Frequently Asked Questions

Category: Grade Estimation

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How do I regularize data using the moving window method? The moving window method can be used to create a regular set of grid points from an irregularly spaced dataset. Set out a series of regularly-spaced grid points then estimate the value of each grid point using the average of the surrounding samples within a defined search area; usually a two dimensional box. Often this method is used to regularize topographic information. This may be done in Datamine by estimating a block model which is only one block thick. GRADE or ESTIMA processes may be used to do this. Procedure:
1) Create a block-model prototype with the X-Y cell size equal to your required increment between windows. The Z cell dimension may be set to any size for a 2D method

2) ESTIMA or GRADE with inverse distance should be used to calculate the mean and variance at each cell centre. 
POWER=0 would give you the arithmetic means without any distance weighting. 

3) The window size would be defined by the search volume. 

Advantages of using ESTIMA would be that you could then use:
Either rectangular or elliptical windows, 
Either 2D or 3D searches
Multiple window size based of availability of samples etc.
Multiple runs of an estimate using different criteria.
How do I calculate Tonnage and Grade from a Datamine model? Use the TONGRAD process.
This process calculates the volume, tonnage and grade for up to 10 specified grade fields. The results may be classified by up to three levels of keyfield. 
The output is written to a Datamine file and may optionally be saved in a system file in Comma Separated Variable (CSV) format. The .csv file contains the same results as the Datamine OUT file, but is suitable for direct input to a spreadsheet.		 The attached file describes how this process might be used.  TONGRAD

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