基于奇异值分解法的含量-面积法对化探异常的确定

Identification of geochemical anomalies based on the singular value decomposition and fractal content-area method.

地球化学场的数据通常具有分形的特征。应用奇异值分解方法对元素含量数据矩阵进行分解,对奇异值进行分形统计,得到了分形模型,重建元素含量的数据矩阵。然后利用含量-面积的分形方法对重建后的数据矩阵进行分形处理,使用MAPGIS软件进行统计分析,得出研究地区元素的异常下限,做出元素异常分布图,并与该地区已知矿点的分布图进行叠加分析,预测潜在的成矿区。

The data of the geochemical field commonly have the fractal character. In this paper, the fractal theory is used to analyze the geochemical data. Firstly, singular value decomposition is used to decompose the element content data matrix and a fractal statistics is conducted for the singular values, and then a fractal model acquired and the element content data matrix is re-established. Afterwards, the fractal processing of the re-established data matrix is conducted using the fractal content-area method and a statistical analysis is performed using the MAPGIS software. Thus, the geochemical anomalies of the elements in the study are separated from the background, the lower limits of the element anomalies are obtained and a map of element anomaly distribution is constructed. Finally, a superimposition analysis of this distribution map of element anomalies and the distribution map of known ore occurrences is made to forecast potential gold districts.