CLC number: TE122; TE347
On-line Access: 2024-08-27
Received: 2023-10-17
Revision Accepted: 2024-05-08
Crosschecked: 2013-01-23
Cited: 5
Clicked: 5690
Peng-hui Zhang, Jin-liang Zhang, Wei-wei Ren, Jun Xie, Ming Li, Jing-zhe Li, Fang Ding, Jin-kai Wang, Zi-rui Dong. Identification of waterflooded zones and the impact of waterflooding on reservoir properties of the Funing Formation in the Subei Basin, China[J]. Journal of Zhejiang University Science A, 2013, 14(2): 147-154.
@article{title="Identification of waterflooded zones and the impact of waterflooding on reservoir properties of the Funing Formation in the Subei Basin, China",
author="Peng-hui Zhang, Jin-liang Zhang, Wei-wei Ren, Jun Xie, Ming Li, Jing-zhe Li, Fang Ding, Jin-kai Wang, Zi-rui Dong",
journal="Journal of Zhejiang University Science A",
volume="14",
number="2",
pages="147-154",
year="2013",
publisher="Zhejiang University Press & Springer",
doi="10.1631/jzus.A1200165"
}
%0 Journal Article
%T Identification of waterflooded zones and the impact of waterflooding on reservoir properties of the Funing Formation in the Subei Basin, China
%A Peng-hui Zhang
%A Jin-liang Zhang
%A Wei-wei Ren
%A Jun Xie
%A Ming Li
%A Jing-zhe Li
%A Fang Ding
%A Jin-kai Wang
%A Zi-rui Dong
%J Journal of Zhejiang University SCIENCE A
%V 14
%N 2
%P 147-154
%@ 1673-565X
%D 2013
%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.A1200165
TY - JOUR
T1 - Identification of waterflooded zones and the impact of waterflooding on reservoir properties of the Funing Formation in the Subei Basin, China
A1 - Peng-hui Zhang
A1 - Jin-liang Zhang
A1 - Wei-wei Ren
A1 - Jun Xie
A1 - Ming Li
A1 - Jing-zhe Li
A1 - Fang Ding
A1 - Jin-kai Wang
A1 - Zi-rui Dong
J0 - Journal of Zhejiang University Science A
VL - 14
IS - 2
SP - 147
EP - 154
%@ 1673-565X
Y1 - 2013
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/jzus.A1200165
Abstract: This paper describes the identification of waterflooded zones and the impact of waterflooding on reservoir properties of sandstones of the Funing Formation at the gao 6 Fault-block of the gaoji Oilfield, in the Subei Basin, east China. This work presents a new approach based on a back-propagation neural network using well log data to train the network, and then generating a cross-plot plate to identify waterflooded zones. A neural network was designed and trained, and the results show that the new method is better than traditional methods. For a comparative study, two representative wells at the gao 6 Fault-block were chosen for analysis: one from a waterflooded zone, and the other from a zone without waterflooding. Results from this analysis were used to develop a better understanding of the impact of waterflooding on reservoir properties. A range of changes are shown to have taken place in the waterflooded zone, including changes in microscopic pore structure, fluids, and minerals.
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