Big Data Processing Application on the Identification Method of the Dominant Channel in Polymer Flooding

Polymer flooding is a critical enhanced oil recovery technique; however, the development of polymer channeling along dominant channels during its later stages can adversely affect the process by increasing comprehensive water cut and dispersing remaining oil, thereby diminishing development benefits. This study aims to address this challenge by investigating the identification methods and distribution patterns of dominant channels in polymer flooding to inform and optimize the development strategy. Through a series of experiments, we analyzed how factors such as permeability, heterogeneity, reservoir thickness, and mineral composition influence the formation of dominant channels. We developed an identification method for dominant channels post-polymer flooding using a combination of reservoir engineering and mathematical analysis techniques. Our results highlight the significant role of rock and mineral composition, injection rate, and injection pressure in the formation of dominant channels. By integrating formation physical properties and production data from oil and water wells with the grey correlation method, we effectively identified dominant channels. This identification is crucial for guiding the development and adjustment of polymer flooding, enhancing oil recovery efficiency, and maximizing reservoir performance.