GIS model. Combined results from false color composite images, particularly the RGB parameters (PC2, PC1, and PC3) and the RGB parameters (MNF1, MNF2, and MNF3) classified the host rocks in both prospects. PCA-based extraction of lineaments was considered using line algorithm of PCI Geomatica. QuickBird band math (G+B), (R+G), and (G-B) for RGB was successful in delineating ancient workings within the mineralized zones. Old trenches layers were buffered to 20 m wide bands extending in all directions. Landsat-8 band ratios imagery (6/5 * 4/5, 6/7, and 6/2) in red, green, and blue (RGB) is potent in defining alteration zones that host gold and copper mineralizations. Acceptable scores of 30%, 30%, 20%, and 20% were assigned for the alteration zone maps, ancient workings buffer analysis, lithology maps and lineament density maps, respectively. Two favorability maps for mineralizations were generated for the SGUM and GKZ prospects. Validation of these maps and their potential application to detect new mineralization sites in the northern Eastern Desert were discussed.

This paper elucidates a new idea and concept for exploration of the gold ore deposits.  The cyanidation method is traditionally used for gold extraction. However, this method is laborious, time-consuming, costly, and depends upon the availability of the processing units. In this work, an attempt is made in order to update the gold exploration method by the Monte Carlo-based simulation. An excellent approach always requires a high quality of the datasets for a good model. A total of 48 incomplete datasets are collected from the Shoghore district, Chitral area of Khyber, Pakhtunkhwa, Pakistan. The cyanidation leaching test is carried out in order to measure the percentage of the gold ore deposits. In this work, the mean, median, mode, and successive iteration substitute methods are employed in such a way that they can compute the datasets with missing attributes. The multiple regression analysis is used to find a correlation between the potential of hydrogen ion concentration (pH), solid content (in %), NaCN concentration (in ppm), leaching time (in Hr), particle size (in µm), and measured percentage of gold recovery (in %). Moreover, the normal Archimedes and exponential distributions are employed in order to forecast the uncertainty in the measured gold ore deposits. The performance of the model reveals that the Monte Carlo approach is more authentic for the probability estimation of gold ore recovery. The sensitivity analysis reveals that pH is the most influential parameter in the estimation of the gold ore deposits. This stochastic approach can be considered as a foundation to foretell the probabilistic exploration of the new gold deposits.

Oxidation of sulfide-containing ores is the main cause of Acid Mine Drainage (AMD), which is an environmental problem associated with both the abandoned and active mines. Iron-bearing sulfide minerals can be oxidized and form mine waters with high sulfate content, low pH, high electrical conductivity, high redox potential, and high concentrations of iron, aluminum, and other heavy metals. In the process of AMD, precipitation of poorly crystalized oxy-hydroxides of iron with a large active surface can occur. On the surface of iron oxy-hydroxide, the precipitated particulate matter, anions, and cations (metals) could be adsorbed. Mine waters can contain a certain amount of precious metals that can also be adsorbed onto an iron particulate matter surface, which is investigated in this research work. In this work, the samples of iron oxy-hydroxide particulate matter at abandoned gold mine waste in Bakovići (Central Bosnia and Herzegovina) are used. Several parameters including pH, water content, particle size distribution, sulfate content, electrical conductivity, redox potential, and amounts of gold, silver, and iron are measured on the selected mine waste samples. The results obtained indicate that significant amounts of gold (average: 6.8 mg/kg) and silver (average: 7.13 mg/kg) are present in the iron precipitate. Adsorption of precious metals onto the iron oxy-hydroxide surface is strongly pH-dependent. At a very low pH value, desorption of precious metals is favorite. Thus, precious metals are only partially adsorbed onto the iron oxy-hydroxide surface.