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为了有效利用资源和选定合理的设计方案,对相应设计单元的储量和品位必须有充分的了解。因此,恰当地应用取样点的数据来推断未知点,是提高储量计算精度的关键。但矿石品位的空间变化具有两重性,既有地质总体上的规律性,又有局部矿化的随机性,从而给单纯的地质法或一般的数理统计法造成了困难。在统计品位过程中,考虑取样点的地质环境,进而求得理想的估值,就是地质统计法所要解决的主要问题。一般应用最小方差法,一个块段的平均品估值B由下式求得:
In order to make efficient use of resources and to select a rational design, the reserves and grade of the corresponding design units must be fully understood. Therefore, proper application of the data from the sampling points to infer the unknown points is the key to improve the accuracy of reserves calculation. However, the spatial variation of ore grade has the dual nature of both the general geological regularity and the randomness of local mineralization, which has caused difficulties for simple geological methods or general mathematical statistics. In the process of statistical grade, consider the geological environment of sampling points, and then find the ideal valuation, which is the main problem to be solved by the method of geostatistics. The general application of the minimum variance method, a piece of the average product valuation B obtained by the following formula: