Artificial Neural Network Model for Prediction of Drilling Rate of Penetration and Optimization of Parameters-Reference-Cited by-同舟云学术

Artificial Neural Network Model for Prediction of Drilling Rate of Penetration and Optimization of Parameters

Published:2014 Issue:2 Volume:57 Page:65-70
ISSN:1346-8804
Container-title:Journal of the Japan Petroleum Institute
language:en
Short-container-title:J. Jpn. Petrol. Inst.

Author:

Bataee Mahmood¹,Irawan Sonny¹,Kamyab Mohammadreza²

Affiliation:

1. Dept. of Petroleum Engineering, Universiti Teknologi PETRONAS

2. Dept. of Petroleum Engineering, Curtin University

Publisher

Japan Petroleum Institute

Subject

Energy Engineering and Power Technology,Fuel Technology

Link

https://www.jstage.jst.go.jp/article/jpi/57/2/57_65/_pdf

Reference11 articles.

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2. 2) Bataee, M., Kamyab, M., Ashena, R., International Oil and Gas Conference and Exhibition in China, ISBN : 978-1-55563-295-3 (2010).

3. 3) Bilgesu, H. I., Tetrick, L. T., Mohaghegh, S., Ameri, S., SPE Eastern Regional Meeting, Lexington, Kentucky, USA, ISBN : 978-1-55563-398-1 (1997).

4. 4) Bourgoyne, A. T., Millheim, K. K., Chenevert, M. E., Young Jr., F. S., "Applied Drilling Engineering (SPE Textbook Series, Vol. 2)," Society of Petroleum Engineers, ISBN-13: 978-1555630010 (1986).

5. 5) Edalatkhah, S., Arabjamaloei, R., Hashemi, A., Journal of Petroleum Science and Technology, 28, (18), 1946 (2010).

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