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Advanced Estimation - Review Variograms Determining the variogram model appropriate for interpolation |
Advanced Estimation - Review Variograms
To access this dialog:
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Using the Advanced Estimation dialog, select the Review Variograms menu item.
To perform grade interpolation using Kriging, an appropriate variogram model is needed. If co-kriging is used, a multivariate variogram model set is required which has the same ranges for all models.
If you have imported data from Datamine Supervisor, variograms derived from the imported project will automatically be associated with the corresponding estimation(s).
If zones are specified on the Select Samples panel then a variogram model set is required for each zone. If one of the non-Kriging estimation methods has been selected (nearest neighbour, inverse distance etc.) then a variogram model is not required.
Usually the variogram models will have been fitted or imported at the Fit Models stage. However it is also possible to import or export a model on the Confirm Variograms panel.
The Confirm Variograms panel allows the user to review the selected model or select a different model.
Note: Advanced Estimation is part of the Studio RM toolset. Additional licensing modules aren't required.
Adding a New Variogram Model Set
You can use the Review Variograms panel to create a new model set, as well as editing any existing one.
Click Add to enter a new row into the Available Variograms table above, then use the Variogram Model Set Properties panel to define the set.
Field Details:
There are three distinct parts to this panel to allow you to choose the required variogram model for the selected estimation run:
Estimation Picker: the estimations you have selected on the Define Estimations panel are displayed in the area on the left area together with the grade and zone values For kriging estimates the default variogram model reference number will also be shown. Highlight one of the estimation runs and use the central panel to review the variogram parameters for that run and select an alternative model if required.
Variogram picker: a list of available variogram model sets is displayed in the central area showing the grades, zone if appropriate, univariate or multivariate and how the fitting was performed - manually, automatically, or a "mix". . Highlight one of the models to display its parameters in the area on the right. To apply a different model to the selected estimation run, highlight the new model and click the Apply variogram model to… button.
Using this panel, you can also:
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Import a previously generated experimental variogram file (as saved using the Create Variograms panel).
Variograms may have been imported from a Datamine Supervisor project using the Import option on the Scenario Setup panel. Regardless, you can import standardised variogram models from Datamine Supervisor using this function. |
During variogram model import, file contents will be analyzed to ensure it contains the fields required to complete the estimation process. For example, if a zone field (either the first or second zone) is expected but cannot be found in the incoming file, a message will be displayed explaining which field is expected and cannot be found. Similarly, other required fields such as VSETNUM, GRADE, GRADE2 and TRANS fields are checked. |
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Add: adds a blank variogram to the table above, which can then be further defined using the Variogram Model Set Properties panel on the right.
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Export the current selected variogram to an independent variogram file
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Clear list - clear all variograms from the list, ready for the import of another file
Variogram Details: this section allows you to view the parameters attributed to the currently selected variogram (as selected in the Variogram Picker area).
The Review Variograms panel displays context-sensitive information about the selected variogram model set. Select a link below for more information:
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Parameters: displays information about the variogram set for the current estimation scenario. More...
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Variogram Model Set Properties: the panel can be used to define the variogram models within the univariate or multivariate estimation case. More...