One of the most important outputs of the static model is the volumetrics of the original hydrocarbon in place (OHIP). According to the type of reservoir driving mechanism, the reservoir engineer can assume the recovery factor and hence the recoverable reserves. Most simulation studies are being conducted on fields considering a period of production performance to determine the remaining reserves and the best scenario of development to produce these reserves, which is the main function of the dynamic model.

The volumetrics could be approached using a Monte Carlo technique, the end product of which is a range of probable OHIP and, consequently using the proper recovery factor, getting probability distribution of the recoverable reserves. Therefore, using the probabilistic approach is superior in green fields rather than brown fields because it captures the full range of reality and where models are not yet calibrated to dynamic data.

Sometimes, the dynamic data may take a surprise turn from the geological understanding. Different realizations, even the crazy ones, may help under the probability distribution functions in defining some certainties that have not yet even been imagined. In addition, each of the dynamic model's scenarios yields extra recovery, the certainty of which can be evaluated using the probability distribution curve of the remaining reserves. This certainty has direct influence on the economics approval of one scenario over the others.

The current work introduces actual case histories demonstrating how the probabilistic approach could be of real help in selecting the production enhancement scenario and how this tool also could be used to prioritize management interests.

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