Prospectivity mapping for gold deposits hosted by iron formation, in a portion of Western Churchill Province that includes Melville Peninsula, Nunavut, Canada

P. Behnia, J. Kerswill, G. Bonham-Carter, Jeff Harris
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引用次数: 1

Abstract

Data-driven models employing weights of evidence (WofE) and logistic regression (LR) have been used in a series of experiments to characterize the spatial association of iron formation-hosted gold with geological and geophysical features in the Meadowbank to Melville Peninsula corridor of the northern Rae Domain. A number of geological features were extracted from a 1:550,000 bedrock compilation map and used as evidence. A total of 52 BIF-hosted gold occurrences were available for use in the training sets. For each experiment, weights were determined for individual evidence layers based upon the selected training sites. The evidence maps were reclassified into binary or ternary (2- or 3-class) maps guided by contrast values and associated studentized contrast values calculated on the ordered data. The evidence layers were combined using WofE and LR models to create posterior probability target maps for BIF-hosted gold deposits. To evaluate the validity of the mineral potential maps, training and testing sets were used to assess efficiency of classification and prediction of potential maps respectively.
加拿大努纳武特省西部丘吉尔省包括梅尔维尔半岛在内的部分地区含铁矿的金矿远景图
采用证据权重(WofE)和逻辑回归(LR)数据驱动模型进行了一系列实验,以表征Rae域北部Meadowbank至Melville半岛走廊铁地层含金与地质和地球物理特征的空间关联。从1:55万基岩编绘图中提取了一些地质特征作为证据。共有52个bif托管的金矿可供训练集使用。对于每个实验,根据所选择的训练场地确定单个证据层的权重。根据对比值和在有序数据上计算的相关学生对比值,将证据图重新分类为二元或三元(2类或3类)图。利用WofE和LR模型结合证据层,为bif含矿金矿创建后验概率目标图。为了评价矿物势图的有效性,利用训练集和测试集分别对矿物势图的分类效率和预测效率进行了评价。
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