Modeling of well performance during oil reservoir development on the elastic-water-drive mode using regression analysis

One of the important tasks of analyzing oil field development is predicting well performance. For this purpose, displacement characteristics are often used, which represent the dependence of some indicators on others. To determine the parameters of these dependencies, regression analysis of historical data is used. Dependences of the choice of watering production wells with water pumped into injection wells, water or the law of the exhausted aquifer.
A feature of displacement characteristics is generally considered to be that they can only be used when fluid flows in the formation are established. This is due to the fact that with the classical approach, displacement of characteristics is not observed in the explicit form of well interference. Therefore, the search for displacement characteristics, with the help of which we can talk about the mutual influence of wells, is an important factor. This is the subject of this work.
Water cut and water-oil ratio (WOR) are related by a well-known formula. The paper proposes regression models for WOR. They obtained the result taking into account the classical logic of the WOR from accumulated oil production.
Water cut is calculated from water saturation. The proposed regression models of water saturation are based on the analysis of equations of theories of two-phase filtration in difference form.
11 watering models were studied, two including classical ones and 9 new ones. Dependencies for reservoir and bottomhole pressures were also developed. The proposed models are intended to analyze the operation of wells during the development of an oil reservoir in an elastic-water-pressure mode. The models were tested on a real field and their effectiveness was analyzed. Some new models perform well in a selection of tests. In particular, all the proposed models give better results than the classical model: the logarithm of the water-oil ratio from the accumulation of oil production.

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