Determining CO₂ front in CO₂-EOR using a well-testing method

Abstract

CO₂ flooding is a widely recognized method for enhanced oil recovery (EOR). This study aims to develop an accurate prediction method for determining the location and migration pathway of CO₂ front, which plays an essential role in designing effective CO₂ injection schemes and optimizing production strategies. Given the challenges of directly monitoring CO₂ front movement in subsurface reservoirs, numerical well testing serves as an effective tool for indirectly inferring the location and migration characteristics of the CO₂ front. This study established a numerical well-testing model based on a compositional framework to characterize interactions among multiple components during CO₂ flooding. The methodology used in this model involves generating well-testing curves of CO₂ flooding and then determining their flow stages based on CO₂ distribution within reservoirs. Accordingly, a new well-testing analysis approach was proposed to determine the CO₂ zone front and mixing zone front. This approach was applied to a pilot study of a practical oilfield, where it effectively predicted the positions of both fronts. The findings of this study reveal that the CO₂ zone front and the mixing zone front correspond to the beginning of the first horizontal segment and the endpoint of the upward segment in the pressure derivative curve, respectively. This study introduces a cost-effective and time-efficient method for CO₂ front monitoring, addressing the challenges of high costs and prolonged durations typically associated with CO₂-EOR operations.