Identification of geochemical anomalies in multibackground areas using the combined k-means clustering and residual contrast value method: A case study in a district in Hunan, China.

Due to the complex characteristics of geological structures, identifying geochemical anomalies in valuable deposits using regional geochemical datasets of stream sediments is challenging. In this study, an effective combined method was proposed to solve the problem of anomaly identification in multibackground areas. First, samples were classified into different clusters through the k-means clustering method using major elements/minerals (such as SiO 2 and Na 2 O) that can reflect the lithology and were chosen as classification indicators. Considering the double restriction of the contour coefficient and lithological background, each sample within the same cluster was considered to have the same background. Then, the residual value between each sample and the mean data of adjacent samples within the same cluster was calculated, and the original data of each sample were replaced with the ratio (a new parameter defined as the residual contrast value) of the residual value and the anomaly threshold obtained for the corresponding cluster. Finally, geochemical maps and anomaly maps were generated using the residual contrast values. A practical example involving a regional geochemical dataset of stream sediments in Hunan, China, was examined in detail to clarify the procedure. Moreover, a comparative analysis through success rate curves of the percentage of deposits correctly determined was performed between the traditional method, singularity method and new combined method. The results showed that the anomalies identified by the proposed method were closely associated with known deposits, and the residual contrast value, which considers the effects of the lithological background, random error, and structural anomalies, could eliminate the influence of lithology and enhance weak anomalies. Moreover, the geological significance of this method is clear, and the calculation procedure is simple. Thus, this method could be applied for identifying regional geochemical anomalies in multibackground areas and could be used as a guide for new exploration targets. • Proposed an effective combined method for geochemical anomaly identification in multibackground areas. • Proposed a new parameter: residual contrast value • Lithological, random error, and structural anomaly are considered in the method. • Anomalies identified by this method has stronger association with the known deposits. • A comparative analysis was made through success rate curves of the percentage of deposits correctly determined among different methods. [ABSTRACT FROM AUTHOR]