Application of neural network modelling for classifying hydrocarbon bearing zone, water bearing zone and shale with estimation of petrophysical parameters in Cauvery basin, India
Author:
Publisher
Springer Science and Business Media LLC
Subject
General Earth and Planetary Sciences
Link
http://link.springer.com/content/pdf/10.1007/s12040-019-1285-4.pdf
Reference44 articles.
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3. Aguilera R and Aguilera M S 2002 The integration of capillary pressures and Pickett plots for determination of flow units and reservoir containers; SPE Reserv. Eval. Eng. 5(6) 465–471.
4. Anifowose F, Adeniye S, Abdulraheem A and Al-Shuhail A 2016 Integrating seismic and log data for improved petroleum reservoir properties estimation using non-linear feature-selection based hybrid computational intelligence models; J. Pet. Sci. Eng. 145 230–237.
5. Archie G E 1942 The electrical resistivity logs as an aid in determining some reservoir characteristics; Trans. AIME 146(01) 54–67.
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