Self organizing map neural networks approach for lithologic interpretation of nuclear and electrical well logs in basaltic environment, Southern Syria-Reference-Cited by-同舟云学术

Self organizing map neural networks approach for lithologic interpretation of nuclear and electrical well logs in basaltic environment, Southern Syria

Published:2018-07 Issue: Volume:137 Page:50-55
ISSN:0969-8043
Container-title:Applied Radiation and Isotopes
language:en
Short-container-title:Applied Radiation and Isotopes

Author:

Asfahani J.,Ahmad Z.,Ghani B. Abdul

Publisher

Elsevier BV

Subject

Radiation

Reference33 articles.

1. Aliouane Leila, Sid-Ali, Ouadfeul, Abdessalem, Rabhi, Fouzi, Rouina, Zahia, Benaissa, Amar, Boudella, 2013. Automatic lithofacies segmentations from well-logs data. A comparative study between the self-organizing map (SOM) and Walsh transform. EGU General Assembly 2013, held 7–12 April 2013 in Vienna, Austria, id. EGU2013-13569.

2. Basalt characterization by means of nuclear and electrical well logging techniques. Case study from Southern Syria;Asfahani;Appl. Radiat. Isot.,2011

3. Automated interpretation of nuclear and electrical well loggings for basalt characterization. Case study from Southern Syria;Asfahani;Appl. Radiat. Isot.,2012

4. Statistical factor analysis technique to interpret nuclear and electrical well logging measurements for basalt characterization. Case study from Southern Syria;Asfahani;Appl. Radiat. Isot.,2014

5. Fractal theory modeling for interpreting nuclear and electrical well logging data and establishing lithological cross section in basaltic environment (case study from Southern Syria);Asfahani;Appl. Radiat. Isot.,2017

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