Petroleum Reservoir Evaluation and Development >
2021 , Vol. 11 >Issue 5: 730 - 735
DOI: https://doi.org/10.13809/j.cnki.cn32-1825/te.2021.05.010
A method for oil recovery prediction of sandstone reservoirs in the eastern South China Sea based on neural network
Received date: 2021-04-26
Online published: 2021-10-12
At present, the methods such as numerical simulation and linear regression are mostly used to predict the oil recovery of sandstone reservoirs in the eastern South China Sea, but some of them are time-consuming or with low accuracy. In order to predict the oil recovery quickly and accurately, 50 developed reservoirs are selected as the data samples. Based on the feature extraction of the influencing factors of the principal component analysis on recovery, a recovery prediction model suitable for sandstone reservoirs in the eastern South China Sea is established by the neural network. Compared with that of two methods of support vector machine regression and linear regression, the prediction results of neural network regression model have high prediction accuracy, which can evaluate the development potential of the similar reservoirs quickly.
Wei LI , Fang TANG , Boheng HOU , Yin QIAN , Chuanzhi CUI , Shuiqingshan LU , Zhongwei WU . A method for oil recovery prediction of sandstone reservoirs in the eastern South China Sea based on neural network[J]. Petroleum Reservoir Evaluation and Development, 2021 , 11(5) : 730 -735 . DOI: 10.13809/j.cnki.cn32-1825/te.2021.05.010
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