Analysis of closed and open numerical systems of geochemical data in spatial statistics environment in order to separate anomalous areas.

Geochemical data are expressed in closed numerical systems due to their non-normality and the presence of outliers. The specificity of such data makes it challenging to analyze them using standard statistical techniques. The U-modeling of log-transformed data represents a novel approach to geochemical anomaly separation. This method models the geochemical open or log-transformed data by the U-spatial statistics algorithm and has been used for the first time in this paper. In this research, Additive and Centered Logarithmic Transformations (ALR and CLR) were applied to data from the Doostbiglou region in Ardabil province, Iran, known for its copper-gold and molybdenum mineralization. After transforming the data into an open numerical system, the correlation between elements was calculated for both systems to compare the results. The output data were modeled using the U-spatial statistics method, and anomaly maps were subsequently generated. Validation and comparison of the results, considering field data obtained from the local and regional exploration, revealed that both models produced similar results in separating anomalous areas and showed a high degree of agreement with field data. However, the U-modeling of the ALR data more closely aligns with field observations and provides a more precise representation of the mineralization trend. Therefore, these new models are recommended for evaluating the spatial distribution of elements and determining the threshold value.