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This paper presents a refined model for predicting the brittleness index (BI) of rocks by integrating mineral-based brittleness index (MBI) with geomechanical data. Utilizing a dataset of 87 data points from various rock types, the model achieved high predictive accuracy with an average R2 of 95%. The study highlights the importance of considering both mineralogical composition and mechanical behavior for improved BI assessment in geoenergy applications.

Author

Paulo Soares

Language

EN