Productivity Prediction of Tight Sandstone Reservoir Based on BP Neural Network
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Acton, P. D., & Newberg, A. (2006). Artificial neural network classifier for the diagnosis of Parkinson’s disease using [99mTc]TRODAT-1 and SPECT. Physics in Medicine & Biology, 51(12), 3057-3066.
Deng, Y., Huang, R., & Guo, D., et al. (2005). Affecting factors of coal-bed gas production and production prediction of unstable percolation. Natural Gas Industry, 25(1), 117-119.
Hoek, P. J. V. D., Hertogh, G. M. M., & Kooijman, A. P., et al. (1996). A new concept of sand production prediction: Theory and laboratory experiments. Spe Drilling & Completion, 15(4), 261-273.
Kakouei, A., Masihi, M., & Sola, B. S., et al. (2014). Lithological facies identification in Iranian largest gas field: A comparative study of neural network methods. Journal of the Geological Society of India, 84(3), 326-334.
Lee, J. Y., Shin, H. J., & Jong, S. L. (2011). Selection and evaluation of enhanced oil recovery method using artificial neural network. Geosystem Engineering, 14(4), 157-164.
Morita, N., Whitfill, D. L., & Fedde, O. P., et al. (1989). Parametric study of sand-production prediction. SPE Production Engineering, 4(1), 25-33.
Paul, A. P., Fiona, M. D., & Luiz, M. (2001). The interactive effects of strategic marketing planning and performance: A neural network analysis. Journal of Marketing Management, 17(1-2), 159-182.
Serpen, G., Tekkedil, D. K., & Orra, M. (2008). A knowledge-based artificial neural network classifier for pulmonary embolism diagnosis. Computers in Biology & Medicine, 38(2), 204-220.
Shen, Y., & Zhang, A. (2010). The stability classification system of roadway surrounding rock based on VC++ 6.0 and BP neural networks. Proceedings of the International Symposium on Electronic Commerc.
Shi, Z., Shi, Y., & Zhang, H., et al. (2012). Productivity prediction of tight sand reservoir with low permeability in sulige gas field. Well Logging Technology, (06).
Sun, Z. X., Yao, J., & Sun, Z. L., et al. (2011). The application of cluster analysis based on neural network methods in identification reservoir flow unit. Geophysical & Geochemical Exploration, 35(3), 349-353.
Yang, J. S., & An-Qi, L. I. (2008). Dynamic analysis and classification evaluation of CBM well development in Fanzhuang block. Natural Gas Industry, 28(3), 96-98.
Yang, P., Zhu, Q., & Zhong, X. (2009). Subtractive clustering based RBF neural network model for outlier detection. Journal of Computers, 4(8).
Yong, B. Z., & Yong, L., et al. (2011). Classification of carbonate gas condensate reservoirs using well test and production data analyses. Petroleum Science, 8(1), 70-78.
Zeng, B., & Xiang, W. (2007). Application of artificial neural networks on stability evaluation of shifo-temple landslide. Journal of Engineering Geology, 15(Suppl.), 379-385
Zhang, X. F., Tang, J. W., & Wei, Y. S., et al. (2009). Individual well management and dynamic production analysis of sulige gas field. Journal of Southwest Petroleum University, 31(3), 110-114.
DOI: http://dx.doi.org/10.3968/9476
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