neural networks
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The authors present a new data-driven approach to estimate the injection rate in all noninstrumented wells in a large waterflooding operation accurately. -
This paper will describe how one integrates a comprehensive methodology of data-mining techniques and artificial neural networks (ANNs) in reservoir-petrophysical-properties prediction and regeneration.
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The optimization algorithm used in this work is a hybrid genetic algorithm (HGA), which is the combination of GAs with artificial neural networks (ANNs) and evolution strategies (ESs).
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With more wells to check than tools and time to do so, a methodology to predict wells with the highest risk of corrosion was developed.
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