Characterization and ranking of reservoir models using geostatistics and streamline simulation

The purpose of this dissertation is twofold. First, we investigate the possibility of estimating interwell saturation distribution using cross-well seismic and well data. A geostatistical field study is presented to examine the practical feasibility of this approach. Second, a criterion to rank geostatistical realizations for quantification of uncertainty is proposed. A 3-D streamline model is used to simulate fluid flow through multiple geostatistical realizations. A "connectivity" criterion based on streamline time-of-flight is proposed for ranking realizations.;One of the goals of reservoir characterization is to identify unswept regions containing high oil saturation for targeted infill drilling or enhanced recovery. A common approach to this problem is to generate high-resolution distribution of reservoir properties and then conduct flow simulation. One possible alternative to flow simulations would be to generate spatial distribution of properties that are related to fluid saturations and then infer fluid saturation distribution through the use of appropriate correlations. Seismic data can be particularly suitable for this purpose because of its dense spatial coverage. A field application is presented in which interwell water saturation distribution is inferred by combining cross-well seismic and well data.;Geostatistical techniques are increasingly being used for modeling reservoir heterogeneity and assessment of uncertainty in performance predictions. Although a large number of stochastic reservoir models or realizations may be generated, in practice, only a small fraction can be considered for comprehensive flow simulation. This limited number of realizations is selected through a process of ranking. Rankings that rely on permeability connectivity have been shown to be ineffective because they do not account for the interaction between the flow field and heterogeneity. In this study, we propose a connectivity criterion based on the streamline time-of-flight and use this criterion to rank geostatistical realizations for detailed flow simulation purposes. Because the time-of-flights reflect the fluid front propagation at various times, the connectivity in the time-of-flight provides us with a direct measure of volumetric sweep efficiency. Thus, the proposed approach provides, for the first time, a method for computing volumetric sweep efficiency for arbitrary heterogeneity and well configuration. The proposed approach is applied to synthetic and field examples.