Select the name of Error Grid file

Script Parameter: KRIGRID.ERR

Select the name of Input Variogram file.

Script Parameter: KRIGRID.INVAR

Select the name of Output Variogram file

Script Parameter: KRIGRID.OUTVAR

You can either grid the original data or its logarithmic (base 10) representation. Gridding the log of the data can be a very effective way to reduce distortion due to highly skewed data such as geochemical data.

The options are:

• linear: grid the data as it is.
• log, save as linear: grid the data in logarithmic space and clip all values less than ‘Log minimum’ to the ‘Log minimum’ value, then convert the data back to linear space before saving it to the grid file.
• log-linear, save as linear: grid the data above the positive ‘Log minimum’ and below the negative ‘Log minimum’ in logarithmic space (flip the sign of the data originally in the negative range to take the logarithm then inherit back the sign of the original data; grid the conditioned data). After gridding, all cell values outside the ± ‘Log minimum’ range are converted back to linear space and scaled to maintain continuity at the boundary. Data within the ± ‘Log minimum’ range remains intact and is gridded in a linear sense.
  Finally, the linear representation of the data (in both ranges) is saved to the grid file.
• log, save as log: same as ‘log, save as linear’ except that the grid values are kept in log space: the gridded values are saved to the grid file in their logarithmic representation.
• log-linear, save as log: same as ‘log-linear, save as linear’ except that the grid values are not converted back from log space. The output grid is in logarithmic space with the large amplitude anomalies being somewhat moderated.

Script Parameter: KRIGRID.LOGOPT
  linear: 0
  log, save as linear: -1
  log-linear, save as linear: -2
  log, save as log: 1
  log-linear, save as log: 2

If gridding in log space (see the Log options above), this parameter specifies the minimum value. The default is 1.

Script Parameter: KRIGRID.LOGMIN

The de-sampling factor is defined as a function of the grid cell size. Before any further calculations, all points within cells of dimension cell_size x desampling_factor are averaged into a single value and placed in the center of the cell.

The default desampling (desampling_factor) is set relative to the contributing points as:

Desampling has two impacts:

• Effectively it acts as a low-pass filter. The larger this parameter the smoother the output grid.

• Speeds up the variogram calculation when the input database is very large.

If the database contains less than 100000 contributing points, the default is set to 1, and the only pre-filtering consists of de-aliasing at the cell level.

The variogram calculation duration is a function of the square of the contributing points. Increasing this factor visibly cuts down the variogram calculation time while little impact is seen on the variogram curve.

Script Parameter: KRIGRID.DSF

All grid cells farther than the blanking distance from a valid point will be set to dummies in the output grid.
The default blanking distance is calculated as:

Preferably this parameter should be set to just greater than the maximum distance through which interpolation is desired.

Script Parameter: KRIGRID.BKD

Select "Yes" or "No" to remove a trend (drift).

Script Parameter: KRIGRID.RT

Select Variogram model to be used.

• "User defined" (requires input variogram)

• "Power" model using power n (n=0 for linear)

• "Spherical" model (requires nugget, range and sill) 

• "Gaussian" model (requires nugget, range and sill)

• "Exponential" model (requires nugget, range and sill)

Script Parameter: KRIGRID.MODEL.

This is the power for the power model. The default is 1. In this case, the nugget and slope are fit to the data by default if not specified.

Script Parameter: KRIGRID.POWER

Range/Slope. For spherical, Gaussian and exponential models, the range is the distance at which the variogram model reaches the sill value. Beyond the range, the data is uncorrelated. The range must be entered for the spherical, Gaussian and exponential models. For the power model, this is the rate of climb, or slope for a linear model.

Script Parameter: KRIGRID.RS

The nugget for all models. The nugget is the average error in each data point, and is indicated by the intersection of the variogram model with the h=0 axis. The default is 0.

Script Parameter: KRIGRID.NUG

Sill. This is the level at which the variogram becomes uncorrelated, or goes flat. Beyond the (range, sill) point, the variogram is flat. The sill must be specified for the spherical, power and Gaussian models.

Script Parameter: KRIGRID.SILL