This paper describes one solution to the problem of constraining geostatistical models by well-test results which has been obtained within the frame of the HELIOS research project conduced by Elf and IFP in the field of reservoir engineering. To do so, a numerical simulation program devoted to the simulation of well-tests has been coupled with a nonlinear constrained optimization program to mak...

Spatial data, either areal or geostatistical (point-referenced), are becoming increasingly utilized in the study of many scientific fields due to the accessibility of data monitoring systems and associated datasets. When both types of data are available for the same underlying spatial process, computationally efficient and statistically sound methods are needed for their joint analysis. Markov ...

in many urban areas, groundwater has been exploited neglecting to wet and dry periods owing to of surface water deficit. in this study, using the percent of normal rainfall index, 36 year (1971-2008) were studied and a drought event and a wet event were determined. the reason to choose two consecutive years is the effect of early wet period on groundwater quality. physicochemical characteristic...

In this study we evaluated the diffusion of nitrous oxide in a few operating rooms, using spatial data modelling techniques, in order to assess hospital staff exposure and to promote risk management. Indoor air sampling was carried out, during routine operating activity, by means of transportable infrared spectrometer, with geostatistical techniques. We detected high average concentrations of n...

Many state and national geological surveys produce map products from surficial and bedrock geologic maps as a value-added deliverable for a variety of stakeholders. Improvements in powerful geostatistical exploratory tools and robust three-dimensional capabilities within geographic information systems (GIS) can facilitate the production of derivative products. In addition to providing access to...

The IsoMAP uses the multiple linear regression and geostatistical methods to analyze isotope data. Suppose the response variable Y (s) and the vector of independent variable x(s) are observed at a finite number of sites s1, · · · , sn. The multiple linear regression method assumes Y (s) and Y (s′) are independent but the geostatistical method assume they are not. In the following, we will first...

INTRODUCTION A geostatistical approach to characterize MS-lesion patterns based on their geometrical properties is presented. METHODS A dataset of 259 binary MS-lesion masks in MNI space was subjected to directional variography. A model function was fit to express the observed spatial variability in x, y, z directions by the geostatistical parameters Range and Sill. RESULTS Parameters Range...

Spatial dependence exists when the variation between observations is dependent on spatial location. In the present study, geostatistical methods were used to examine spatial dependence in adolescents’ perceptions of their neighborhoods: whether adolescents living in close proximity perceived their neighborhoods more similarly than adolescents living further apart. Participants included 343 adol...

We consider the problem of model selection for geospatial data. Spatial correlation is often ignored in the selection of explanatory variables, and this can influence model selection results. For example, the importance of particular explanatory variables may not be apparent when spatial correlation is ignored. To address this problem, we consider the Akaike Information Criterion (AIC) as appli...