The Study On Metallogenic Environment And Quantitative Prediction For BIF Iron Ore Deposit In Anshan-benxi Area

The Anshan-Benxi area is located in Liaodong area,northeastern margin of the North China Craton,being famous for its Banded Iron Formation(BIF)which are produced in Archean granite-greenstone belt.Because of very complex and chronic geologic processes,metallogenic environment for BIF formation has not yet been recognized perfectl in this area.Because of the increasing demand of iron ores and the shortages of known resources,this area now is faced with a problem to enlarge the prospecting space and potential of iron ore resources.With the increase of ore-finding difficulty,it is very important for this area how to combine the geological theory with the mathematical approach to predict the mineral potential and estimate the resource quantity.Firstly,the paper presents a comprehensive study on the minerogenetic condition and metallogenic environment of BIF from Cigou Formation in Anshan-Benxi area by applying indoor microscopic observation,petrology and geochemistry,combining the geological age results based on detailed geological characters analysis.Secondly,the paper presents a detailed study on the improvement of the mineral prospectivity mapping and the ore grade estimation methods by mainly introducing the artificial intelligence technology based on comparison analysis of the traditional mathematical models in the field of mineral prospectivity and resource estimation.Thirdly,the paper presents an in-depth study on mineral prospectivity mapping and ore grade estimation for BIF by combining geological ore-forming model with the appropriate mathematical model in Anshan-Benxi area.The main conclusions are as follows:(1)Iron-bearing rock series from Cigou Formation in Anshan-Benxi area mainly consists of the basic volcanic metamorphic rocks,sometimes interbedded with sedimentary.Among them,BIF mainly has the spatial and temporal association with their basaltic volcanic wall rocks such as amphibolites from Gongchangling and Waitoushan and chlorite hornblende schist from Nanfen districts.Iron ore bodies,which hosted with multilayer in the iron-bearing rocks series,mainly consist of the low-grade magnetite quartzites with the minor high-grade iron ore bodies.It usually has a length of thousands of meters and a thickness in hundreds of meters.The high-grade iron ore bodies from Gongchangling is biggest,the next is Nanfen and Waitoushan district.Low-grade iron ore has approximately 20?40%of iron grades,while high-grade iron ore has the iron grades more than 55%.(2)The metallogenic materials of BIF mainly come from the mix of submarine high-T hydrothermal fluids and seawater,which are formed in the reducing environment related with the submarine volcanic activities.The high-grade iron ore and low-grade iron ore have both of similarities and differences.The high-grade ores are most likely originated from the primary low-grade BIFs,of which formation is closely related with metamorphic hydrothermal activities.(3)The basaltic volcanic wall rocks have a value of(Nb/Yb)N>1 and distinct fractionation of Nb/Ta ratios.Their protolith is the intra-continental back arc basin basalt.With the development of the basin,the features of rocks were changed from the island arc-type to MORB-type.Combining their material source and HFSE characteristics,related stratigraphic position and geological age data,it can be concluded that the metallogenic environment for BIFs from Cigou Formation is intra-continental back arc basin,of which evolution is associated closely with the oceanic plate subduction.(4)Based on the metallogenic environment and metallogenic regularity,the geological evidence factors and aeromagnetic evidence factors are determined to predict the mineral prospectivity in Anshan-Benxi area.Furthermore,by applying the principle of the vegetation geochemistry,the iron mineralization-related information is extracted successfully from remote sensing image.(5)For the weakly conditional independence of Weights-of-Evidence(WofE)method,the mineral prospectivity modeling is done by using the WofE-LR method and also introducing the WofE-SVM method,which effectively combine the univariate statistical analysis ability of WofE with the multivariate statistical analysis ability of support vector machine(SVM).The resultant mineral prospectivity maps are evaluated using the AUC value,which are bigger than 0.9,showing the high predictive ability.The favorable prospecting districts are distributed in approximately SW-NE direction.As a result,the performance of WofE-SVM model is better than WofE-LR model,which also reflects well the remote sensing mineralization-related information.(6)For improving the estimation accuracy of the ore grade for resource evaluation,the paper proposed the new variogram modeling method using Multi-gene genetic programming(MGGP),which overcame the limitation and subjectivity of the traditional method and also improved the performance of Kriging for ore grade estimation.For many assumptions in Kriging method,SVR and MGGP method are directly used to estimate the ore grade with the better performance and higher accuracy.Moreovere,SVR and MGGP method show the good robustness and feasibility for the ore grade estimation in 3-dimension space.