Enhancing Geological Understanding and Identifying Gold Anomalies in the Ailaoshan Orogen

The Ailaoshan Orogen in the southeastern Tibet Plateau,situated between the Yangtze and Simao blocks,underwent a complex structural,magmatic,and metamorphic evolution resulting in different tectonic subzones with varying structural lineaments and elemental concentrations.These elements can conceal or reduce anomalies due to the mutual effect between different anomaly areas.Dividing the whole zone into subzones based on tectonic settings,ore cluster areas,or sample catchment basins(Scb),geochemical and structural anomalies associated with gold(Au)mineralization have been identified utilizing mean plus twice standard deviations(Mean+2STD),factor analysis(FA),concentration-area(CA)modeling of stream sediment geochemical data,and lineament density in both the Ailaoshan Orogen and the individual subzones.The FA in the divided 98 Scbs with 6 Scbs containing Au deposits can roughly ascertain unknown rock types,identify specific element associations of known rocks and discern the porphyry or skarn-type Au mineralization.Compared with methods of Mean+2STD and C-A model of data in the whole orogen,which mistake the anomalies as background or act the background as anomalies,the combined methods of FA and C-A in the separate subzones or Scbs works well in regional metallogenic potential analysis.Mapping of lineament densities with a 10-km circle diameter is not suitable to locate Au deposits because of the delineated large areas of medium-high lineament density.In contrast,the use of circle diameters of 1.3 km or 1.7 km in the ore cluster scale delineates areas with a higher concentration of lineament density,consistent with the locations of known Au deposits.By analyzing the map of faults and Au anomalies,two potential prospecting targets,Scbs 1 and 63 with a sandstone as a potential host rock for Au,have been identified in the Ailaoshan Orogen.The use of combined methods in the divided subzones proved to be more effective in improving geological understanding and identifying mineralization anomalies associated with Au,rather than analyzing the entire large area.

The efficiency and accuracy of probability diagram, spatial statistic and fractal methods in the identification of shear zone gold mineralization: a case study of the Saqqez gold ore district,NW Iran

In this study,geochemical anomaly separation was carried out with methods based on the distribution model,which includes probability diagram(MPD),fractal(concentration-area technique),and U-statistic methods.The main objective is to evaluate the efficiency and accuracy of the methods in separation of anomalies on the shear zone gold mineralization.For this purpose,samples were taken from the secondary lithogeochemical environment(stream sediment samples)on the gold mineralization in Saqqez,NW of Iran.Interpretation of the histograms and diagrams showed that the MPD is capable of identifying two phases of mineralization.The fractal method could separate only one phase of change based on the fractal dimension with high concentration areas of the Au element.The spatial analysis showed two mixed subpopulations after U=0 and another subpopulation with very high U values.The MPD analysis followed spatial analysis,which shows the detail of the variations.Six mineralized zones detected from local geochemical exploration results were used for validating the methods mentioned above.The MPD method was able to identify the anomalous areas higher than 90%,whereas the two other methods identified 60%(maximum)of the anomalous areas.The raw data without any estimation for the concentration was used by the MPD method using aminimum of calculations to determine the threshold values.Therefore,the MPD method is more robust than the other methods.The spatial analysis identified the detail soft hegeological and mineralization events that were affected in the study area.MPD is recommended as the best,and the spatial U-analysis is the next reliable method to be used.The fractal method could show more detail of the events and variations in the area with asymmetrical grid net and a higher density of sampling or at the detailed exploration stage.