Abstract
In order to improve oil and gas production, taking advantage of advanced neural network tools to design an appropriate algorithm to predict the extent of oil and gas damage and then to protect the oil and gas layer provided a strong guarantee of promoting oil and gas production. The application in Karamay Oilfield shows that combining neural network toolbox of Matlab with the sample data of the oil and gas layer training and establishing a set of mathematical models to predict the damage extent of oil and gas layer provides a powerful help to protect the oil and gas layer. The neural network prediction model has played a positive role in promoting the oil and gas production and enhancing the application of neural network system in oil and gas forecasting.
Hubei Provincial Department of Education Science and Technology Research Project(B20101304): BP neural network prediction analysis in cleft lip surgery research.
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References
Lu, S., Liu, L., Shek, L., Li, Y.: Based on automated reasoning in intelligent planning method. Journal of Software, Nian 05, 1226–1238 (2009)
Chen, M.: The Tactics Analysis about Early Phase Ends of the Partial Distortion Search. IEEE, Los Alamitos (2008), doi: 10.1109/WGEC, 17, 324-327
Jiang, Q.: The Realization of the Passive Caller Resumption about Mobile System Core Pool. IEEE, Los Alamitos (2008), doi: 10.1109/WGEC.2008.17, 487-490
Zhou, Z., Chen, S.: Neural network integration. Journal of Computers, Nian 01, 1–8 (2002)
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Shi, J. (2011). The Algorithm Design and Application of the Neural Network. In: Zeng, D. (eds) Applied Informatics and Communication. ICAIC 2011. Communications in Computer and Information Science, vol 224. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23214-5_21
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DOI: https://doi.org/10.1007/978-3-642-23214-5_21
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