Decision-Driven Geosteering Under Uncertainty: A Unified Framework for Sequential Decision Optimization
This work presents an uncertainty-aware geosteering framework that combines particle filtering for subsurface interpretation with value-based reinforcement learning for sequential decisions. It moves beyond simple trajectory correction by using a belief state to inform control actions, leading to smoother and more robust drilling paths.