In recent years, it was found that identification of weak geochemical anomalies in thick overburden areas is of great economic significance, such as areas thick covered with vegetation, weathering layer or desert. According logarithmic transformation can avoid the closure effect of composite data, logarithmic ratio transformation and robust component analysis (CODA FA) were used to identify the combination of mineralization elements. In Lüliangshan research area, North Qaidam, based on stream sediment sampling geochemical data, it was determined that Cu, Zn and Co have high correlation, and the geochemical mineralization anomalies of single geochemical element Cu, Zn, Co and combined element Cu+Zn+Co were identified by traditional geochemical statistical method and Multifractal singularity analysis (S-A), and potential exploration targets were delineated in this sutdy. It was found that S-A method can not only accurately delineate more obvious anomalies but also more prominent weak anomalies than the abnormal lower limit mean ± 2 standard deviation (mean ± 2STD) of statistical method. And then, the analysis results obtained by statistical method and S-A method were compared with field geological exploration, several copper ore bodies and massive copper mineralization have been discovered in the designated anomalous area that targeted by combinatorial elements anomaly map. Therefore, the target area had considerable accuracy and economic value, it can point out the direction for future exploration of copper deposits in this area. And it can be concluded that the combination of log-ratio approach, Robust compositional factor analysis and Multifractal singularity analysis is an effective method for identifying geochemical anomalies.