Why characterization of mineralization affects profits: Gold in West Africa

There are many elements that collectively define what is referred to here as mineralization character. Some of these are:

• The geometry of the mineralization, such as shape and lateral continuity.
• How a boundary is defined, for example by structure, lithology, alteration, or grade.
• Grade characteristics at the boundaries, which may be sharp, gradational, or very irregular.
• Internal grades variability both within and between drilling/sampling intersections.
• The degree to which a zone has been disrupted by folding and faulting.
• Geometallurgical parameters, such mineralogy and hardness.

While these largely appear to be of interest only for geological activities, most technical and production personnel will have some appreciation of how these characteristics are expressed and distributed in the orebodies that they deal with. However, proper accounting for the ways in which these characteristics can affect metal produced is often lost in the daily production processes. Poor operational performances arise through persistent use of entrenched procedures, particularly where the ore characteristics have changed from those recognized at the time when procedures were first established. This effect can be exacerbated where significant levels of automation have been introduced, and the systems fail to adequately account for variability or to respond to change.

The following example of ore distribution is based on observations at a West African deposit, but has been simplified and exaggerated for illustration. The main observable (dominant) feature is a broad trend inclined gently to the left, as shown in Figure 1 (left hand box). In the right hand box, a local subordinate trend has been added.

Figure 1 – Example ore distribution

Misclassification occurs as both dilution, where predicted ore is actually waste (O/W), and ore loss, where predicted waste is actually ore (W/O). The win-win area is in the centre (O/O), where ore is both predicted and realized. In an operational situation, it is easy to envisage significant concurrent unplanned dilution and ore loss, even before mining dilution has been incurred.

AMC selected a small part of the deposit, and considered a simple set of scenarios to quantify the profit implications that might be achieved from improved classification of ore due to better characterisation. The scenarios envisaged a 3% reduction in tonnage and a 3% increase in mined grade (Table 1). While the net effect is a negligible improvement in metal revenue, the mining of 25 kt less material for a higher grade (revised case) should lead to a chain of benefits, ranging from mining and material movement, through to plant throughput and processing reagent use. Under the revised case, comparable ounces to the base case will be mined, but with an expected increase in profitability