Geostatistics for natural resources evaluation / Геостатистика для оценки природных ресурсов

Earth sciences data are typically distributed in space and/or in time. Knowledge of an attribute value, say, a mineral grade or a pollutant concentration, is thus of little interest unless location and/or time of measurement are known and accounted for in the data analysis. Geostatistics provides a set of statistical tools for incorporating the spatial and temporal coordinates of observations in data processing.
The development of geostatistics in the 1960s resulted from the need for a methodology to evaluate the recoverable reserves in mining deposits. Priority was given to practicality, a current trademark of geostatistics that explains its success and application in such diverse fields as mining, petroleum, soil science, oceanography, hydrogeology, remote sensing, and environmental sciences. Until the late 1980s, geostatistics was essentially viewed as a means to describe spatial patterns and interpolate the value of the attribute of interest at unsampled locations. Geostatistics is now increasingly used to model the uncertainty about unknown values through the generation of alternative images (realizations) that all honor the data and reproduce aspects of the patterns of spatial dependence or other statistics deemed consequential for the problem at hand. A given scenario or transfer function (remediation process, flow simulator) can be applied to the set of realizations, allowing the uncertainty of the response (remediation efficiency, flow properties) to be assessed. Stochastic imaging is one of the most vibrant and promising areas of research in geostatistics. <...>