Perpustakaan Digital ITB

It has been known that infill drilling can increase oil and gas recovery by accelerating oil and gas production because most reservoirs in the real world are not homogeneous. With the increase in energy demand and the rise in oil and natural gas prices, more and more oil fields around the world are undergoing infill drilling. For most conventional oil reservoirs, numerical simulation can successfully predict and extract valuable information about the optimal location of a new well. However, due to the particularity of the reservoir, the numerical simulation results in some cases were not successful. Machine learning (ML) has received attention recently because it does not require a specific physical model, but if there is enough data, it can provide good estimates. Due to its feature, ML has strong applicability in Field X. The method used in this study allows operators to identify the best location for infill drilling to optimize well placement and additionally helps operators benefit from their previously gathered knowledge in a cost-effective way.