جستجوی مقالات مرتبط با کلیدواژه « staged factor analysis » در نشریات گروه « مهندسی معدن »

The purpose for this research is to define the gold mineralization potentials by the concentration-number fractal and staged factor analysis modeling based on rock samples at the Bardaskan area (NE Iran). Two main gold mineralization types are epithermal and disseminated systems in this district. First, the staged factor analysis is carried out at four stages. The stepwise factor analysis was applied in three stages to remove noise elements. Moreover, staged factor analysis was applied in the fourth step based on metallic elements including Au, Ag, Cu, As, Fe, Mo, Bi, La, S, Zn, and Cd were grouped. These elements are grouped at four factors, and related factors for gold mineralization are F1-4 (first factor in the fourth stage) which is consisting of As, Mo, S and Fe and F3-4 (third factor in the fourth stage) includes Au and Ag. The concentration-number log–log plots for factor scores of F1-4 and F3-4 were generated, and their threshold values were calculated to create the factor score’s geochemical maps. Based on these results, the gold mineralization potentials are positioned in the NE, northern and SE sections of the district, which indicate a correlation among alteration zones, including chloritization, sericitization, and silicification alteration zones and faults and fault’s intersections. Main Au mineralization occurred in silicified-sulfidic veins/veinlets in NE and northern portions of the region. However, high grade F3-4 anomalies are located in intersection of faults and neighboring fault zones especially at the northern part of this district. Moreover, Samples with Au≥ 100 ppb were situated in major anomalous parts of F3-4 (Au-Ag) and marginal parts of the F1-4, which include pathfinder of gold mineralization.

The traditional approaches of modeling and estimation of highly skewed deposits have led to incorrect evaluations, creating challenges and risks in resource management. The low concentration of the rare earth element (REE) deposits, on one hand, and their strategic importance, on the other, enhances the necessity of multivariate modeling of these deposits. The wide variations of the grades and their relation with different rock units increase the complexities of the modeling of REEs. In this work, the Gazestan Magnetite-Apatite deposit was investigated and modeled using the statistical and geostatistical methods. Light and heavy REEs in apatite minerals are concentrated in the form of fine monazite inclusions. Using 908 assayed samples, 64 elements including light and heavy REEs from drill cores were analyzed. By performing the necessary pre-processing and stepwise factor analysis, and taking into account the threshold of 0.6 in six stages, a mineralization factor including phosphorus with the highest correlation was obtained. Then using a concentration-number fractal analysis on the mineralization factor, REEs were investigated in various rock units such as magnetite-apatite units. Next, using the sequential Gaussian simulation, the distribution of light, heavy, and total REEs and the mineralization factor in various realizations were obtained. Finally, based on the realizations, the analysis of uncertainty in the deposit was performed. All multivariate studies confirm the spatial structure analysis, simulation and analysis of rock units, and relationship of phosphorus with mineralization.

The aim of this work was to delineate the prospects of podiform-type chromite by staged factor analysis and geochemical mineralization prospectivity index in Balvard area, SE Iran. The stream sediment data and fault density were used as the exploration features for prospectivity modeling in the studied area. In this regard, two continuous fuzzified evidence layers were generated and integrated using fuzzy operator. Then fractal modeling was used for defuzzification of the prospectivity model obtained. Furthermore, the prediction-area plot was used for evaluation of the predictive ability of the generated target areas. The results obtained showed that using the prospectivity model, 82% of mineral occurrences was predicted in 18% of the studied area. In addition, the target areas were correlated with the geological particulars including ultrabasic and serpentinization rocks, the host rocks of the podiform-type chromite deposit type.