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Keywords: machine learning
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Proceedings Papers
Publisher: ISAVFT
Paper presented at the ISAVFT 12th North American Conference on Multiphase Production Technology, May 22–24, 2024
Paper Number: ISAVFT-2024-165
... research aimed at further enhancing modelling capabilities to meet the demands of the next generation of challenges on the horizon. artificial intelligence flow in porous media production monitoring machine learning production logging production control isavft ltd flow model liquid holdup...
Proceedings Papers
Publisher: ISAVFT
Paper presented at the ISAVFT 12th North American Conference on Multiphase Production Technology, May 22–24, 2024
Paper Number: ISAVFT-2024-213
... deterministic predictions. In contrast, machine learning can continuously learn from data and provide stochastic results, complementing existing mechanistic models. In this study, we developed a stochastic deep ensemble neural network applied to gas-liquid pipe flow and tested it against lab data to predict...
Proceedings Papers
Publisher: ISAVFT
Paper presented at the ISAVFT 12th North American Conference on Multiphase Production Technology, May 22–24, 2024
Paper Number: ISAVFT-2024-307
... from images of this flow. This tool consists of in-house Python routines based on a convolutional neural network (CNN) within the scope of machine learning. To validate the tool, we conducted visualization experiments in a transparent tube mounted on an oscillatory apparatus. The CNN successfully...
Proceedings Papers
Publisher: ISAVFT
Paper presented at the ISAVFT 12th North American Conference on Multiphase Production Technology, May 22–24, 2024
Paper Number: ISAVFT-2024-339
..., and leveraging machine learning to predict void fraction and flow pattern. A comprehensive dataset is compiled including 1500 points from 11 studies. The models are developed and evaluated for two cases, one using dimensional features, and then using dimensionless parameters. LGBM and CatBoost models perform...
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