Lithologic Reservoirs ›› 2018, Vol. 30 ›› Issue (6): 125-130.doi: 10.12108/yxyqc.20180615

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Improvement of characterization method based on type A water drive curve

LING Haochuan, MENG Zhiqiang, SHI Hongfu, SUN Qiang, PAN Jie   

  1. Bohai Oilfield Research Institute, Tianjin Company of CNOOC Ltd., Tianjin 300459, China
  • Received:2018-07-08 Revised:2018-09-16 Online:2018-11-16 Published:2018-11-16

Abstract: Type A water drive curve can be approximated to hyperbolic decline curve by Taylor expansion method to study the law of reservoir production decline. This method only has second-order precision in the neighborhood of initial oil cut, resulting in a large error in the late production prediction. In order to establish the relationship between the type A water drive curve and Arps decline law, and to improve the calculation accuracy of forecasting annual production of oilfields by the type A water drive curve, by comparing and analyzing the decline rate formulas of commonly used water drive curves, an oil cut power function fitting method for the decline rate of the type A water drive curve was proposed. The error of the oil cut power function fitting in different water cut stages was obtained by using the method of minimum value analysis of variance function. The results show that the higher the water cut is, the smaller the error of the oil cut power function fitting is, and when the water cut is greater than 70%, the oil cut power function fitting of the type A water drive curve not only fit better in the neighborhood of initial oil cut but also fit best in overall prediction time. The improved oil cut power function fitting method can be used to predict the annual oil production of the type A water drive curve quickly. The application proves the high accuracy of this method, and it is suitable for predicting the production of reservoirs with water cut greater than 70% which conform to the characteristics of type A water drive.

Key words: water drive curves, decline law, power function, oil cut, oil production forecast

CLC Number: 

  • TE341
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