Variogram Modeling (Advanced Topic)
Some really powerful packages offer additional functionality such as variogram modeling, particularly useful for selecting an appropriate variogram model when gridding with the kriging algorithm.
The variogram is a measure of how quickly things change on the average. The underlying
principle is that, on the average, two observations closer together are more similar than
two observations farther apart. Because the underlying processes of the data often have
preferred orientations, values may change more quickly in one direction than another. As
such, the variogram is a function of direction.
Variogram modeling is not an easy or straightforward task. The development of an
appropriate variogram model for a data set requires the understanding and application of
advanced statistical concepts and tools. In addition, the development of an appropriate
variogram model for a data set requires knowledge of the tricks, traps, pitfalls, and
approximations inherent in fitting a theoretical model to real world data: this is the art
of variogram modeling. Skill with the science and the art are both necessary for success.
(As an aside, the HELP file supplied with Surfer has an excellent section detailing variogram modeling and includes sections on lag parameters, anisotropy, nugget effects, and references for further reading - I highly recommend it!)