Mineral Prospectivity Mapping Method Integrating Multi-Sources Geology Spatial Data Sets and Case-Based Reasoning

Extracting and synthesizing information from existing and massive amounts of geology spatial data sets is of great scientific significance and has considerable value in its applications. To make mineral exploration less expensive, more efficient, and more accurate, it is important to move beyond traditional concepts and establish a rapid, efficient, and intelligent method of predicting the existence and location of minerals. This paper describes a case-based reasoning (CBR) method for mineral prospectivity mapping that takes spatial features of geology data into account and offers an intelligent approach. This method include a metallogenic case representation that combines spatial and attribute features, metallogenic case-based storage organization, and a metallogenic case similarity retrieval model. The experiments were performed in the eastern Kunlun Mountains, China using CBR and weights-of-evidence (WOE), respectively. The results show that the prediction accuracy of the CBR is higher than that of the WOE.

Chemical composition of oscillatory zoned garnets from the largescale Mengya'a Pb–Zn skarn deposit: implications for fluid physicochemical conditions and formation

The Mengya’a Lead–zinc deposit is a large skarn deposit in the north of the eastern segment of Gangdese metallogenic belt.The garnet is the main altered mineral in the Mengya’a area.The color of the garnet varies from chartreuse to dark yellow brown and to russet.The brown garnet(Grt1)is related to pyrrhotite and chalcopyrite,and the green garnet(Grt2)is associated with lead–zinc mineralization.LA-ICP-MS is the induced coupled plasma mass spectrometry.This paper has used this technique to investigate Grt1 and Grt2.Grt1 develops core–rim textures with strong oscillation zone occurring in rim,whereas Grt2lacks core–rim textures and featured by oscillation zone.LA–ICP–MS analysis shows that garnets of Mengya’a are rich in CaO(29.90–37.52%)and FeO(21.17–33.35%),but low in Al_(2)O_(3)(0.05–4.85%).The calculated end members belong to grandite(grossular–andradite)garnets andradite.The negative Al(IV)versus Fe^(3+),positive Al(IV)versus total Al stoichiometric number,the positive Al(IV)versus Fe^(3+),and the negative Al(IV)versus total REE,all indicate that the substitution of REEs in garnets is controlled by YAG.All Garnets are depleted in large lithophile elements(e.g.,Rb=0.00–4.01 ppm,Sr=0.03–8.56 ppm).The total REE in Grt1 core is high(ΣREE=233–625 ppm),with HREE enriched pattern(LREE/HREE=0.33–1.69)and weak negative Eu anomalies(δEu=0.21–0.47).In contrast,the total REEs in the Grt1 rim and Grt2 are low(ΣREE=12.4–354 ppm;ΣREE=21.0–65.3 ppm),with LREE enriched pattern(LREE/HREE=0.54–34.4;LREE/HREE=11.4–682)and positive Eu anomalies(δEu=0.35–27.2;δEu=1.02–30.7).After data compilation of garnet chemicals,we found that the early fluid responsible for the core of Grt1 was a relatively closed and chloride-depleted fluid system.It was close-to-neutral,with a low water–rock ratio.The core of garnet was formed by fluid diffusion in metasomatic processes.The fluid was changed into a relatively open system with reduced,chloride-rich,and weakacid fluid.It was fluid infiltration and metasomatism that resulted in the formation of Grt1 rim and Grt2.