COMPARATIVE ANALYSIS BETWEEN GEOLOGICAL MODELLING METHODS
ResumoSeveral stages of a mining enterprise depend on the existence of a geological model. Each of these steps is conducted by professionals who based on this model, perform tasks, and make decisions and plans. However, it is built from a sample dataset, and is therefore subject to uncertainties, which can be reduced with the accuracy of the data and the choice of a modelling method appropriate to each type of deposit. The purpose of this work was to analyze comparatively three methods for the elaboration of digital solid models, which involved manual, geostatistical and implicit modelling methodologies .The data used come from surveys of an iron ore deposit. The lithologies modeled were hematite and itabirite. The manual modelling was built through the parallel section method, which is based on interpretations that depend on the geological knowledge and the experience of the professional. However, the main problem that arises in this context is that many interpretations can be viable, making the method subjective. The elaboration of the geostatistical modelling was through the indicator kriging technique, which partly depends on interpretations, but the result is based on statistical principles, being less subjective than the manual method. Finally, implicit modelling, which uses radial-based functions, is performed “automatically,” so it does not offer the opportunity to add professional knowledge and experience. The results obtained in this research, using the mentioned methodologies, showed similarities in the determination of the models between the lithological contacts, but there were significant divergences in quantitative terms. Thus, it can be concluded that a fast automatic model can help in the interpretation or point out regions where more samples are needed, and that there may be interactivity between the professional who performs the interpretation of the sample data and the methodologies used, so that they can assist in the geological modelling process.