AES can provide the client with a detailed resource base analysis utilizing one of several Geostatistic Kriging methods that suits
the mineralization. Data mining using average ore grade, mineral thickness, density of the ore, and the x,y coordinates are the minimum data required to perform a geostatistical
study to develop a resource evaluation for any deposit. Minimum Grade-Thickness (GT) cut-offs products can then easily be evaluated to develop a sensitivity
analysis with the basic data. Volume of mineral and the area above a constant GT cut-off is calculated by commerical software. From this information, uranium resource tonnage and average
grade (%U) can easily be calculated.
Kriging is a method of interpolation named after a South African mining engineer named D. G. Krige who developed the technique in an attempt
to more accurately predict ore reserves in the early 1960s. Over the past several decades kriging has become a fundamental tool in the field
of geostatistics. Kriging is based on the assumption that the parameter being interpolated can be treated as a localize variable.