Stratigraphy and Structural Prediction through Advanced Machine Learning: Case Studies for Hydrocarbon Exploration and Carbon Storage

Seismic stratigraphy mapping, a crucial technique in subsurface exploration, is enhanced by the integration of machine learning methodologies to identify and assess potential reservoirs for both hydrocarbon exploration and carbon capture, utilization and storage (CCUS) applications. This study explores the integration between traditional seismic stratigraphy mapping and machine learning algorithms, demonstrating its efficiency in mapping and derisking the subsurface structures, and optimizing decision-making processes whether for reservoir exploration, development or management.