Geostatistics-based estimators, i.e. ordinary kriging and simple kriging, are state-of-the-art estimation techniques widely used in the mining industry. However, the estimation result of kriging techniques is not able to cope with the well-known uncertainty of geological attributes in mineralization deposits. Moreover, the smoothing effect of kriging algorithms has led to over/under estimation in many circumstances. To overcome these drawbacks, the deterministic estimation result of kriging is usually followed by stochastic results provided by stochastic simulation. In this paper, the application of ordinary kriging and stochastic simulation are performed to build the resource model together with the uncertainty assessment of the Sinquyen copper mine.