The importance of calculating recoverable resources and reserves was recognized early on in geostatistics (Matheron, 1962 and 1963), but it was M. David’s early work (1977) that demonstrated the practical significance of estimating recoverable reserves, while Journel and Huijbregts (1978) provided the theoretical and practical foundations for the most common methods used to estimate resources at different volumes.
The resource model contains blocks with dimensions that should relate to the spacing of the data, hopefully determined based on the quantity of information available to predict grades. Block sizes may be larger than the selective mining unit (SMU) of the operation. The smoothing effect of kriging will generally result in a grade distribution that does not match the distribution of grade of the SMUs. In addition, in-pit selection is not perfect. The grade-tonnage predictions based on blast holes may need to be corrected for unplanned dilution and other errors of estimation in the short-term model.
GeoSystems International, Inc. applies an integrated approach to predicting resources, reserves, and mine performance for more accurate predictions. Specifically, the volume-variance relationship, the selectivity of the mining operation, planned dilution and ore loss must be accounted for. Additionally, incorporating an allowance for unplanned dilution at the time of mining is commonly reasonable.
Traditional estimation techniques provide limited flexibility to account for these factors. The estimation of recoverable resources is based on limited information about the SMU distribution of grades. There are a number of methods and techniques that help estimate point distributions, but relatively little research has been done to develop robust methods for estimating block distributions. It is a difficult task, since little is known a-priori about the SMU distribution. An important option available is the use of conditional simulation models to resolve the issues related to recoverable resources.
An alternative approach to resource evaluation is the use of conditional simulation which provides a set of possible values for each block, thus representing a measure of uncertainty. The simulated realizations reproduce the histogram and the variogram of the original drill hole information, correctly representing the proportion of high and low values, the spatial complexity of the orebody, the connectivity of high and low values, and the overall grade continuity in three dimensions. These characteristics of the mineralization are important aspects that play a significant role in designing, planning, and scheduling a mining operation.
When a number of these realizations have been created and checked, then, for each node defined in the grid, there will be a corresponding number of different grades available. This set of multiple grades is a model of uncertainty for that node. These simulated points can be re-blocked to any block size desired such as the Selective Mining Unit SMU size of the operation. These results are used further by mining engineers.
Important parameters can be obtained from the distributions of local uncertainty such as the mean, median, and probability of exceeding of exceeding a specified cutoff grade. Therefore, the information provided by a simulation model is significantly more complete than the single estimate provided by an estimated block model. The simulation models can provide recoverable resources for any selectivity by re-blocking the simulated grades to the chosen SMU block size.
GeoSystems International, Inc., has developed a rigorous work approach to checking resource models, which involves several steps and requires a significant amount of time and effort.
Graphical checks involve 3-D visualization and plotting the estimated values on sections and plans. Every estimated block grade should be explained by the data surrounding it and the modeling parameters and method used. Although these graphical checks can be performed on computer screens, it is often worthwhile to have a hardcopy set of maps because of the level of detail required and the important record-keeping and audit trails. Unfortunately, this practice is disappearing, as some operations do not take the time to produce sets of geological sections and plans views on paper.
Statistical checks are both global (large scale or deposit-wide) and local (block-wise or by smaller volumes, such as monthly production volumes). The checking, validation, and reconciliation procedures should ensure the internal consistency of the model, as well as reproduction of past production if available.
Reconciliation against past production if available should be done based on pre-defined volumes of interest and according to specified error acceptance criteria. Additionally, production can provide an initial indication of the expected uncertainty of the resource model. But production information should be used with great care. Oftentimes, tonnages and grades reported by the processing plant do not adequately represent true mill feed (head) tonnages and grades, that is, the material delivered by the mine. Rather, they may be influenced by plant performance parameters, which will bias the comparisons with the head grades and tonnages reported by the mine. Reliable head tonnages and grade information are best obtained from direct sampling of the material delivered at the entrance of the plant.
The purpose of classifying resources is to provide a global confidence assessment to the project’s stakeholders including mining partners, stockholders, and financial institutions investing in the project. There are several resource and reserve classification systems used by different government agencies around the world. Most of them share in their main characteristics and objectives. GeoSystems’ Independent Associates are competent in the all the existing classification systems, including Australia’s JORC and Canada’s NI 43-101, the two most referred-to systems in the world.
The assessment of confidence is critical for project development since sufficient resources and reserves must be known with enough confidence to be considered assets. For operating mines, continued confidence in future long-term production is also important in providing shareholder value and supporting long-term planning.
The terminology used in most guidelines for classification is purposefully vague. They must be applicable to many different types of deposits, locations and mining methods. The guidelines do not prescribe specific methodology for quantifying uncertainty or risk. Rather, there is increased reliance on the judgment of the resource estimator, formalized through the figure of the competent or qualified person. A common basis for comparison is therefore difficult to achieve, since the wording may have different meaning under different circumstances, and depends on the individuals involved. GeoSystems’ Independent Associates to attempt to describe confidence in traditional statistical terms, and as a function of production units. There is an industry trend towards using a statistical description of uncertainty to supplement traditional classification criteria.
The confidence assessment required by the shareholders of a mining project is generally global, and mostly concerned with long-term performance. This is different from the shorter-term mining risk assessment that engineers need in the day-to-day operation of the mine. Unfortunately, a global confidence assessment is frequently also used as a local measure of uncertainty, which often leads to unreasonable expectations in the resource model. This should be avoided.
There are shortcomings and pitfalls in the practice of resource classification. Many of these can be resolved with a defensible model of uncertainty based on geostatistical simulation. Inevitably, the process of classifying resources depends on the circumstances and conditions of the mining project being assessed in addition to purely geologic conditions and technical issues, and most importantly, the Competent Person’s criteria and judgement. Nevertheless, in all cases, GeoSystems’ Independent Associates will provide resource classifications that comply with the international standards indicated and are defendable by the professional that signs off on the resource model.