ArticleScientific reports2026
Integrated CNN-LSTM-XGBoost hybrid model predicts shale oil seismic attributes and global oil price trends.
Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
This study proposes a hybrid CNN-LSTM-XGBoost model that integrates shale oil seismic attributes with macroeconomic indicators to predict global oil prices. The model extracts spatial features from seismic volumes using 3D CNNs and captures temporal dependencies in economic data via LSTM, with fused features processed by XGBoost regression. It achieves an RMSE of 3.61 USD/barrel, R
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