Current computer technology has given us the ability to generate realizations of spatial reservoir properties as never before. However, achieving the goal of generating reservoir descriptions which are consistent with all of the available information continues to be a difficult and time-consuming process. Especially, the inability to constrain probabilistic-based reservoir descriptions using (dynamic) production data is becoming recognized as one of the primary short-comings of existing techniques.
This paper describes a procedure to identify, quantify and incorporate within a conditional simulation procedure the spatial reservoir characteristics which dominate well performance. Primary production data are used to determine controlling spatial characteristics. The primary production parameters are combined with waterflood constraints and the method of simulated annealing to produce realistic reservoir descriptions-both in terms of their spatial characteristics and simulated well performance. Although excellent matches of well performance are also obtained using these "indirect performance constraints" while excluding the variogram constraint, it is shown that the resulting alternative reservoir descriptions poorly reproduce actual spatial reservoir properties. Thus, it is concluded that spatial correlation structures cannot be extracted from performance data. The robustness and flexibility of the approach is demonstrated using a two-dimensional areal, field scale reservoir study. The proposed technique can be used to greatly reduce the uncertainty of predicting future reservoir performance.