Validate Grade Estimates

The exact model validation process undertaken varies depending on the plots used to analyse and compare data. The general process is described below.

This workflow describes validation of estimated grades against point (assay) data. Model Validation can also be applied directly to block model datasets to compare estimation results.

Activity Steps

Validation against point data

1. Import point data. See how to Load Data.
2. Import block models to validate.

   Important: The block model Assay/Domain grouping must match the grouping on the point data.

3. Insert a Model Validation component below the desired point Data Component in the Project Tree. This may be the Assay, or a filtered data component.

   Note: By default, three Trend Plot components are automatically inserted, in the X, Y and Z orientations respectively, as well as a Histogram, Q–Q Plot, GT Curve and statistical comparison table.

4. Link the Model Validation component to one, two or three block models for comparison via the Block Model Tab.

   Important: The point data and block models used in Model Validation must have overlapping spatial extents. If there is no overlap between the datasets, they cannot be compared and an error message is displayed.

5. Add any additional validation components below the Model Validation component in the Project Tree.

Validation between block model datasets

Model Validation can also be used to compare multiple block model estimation results without reference to point data.

1. Import the block model datasets to compare.
2. Insert a Model Validation component below a block model Data Component in the Project Tree.
3. Link the Model Validation component to one, two or three block model datasets via the Data tabs.
4. Add the required validation plots and tables.

In this configuration, comparisons are performed directly between the selected block model datasets.