Geostatistical simulation of optimum mining elevations for nickel laterite deposits

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Uncertainty is an inherent aspect in mine planning. Geological architecture and heterogeneity between drillhole samples is impossible to predict exactly. Estimation provides a single biased prediction of geology; however, conditional simulation allows alternative geological realizations or truths with the right heterogeneity to be created. Each realization honours the conditioning data value and the realization fluctuations in the space between data is a measure of geological uncertainty. This geological uncertainty can be transferred into uncertainty in mine planning parameters, which can then be used to make improved and confident production decisions. This principle is applied to a small nickel laterite mining scenario.

Nickel laterite deposits are typically formed from tropically weathered mafic to ultramafic complexes and constitute a major reserve of nickel worldwide. Typically, small dozer blade units are used to mine the loose nickel laterite soil material. Selectivity is excellent. Selective mining unit (SMU) digging elevations and the dilution and lost ore costs associated to these digging elevations are important mine planning parameters. A conditional simulation approach is used to calculate optimum representative dozer region (RDR) digging elevations.

There are two main phases to the methodology: (1) simulation of the ore-waste contact surface conditional to orewaste contacts, and (2) post-processing these ore-waste contact surface realizations through an optimization transfer function for determination of optimum mining elevations and minimum dilution and lost ore costs at each SMU.

Using ore-waste contact elevations interpreted from exploratory drillholes (based on a per cent Ni/m cutoff), geostatistical simulation is used to create multiple ore-waste contact surface realizations. The ore-waste contact surface is simulated at a resolution higher than the RDR. At one RDR location, the ore-waste contact surface is used to calculate dilution and lost ore for a range of possible digging elevations (see figure). The optimum digging elevation is the elevation that simultaneously minimizes the lost ore and dilution costs. This is repeated for all ore-waste surface realizations within the RDR from which the expected optimum digging elevation is found. This is repeated for all RDRs in the mine plan so that the resulting optimum mining elevation and the associated minimum dilution and lost ore costs can be used for mine planning purposes. The minimum RDR dilution is the cost of mining the volume of waste located below the expected orewaste contact and above the optimum mining elevation. The minimum RDR lost ore is the cost of not mining the volume of ore above the expected ore-waste contact and below the optimum mining elevation.

Hand contouring for digging elevations is sub-optimal. Notional hand contoured digging elevations or retrospective dilution and lost ore costs are hard to trust for important mine planning decisions. Within the conditional simulation framework presented, forecasts of dilution and lost ore costs at each RDR location are simultaneously minimized over multiple possible true ore-waste surfaces. The associated digging elevations are optimum for production planning and mine economics.

The methodology is straightforward and can be automated on virtually any moderately powered personal computer. Additional grade control information beyond the information available at the time of the simulation study is easy to incorporate in order to update the optimum digging elevations and minimum dilution and lost ore forecasts.
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In recent years, large numbers of algorithms have been developed for the optimization of pit limits, which are either rigorous or heuristic. They may or may not guarantee the true optimization solution. However, most of these algorithms follow a deterministic approach, which predicts a single outcome from a given set of circumstances. In this paper, a new algorithm is introduced using a stochastic approach, which predicts a set of possible outcomes weighted...
Publication: CIM Bulletin
Author(s): S.E. Jalali, M. Ataee-pour, K. Shahriar
Issue: 6
Volume: 1
Year: 2006
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Controlling acid mine drainage (AMD) produced by reactive mine wastes is one of the most challenging environmental issues currently facing the mining industry. The LTA impoundment (property of Barrick Gold Corp.) located near Malartic, Quebec, contains sulphide tailings that have the potential to generate acidic leachate. The selected closure option was to construct a cover with capillary barrier effects (CCBE) shortly after the end of tailings deposition....
Publication: CIM Bulletin
Author(s): B. Bussière, A. Maqsoud, M. Aubertin, J. Martschuk, J. McMullen, M.R. Julien
Issue: 6
Volume: 1
Year: 2006
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