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Geosciences Journal

, Volume 20, Issue 2, pp 221–228 | Cite as

Estimating shear wave velocities in oil fields: a neural network approach

  • Sagar Singh
  • Ali Ismet Kanli
Article

Abstract

In this study, we applied the back-propagation Artificial Neural Network (ANN) technique to test the shear-velocity for the two wells from an oil field in southeastern region of Turkey estimated from an empirical relationship. The input to the neural network includes neutron porosity, density, true resistivity, P-wave velocity and gamma-ray logs which are known to affect the shearwave velocity. The correlation between the shear-wave velocity from the empirical relationship and that from the neural network is close to one in both the training and testing stages. Thus, the ANN technique can be used to predict shear-wave velocity from other well log data.

Key words

ANN back-propagation well-log data shear wave velocity oil field 

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Copyright information

© The Association of Korean Geoscience Societies and Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  1. 1.Department of Earth SciencesIndian Institute of Technology RoorkeeRoorkeeIndia
  2. 2.Department of Geophysical Engineering, Faculty of EngineeringIstanbul University, Avcilar CampusIstanbulTurkey

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