Abstract

CHANDERMAN, L.; DOHM, C.E.  and  MINNITT, R.C.A.. 3D geological modelling and resource estimation for a gold deposit in Mali. J. S. Afr. Inst. Min. Metall. [online]. 2017, vol.117, n.2, pp.189-197. ISSN 2411-9717.  http://dx.doi.org/10.17159/2411-9717/2017/v117n2a10.

Mineral Resource estimation (MRE) and classification are highly dependent on the confidence in the model of the orebody geometry, known as the geological model, within which the estimates are constrained. An understanding of the geology of a deposit is thus fundamental to the Mineral Resource evaluation process. The geological model is a function of the structural and depositional complexity of the geology captured by drilling information, which is limited in the early stages of a project. The information effect has a significant impact in terms of the interpretation of the geology as well as the estimation of grade continuity and the resultant risk associated with the Mineral Resource estimate and classification. Therefore, as new drilling information becomes available, it is necessary to update and refine the geological model to appropriately constrain the resource estimates. The grade information is also updated, including statistics and the spatial correlation characteristics. This refinement is based on geological interpretations derived from the drillhole information that becomes available throughout the life of the mine; orebody knowledge that comes from working experience of the deposit, as well as familiarity with the software package used for modelling, is also important. In updating, the potential to identify new resources in previously unknown areas may be realized. The opposite may also occur where previous interpretations of ore continuity are refuted. Both scenarios could result from a better understanding of the geology of the deposit and thus a more realistic MRE, which reduces geological risk. This paper describes how newly drilled advanced grade-control holes for a gold deposit in Mali were used to refine the 3D geological model for the deposit in an attempt to identify the potential for additional oxide ore using conventional geostatistical evaluation techniques.

Keywords : geological modelling; resource estimation; geostatistical evaluation.

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