Applying a Structural Multivariate Method Using the Combination of Statistical Methods for the Delineation of Geochemical Anomalies

Abstract

Quantitative descriptions of geochemical patterns and providing geochemical anomaly map are important in applied geochemistry. Several statistical methodologies (nonstructural and structural) are presented in order to identify and separate geochemical anomalies. Structural methods take the sampling locations and their spatial relation into account for estimating the anomalous areas. In the present study, a nonstructural method (Mahalanobis distance method as a multivariate method) is used and U-statistic is considered as a structural method to assess prospective areas of Susanvar district as a gold mineralization index in the Torud-Chah Shirin mountain range of Semnan Province, northern Iran. Results show that the U-statistic method is an efficient method according to spatial distribution of the anomalous samples. In the present study, according to the ability of U-statistic method in combining with other methods, the goal is to use and develop Mahalanobis distance method in structural mode. For this purpose, Mahalanobis distance should be combined with a structural method which devotes a new value to each sample based on its surrounding samples. For this reason, the combination of efficient U-statistic method and multivariate Mahalanobis distance method has been used to separate geochemical anomalies from background. Combination results show that the performance of these two methods is more accurate than using just one of them. Because samples indicated by the combination of these methods as anomalous are less dispersed and closer to each other than in the case of using just the U-statistic and 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 study 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 Mahalanobis distance method.