区域矿产预测中的小单元法和矿化模型系列

Small Cells and Mineralization Model Series in Mineral Resource Prognosis

用各种异常圈定的靶区可进一步划分成含矿与非含矿两大类,尽量删除非含矿部分是降低预测风险的关键。由于地质、地球物理、地球化学和遥感影像特征在隐伏资源体上方与非含矿区并无显著差异,高精度的识别和预测工具十分重要;无矿模型对剔除非含矿异常有特殊意义;使用"小单元法"和"矿化模型系列"除了可以预测资源量外,还更细致地预测资源体的品位、埋深和空间形态等。

A target area delineated from different kinds of anomalies usually contains orebearing and nonorebearing parts.Eliminating the non-orebearing part is the key to reduce the risk of mineral resource prognosis.High solution tools for pattern recognition and prediction are needed because of the ambiguity of geological,geochemical,geophysical and remote sense evidences on blind mineral deposits and non-orebearing areas.Samll ceils and mineralization model series are proposed to meet the more and more scrupulous demand of mineral resource prognosis.