Abstract: The deep mining of geological mineral information from geochemical exploration data has been a hot research topic in mathematical geology and geological big data. Despite China's abundant regional geochemical exploration data, the deep mining of geological mineral information from these data remains limited, necessitating a scientific, efficient, simple, and feasible data processing workflow and analytical methodology. This study investigated the Gaoqiao area in Huixian County, Gansu Province, China. According to the geological background and the theories of element properties and geochemical behavior, this study processed relevant element data to mine the geological mineral information in geochemical exploration data. It established preliminary mathematical models for the boundary delineation and lithofacies classification of intermediate-acid rock masses, and the boundary delineation of mafic volcanic rocks in the Gaoqiao area to scientifically guide geological mapping. It preliminarily established the target delineation model for tectonic altered rock-hosted gold deposits. The model's effectiveness was substantiated by seven newly delineated target areas with promising prospecting potential. The mineral inspection identified five ore occurrences, including four reported for anomalies related to mineralization, with two currently under provincial geological exploration. The results of this study show that by calculating and processing data based on the geochemical properties of elements, the hidden information in regional geochemical exploration data can be further mined to effectively guide and modify geological mapping, thereby enhancing mapping efficiency and quality. High-quality anomaly information can be further extracted from geochemical exploration data to effectively guide mineral prospecting in new areas.