Reservoir characterization using experimental design and response surface methodology

Abstract

This research combines a statistical tool called experimental design/response surface methodology with reservoir modeling and flow simulation for the purpose of reservoir characterization. Very often, it requires large number of reservoir simulation runs for identifying significant reservoir modeling parameters impacting flow response and for history matching. Experimental design/response surface (ED/RS) is a statistical technique, which allows a systematic approach for minimizing the number of simulation runs to meet the two objectives mentioned above. This methodology may be applied to synthetic and field cases using existing statistical software tools. The application of ED/RS methodology for the purpose of reservoir characterization has been applied for two different objectives. The first objective is to address the uncertainties in the identification of the location and transmissibility of flow barriers in a field in the Gulf of Mexico. This objective is achieved by setting up a simple full-factorial design. The range of transmissibility of the barriers is selected using a Latin Hypercube Sampling (LHS). An analysis of variance (ANOVA) gives the significance of the location and transmissibility of barriers and comparison with decline-type curve analysis which gives us the most likely scenarios of the location and transmissibility of the flow barriers. The second objective is to identify significant geologic parameters in object-based and pixel-based reservoir models. This study is applied on a synthetic fluvial reservoir, whose characteristic feature is the presence of sinuous sand filled channels within a background of floodplain shale. This particular study reveals the impact of uncertainty in the reservoir modeling parameters on the flow performance. Box-Behnken design is used in this study to reduce the number of simulation runs along with streamline simulation for flow modeling purposes. In the first study, we find a good match between field data and that predicted from streamline simulation based on the most likely scenario. This validates the use of ED to get the most likely scenario for the location and transmissibility of flow barriers. It can be concluded from the second study that ED/RS methodology is a powerful tool along with a fast streamline simulator to screen large number of reservoir model realizations for the purpose of studying the effect of uncertainty of geologic modeling parameters on reservoir flow behavior.