Potential of Machine and Deep Learning for Enhanced first-break Picking and Accurate Reservoir Characterization

Summary This study explored the potential of commonly used machine learning (ML) tools to enhance first-break picking, predict reservoir properties, and achieve accurate reservoir characterization. The findings highlight the versatility and promise of ML-driven methods, which can improve both the speed and accuracy of data processing and interpretation in geophysical contexts.