The analysis of the mining project involves the need to know three main concepts including the resource model, geological uncertainty, and the JORC Code. The mineral resource model is the mathematical description of the grade, tonnage, and spatial distribution of the mineral deposit. Geological uncertainty can be described as the risk that exists within the resource model due to the sampling process. The JORC Code is the professional standard for how resources should be reported (Moore & Friederich, 2021).
Geological uncertainty exists mainly due to limited data and interpretations. Given that the resource assessment depends on drilling within specific areas, any interpolation from such limited spots can lead to certain mistakes (Dominy, 2002). In addition, different styles of mineralization and difficulties in the process of defining the space domain make the task complicated. The result is that any deterministic model is simply an interpretation, which makes the whole estimation extremely sensitive to systematic error (Reid & Cowan, 2023).
This uncertainty requires quantitative techniques instead of relying on intuitive ideas. Geostatistical approaches based on conditional simulations provide quantitative measures of risk through the creation of several equally likely realizations of the geological and metallogenic characteristics of the ore body (Emery et al., 2006). While ordinary interpolation techniques tend to smooth out data, conditional simulations measure the variability and the local variabilities of block grades. This stochastic technique is vital for evaluating risks associated with economic cutoff grades.
Today, progress in technology focuses on combining these statistical approaches with proper structural assessment. The trend nowadays is the use of structural analysis at deposit scale to rule out unfeasible geometries from the models (Reid & Cowan, 2023). In addition, validation in the spatial domain is applied to numbers and geology in an iterative manner to properly understand the uncertainty of the models (McManus et al., 2021). With these computational approaches, areas of high conceptual risks are identified and help classify resources.
It is a professional responsibility to communicate this uncertainty effectively through the JORC code-based report. The JORC Code demands the description of the degree of accuracy and certainty of the estimates. Yet, as has been found by the review of industrial practice, quantitative assessment is still absent in most reports, and the interpretation quality is communicated in an extremely subjective manner using qualitative statements (McManus et al., 2021). If a report needs to be truly useful, all of these aspects should be included in it.
To sum up, the assessment and communication of the uncertainties associated with geology is critical in the objective evaluation of mineral resources. With the use of well-defined structural control and geostatistical modeling techniques, the geologists will be able to develop very reliable models. In essence, once the Competent Person is able to document all these uncertainties in the JORC report, the requirement will be met, and informed decisions will be made.
References
Dominy, S. C. (2002). Errors and Uncertainty in Mineral Resource and Ore Reserve Estimation: The Importance of Getting it Right. Exploration and Mining Geology, 11, 77–98. https://doi.org/10.2113/11.1-4.77
Emery, X., Ortiz, J. M., & Rodríguez, J. J. (2006). Quantifying Uncertainty in Mineral Resources by Use of Classification Schemes and Conditional Simulations. Mathematical Geology, 38, 445–464. https://doi.org/10.1007/s11004-005-9021-9
McManus, S., Rahman, A., Coombes, J., & Horta, A. (2021). Uncertainty assessment of spatial domain models in early stage mining projects – A review. Ore Geology Reviews, 133, 104098. https://doi.org/10.1016/j.oregeorev.2021.104098
Moore, T. A., & Friederich, M. C. (2021). Defining Uncertainty: Comparing Resource/Reserve Classification Systems for Coal and Coal Seam Gas. Energies, 14, 6245. https://doi.org/10.3390/en14196245
Reid, R. J., & Cowan, E. J. (2023). Towards quantifying uncertainties in geological models for mineral resource estimation through outside-in deposit-scale structural geological analysis. Australian Journal of Earth Sciences, 70, 990–1009. https://doi.org/10.1080/08120099.2023.2217882
