Incorporating Blast Hole Data In The Development Of A Computer Block Model In An Active Mine

A new method for interpolating a block model is proposed, where both the diamond drill holes (DHs) and blast holes (BHs) data are used. Combining these data types poses a geostatistical "class size" problem due to the different statistical properties of the densely populated BHs and the sparsely populated DH data. This paper discusses how linear regression was used to adjust the DH values prior to the interpolation to account for the "class size" problem which is inherent to the procedure. The correlation between the BHs and the DHs is found. The DHs are then corrected based on the regression line. Each block that falls within a certain range of influence of a blast hole is assigned a different code and is interpolated with the combined BH and regressed DH data set. Blocks that fall outside the range of blast hole influence are interpolated using the original DH data set. A comparison against other methods, indicate a 12% improvement over using DHs only and a 2% improvement over using BHs only.