New Model for Pore Pressure Prediction While Drilling Using Artificial Neural Networks-Reference-Cited by-同舟云学术

New Model for Pore Pressure Prediction While Drilling Using Artificial Neural Networks

Published:2018-10-04 Issue:6 Volume:44 Page:6079-6088
ISSN:2193-567X
Container-title:Arabian Journal for Science and Engineering
language:en
Short-container-title:Arab J Sci Eng

Author:

Ahmed Abdulmalek,Elkatatny Salaheldin,Ali Abdulwahab,Mahmoud Mohamed,Abdulraheem Abdulazeez

Publisher

Springer Science and Business Media LLC

Subject

Multidisciplinary

Link

http://link.springer.com/content/pdf/10.1007/s13369-018-3574-7.pdf

Reference34 articles.

1. Hu, L.; Deng, J.; Zhu, H.; Lin, H.; Chen, Z.; Deng, F.; Yan, C.: A new pore pressure prediction method-back propagation artificial neural network. Res. Gate 18(18), 4093–4107 (2013)

2. Keshavarzi,; Jahanbakhshi, : Real-time prediction of pore pressure gradient through an artificial intelligence approach: a case study from one of middle east oil fields. Eur. J. Environ. Civ. Eng. 17(8), 675–686 (2013)

3. Mitchell, R.L.; Miska, S.Z.; Aadnoy, B.S.: Fundamentals of Drilling Engineering. Society of Petroleum Engineers, Richardson (2011)

4. Adams, N.J.: Drilling Engineering: A Complete Well Planning Approach. Pennwell, Tulsa (1985)

5. Wang, Z.; Wang, R.: Pore pressure prediction using geophysical methods in carbonate reservoirs: current status, challenges and way ahead. J. Nat. Gas Sci. Eng. 27, 986–993 (2015)

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