Enhanced velocity-based pore-pressure prediction using lithofacies clustering: a case study from a reservoir with complex lithology in Dezful Embayment, SW Iran-Reference-Cited by-同舟云学术

Enhanced velocity-based pore-pressure prediction using lithofacies clustering: a case study from a reservoir with complex lithology in Dezful Embayment, SW Iran

Published:2019-01-31 Issue:1 Volume:16 Page:146-158
ISSN:1742-2132
Container-title:Journal of Geophysics and Engineering
language:en
Short-container-title:

Author:

ArabAmeri Farid¹,Soleymani Hamidreza²,Tokhmechi Behzad³

Affiliation:

1. Institute of Petroleum Engineering, Faculty of Engineering, Intersection of North Kargar St. & Jalal-Al-Ahmad Hwy., Tehran 11365-4563, Iran

2. The Graduate Center, City University of New York, 365 5th Ave, New York, NY 10016

3. Department of Mining, Petroleum and Geophysics, Shahrood University of Technology, Shahrood 3619995161, Iran

Publisher

Oxford University Press (OUP)

Subject

Management, Monitoring, Policy and Law,Industrial and Manufacturing Engineering,Geology,Geophysics

Link

http://academic.oup.com/jge/article-pdf/16/1/146/28296567/gxy013.pdf

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4. An integrated application of neural network and Markov chain techniques to prediction of lithofacies from well logs;Bohling;Kansas Geological Survey Open File Report 2003-50,2003

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