Compositional data analysis of regional geochemical data in the Lhasa area of Tibet, China

It is now widely recognized that geochemical survey data are compositional in nature, with each component having relative importance as part of a whole. Compositional analysis (CoDA) based on log-ratio transformations can be used to deal the ‘sum one’ constraint. This study explored use two data-driven CoDA approaches, centered (clr)-biplot and compositional-balance approach, investigate associations between elements for potential mineral exploration Lhasa area Tibet, China. Results revealed (1) hierarchical cluster sequential binary partition (SBP) technique, well reflects range rocks metal deposits area; (2) clr-biplot indicates associated relationships elements, consistency found principal (PC1 PC2) key balances (Balance 1 4); (3) comparison traditional integrated mapping, knowledge-driven method, proves validity methods. These results provided metallogenic petrogenetic information crucial evidence supporting further geological exploration. The improved knowledge demonstrates using approach before performing statistical analysis.