Comparative Analysis of 3d Domain Modelling Alternatives: Implications for Mineral Resource Estimates

Accurate estimation of resources is one of the major challenges in mineral project evaluation. Contemporary mineral resource estimation practice calls for contribution from several disciplines and execution of several interdependent tasks. 3D estimation domain modelling is obviously one of the most essential components of such a substantial process which forms the basis of this research. The study constitutes a comparative analysis of four major domain modelling techniques; (i) explicit modelling, (ii) implicit modelling, (iii) indicator kriging, and (iv) conditional simulation. It involves comparison of outcomes for alternative scenarios to assess the implications of the modelling decision on resource estimates of a polymetallic massive sulfide deposit located in western Turkey. Thus, identical grade estimation method and parameters are considered to identify the discrepancies arising only from the choice of the domain modelling approach and underlying assumptions. Economic implications are demonstrated in the form of range of outcomes for the extends of the ultimate pit, ore tonnages (min:37.0 Mt, max: 46.7Mt), waste tonnages (min:201.2 Mt, max: 251.2 Mt), stripping ratios (min:5.18, max: 5.71), and total pit values (min: $1.05B, max: $1.45B). Examination of solid models as well as cross-sections revealed that major discrepancies are observed beyond outlying drillholes. Therefore, it has been proposed that assumptions regarding extrapolation distance is the main source of mentioned dissimilarities. Key words: Domain modelling, explicit modelling, implicit modelling, indicator kriging, conditional simulation INTRODUCTION Resource estimation is apparently a challenging process calling for extensive expertise and input from several sources, each of which introducing its related uncertainties. In the last decades, substantial role of quantitative analysis of several forms of risk and uncertainty in evaluating projects’ upside potential and downside risks has been realized. Studies indicated that mining companies have been severely impacted because of not meeting project expectations. As noted by Vallee (2000) “… in the first year of operation after start-up, 60% of mines surveyed had an average rate of production less than 70% of designed capacity”. Several other studies on mining projects also revealed that uncertainties related with the resource model are one of the major contributors of mentioned shortfalls. In this perspective, quantification of uncertainties associated with each component of estimation process is critical. 3D estimation domain models capturing major mineralization controls are the fundamental components of contemporary mineral resource estimation. Domain models are key guiding tools for estimation and are products of a complex process involving many unknowns and assumptions. There exists a number of 3D modelling alternatives which are distinct with respect to complexity, time and effort involved. Acknowledging potential influences on downstream mining practices and relavent economic implications, risks and uncertainties associated with 3D domain modelling are critical yet poorly studied aspects.