The Wiener filter is the well-known solution for linear minimum mean square error (LMMSE) signal estimation. This filter assumes the mean to be known and usually constant. On the other hand, the Kriging filter is an incremental theory, developed within the Geostatistical community, with respect to that of Wiener filters. The extension relies on adopting a parametric model for the mean (usually ...

here in, an application of a new seismic inversion algorithm in one of iran’s oilfields is described. stochastic (geostatistical) seismic inversion, as a complementary method to deterministic inversion, is perceived as contribution combination of geostatistics and seismic inversion algorithm. this method integrates information from different data sources with different scales, as prior informat...

The main efforts and applications up to now are focused on the spatial variability analysis within a field. The spatial variability of soil properties within a field was evaluated using geostatistical analysis and the interpolation methods for mapping soil properties were compared in this paper. This experimentation was conducted in a wheat field of the trail farm in Shunyi County, Beijing. The...

Synopsis The regression effect in ore-reserve estimation has been identified, described and quantified in vein and reef deposits for more than twenty years. Its importance in ‘three-dimensional’ deposits whether underground or open-pit -has been recognized under the alternate guise of the geostatistical volume-variance relationship. The Fontainebleau school has developed the technique of disjun...

In the last years there has been a growing interest in proposing methods for estimating covariance functions for geostatistical data. Among these, maximum likelihood estimators have nice features when we deal with a Gaussian model. However maximum likelihood becomes impractical when the number of observations is very large. In this work we review some solutions and we contrast them in terms of ...

Geostatistics have become the dominant tool for probabilistic estimation of properties of heterogeneous formations at points where data are not available. Ordinary kriging, the starting point in development of other geostatistical techniques, has a number of serious limitations, chief among which is the intrinsic hypothesis of the (second order) stationarity of the underlying random field. Atte...

The estimation of pollution fields, especially in densely populated areas, is an important application in the field of environmental science due to the significant effects of air pollution on public health. In this paper, we investigate the spatial distribution of three air pollutants in Tehran’s atmosphere: carbon monoxide (CO), nitrogen dioxide (NO2), and atmospheric particulate matters less ...

Here in, an application of a new seismic inversion algorithm in one of Iran’s oilfields is described. Stochastic (geostatistical) seismic inversion, as a complementary method to deterministic inversion, is perceived as contribution combination of geostatistics and seismic inversion algorithm. This method integrates information from different data sources with different scales, as prior informat...

One of the effective steps in use of water resources is accurate estimation of plants water requirement. Lack of accurate estimation of this amount leads to water loss and failure to achieve optimum yield, reduced potential of production, soil resources degradation by too much irrigation or lack of enough leaching and salinization of soils by irrigation less than necessary level, which would ul...