Evaluating interwell connectivities can provide important information for reservoir management by identifying flow conduits, barriers, and injection imbalances. Injection and production rates, in ideal conditions, contain connectivity information. A number of methods have been proposed to predict connectivity based on these data. Unfortunately, many of these rate based methods have not proven to be as successful as intended because of factors external to the reservoir. Field maintenance procedures, such as shut-ins and work-overs, cause production rate changes which are not caused by injection rate fluctuations but which mislead connectivity estimators. We have developed a method which is tolerant to changes caused by external factors.

This method, called the Multiwell Compensated Capacitance Model (MCCM), is based on the superposition principle. It can analyze injection and production data when producers' skin factors change, new producers are added, or active producers are shut-in. The MCCM also deals with another common problem in field data, which is when there are frequent producer shut-ins within sampling intervals (mini-shut-ins). For example, a producer is shut-in for a few days when flow rates are measured every month. By deriving the MCCM equations using average rates, we have developed an efficient approach to overcome this problem.

In several synthetic cases with varying skin, long term shut-in, and frequent mini-shut-ins, the MCCM successfully determined the true connectivity parameters and predicted the production rates accurately. For a set of field data from a heavy oil waterflood in Saskatchewan, we could improve the R2 of the predicted rates by 20 to 35% compared to another method and observed good agreement with geological information.

In general, we may not find a long enough time interval of injection and production data where the producers' conditions stay constant. Applying earlier methods in such cases may give misleading connectivity results and inaccurate rate predictions. Adopting the approaches described in this paper helps geoscientists and engineers to have a better understanding of reservoir heterogeneity and its effects on fluid flow in the reservoir.

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