Neural networks in petroleum engineering: a case study
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Updated: Oct 5, 2026
11:20
In Situ Visualization of the Phase Behavior of Oil Samples Under Refinery Process Conditions
Published on: February 21, 2017
Abstract:
A multilayer neural network has been used for deciding which oil reservoir layer has to be perforated. Many network architectures were tested until we found those with the best generalization capability. The network performs better than human experts and its achievements are higher than the historical average in the test area. As in other applications of neural networks, the learning capability improves with more hidden neurons but the generalization does not.
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