The evaluation of the recoverable hydrocarbon volume and further development opportunities in complex reservoirs (where two or more reservoirs are hydraulically connected) primary challenges the engineer faces in managing such reservoirs. In this study, multi-tank material balance models have been built to solve these problems.

The key criteria for a robust material balance modelling of hydraulically connected reservoirs in a single system are: (i) transmissibility across the reservoirs should be properly defined. Transmissibility is a major modelling component in achieving sound multi-tank MBAL models. It is useful to the estimation of the rate of aquifer movement across the reservoirs. (ii) Good understanding of the geology and production data of the reservoirs is helpful in estimating the appropriate transmissibility. (iii) Sufficient and quality Carbon-Oxygen logs, BHP and production data. CO logs are very important for proper calibration of hydrocarbon contact. Accurate BHP data is critical in the establishment of dynamic communication and matching of simulated versus measured reservoir pressure.

In this paper two cases with over 30 years of production history are discussed in detail including the full methodology and the associated results. The results from these studies show good and reliable outcome which has provided the basis for the reported hydrocarbon resource volumes of the reservoirs (B1.0X, B1.0N, C1.0X, E9.0X, E10.0X, E11.0X, G1.0X, H1.0X)

Results were compared with other methodologies (existing simulation models and DCA of NFA wells) and indicate good comparisons. The number of development opportunities in the 8 reservoirs were optimised from 22 to 20 wells using the multi-tank material balance model.

Despite some known limitations of material balance generally, multi tank material balance model has proven to be a simple and reliable methodology in evaluating complex reservoir system with hydraulic communication. Especially, in situations where time and budget constraints will not support full field reservoir simulation modelling.

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