ML-Driven Reservoir Characterization Case Study in D Field PM Basin Malaysia

Summary This study heralds a new era in geoscience, showcasing the revolutionary impact of Artificial Intelligence (AI) and Machine Learning (ML) technologies in maximizing the utility of subsurface data for energy production. Focused on the D field offshore Malaysia, it unveils the critical role of AI/ML in unraveling the complexities of the seismic inverse problem, facilitating the accurate prediction of elastic and reservoir properties from seismic data. The research distinguishes itself through a sophisticated methodology that leverages AI/ML technologies for a comprehensive workflow encompassing data preparation, well scale quality control, and seismic scale property prediction. This approach not only fills existing data voids but also underscores the scalability and efficacy of AI/ML solutions in geophysical research. The findings emphasize the paramount importance of robust data quality control and the strategic application of pre-trained models to enhance predictive accuracy and operational efficiency. By pioneering the use of AI/ML in geoscience, this study marks a significant milestone in the evolution of energy resource exploration and management, setting a precedent for future technological advancements in the field.