Geochemical anomaly delineation utilizing copula-based outlier detection method

Abstract

This study evaluates the effectiveness of Copula-Based Outlier Detection (COPOD) in identifying geochemical anomalies within the Toroud–Chah Shirin belt (TCSB) in Iran. The TCSB is a significant mineralized zone containing epithermal precious and base metal veins, skarn, gold placer, and Pb–Zn sedimentary-hosted deposits. Unlike proximity-based or learning-based models, COPOD is a fully deterministic and unsupervised statistical approach. It requires no hyperparameter tuning or assumptions regarding data distribution, making it ideal for the skewed, non-Gaussian nature of stream sediment datasets. By modeling multivariate dependencies through empirical cumulative distribution functions (ECDFs), COPOD captured complex element relationships, such as Ag–Pb and Bi–Au, which relate to sedimentary-hosted and epithermal gold deposits in the region. Comparative analysis using Receiver Operating Characteristic (ROC) curves demonstrates that COPOD outperforms both traditional uni-element mapping and the state-of-the-art Isolation Forest (IF) method. Using a 10% contamination threshold, the COPOD method identified 23 out of 32 known mineral occurrences, whereas the IF method captured 19. Furthermore, this study uses dimensional outlier graphs to provide transparent results, highlighting the influence of Co, Zn, Sb, and Pb on anomaly scores. Results from Lasso regression and random forest analysis further confirmed these elemental impacts. Comparison with the regional geological map shows that most anomalies occur within Paleogene volcanic units and the Cretaceous sedimentary unit that hosts Pb–Zn mineralization. However, some extend into surficial areas due to geochemical dispersion. Overall, COPOD offers a robust, efficient, and explainable alternative for multivariate geochemical anomaly delineation.