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Stochastic approach in reserve estimation

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2004
Ülker, Emine Buket
Geostatistics and more specifically stochastic modeling of reservoir heterogeneities are being increasingly considered by reservoir analysts and engineers for their potential in generating more accurate reservoir models together with usable measures of spatial uncertainty. Geostatistics provides a probabilistic framework and a toolbox for data analysis with early integration of information. The uncertainty about the spatial distribution of critical reservoir parameters is modeled and transferred all the way to a risk conscious reservoir management. The stochastic imaging (modeling) algorithms allow the generation of multiple, equiprobable, unsmoothed reservoir models yet all honoring the data available. This thesis presents stochastic reserve estimation methods as related to the various stages of development of an oil field. Advances in technology are leading to better deterministic estimates as well as stochastic estimates with narrower ranges. Practices in the industry vary from complete dedication to deterministic or stochastic to a choice of the method depending on the stage of the development. In this study, reserves are calculated from the data available in Southeastern Turkey by using stochastic methods. Probability density functions, number of iterations are important statistical concepts. Increasing number of iterations leads to a normal distribution of histogram.