Using Meaningful Reconciliation Information To Evaluate Predictive Models (f422be80-ebd4-4e59-9f97-b10db17502b0)

Reconciliation of production information is critical to evaluating the effectiveness of the predictive models, and to allow for optimization of mining operations. Whether mining open pit or underground, mine-to-mill reconciliations can be one of management's better tools to perform proper accounting, and a very useful evaluation and optimization tool. This paper proposes a set of criteria and objectives for a typical reconciliation program; also presents a stepwise, logic approach to performing reconciliations, and discusses the benefits and costs associated with the up-keeping of the information. It also highlights some of the potential pitfalls involved, and methods used to avoid collecting misleading information. These issues are illustrated with an example of a model-to-mine-to-mill reconciliation program being implemented at an operating mine; the program involves multiple predictive models (Long-term and Short-term block models), different open pit and underground mines, stockpiling, and at least 23 different mill streams. This paper presents the initial results of the program implemented at Minera Michilla S.A.