Decluster Data

To decluster data, you first need to set the optimal cell size where the mean of the weighted samples are either at a minimum (for high grade preferential sampling) or a maximum (for low grade preferential sampling). You can then set the optimal cell size and apply it to generate the new declustered mean weighting that replaces the weight column in other plots.

Activity Steps

  1. Select or insert the Decluster component in the Project Tree. See Insert a Component for more information.

    The decluster plot displays with a green background.

    Note: The plot remains green until it is updated with cell dimensions. If you know the cell dimensions, go to step 6.

  2. In the Cell sizes field group, set the cell dimensions and steps to determine the optimal cell size by entering values in the following fields for the X, Y and Z data columns. For more information, see Cell Size Optimisation.
    1. Min – Minimum cell size that steps start from.
    2. Max – Maximum cell size that steps start from.
    3. Step – Intervals at which Supervisor calculates the optimised declustered mean.

      Tip: Assess your data in the 3D viewer to help set your cell dimensions and intervals. Supervisor cannot calculate thousands of steps, so only enter a range that is relevant to your data.

  3. Click Optimise.

    Data points calculate and display on the plot.

  4. Configure options from the Drawing field group as required.
    • X – Keep the X direction at a constant value. If checked, enter a constant.
    • Y
    • Z
    • Link – Link two axes to limit the number of points displayed and make viewing data easier on the declustering plot. Select from None, XY, XZ and YZ.
    • Draw lines – Draw lines connecting cell sizes.
    • Mean lines
  5. Click the data point on the plot that represents the optimal declustered mean.

    The X, Y and Z values for this point are filled into the Cell size fields at the top of the property panel.

  6. Click Apply to apply the new weighting column to the data.