Geochemical anomalies associated with mineralization represent one of the most significant types of geo-anomalies for mineral exploration.This study develops a AI method that combines geological knowledge with a flexible deep learning model. It helps identify geochemical anomaly patterns more accurately and reliably by focusing on key features like ore-controlling faults. The model's decisions are easier to understand through visual explanations, increasing transparency and trust in the results.