非线性矿床模型与非常规矿产资源评价

Non-Linear Mineralization Model and Information Processing Methods for Prediction of Unconventional Mineral Resources

探讨了建立非线性矿床模型对难识别的非常规矿产资源评价的可能性 .首先评述了非线性理论在成矿动力学和矿产勘查中的应用 ,以及非常规矿床与非常规矿产资源评价的研究现状 .然后引进了以岩浆结晶分异成矿作用为例的多维分形非线性成矿系统模型 .在此基础上揭示了非线性成矿系统必然导致元素富集和聚集的奇异分布及矿床分布的广义自相似性规律 .广义自相似性刻画了成矿的外在多样性和内在相似性 .介绍了 2种最新研究的“奇异分析”和“广义自相似性”异常分解方法 .采用文中所建议的非线性矿床模型方法对加拿大北部Gowganda地区的热液型Co ,Ni,Ag ,As,Pb 5种元素矿产进行了预测和评价 .结果表明 ,以“广义自相似性”和“奇异分析”为基础的非线性矿床模型及GIS信息综合技术对非常规难识别矿产资源评价是有效的 .

A non-linear mineralization model was proposed on the basis of a classical igneous differentiation mineralization model which can describe the generation of multi-fractal distribution of element concentration as well as grade-tonnage fractal/multi-fractal model. The work has also led to a model to explain the common properties of mineralization and mineralization-associated geochemical anomaly diversity and generalized self-similarity of the anomalies. Generalized self-similarity is related to the generalized scaling invariance which can characterize the external diversity and internal similarity of natural phenomena including mineralization and occurrence of mineral deposits. The models based on core principal of generalized self-similarity and singularity analysis have been applied to a case study of Co-Ni-Ag-As-Pb mineral resources assessment in the Gowganda area of Abitibi district, northern Ontario, Canada. The results have demonstrated that the non-linear models proposed in the current research are effective for delineating week lake sediment and water geochemical anomalies caused by deeply buried sources or week anomalies superimposed to low background values.