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Mining Analytics

Data Analysis Australia has a long history of working with clients from across the mining, oil and gas sectors to help them gain new insights from their existing data resources and to design and inform effective data collection strategies.   As consultant statisticians with experience across many industries and sectors we utilise not only statistical techniques that have proven applications in mining but also adapt techniques traditionally used in other sectors to provide innovative solutions to mining challenges.

Techniques used by Data Analysis Australia’s statisticians for mining applications include:

  • Regression modelling, including generalised linear models and semi-parametric regression;

  • Predictive modelling and forecasting;

  • Model selection algorithms and cross-validation;

  • Geostatistics and spatial analysis;

  • Simulation and optimisation;

  • Cluster analysis to understand groupings amongst ore samples;

  • Classification and Regression Trees to model key variables by partitioning a data set; and

  • Experimental design for mineral grade, recovery and hardness testwork programs.

Industry Case Studies

Efficiency of Electrowinning Circuit
Understanding Environmental Impacts
Identifying Cycles in a Chemical Plant
Simulation of Coal-Barging on a River
Making Cyanide Work Faster