Introducing a novel model and tool for design and performance forecasting of waterflood projects

Although the waterflood process as an improved oil recovery method for increasing production and pressure maintanence has been around and widely used for more than six decades, it still holds a significant portion of world oil production. In some giant international companies, e.x. BP, about half of their production is by waterflooding. On the other hand, forecasting the performance of waterflooding projects plays an important role in successful study, design and selection of the best candidates from company reservoir asset. A model which is fast, robus, easy to use and reasonably accurate with a few input data required is of great desire. In this paper we address this deficiency by presenting a novel analytical-base forecasting model/tool that does not rely on conventional numerical simulation. Using the concepts of material balance, momentum balance, segregated flow and fractional flux (F-C or F-Phi) we achieve an analytical approach for modeling waterflooding behavior in reservoir. We used a Koval flow-storage capacity (F-C) model in the current research because of its strength and wide applicability for both homogenous and heterogeneous permeable media. The validity of the forecasting model was investigated by matching numerous actual field, single well and also simulation results. History matching showed good agreement between field data and forecasting results. The forecasting model demonstrates a strong ability to forecast the oil saturation, recovery efficiency, cumulative oil recovery, oil cut and oil rate changes with time. In addition, predicting the recovery efficiency enables us to generate the volumetric efficiency change with time which is of great importance for studying and evaluating waterflood process. These valuable results are produced using a few input data required.