Supervisor provides a range of univariate and multivariate data analysis tools that allow you to rapidly understand the characteristics of the orebody. Importing point and block data from multiple sources and formats you can easily examine and compare statistical populations, perform contact boundary analysis and declustering.

Supervisor’s global topcut analysis lets you set different topcuts using the histogram, probability plot, mean-variance plot and cumulative metal plot independently and assess the impact on associated statistics. The local topcut transition model allows you to apply a topcut to each sample based on its distance from the block centroid. When used in conjunction with the LKNO functionality you can account for the variability of informing samples on a block by block basis.

Variograms represent the grade continuity within your deposit and are a key input to the kriging process. Supervisor’s easy to use variogram analysis is interactive, allowing the user to view and model variograms for all directions at once and view them in 3D.

Optimise block size and estimation parameters with an interactive and simple to use Kriging Neighbourhood Analysis (KNA) interface to ensure a better quality estimate and to reduce oversmooothing. Supervisor also provides an alternative approach to optimising estimation parameters using Local Kriging Neighbourhood Analysis (LKNO). LKNO ensures that each block is estimated with the best possible combination of estimation parameters.

Ensure the accuracy of your estimate against the input data in a fraction of the time and test the theoretical grade tonnage curve using global change of support. Model validation generates grade trend plots, histograms, log probability plots, statistics and global change of support to assess the quality of an estimate.

Supervisor provides a streamlined workflow which allows users to run multiple-realisation Sequential Gaussian Simulations over multiple domains in a single run. Our suite of post-processing tools means that reblocking for multiple block sizes, generating probability plots and comparing results with a range of grade tonnage curve tools is a breeze.

Supervisor’s multivariate conditional simulation component allows users to perform conditional sequential gaussian simulation for multiple variables simultaneously while maintaining complex compositional correlations. The feature rich workflow allows for multiple compositional and gaussian transformation techniques with automated data handling and validation plot generation to ensure robust results for all data types.

This multivariate comparison tool allows users to easily identify correlation features within their data and overcome obfuscation issues inherent in datasets with large numbers of values.

With full control over the number of bins, legend calculation method and axis adjustments, these plots are an essential part of every geostatisticians toolkit.

• Fully Featured Estimation Module
• Dynamic Anisotropy
• Global and Local Uniform Conditioning
• Enhanced Covariogram Modelling