Machine Learning Based Reservoir Characterization and Numerical Modeling from Integrated Well Log and Core Data

Geoenergy Science and Engineering, Journal Year: 2024, Volume and Issue: 243, P. 213296 - 213296

Published: Sept. 7, 2024

Language: Английский

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Explainable machine-learning-based prediction of equivalent circulating density using surface-based drilling data

Scientific Reports, Journal Year: 2024, Volume and Issue: 14(1)

Published: Aug. 1, 2024

When drilling wells for energy explorations, it is important to regulate the formation pressures appropriately prevent kicks, which can lead unimaginable loss of lives and properties. This usually done by controlling equivalent circulating density (ECD), responds dynamic conditions that occur during drilling. The conventional approach determine ECD via mathematical modeling or downhole measurements. However, measurement tools be very expensive, models do not provide a high degree accuracy. Some previous authors have proposed using machine learning (ML) techniques improve accuracy predictions. In this work, we employed an extreme gradient-boosting (XGBoost) methodology predict values. model's was determined correlation coefficients (R2) root mean square errors (RMSE) as their performance metrics. results showed strong prediction capability with R2 RMSE 1.00 0.0005 training data 0.989 0.023 testing/blind set, respectively. developed model outperformed those obtained other popular techniques. Lastly, interpretation mud weight, weight on hook, standpipe pressure contributed most

Language: Английский

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Advanced Source Rock Characterization Integrating Pyrolysis, Petrophysical Logs, and Machine Learning in the Unconventional Cane Creek Reservoir, Utah

Geoenergy Science and Engineering, Journal Year: 2025, Volume and Issue: unknown, P. 213835 - 213835

Published: March 1, 2025

Language: Английский

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Extracting useful information from sparsely logged wellbores for improved rock typing of heterogeneous reservoir characterization using well-log attributes, feature influence and optimization

Petroleum Science, Journal Year: 2025, Volume and Issue: unknown

Published: March 1, 2025

Language: Английский

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Deep learning-based adaptive denoising method for prediction of crack opening displacement of rock from noisy strain data

International Journal of Rock Mechanics and Mining Sciences, Journal Year: 2025, Volume and Issue: 190, P. 106112 - 106112

Published: April 10, 2025

Language: Английский

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Entropy-Based Measure of Rock Sample Heterogeneity Derived from Micro-CT Images

Transport in Porous Media, Journal Year: 2025, Volume and Issue: 152(7)

Published: June 3, 2025

Language: Английский

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Gradation regression prediction for engineering based on multiscale rockfill instance segmentation

Advanced Engineering Informatics, Journal Year: 2024, Volume and Issue: 64, P. 103090 - 103090

Published: Dec. 27, 2024

Language: Английский

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