Practical use of Multiple Geostatistical Realizations in Petroleum Engineering

Abstract

Ranking of multiple realizations is an important step when the processing time for a realization is large. This is the case in reservoir flow simulation and in other areas of geology, environmental and even medical applications. Significant uncertainty exists in all reservoirs especially at unsampled locations where the geological heterogeneity and connectivity are impossible to exactly predict between wells. Geostatistical techniques are used to construct models of static properties such as lithofacies, porosity, permeability and residual fluid saturations and provide multiple equally probable realizations of these properties. The number of realizations that is required for modeling the uncertainty may be large; usually 100 realizations are considered enough to quantify uncertainty. However, this number of realizations is still too high for processing by a flow simulator. This thesis aims at developing a robust and reliable ranking methodology to rank the realizations using a static ranking measure. The outcome is the identification of the high, low, and intermediate ranking realizations for further detailed simulations. The methodology was developed for the steam assisted gravity drainage (SAGD) reservoir application. This thesis will consider the cumulative oil produced (COPrate) and cumulative steam-oil-ratio (CSOR) as the ranking parameters in the flow simulations, hereafter called performance parameter. Connected hydrocarbon volume (CHV) was the parameter that was used in the ranking methodology as the static ranking measure. High calibration between the performance parameters and the CHV would indicate the success of the proposed ranking methodology. The ranking methodology was validated against the results of the flow simulations. The results indicate a mediocre correlation between the SAGD performance parameters and CHV. The ranking methodology was modified by incorporating the average reservoir permeability. Significant improvement in the correlation between the static ranking measure and the SAGD performance parameters resulted.