In many mineral deposits metal zonation is present and can be related to grade trends. If the geology of the host rock possesses certain geochemical and/or geophysical properties (such as porosity) then the resulting mineral deposit could form zoned ore bodies (disseminated ore) with locally varying mineralization. Disseminated metal of varying degrees poses a significant challenge to grade estimation since it is possible that no clear boundary exists in which to differentiate distinct populations.
Therefore, properly defining grade/geology domains may prove elusive. Current resource estimation workflows can sometimes address this problem reasonably well by using pairwise relative variograms and localizing the kriging estimate. However, these geostatistical techniques may not fully account for all of the geology components or account for local variations in mineralization by assuming a single direction of continuity. By using geologic knowledge and current software technology to model the metal zonation and associated trends, local variations in mineralization can be properly accounted for in grade estimation using nonlinear block search paths. A subset of the Galore Creek gold data was used as a test case.