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

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

Reference69 articles.

1. Comparisons between data clustering algorithms;Abu Abbas;The International Arab Journal of Information Technology,2008

2. Reservoir permeability prediction by neural networks combined with hybrid genetic algorithm and particle swarm optimization;Ahmadi;Geophysical Prospecting,2013

3. Modulation classification of QAM and PSK from their constellation using Genetic Algorithm and hierarchical clustering;Ahmadi,2008

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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