基于深层土壤数据的多维分形成矿异常识别研究——以铜陵矿集区Cu元素为例

以铜陵矿集区Cu元素为例,开展基于深层土壤数据的多维分形成矿异常识别研究。结果表明,在土壤采样密度相对较低、元素含量空间分布差异不大的情况下,多维分形克里格插值法较普通克里格插值法对于成矿异常的识别具有极大的优势。对于铜陵矿集区这类矿床开采、开发程度已较高,表层土壤元素分布主要受控于外源污染的老矿集区,基于深层土壤样品数据的多维分形克里格方法可以有效地进行成矿异常识别,服务于老矿集区的深部、外围隐伏矿床找矿。而对于空白研究区,无论是基于深层土壤数据还是表层土壤数据,多维分形克里格方法应同样有效。多维分形方法下土壤元素成矿预测的异常下限值确定尚无标准,文中采用元素含量 矿床数目累积频率的计算方法,基于该方法提取的成矿异常区域较好地识别出了绝大多数已知矿床,同时识别出了值得作进一步异常查证的空白异常区域。

The study of metallogenic anomaly identification based on deep soil data with multifractal method—A case study of Cu element in Tongling ore clustering area.

In this paper, we take Cu element of Tongling ore clustering area as an example, and carry out the research on metallogenic anomaly identification with multifractal method, based on deep soil data. The results show that the Krige multifractal interpolation method has tremendous advantage compared with the krige interpolation method when soil sampling density is relatively lower and spatial distribution of element content has little difference. For the kind of old ore clustering area, such as Tongling ore clustering area, which has a higher level of ore mining, and the spatial distribution of surface soil elements is mainly controlled by external pollution sources, the multifractal method that is based on deep soil data can identify anomalies efficiently and provide special services for deep and peripheral concealed ore prospecting in old ore clustering area. Moreover, for the blank researching area, multifractal method works the same way whether it is based on surface or deep soil data. For the multifractal method, there is still no standard being set up to determine the threshold anomaly of metallogenic prognosis by the soil elements. This paper presents a calculation method using the cumulative frequency of elemental contents number of deposits. The anomaly area obtained by this method can well identify the most of known deposits. Meanwhile, by this method some blank abnormal areas which are worthwhile to do further anomaly inspection have been identified.