Conditional Bias of Geostatistical Simulation for Estimation of Recoverable Reserves

Conditional bias is an infamous problem with estimation methods including kriging. Changing estimation parameters will mitigate, but not remove, conditional bias. The conditional bias of kriging is well understood; however, there is widespread confusion in the literature and among practicing geostatisticians regarding the conditional bias of geostatistical simulation. There is no conditional bias of simulation when the simulation results are used correctly. The correct use of simulation for recoverable reserves estimation is to (1) generate multiple realizations conditional to all available data at a small scale, (2) linearly average all realizations to the chosen block size and (3) calculate the probability of each block being ore and the ore grade of each block. The ?probability of ore? and the ?ore grade? are conditionally nonbiased.