Simulation of mineral grades and decrease of conditional variance of simulation using hard and soft conditioning data, based on Local moment constraints method.

This work deals with the geostatistical simulation of mineral grades whose distribution exhibits spatial trends within the ore deposit. Such trends can be reproduced via the definition of conditioning data. These conditioning data can be available from hard data or some soft data، which are produced from the result of cokriging. The conditioning process forces its realizations to conform these data and therefore، their local properties، in particular the local mean (trend)، could be reproduced. In fact، soft data can compensate the lack of hard data in sampled areas with insufficient data and force the realizations to reproduce the trend in the study area. The proposed method was applied on obtained data، located at 1850 m، from exploration boreholes of Sungun mine. The study area was divided into two rock type domains: Sungun Porphyry (SP) and Dyke (DK) and it was shown that the incorporation of soft and hard conditioning data improves the modeling of the uncertainty in the actual copper grades and decreases the conditional variance of simulation significantly.