Optimization of CO₂-Assisted Gravity Drainage Operational Parameters: Insights from a 2D Hele-Shaw Model

Abstract

This study investigates the optimization of key operational parameters in the CO₂-Assisted Gravity Drainage (CO₂-AGD) process using a two-dimensional (2D) Hele-Shaw model packed with silica sand to mimic a bottom-water-drive oil reservoir. The experimental work varied two primary parameters—gas injection pressure and oil production rate—to assess their influence on oil recovery and gas breakthrough timing. A total of six experiments were conducted under constant-pressure conditions, and the results were analyzed using Response Surface Methodology (RSM) to develop predictive regression models. To navigate the trade-off between maximizing oil recovery and delaying gas breakthrough, a desirability function-based optimization was applied. The optimal condition was identified at an injection pressure of 1.3 psig and a fully opened production valve, yielding a predicted recovery of 79.3% and a breakthrough time of 157.7 minutes. These findings underscore the role of data-driven optimization in improving CO₂-AGD performance and guiding field-scale operational decisions in enhanced oil recovery (EOR).