The estimation of sampling density in improving geostatistical prediction for geotechnical characterization

ABSTRACT

Optimum sampling grid was established using geostatistical estimation in order to improve the accuracy of spatial prediction to characterize Rock Quality Designation (RQD). Ordinary Kriging (OK) present in the software GEOVIA Surpac™ module was implemented to undertake geostatistical estimation. The cross-validation method was used to determine the level of accuracy in the process of establishing the optimum sampling density. Generally, the optimal sampling density for this project is 50.1 m, although taking into consideration the results of cross-validation it is deduced that the sampling density laying within 50.1m to 235.68 m is ideal for this project to characterize the RQD. Taking into account the cost of geotechnical drilling, the leave one out cross-validation (LOOCV) method can be used to establish the range of sampling density for RQD. The study area was subdividing into three scenarios and each scenario had training and testing samples for the application of cross-validation technique.

KEYWORDS:

• Geostatistics
• rock quality designation
• sampling density; leave one out cross-validation

Acknowledgements

We are grateful to The University of Zambia, School of Mines, Dr Bunda Besa, The Dean, for providing us with the connection to the Konkola Copper Mine management team and Konkola Copper Mine Plc for their remarkable support in the collection of data and permission to undertake this study. We would also like to express our gratitude towards Mr Kelvin Mwamba Chembe and Mr Soumyakanti Sengupta from Konkola Copper Mine Plc.

Disclosure statement

No potential conflict of interest was reported by the authors.