Applying BP Neural Network to Determine Proper Water Injection Intensity of Water Drive Oil Field

Abstract:

In this paper, combining previous research on methods of determining water injection rate, dividing coefficient is introduced into this process. Influential factors of water injection rate are also taken into consideration. Based on those theories mentioned above, an analysis on determining dividing coefficient is made by applying BP neural network. Data from one particular year of exploitation was chosen to build up a neural network model between the dividing coefficient and other factors to determine the dividing coefficient, and then single well water injection rate was determined.

• Periodical: Advanced Materials Research (Volumes 734-737)
• Pages: 1358-1361
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.734-737.1358
• Online since: August 2013
• Authors: Wu Yi Shan, Wei Lin Cui, Yong Sheng Li
• Keywords: BP Neural Network (BPNN), Dividing Coefficient, Water Injection Rate

References

[1] Chensheng Li, Minxi Tan. Scientific Technology and Engineering. Vol. 31(2011), p: 66.

[2] Lou Jingjie, Zhang Qingsong. Xinjiang oil and gas. Vol. 3 (2007). p: 31.

[3] Jian Liu. Research on Neural network and reservoir dynamic model. China Petroleum University (Beijing), (2010).

[4] Xiao Wei, Liu Zhibin. Computer and Communications. Vol. 15(1997). p: 57.

[5] Yang Yanming, Su Jiandong, Ma Peisen. Petroleum exploration and development. Vol. 25 (1998). p: 69.

[6] Qi Yufeng. Petroleum Exploration and Development. Vol. 1(1990). p: 45.