Dissertation > Astronomy,Earth Sciences > Geology > Of ore deposits > Metallogenic mineralization forecast and metallogenic regularity

Comparative Study on Quantitative Prediction Models Based on the Spacial Geodatabase

Author NuLiManGu·ABuDuKeLiMu
Tutor ZhangXiaoFan
School Xinjiang University
Course Earth Exploration and Information Technology
Keywords Boxiekuli-Chengjisi metallogenic belt Metallogenic prediction Weightsof Evidence Weighted Logistic Regression
CLC P612
Type Master's thesis
Year 2012
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Domestic and foreign deposits emphasize the necessity of cross-broadermetallogeny belt comparison on minerals, number and size. In which, taken overseashigher degree research area in Cross-border metallogenic belt is the model zoneestablish the model of metallogenic prediction. Achieved metallogenic prediction ofthe low level of study area. It is the important content of the overall study ofcross-border metallogenic belt. This paper chooses Boxiekuli-Chengjisi cross-broadermetallogeny belt,China-Kazakhstan border, as its study area, proceeds withComparative Study of quantitative prediction model based on the spatial database.Therefore, the comparison study of quantitative prediction models on cross-broadermetallogeny belt builds the foundation for the low level of study area’s (xinjiang)copper-gold metallogeny prediction.The main objectives of this paper are medium acidic hydrothermal copper mineand gold mine. It explores the relationships between target area and types of copperand gold that are closely related to terrane and geological phenomena of relevancebased on spatial data model. Moreover, this paper establishes the multiple informationspecial databases with ArcGIS as the platform on this cross-border belt, regionalmetallogeny theory as guidelines, spatial data technology as major pattern, aided withthe necessary geological, geophysical, and geochemical methods as means to explorethat study area. It employs weights of evidence model and weighted Logisticregression models. In addition, this article summarizes regional ore-forminggeological conditions and ore-forming regularity, outlines the prospective areas ofmineralization. Two predict models of this article were compared to the results,thatconfirms the most appropriate predicting model of the study area is Weighted logisticregression model.This addition to ore-forming prediction models, research of copper mine and gold mine made a quick and accurate assessment of resource potential. Providestheoretical basis, predicting models, technical support and data supports for furtherexploration of copper mine and gold mine in the study area to serve for a largeprospective land area and makes exploration profitable.

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