The variogram is a critical input to geostatistical studies. It is the most widely used tool to investigate and model spatial variability of lithofacies, porosity, and other petrophysical properties. In addition, 90% of geostatistical reservoir characterization studies use variogram-based geostatistical modeling methods. Furthermore, the variogram reflects our understanding of the geometry and ...

In this paper we propose an extended version of a model-based strategy for clustering spatial functional data. The strategy, we refer, aims simultaneously to classify spatially dependent curves and to obtain a spatial functional model prototype for each cluster. The fit of these models implies to estimate a variogram function, the trace variogram function. Our proposal is to introduce an altern...

Before optimal linear prediction can be performed on spatial data sets, the variogram is usually estimated at various lags and a parametric model is fitted to those estimates. Apart from possible a priori knowledge about the process and the user’s subjectivity, there is no standard methodology for choosing among valid variogram models like the spherical or the exponential ones. This paper discu...

Measured grades rely on the relative positions of measurement locations within the ore site. These measurements at a set of locations give some insight into regional variability. This variability determines the regional behaviour as well as the predictability of the grade. The larger the variability, the more heterogeneous is the geological environment1. One of the tools used to measure regiona...

Spatial disagregation is needed when environmental models of climate, air quality, hydrology, etc. require input data at a finer scale than available or when models produce outputs at a coarser scale than required by users. Area-to-Point Kriging is a common geostatistical framework to address the problem of spatial disaggregation from block to point support. Spatial disaggregation using Area-to...

In recent years, methods of fuzzy reasoning have been successfully developed for land evaluation. The accuracy of such land evaluation depends on the quality of weighing land characteristics with respect to their effects on crop production. This paper presents a spatially-based model of land suitability analysis. The main purposes were to (1) establish land suitability indices for irrigated whe...

The soil roughness at the field level is an easy visually perceptible notion, but difficult to describe numerically. The objective of this paper is to propose a method to establish quantitative and descriptive soil roughness indices. A measurement system was developed using a laptop-computer and a laser cell. The elevation data are measured on the ground along a square array. They are treated w...

The spatial continuity of the variables we model in geostatistics is dependent on the modelling and reproduction of the variogram. The variogram defines the relationship between variability (or geologic distance) and the lag distance (or Euclidian distance). As the magnitude of the lag separation vector increases, we typically expect the variogram to also increase. This is generally observed. T...

We investigate the accuracy and resolution of the variogram analysis method (Maus, 1999) on syn thetic and real data. Syn thetic magnetic ight line data are generated forbasemen t models of idealized geological setups. Comparing variogram depths of the data with true model depths shows that variogram depths are accurate and un biased as long as the data analysis window is larger than 10 times t...

In this paper we consider the estimation of the variogram using the method of weighted least squares and in the process we propose two alternative set of weights. We study the asymptotic sampling properties of these estimators and compare their efficiencies both analytically and through simulations. To illustrate the above methods, we consider daily rainfall across Switzerland measured at 467 l...