Background & Objective

Key Pain Points:

• Aspire to have more definitive approach in feed zone identification and well targeting
• Heavily rely on geoscientist subjectivity (prone to human error)
• Time consuming process

Solution Design:

• Develop feed zone identification workflow leveraging machine learning models to process subsurface data and producing more accurate and efficient analysis

Potential Benefit

• Derisking exploration stage by implementing quantitative approach in identifying feed zone.
• Compiling multiple subsurface data into model enhancing time to decision in well targeting process.
• Provide more detailed yet accurate target to aid drilling team in improving efficiency in drilling execution.

Project Managers

• Business : Inusa Pamusyawara, M Ikhwan Aziz
• Digital : Bayu Alfajri