oa Application of Advanced Artificial Intelligence and Machine Learning System for Subsurface

The study proposes a new approach to interpret overburden faults in CCS storage studies using AIML. The approach aims to process large amounts of data with efficiency and precision than traditional methods. The study focuses on identifying potential risk zones for CO2 storage in depleted oil/gas reservoirs. The AIML system enhances the precision of fault location and identifies new faults, which could aid in future CCS storage program planning and risk mitigation studies.