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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。
Taking Cu element in Tongling ore concentration area as an example, anomalous identification of multidimensional fractal mineralization based on deep soil data was carried out. The results show that the multidimensional fractal kriging method has a great advantage over the ordinary kriging in identifying the ore-forming anomalies under the condition of relatively low soil sampling density and little difference in the spatial distribution of the element contents. For the mining and development of such deposits in Tongling Ore Concentration Area, the degree of exploitation is relatively high. The distribution of surface soil elements is mainly controlled by the old mine areas with exogenous pollution. The multidimensional fractal Kriging method based on deep soil samples can be effectively carried out Abnormal ore identification, service in the old mining area in the deep, the periphery of the hidden deposits prospecting. For the blank study area, the multidimensional fractal Kriging method should be equally effective, either based on deep soil data or surface soil data. There is no standard to determine the anomalous lower limit value of soil element mineralization prediction based on multidimensional fractal method. In this paper, the element content-the calculation method of the cumulative frequency of the deposit number is used in this paper. Known deposits, while identifying blank anomalies that deserve further verification.