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The study focuses on predicting the shear modulus of embedded pressurized salt layers to identify zones at risk of casing collapse in oil and gas wells, particularly in the Gachsaran formation of the Marun oil field in Iran. Utilizing hybrid machine-learning algorithms, the researchers achieved high prediction accuracy for shear modulus, which is crucial for assessing wellbore stability and preventing casing failure. The findings highlight the importance of detailed geomechanical models and indirect estimat
- Author
- Laurentiu Popescu
- Language
- EN