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August 16, 2025

Application of Machine Learning for Permeability Prediction from Well Logs in Sandstone Reservoir: A Comparative Study of Model Performance

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Random Forest Regression achieved a high prediction accuracy of R2 0.9893, confirming its effectiveness.
Evaluation based on key metrics such as R2 and Mean Squared Error (MSE) highlighted performance differences.
Two predictive scenarios demonstrated trade-off between data complexity and prediction accuracy, impacting results.
Scenarios utilized comprehensive and limited log data, showcasing cost-efficiency but reduced accuracy in the latter.

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Comparative analysis reveals Random Forest Regression outperforms other algorithms for permeability prediction in sandstone reservoirs.

Chinyereugo et al. (2025) studied this question.

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