نتایج جستجو برای: geostatistical modeling
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Abstract Point bar reservoir geology is frequently encountered in oil and gas developments worldwide. Furthermore, point many sites being considered for large scale CO 2 injection sequestration. A comprehensive modeling method that adequately preserves internal architecture its associated heterogeneities still not available. Traditional geostatistical methods cannot capture the curvilinear of b...
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 ...
Raster based digital elevation models (DEM) are the basis of some of the most important GIS workflows: hydrologic modeling, site suitability, and cost path analysis. While there are several techniques for generating digital elevation models (DEMs), none of them can produce a true elevation surface. Locally varying measurement error and the inexactness of the interpolation methods contribute to ...
The first step in statistical data analysis is to verify three data features: dependency, stationarity, and distribution. If data are independent, it makes little sense to analyze them geostatisticaly. If data are not stationary, they need to be made so, usually by data detrending and data transformation. Geostatistics works best when input data are Gaussian. If not, data have to be made to be ...
Kriging techniques are used to map national public health data routinely reported to the Centers for Disease Control and Prevention (CDC). Although choropleth maps are commonly used to display geographic and temporal disease-related events for political (state and county) jurisdictions, kriged maps may offer opportunities to enhance visual communication of event patterns over time. As a geostat...
Geostatistical modeling of reservoir properties is common in the assessment of expected reservoir flow. Typically, static properties such as porosity, saturation and permeability are modeled with geostatistical techniques to quantify the level of uncertainty in reservoir characterization. Lately, practitioners have become concerned that purely statistical techniques do not sufficiently integrat...
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