A method for extracting anomaly map of Au and As using combination of U-statistic and Euclidean distance methods in Susanvar district, Iran

Quantitative descriptions of geochemical patterns and providing geochemical anomaly map are important in applied geochemistry. Several statistical methodologies are presented in order to identify and separate geochemical anomalies. The U-statistic method is one of the most important structural methods and is a kind of weighted mean that surrounding points of samples are considered in U value determination. However, it is able to separate the different anomalies based on only one variable. The main aim of the presented study is development of this method in a multivariate mode. For this purpose, U-statistic method should be combined with a multivariate method which devotes a new value to each sample based on several variables. Therefore, at the first step, the optimum p is calculated in p-norm distance and then U-statistic method is applied on p-norm distance values of the samples because p-norm distance is calculated based on several variables. This method is a combination of efficient U-statistic method and p-norm distance and is used for the first time in this research. Results show that p-norm distance of p=2 (Euclidean distance) in the case of a fact that Au and As can be considered optimized p-norm distance with the lowest error. The samples indicated by the combination of these methods as anomalous are more regular, less dispersed and more accurate than using just the U-statistic or other nonstructural methods such as Mahalanobis distance. Also it was observed that the combination results are closely associated with the defined Au ore indication within the studied area. Finally, univariate and bivariate geochemical anomaly maps are provided for Au and As, which have been respectively prepared using U-statistic and its combination with Euclidean distance method

Lead and zinc geochemical behavior based on geological characteristics in Parkam Porphyry Copper System, Kerman, Iran

Parkam (Sarah) porphyry system is located on the metallogenic belt of Kerman, Iran. Due to existence of some copper-rich resources in this region, finding out the exact statistical characteristics such as distribution of data population, mean, variance and data population behavior of elements like Cu, Mo, Pb and Zn is necessary for interpreting their geological behavior. For this reason, precise calculation of statistical characteristics of Pb and Zn grade datasets was performed and results were interpreted geologically. The natures of Pb and Zn distributions were initially identified and their distributions were normalized through statistical treatment. Subsequently, the variograms were calculated for each exploration borehole and show that both Pb and Zn geochemical variates are spatially correlated. According to the similarity of the behavior of Pb and Zn in these calculations, it is decided to measure their exact behavior applying K-means clustering method. K-means clustering results show that the Zn grade varies linearly relative to that of Pb values and their behavior is similar. Based on the geochemical behavior similarity of Pb and Zn, throughout the pervasive secondary hydrothermal activity, they are remobilized in the similar manner, from the deep to the shallow levels of the mineralization zones. However, statistical analysis suggests that hydrothermal activity associated with secondary waters in Parkam is effective in remobilizing and enriching both Pb and Zn since they have similar geochemical characteristics. However, the process does not result in generation of economic concentrations