Physics-Guided Machine Learning for Transient Reservoir Characterization: Synthetic Dataset, Models, Validation and Benchmark Results

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.