Physics-Guided Machine Learning for Transient Reservoir Characterization: Synthetic Dataset, Models, Validation and Benchmark Results
Domaine:
environment and energyType de record:
dataset
Créateur:
Hez T.
Éditeur:
Men
Hôte:
This dataset supports the study “Physics-Guided Machine Learning for Transient Reservoir Characterization: Accuracy, Out-of-Distribution Generalization, and Noise Robustness in Niger Delta Sandstones.” It contains synthetic pressure-transient reservoir data generated across representative sandstone reservoir and fluid-property ranges, together with variables used for physics-guided machine-learning model development, training, validation, testing, out-of-distribution generalization assessment, and noise-robustness evaluation. The dataset includes reservoir and fluid parameters, transient pressure-response features, and corresponding target reservoir properties. It is provided to support reproducibility, independent verification, and further research on machine-learning-assisted transient reservoir characterization.
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