The main challenge in reservoir description is to integrate the different data sources and in particular be able to handle the uncertainty in the reservoir description. This paper presents a stochastic approach which integrates the different data sources. The method presented may be used for improving the predictions of the performance and for assessing the associated uncertainties. The latter is, however, a more complicated task.

The method consists of a combination of many different techniques, each of them used to model particular reservoir phenomena. The examples shown includes the use of Gaussian random fields, marked point processes and Markov random fields and the respond variables are hydrocarbon in place, oil production and recovery factor.

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