Integrating sequential indicator simulation and singularity analysis to analyze uncertainty of geochemical anomaly for exploration targeting of tungsten polymetallic mineralization, Nanling belt, South China

摘要: Abstract The Nanling belt (South China) is one of the most important metallogenic region in world regard to tungsten polymetallic resources. In this and surrounding area, elements accompanying deposits are Sn, Bi, Mo. Modelling spatial variability uncertainty W, Mo anomalies critical for exploration risk assessment. However, traditional interpolation methods (e.g., kriging, polynomial trend surface inverse distance weighted method) modelling continuous geochemical fields based on sparse sampling data provide smoothed representations element concentrations, which often result unreliable decisions. Here, analysis anomaly targeting was investigated through combined sequential indicator simulation local singularity analysis. Anomalous thresholds E-type indices selected (W, Bi) were determined by singularity-quantile plot distribution pattern probability not exceeding a threshold index obtained from series equally probable individual algorithms. Based four probabilistic models, per element, synthetic map produced assessment targeting. results indicate that zones with very high probabilities significantly correlated known closely associated lithostratigraphic contacts. These decision-making evaluation spare stream sediment belt.