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Conditioning generative adversarial networks on nonlinear data for subsurface flow model calibration and uncertainty quantification

Syamil Mohd Razak, Behnam Jafarpour

2021Computational Geosciences18 citationsDOI

Topics & Concepts

Nonlinear systemComputer scienceCalibrationCluster analysisFlow (mathematics)Uncertainty quantificationData miningRepresentation (politics)Artificial intelligenceAlgorithmMachine learningPattern recognition (psychology)MathematicsStatisticsLawQuantum mechanicsGeometryPolitical sciencePhysicsPoliticsSeismic Imaging and Inversion TechniquesReservoir Engineering and Simulation MethodsDrilling and Well Engineering
Conditioning generative adversarial networks on nonlinear data for subsurface flow model calibration and uncertainty quantification | Litcius