Important concepts

Overview

In order to reduce estimation errors, you should:

• understand the domains
• validate the input data
• understand estimation methods and parameters
• validate the output model

Requirements

There are no requirements for reading this chapter, but you may find some of the principles easier to understand if you:

• have some understanding of basic statistics
• know what a geostatistical model is or
• have previously performed a geostatistical estimation

Understand the domains

It is important to recognise separate "regions" or "domains" within a model.  After you have identified the domains, it is important to group all sample data contained within each domain into distinct subsets.  After that, you can analyse each subset individually, and use data from each separate domain to make estimations within that domain.

Validate the input data

The saying "Garbage in = Garbage out" is certainly true in geostatistics.  Although sampling theory and laboratory quality control practices are important concepts which impact the quality of any estimation made using a set of data values, these subjects are outside the scope of this tutorial.

Assuming that the quality of the data is as good as you’re going to get, there are a couple of potentially hazardous characteristics of the data which you should look for: "bimodalism" and "outliers".  You can look for both of these features with a histogram.   A data set is said to be "unimodal" if the histogram shows a single peak.  If there are two peaks, the data is said to be "bimodal".  If you use some of the more common estimation techniques to create a model based on a bimodal distribution, it is likely to contain more estimation errors than a model created from a unimodal data set.  Additionally, "outliers", or values which are significantly distant from the majority of the data, can cause estimation errors.

Understand estimation methods and parameters

There are a large number of estimation methods, and a large number of parameters within each method.  Before using a particular estimation method, you should have a good background in basic statistics, as well as basic geostatistical principles.

There are a number of functions that the geostatistics module will perform for you. However, it is important that you understand the underlying principles of geostatistics, so that you understand the impact of performing a function on the final result.

Validate the output model

A final method you should use to check the quality of estimation is to take time to examine the output. Histograms of estimated values, contours of plans, cross-sections of block models, colour-coded and rotated in three-dimensional space are all methods which can be used to verify the output values.