Data Leveling of Multi-Map Geochemical Exploration Data Using Compositional Data Analysis: A Case Study from the Baiyinchagan–Maodeng Area, Inner Mongolia, China

Exploration geochemical data are typically collected and analyzed according to standard map sheets. Different map sheets may be tested by different companies, at different times, or using different instruments. As a result, “systematic errors” inevitably arise, which are directly reflected in the “shift” effect between different map sheets. This study compares various leveling methods, including contrast return (CR), boundary leveling (BL), and multi-scale correction (MSC), based on compositional data transformation of six map sheets from the Baiyinchagan–Maodeng area. The results show the following features: the raw data from multiple map sheets contain certain errors, and these raw data cannot be directly used to create geochemical maps; the CR method is unsuitable for leveling in areas with small scales or significant geological background differences; the BL method yields more reasonable results when there is a similar geochemical background (geological background) between map sheets, and it is better suited for leveling between map sheets in areas with small scales or significant regional differences in geochemical backgrounds; finally, the MSC method yields results similar to the BL method, but it does not require boundary consistency, thus having fewer limitations, although it requires multi-scale geochemical data. In practical terms, this study provides valuable guidance for selecting appropriate geochemical data leveling methods in exploration projects, thereby improving the accuracy and reliability of geochemical mapping and enhancing the effectiveness of mineral exploration.