The three-dimensional (3-D) modeling of glacial sediments often requires the use of lithologic logs from public water well data. The interpretation of such data is difficult because data collection methods are not standardized among contributing drillers, and the sequence of recorded lithologies contains both stratigraphic and facies-scale information. Geostatistics coupled with interpretation ...

One of the main challenges of geostatistics in reservoir characterization is to populate a portion of 3-D earth model with its petrophysical properties. This operation must be carried out while still honoring the information available along well logs: in our jargon, we say that it must be conditional. No restriction is required on this conditioning information, either in number or in its geomet...

Nowadays machine learning (ML), including Artificial Neural Networks (ANN) of different architectures and Support Vector Machines (SVM), provides extremely important tools for intelligent geoand environmental data analysis, processing and visualisation. Machine learning is an important complement to the traditional techniques like geostatistics. This paper presents a review of several contempor...

Prediction of annual average precipitation over a regin is one of important issues in watersherd management and natural resources planning. Geostatistics is one of the useful methods for precipitation prediction which varies based on type of the variable. This study was conducted in Karoon and Dez Basins located in southwertern of Iran. The data set including 20 years of annual precipitation of...

Variograms and covariance functions are key tools in geostatistics. However, various properties, characterizations, and decomposition theorems have been established for covariance functions only. We present analogous results for variograms and explore the connections to covariance functions. Our ndings include criteria for covariance functions on intervals, and we apply them to exponential mode...

Geostatistics deals with spatial and temporal data from natural phenomena and involves estimating values of regionalized variables. In this analysis the fundamental tool is the variogram that is a variability measure; for example, geological variability related to distance. The variogram shows the degree of spatial dependence between samples for a specific support. The squared differences betwe...