The variogram model is one of the most relevant parameters in geostatistical estimation and simulation methods. The sample variogram is inferred from available data, which may be subject to spatial bias and proportional ...

Geostatistics offers a set of methods for modeling, predicting, or simulating geological domains in space. In addition of being an input of some of these methods, indicator direct and cross-variograms convey valuable ...

This paper describes two new approaches that can be used to compute the two-dimensional experimental wavelet variogram. They are based on an extension from earlier work in one dimension. The methods are powerful 2D ...

Identification and categorization of geological, geotechnical, or geometallurgical domains is a common practice in the modeling of mineral deposits, in order to account for the controls exerted by categorical variables ...

In the analysis of regionalized data, irregular sampling patterns are often responsible for large deviations (fluctuations) between the theoretical and sample semi-variograms. This article proposes a new semi-variogram ...

Geostatistical estimation and simulation techniques are useful for characterizing the spatial distribution of soil properties. These techniques usually rely on a variogram model that measures the spatial variability of the ...

Deals with some common problems in structural analysis when calculating the experimental semi-variogram and fitting a semi-variogram model. Geochemical data were used and the following cases were studied: regular versus ...

Deals with some common problems in structural analysis when calculating the experimental semi-variogram and fitting a semi-variogram model. Geochemical data were used and the following cases were studied: regular versus ...

Moving average simulation can be summarized as a convolution between a spatial kernel and a white noise random field. The kernel can be calculated once the variogram model is known. An inverse approach to moving average ...