A stochastic approach in reserve estimation

Geostatistics and more especially 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 an 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 they all honor the data available. This research presents stochastic reserve estimation methods related to various stages of the 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 a complete dedication to deterministic or stochastic approach 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. A probability density function and number of iterations are important statistical concepts. An increasing number of iterations leads to a normal distribution of a histogram.