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A novel model for predicting water cut based on trigonometric function growth curve

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Abstract

Water cut prediction is one of the most important contents of reservoir production performance analysis. Accurate prediction of water cut is crucial to formulate reasonable development plan and adjustment measures. However, the traditional method cannot predict the relationship between water cut and time, and the solution of parameters is also complicated. Based on the similar change rules of water cut and cumulative oil production, six new trigonometric function growth curves are established to predict the water cut of an oilfield. The results show that the new models based on the trigonometric function growth curve are simple and easy to solve. The prediction results of six water cut models are close to each other. Anyone model can be selected in water cut calculation, which saves a lot of calculation time and work. Compared with the Logistic model and Usher model, the prediction error of the new trigonometric function growth curve model is smaller. The model prediction results are in line with the actual development of the oilfield, and have certain practicability and reliability.

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Data availability

The data used to support the findings of this study are available from the corresponding author upon request.

Abbreviations

a, b :

model parameters(a and b have different values in YT1 to YT6 growth curves), constants

N Rmax :

recoverable reserves, 104t

N p :

cumulative oil production, 104t

t :

time, year

f w :

water cut, f

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Funding

This study is financially supported by the National Natural Science Fund Projects (no. 51804253), Shaanxi Key Laboratory of Continental Shale Gas Accumulation and Exploitation (YJSYZX18SKF0001).

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Correspondence to Feng Liu.

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The authors declare that they have no conflict of interest.

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Editorial Responsibility: Santanu Banerjee

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Liu, F., Wang, C., Wang, N. et al. A novel model for predicting water cut based on trigonometric function growth curve. Arab J Geosci 13, 1189 (2020). https://doi.org/10.1007/s12517-020-06194-w

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  • DOI: https://doi.org/10.1007/s12517-020-06194-w

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