Interfacing JavaScript Program with Datamine for Block Model Regularisation – A Case Study

Daniel Mireku-Gyimah, S K Takyi


Abosso Goldfields Limited (AGL) uses Datamine for block geolical modelling, Whittle Four-X for pit optimisation, Datamine and Geovia Surpac for pit designs and Runge XPAC and Talpac for production scheduling. To facilitate pit optimisation and production scheduling, there is the need to regularise the input block model, which means converting a block model with variable or fixed unit block size into another block model with uniform unit blocks of preferred size and assigning attributes such as grade and tonnage to the resulting unit blocks. Unfortunately, Datamine and Geovia Surpac software are unable to accurately regularise a block model to generate the input data for pit optimisation and production scheduling. This research aimed to develop a computer program, RegPlus, using JavaScript language and interface it with Datamine to perform block model regularisation. To assess the accuracy and reliability of the grade and tonnage in the regularised block model, the Tomento North Pit 1 block model of AGL was regularised using Datamine, Geovia Surpac and RegPlus. Ten different sets of unit block sizes were randomly selected to effect the block model regularisation using each of these three software. The total grade and tonnage in each of the ten (10) sets of regularised block models from each of the three software were compared with the total grade and tonnage in the original block model. The results revealed that irrespective of the unit block sizes selected for the block model regularisation, the total tonnage and grade in the  regularised block model from RegPlus was 100 percent accurate when compared to the total tonnage and grade of the original block model. As expected, Datamine and Geovia Surpac could not give accurate results. RegPlus is thus a reliable tool to solve the problem of block model regularisation at AGL or any mine with the same problem.


Keywords: Block Model Regularisation, Pit Optimisation, Production Scheduling


Block Model Regularisation; Pit Optimisation; Production Scheduling

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