Water Invasion Prediction Method for Edge–Bottom Water Reservoirs: A Case Study in an Oilfield in Xinjiang, China

Abstract

Clarifying the water invasion rule of edge and bottom water reservoirs can adjust the reservoir development mode and improve the recovery factor of edge and bottom water reservoirs in a timely manner. Influenced by the size of a reservoir water body, energy intensity and reservoir seepage capacity, the change model of reservoir water influx basically belongs to the exponential growth model of the GM (1,1) model or the self-constraint growth model of the logistic model. The above two models are used to predict and analyze the water inflow of edge and bottom water reservoirs, respectively, and it is found that the change in water inflow of the reservoir with sufficient edge and bottom water energy is more consistent with the prediction results of the GM (1,1) model, but it has a large error compared to the prediction results of the logistic model. The change in water influx in the reservoir with insufficient edge and bottom water energy is consistent with the prediction results of the logistic model and GM (1,1) model. The research shows that the strength of edge and bottom water energy of the reservoir can be determined by analyzing the error of the logistic model in predicting water influx. If we focus on the change in reservoir water influx, the improved GM (1,1) model formed by a Newton parabola interpolation polynomial is used to optimize its background value, which can further improve the prediction accuracy and reduce the prediction error of water inflow of edge and bottom water reservoirs. The method in this paper has certain reference significance for studying the water invasion rule and energy intensity of edge and bottom water reservoirs.