While outcrop models can provide important information on reservoir architecture and heterogeneity, it is not entirely clear how such information can be used exhaustively in geostatistical reservoir modeling. Traditional, variogram-based geostatistics is inadequate in that regard since the variogram is too limiting in capturing geological heterogeneity from outcrops. A new field, termed multipl...

Quantitative hydrogeology celebrated its 150th anniversary in 2006. Geostatistics is younger but has had a very large impact in hydrogeology. Today, geostatistics is used routinely to interpolate deterministically most of the parameters that are required to analyze a problem or make a quantitative analysis. In a small number of cases, geostatistics is combined with deterministic approaches to f...

Methods based on two-point geostatistics have been routinely used to interpolate random variables such as groundwater level and concentration and to estimate their values at un-sampled locations. These methods use the observed data to analyze spatial two-point correlations and ignore the higher order moments that may play a key role in the characterization of complex patterns. In this work, a m...

This document presents an extract of an upcoming book written by Nicolas Remy, Alexandre Boucher and Jianbing Wu. The book has 10 chapters detailing how to use the SGeMS software. SGeMS is a software for 3D geostatistical modeling. It implements many of the classical geostatistics algorithms, as well as new developments related to multiple-point geostatistics. The software is open source and fr...

Production of high quality interpolation maps of heavy metals is important for risk assessment of environmental pollution. In this paper, the spatial correlation characteristics information obtained from Moran's I analysis was used to supplement the traditional geostatistics. According to Moran's I analysis, four characteristics distances were obtained and used as the active lag distance to cal...

Geostatistics is used in many different disciplines to characterise spatial variation and for spatial prediction, spatial simulation and sampling design. Archaeology is an inherently spatial discipline and the models and tools provided by geostatistics should be as valuable in archaeology as they are in other disciplines that are concerned with spatially varying properties. However, there have,...

in order to comparing geostatistics and artificial neural networks (ann) methods in predicting soil salinity and clay content this experiment was conducted in sistan region land. 121 soil samples were taken at the depth of 0-30 cm within the grid of 750 750 m and soil ec and clay percent were determined. 105 samples were used for training and 16 samples were used for test in both models. diffe...