Reducing Uncertainties of Reservoir Fluid Due to Lack of Information for Optimum Production Activity Through Lean Sigma Process in Area X of Hevo Field

Area X of Hevo Field, operated by PT. XYZ, produces heavy oil and relies on steamflood as its enhanced oil recovery (EOR) process. Comprehensive subsurface data, particularly from open hole and surveillance logs, is essential to monitor steamflood progress. However, incomplete open hole log data in all wells has created uncertainty in identifying the current fluid conditions at the lower part of Haru Reservoir, hindering an optimal development and optimization plans. To overcome this issue, a Lean Sigma approach using the DMAIC framework was applied to improve data completeness. Rather than performing costly well deepening and re-logging activity, the solution by utilizing Facimage and Offset Well Modeling, a financial benefit of cost avoidance approximately US$1,440,000 is achieved. Additionally, the initiative increased the confidence level of the heavy oil practitioners and reduced the time required to assess remaining reservoir opportunities. This improvement process not only delivered technical and economic value but also demonstrated a replicable model for other areas of Hevo Field and beyond, with appropriate field-specific adjustments. The study highlights how data-driven process optimization can effectively reduce uncertainty and support better decision-making in heavy oil reservoir management.