Category Tech talk

Mining data, by its very nature, is rarely collected in a regular pattern; it is human nature, and very good business sense, to take more samples in the higher-grade parts of orebodies. As a consequence of this data for resource evaluation is almost always clustered. While the most common method of grade estimation, ordinary kriging (OK), inherently declusters the input data through the point-to-point covariance matrix, other estimation methods, such as inverse distance modelling, do not decluster the data for the purposes of estimation, and this can sometimes lead to biased results.

Minerals have been of significant importance for mankind throughout industrial history, from the Copper, Bronze and Iron Ages to the present, demonstrating that every new discovery leads in turn to innovations.