Computer Science and Information Technologies, Computer Science and Information Technologies 2009

Font Size: 
Oil-Gas well trajectory prediction and control with use of neural network technology
V. I. Vasilyev, I. F. Nugaev

Last modified: 2021-01-28


The problem of oil-gas well trajectory-prediction and control is investigated. The possibility of identification of drill bit motion predictive model on the basis of neural network technologies is shown.The approach to structural and parametrical identification of the drill bit neural network model based on use of two RBF networks is offered. The analysis of this model effectiveness is carried out.The possibility of precision increase for the well trajectory prediction compared to the kinematics approach of the model construction is shown.


Oil-Gas; neural network technology; trajectory-prediction


1. Anderson R.A. "Oil Production in the 21 stCentury". In: Scientific American, 1998, pp. 68-73.

2. Alimbekov R.I., Vasilyev V.I., Nugaev I.E.,Agzamov Z.V., Shulakov A.S. "ComputerizedTechnologies for Controll of Inclined-DirectionalDrilling". Oillndustry, 2000; 12: 120-122.

3. Kalinin A.G., Grigorian N.A., Sultanov B.Z"Drilling the Directed Oil Wells". Nedra Pub,Moscow, Russia, 1990.

4. Minaev U.N., Filimonova O.U., Benameur L."Methods and Algorithms of Identification andPrediction on the Basis of Neural Network inUncertainty Conditions". Hot Line Telecom Pub.,Moscow, 2003, Russia.

5. Haykin S. "Neural Networks. A comprehensivefoundation". Prentice Hall, New-York, USA, 1994.

6. Vasilyev V.I., Nugaev I.F. "Neural networksmoothing of Geonavigation Data on the Basis ofMultilevel Regularization Algorithm". Berlin:Springer-Verlag Berlin Heidelberg, ICONIP2008,Part 11, LNCS 5507, 2009, pp. 131-138.

Full Text: PDF