Petroleum Reservoir Evaluation and Development >
2020 , Vol. 10 >Issue 4: 107 - 112
DOI: https://doi.org/10.13809/j.cnki.cn32-1825/te.2020.04.017
Dew point pressure prediction model of condensate gas reservoir based on alternating conditional expectation transform
Received date: 2019-05-13
Online published: 2020-08-07
The efficient development of condensate gas reservoirs requires accurate fluid phase properties data, among which accurate prediction of dew point pressure is an important issue in the development of condensate gas reservoirs. In order to solve the problem of low accuracy of traditional prediction methods for dew point pressure of condensate gas reservoirs, based on optimization theory and applied statistical analysis, and by fitting measured data, a non-parametric regression model determined by alternating conditional expectation transformation（ACE） is proposed, and an explicit correlation of dew point pressure with statistical significance is obtained. Based on Pearson correlation analysis, the independent variables of the model are gas reservoir temperature, mole fraction of （C1, C2-C6, C7+）, and molecular weight and relative density of C7+. The potential function relation between independent and dependent variables is analyzed by 27 sets of experimental data for published dew point pressure, and 9 groups of measured dew point pressure data of TLM oilfields are predicted. The results show that the model has high precision and good generalization ability. The average absolute relative deviation（AARD） of model regression is 2.16 %, and the predicted AARD is only 4.8 %. The maximum absolute relative deviation（ARD） is 9.21 % and the minimum is 0.34 %. This study provides a reference method for dew point pressure prediction of condensate gas reservoirs.
Bowen SUN , Ping GUO , Yiming WU , Zhouhua WANG , Daiyu ZHOU , Zhiliang LIU . Dew point pressure prediction model of condensate gas reservoir based on alternating conditional expectation transform[J]. Petroleum Reservoir Evaluation and Development, 2020 , 10(4) : 107 -112 . DOI: 10.13809/j.cnki.cn32-1825/te.2020.04.017
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