Within the Oil Industry, Reservoir Characterization is carried out to understand reservoir heterogeneity at various scales. It includes the interpretation of depositional environments, facies distributions, and properties distributions. Though the data are quantitative in nature, in practice, the interpretation results are used in a qualitative manner. Most data are presented graphically that shows the external qualitative reservoir description, and insight into the nature of the reservoir framework. For sustainable reservoir development, detail reservoir characterization not only requires the qualitative data but also the quantitative descriptions. For many reservoir applications, quantitative descriptions are required for proper analysis as a part of reservoir management. Geostatistic is increasingly being used for reservoir quantitative descriptions, mainly to predict values at unsampled locations. These statistical methods give a sense of quantitative description to the geologic and reservoir property conditions both vertically, laterally, to understand spatial distributions and correlations between the data. Geostatistics also provides quantitative methods for collecting, organizing, summarizing and analyzing data as well as for drawing conclusions. Common statistical methods used are cross-plots, histograms and variograms. Variograms are a spatial statistical analysis that measures dissimilarity as a function of separation distance, and usually applied to porosity, permeability and saturation. Variograms reflect the geometry and continuity of facies and petrophysical properties. Examples will be shared to demonstrate how the methods have been practically applied to characterize several reservoirs of Duri Field. They address the internal reservoir variabilities quantify the maximum and minimum ranges of property distribution, direction of continuity, property trends, cyclicity that have given better reservoir assessment on predicted flow behavior, and consequent reservoir decisions for further development.
Author : IGP. Oka Ariyasa