关键词: 定量预测评价, 成矿远景, 武夷山成矿带, 地质模型, 空间分析建模

Abstract:

In order to realize digitized, intellectualized and automated mineralization prospect forecast appraisal, first we carried out mineralize prospect quota forecast appraisal question decomposition under the GIS environment, based on data-driven and knowledge-driven approaches such as the evidence weighted method and information mensuration, to realize geological variable screening and Layer through the ArcGIS space analysis model builder, as well as get the comprehensive information prospecting geologic model and information mensuration or evidence weighted quantitative model by the layout description. Next, to the geological variable characteristic, different mathematical quantification method, unit division and the evaluation method and so on, through analysis and comparison under the GIS environment, proposed simultaneously the rule grid (surface shape) or the equal grid center (point shape) as the basic unit, important method, central point method, area method and corresponding"0 or 1"two-state evaluations as recognition variable existence or not through ArcGIS space analysis modelling realization. Thirdly, based on the variable standardization transformation and the multi-dimensional space linearity mapping quantitative evaluation model, we overcomed the influence of geological variables, which, are not equal and not independent, to the appraisal. On that basis, taking the map of Dashen sheet in Wuyishan metallogenic belt of scale 1:50000 as the experimental plot, applying ArcGIS Model Builder method, we finally established the ArcGIS space analysis model on iron, copper, lead-zinc mineralization prospect quota forecast appraisal, selected 12 prospect areas, which included 3 areas of class A, 3 of class B and 6 of class C. The forecast result is basiclly consistent with that of the information mensuration and evidence weighted method.

Key words: spatial analysis model, mineralizing prospect, Wuyishan metallogenic belt, quantitative evaluation, geologic models