Mineral resources should be disclosed according to measured, indicated and inferred. This is legally required and makes practical sense. Probabilistic criteria and all relevant mitigating factors should be considered to support these levels of confidence. The disclosure of probabilistic resources was the subject of a blog in March 2020 where the use of measured/indicated/inferred was recommended over the direct use of uncertainty. This blog reflects on details of the probabilistic criteria to support disclosure.

The format of probabilistic criteria has settled on what Harry Parker recommended, that is, uncertainty in the tonnes, grade and metal within production volumes of relevance for technical and economic decision making. Production volumes are related to nominal monthly, quarterly or annual tonnages. The tolerance is plus/minus some deviation (5%, 10%, 15%, 25%, 50%) with a certain confidence level (80%, 90%, 95%). Influenced by large open pit gold mines, Parker’s criteria are often quoted as (1) Measured is where quarterly production volumes are within 15% of predicted with 90% probability or higher, (2) Indicated is where annual production volumes are within 15% of predicted with 90% probability or higher, and (3) Inferred is where annual production volumes are within 50% of predicted with 90% probability or higher. Parker’s criteria cannot be applied universally. There are many mitigating factors including commodity type, deposit type, and nature of the geological resources.

Parker’s criteria may never be achieved with practical drill hole spacing for small throughput high grade gold deposits. The criteria would be exceeded with very wide drill hole spacing in a base metal or coal deposit. As always, site specific circumstances must be considered. Probabilistic criteria provide a framework to communicate the deemed acceptable uncertainty for a specific disclosure.

Mineral resources within a deposit have varying degrees of confidence. Measured and indicated resources are the subset of resources that are (1) drilled more closely and understood better, and (2) form the basis of detailed economic analysis for development. Inferred resources are likely to form sustaining resources for the long-term economic potential of a deposit. Inferred resources are the subset that may be upgraded to indicated or, ultimately, measured with time and additional drilling. Global reporting, such as P10/P50/P90 of global resources, does not consider this local granularity and is not recommended for mineral resources.

The uncertainty in tonnes, grade and metal within production volumes of relevance requires a carefully applied workflow that includes data uncertainty, parameter/trend uncertainty, geological uncertainty and multivariate rock property uncertainty. The best practice of this uncertainty assessment is becoming routine with the RMSP software. All relevant aspects of uncertainty should be considered to avoid underestimating uncertainty. The production rate and aspects of the mining method such as selectivity and the number of mining faces must also be included for realistic uncertainty assessment.

The commodity and deposit type have a significant impact on the deemed acceptable uncertainty. Some end member cases are (1) gold or precious metals that have inherently high variability, (2) base metal (copper and other) deposits where there are two to three orders of magnitude more of the valuable element in the rock, (3) iron ore deposits where iron constitutes a (near) majority of the rock composition, and (4) coal or industrial minerals where contaminants and details of the rock composition define ore value. Less uncertainty would be tolerated for coal relative to gold. The contract specifications and expectations for a blended run-of-mine product are very different depending on the commodity and deposit type.

My personal recommendations: (1) use 90% confidence in all circumstances; it is easily understood, (2) apply probabilistic criteria to the tonnes, grade and metal of the primary commodity, all secondary elements of significance and all key contaminants, and (3) modify the production period and tolerance for the deposit type. Preliminary thoughts on these parameters:

*As noted, high grade and low throughput gold mines may require tighter than feasible drill spacing to achieve the target. In such circumstances, the deposit and mining factors should be clearly stated for relaxing the required confidence intervals.

For all commodities and mining styles, direct application of probabilistic criteria is not recommended; they support the qualified person (QP) and must be supplemented by all relevant mitigating factors, including the original data, multiple data types, geological complexity not captured in a block model and other considerations related to reasonable prospects of economic extraction. In general, there are two ways to reduce uncertainty and meet these criteria – more data or greater understanding of the phenomena. Greater understanding almost always comes from more data. This explains why the most common approach is to relate uncertainty to drill hole spacing, then base classification on drill hole spacing, see previous blog.

Classification is not achieved by blind application of data spacing or probabilistic criteria. The messages of this blog include: there is always a need for professional judgment, probabilistic criteria support classification, criteria must be adjusted for the commodity/deposit type, and details of mining method, rate and selectivity matter. Any probabilistic statement should be supported by sound science, carefully constructed and thoroughly checked probabilistic predictions, and reasoned consideration of all relevant factors. Resource Modeling Solutions (RMS) has the latest techniques implemented for probabilistic resources.