Identification of oil layer filtering modes by artificial neural networks
Keywords:
neural network, ANN, filtering mode, well testingAbstract
This paper discusses the implementation of the approach based on artificial neural networks to determine the parameters of the filtering mode applying the well test data. The typical characteristics of different filtering modes observed in the diagram of the pressure derivative function are also investigated.References
Харин А. Ю., Харина С. Б. Гидродинамические методы исследования нефтяных скважин : учеб. пособие. – Уфа : Изд-во УГНТУ, 2004. – 108 с.
Кременецкий М. И., Ипатов А. И., Гуляев Д. Н. Оценки продуктивных свойств пласта и скважины по гидродинамическим исследованиям : учеб. пособие. – М. : РГУ нефти и газа, 2003. – 85 с.
Athichanagorn, S. Using Artificial Neural Network And Sequential Predictive Probability Method To Mechanize Interpretation Of Well Test Data: M. S. Thesis. – Stanford University, 1995. – 67 p. – URL: https://pangea.stanford.edu/ ERE/pdf/pereports/MS/Athichanagorn95.pdf (дата обращения: 26.11.2012).
Al-Kaabi, A. U., Lee, W. J. Title Using Artificial Neural Networks To Identify the Well Test Interpretation Model // SPE Formation Evaluation. – 1993. – Vol. 8, Nr 3. – Pp. 233–240.
Хайкин С. Нейронные сети: полный курс. – М. : Вильямс, 2006. – 1104 с.
Horne, R. N. Modern Well Test Analysis: A Computer-Aided Approach. – 4th printing. – Palo Alto, California, USA : Petroway, Inc, 1990.
