An enhanced approach to predict permeability in reservoir sandstones using artificial neural networks (ANN)-Reference-Cited by-同舟云学术

An enhanced approach to predict permeability in reservoir sandstones using artificial neural networks (ANN)

Published:2017-04 Issue:7 Volume:10 Page:
ISSN:1866-7511
Container-title:Arabian Journal of Geosciences
language:en
Short-container-title:Arab J Geosci

Author:

Ben-Awuah Joel,Padmanabhan Eswaran

Publisher

Springer Science and Business Media LLC

Subject

General Earth and Planetary Sciences,General Environmental Science

Link

http://link.springer.com/content/pdf/10.1007/s12517-017-2955-7.pdf

Reference52 articles.

1. Ben-Awuah J, Padmanabhan E, Sokkalingam J (2017) Geochemistry of miocene sedimentary rocks from offshore West Baram Delta, Sarawak Basin, Malaysia, South China Sea: implications for weathering, provenance, tectonic setting, paleoclimate and paleoenvironment of depostion. Geosc J

2. Ben-Awuah J, Padmanabhan E, Andriamihaja S, Amponsah PO, Ibrahim Y (2016) Petrophysical and reservoir characteristics of sedimentary rocks from offshore West Baram Delta, Sarawak Basin, Malaysia. Pet and Coal 56(4):414–429

3. Ben-Awuah J, Padmanabhan E (2015) Effect of bioturbation on reservoir rock quality of sandstones: a case study from the Baram Delta, offshore Sarawak, Malaysia. J Pet Explor Dev 42(2):1–9

4. Ben-Awuah J, Padmanabhan E (2014) Impact of bioturbation on reservoir quality: a case study of biogenically reduced permeabilities of reservoir sandstones of the Baram Delta, Sarawak, Malaysia. J Appl Sci 14(23):3312–3317

5. Boggs S Jr (2009) Petrology of sedimentary rocks, 2nd edn. Cambridge University Press, London

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