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Integrating Neural Network and Numerical Simulation for Production Performance Prediction of Low Permeability Reservoir
Authors:Qingjun Yang  Shulin Zhang  Qi Fei
Affiliation:  a Petroleum Department, Faculty of Resources, China University of Geosciences, Wuhan, Hubei, China and School of Petroleum Engineering, University of New South Wales, Sydney, Australia b Petroleum Department, Faculty of Resources, China University of Geosciences, Wuhan, Hubei, China
Abstract:It is difficult to predict the production performance of low permeability fractured oil reservoirs. This is because complicated factors such as geological and engineering factors affect well production performance. This paper presents a methodology to predict well production performance in the Hanq oil field, which is a low permeability fractured reservoir. Integration of neural network with numerical simulation is employed. First we study the regularity of fluid flow and oil displacement mechanism by injection well group numerical simulation and analysis of production performance. Then we form the “expert knowledge” affecting production performance. The neural networks based on expert knowledge are trained using production data. This method will play an important role in future waterflood management and the design of recovery strategy for the Hanq oil field.
Keywords:Low permeability  Neural network  Numerical simulation  Production performance prediction  Reservoir
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