The problem of local estimation is to find the best estimator of the mean value of a regionalized variable over a limited domain, the dimensions of which are small compared to the dimensions of the quasi-stationary (homogeneous) zones of the deposit, e.g., the mean grade of a block located well within a zone of homogeneous mineralization. Local estimation differs from global estimation in that global estimation considers distances larger than the limits of quasi-stationarity and, thus, sometimes engulfs various heterogeneous mineralizations.
The available information used for local estimation within a quasi-stationary
zone is generally made up of a set of data (e.g., 
core grades)
and structural information (e.g., the variogram model characterizing the
spatial variability in the studied zone).
Kriging is a local estimation technique which provides the best linear unbiased estimator (abbreviated to BLUE) of the unknown characteristic studied. This limitation to the class of linear estimators is quite natural, since it means that only the second-order moment of the random function (i.e., the covariance or variogram) is required, and, in general, it is possible in practice to infer the moment.
The proper name ``Krige'' is adopted from the South African geostatistician D.G. Krige. It is interesting to note that it is quite rare that the name of a living person is used so often in the scientific literature. The word is also declined in all kinds of directions. The corresponding verb is to krige, an ore deposit will be kriged, a kriging is performed (where the pronunciation is not unique), in French it is krigeage, in German it is krigen or kriging. The most surprising creation I found in German is krigeln (Marsal, 1979[15]). There is also a kriging system, a kriging matrix and a kriging variance.