Identification of waterflooded zones and the impact of waterflooding on reservoir properties of the Funing Formation in the Subei Basin, China

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. © 2013 Zhejiang University and Springer-Verlag Berlin Heidelberg.