Recovery functions provide one of the most important tools in the mining industry for summarizing mineral inventory information of a deposit as a function of cut-off grades. They are also used during several stages of the deposit evaluation, including mine planning, financial decision making and management.
Recovery functions are commonly obtained from block grade estimates, and therefore assessment of the underlying uncertainty associated with them is not possible. This limitation can be overcome by generating multiple conditional simulations of the deposit from which the recovery functions are computed. However, this approach is time consuming and may not be feasible for deposits modeled with a large number of blocks.
In this paper, a technique is proposed for simulating recovery functions and easily assessing the corresponding uncertainty without carrying out any conditional simulation. Through a number of case studies with real mining deposits, it is shown that if the sole purpose is to assess the uncertainty in the recovery functions then the proposed technique can be used to eliminate the necessity of carrying out multiple conditional simulations.