A cluster-based approach for visualizing and categorizing the impacts of shale barrier configurations on SAGD production

Abstract

The impact of reservoir heterogeneities in the form of shale barriers on steam-assisted-gravity-drainage (SAGD) production can be analyzed by generating a large number of realizations of shale barrier configurations and subjecting them to flow simulation. However, visualizing and quantifying the (dis)similarities among these realizations is often challenging. A workflow that applies multidimensional scaling (MDS) and cluster analysis techniques is developed to categorize the influences of different shale barrier configurations on SAGD production and to quantify the dissimilarities between realizations. The simulation model (both two-dimensional and three-dimensional) is based on homogeneous oil sand, with reservoir heterogeneities added to the model by superimposing sets of idealized shale barriers located within the oil sand. First, a distance function, which measures the dissimilarity in production responses between any two given shale barrier configurations, is formulated. Next, MDS is used to map the resultant distance matrix into an n-dimensional Euclidean space, where clustering analysis technique is applied to group the cases into multiple clusters. It is expected that the impact of each shale barrier configuration within the same cluster on SAGD production is similar. Specific features corresponding to the shale barriers in each cluster are analyzed, to infer any potential correlation between SAGD production and the particular shale distribution characteristics. The proposed workflow offers an efficient and systematic method for constructing representative datasets for data-driven problems that maximize the spanning of the model parameter space, without exhaustively sampling similar realizations and subjecting them to flow simulation.