Measurement while drilling (MWD) data are gathered during drilling operations and can provide information about the strength of the rock penetrated by the boreholes. In this paper MWD data from a marble open-pit operation in northern Norway are studied. The rock types are represented by discrete classes, and the data is then modeled by a hidden Markov model (HMM). Results of using different MWD data variables are studied and presented. These results are compared and co-interpreted with optical televiewer (OTV) images, magnetic susceptibility and spectral gamma values collected in the borehole using down-the-hole sensors. A model with penetration rate, rotation pressure and dampening pressure data show a good visual correlation with OTV image for the studied boreholes. The marble class is characterized by medium penetration rate and medium rotation pressure, whereas the intrusions are characterized by low penetration rate and medium to high rotation pressure. The fractured marble is characterized by high penetration rate, high rotation and low dampening pressure. Future research will use the presented results to develop a heterogeneity index, develop an MWD-based 3D-geology model and an improved sampling strategy and investigate how to implement this in the mine planning process and reconciliation.
Geometallurgy has developed since the 1970s, primarily on metallic ore operations. In parallel, industrial mineral operations have been optimized through detailed deposit knowledge and market development, without making specific reference to geometallurgical concepts. The Norwegian mining industry is dominated by industrial mineral and construction material operations, and, in this paper, key differences between the industrial mineral and the metallic ore sectors are investigated, along with their influence on the development and the use of economic block models and optimization methodologies. Further, the key levers and factors (mining method selection, processing route, scale, sequence, and cutoff policy) for value creation in industrial mineral operations are discussed, along with how and to what extent geometallurgy has been used. It is concluded that the five key levers cannot be used in industrial minerals operations as effectively as they are used in metallic ore operations. In industrial minerals, in situ strength variations are an important parameter in estimating key performance indicators such as recovery and product quality. When modeling the spatial variation in rock strength potential, additivity issues must be resolved by investigating the process the raw material is exposed to. The Norwegian industrial mineral sector has been using elements of geometallurgy but is facing unresolved issues related to strength variations and the use of measurement while drilling data.
Brønnøy Kalk AS operates an open pit mine in Norway producing marble, mainly used by the paper industry. The final product is used as filler and pigment for paper production. Therefore, the quality of the product has utmost importance. In the mine, the primary quality indicator, called TAPPI, is quantified through a laborious sampling process and laboratory experiments. As a part of digital transformation, measurement while drilling (MWD) data have been collected in the mine. The purpose of this paper is to use the recorded MWD data for the prediction of marble quality to facilitate quality blending in the pit. For this purpose, two supervised classification modelling algorithms such as conventional logistic regression and random forest have been employed. The results show that the random forest classification model presents significantly higher statistical performance, and it can be used as a tool for fast and efficient marble quality assessment.
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