Abstract
Data quality control programs used in the mineral industry normally define tolerance limits based on values considered as good practice or those that have previously been applied to similar deposits, although the precision and accuracy of estimates depend on a combination of geological characteristics, estimation parameters, sample spacing and data quality. This study investigates how the sample quality limits affect the estimates results. The proposed methodology is based on a series of metrics used to compare the impact on the estimates using a synthetic database with an increasing amount of error added to the original sample grades or positions, emulating different levels of precision. The proposed approach results lead to tolerance limits for the grades similar to those recommended in literature. The influence of the positional uncertainty on model estimates is at a minimum, because of the accuracy of current surveying methods that have a deviation in the order of millimeters, so its impact can be considered negligible.
Keywords:
geostatistics; data uncertainty; sensitivity analysis; sampling error; QA/QC
