Select an Appropriate Variogram Type or Data Transformation

Before you create a variogram, you first need to assess your data to determine which variogram is most appropriate to the style of mineralisation you are working with. It is recommended that you first analyse the Basic Statistics graphs to inform your variogram type selection. Histograms are particularly useful when it comes to deciding on a variogram type for calculation and modelling. The distribution of your data, as observed in histograms, indicates some the types of variograms or data transformations that are most appropriate for you to use. Some examples of these are:

• No skew (normal distribution)
  • Traditional variogram
  • Indicator variogram
  • Normal scores transformation
  • Pairwise relative variogram (if working with a small number of samples)
• Positive skew
  • Log transformation
  • Indicator variogram
  • Normal Scores transformation
  • Pairwise relative variogram (if working with a small number of samples)
• Negative skew
  • Traditional variogram
  • Indicator variogram
  • Normal scores transformation
  • Pairwise relative variogram (if working with a small number of samples)
• Mixed populations
  • Indicator variogram
  • Pairwise relative variogram (if working with a small number of samples)

Note: Supervisor supports other variogram types, but it is recommended that you only use these other options if you understand how are to be used.