Geostatistical interpolation of estimated RQD values and its use in geomechanics design considerations – a case study

Authors: Verma, AK; Yao, M

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DOI https://doi.org/10.36487/ACG_rep/1410_41_Verma

Cite As:
Verma, AK & Yao, M 2014, 'Geostatistical interpolation of estimated RQD values and its use in geomechanics design considerations – a case study', in M Hudyma & Y Potvin (eds), Deep Mining 2014: Proceedings of the Seventh International Conference on Deep and High Stress Mining, Australian Centre for Geomechanics, Perth, pp. 587-600, https://doi.org/10.36487/ACG_rep/1410_41_Verma

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Abstract:
Geostatistical interpolation techniques have proved its utility in all disciplines of geosciences and have potential to be used in geomechanics design applications. The principals of geostatistics are developed based on the fact that almost all geosciences data has some relationship with its location in space. Geostatistical tools decipher this relationship and exploit it to estimate the rock properties at an unsampled location. This work is an attempt to apply geostatistics in geomechanical design using nearest neighbour, inverse power and kriging interpolation of estimated Rock Quality Designation index (RQD) values from drill cores from part of one and four shear orebodies of Vale’s Garson Mine in Sudbury, Ontario, Canada. A comparative study of different methods and their correlation with mapped geology provided the most effective method for RQD interpolation. The part of orebody selected for this application has undergone intensive drilling with sufficient data volume to create an RQD block model with high degree of confidence. The RQD block model provided a basis for rock mass classification and creation of RQD maps along planned mining layouts, which served as an important tool for initial geomechanical assessment. This methodology has a potential to expand its application to other geomechanics parameters, such as RMR and Q values.

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