Towards in-depth profile control using dispersed particle gels (DPGs)

In-depth profile control is an important technique used to improve oil recovery from the water-flooded reservoirs. But how to achieve in-depth profile control is a challenging task. This work investigates the feasibility of achieving in-depth profile control by striking a good balance between the plugging efficiency of dispersed particle gel (DPG) and the migration depths of DPGs in a given porous media. First, a polyacrylamide (PAAm) hydrogel is prepared, and its rheological properties are measured. Then, we shear the PAAm hydrogel with different durations to generate DPG suspensions with different particle size distributions. Finally, three DPG slugs with varied particle size distributions are sequentially injected into the sandpacks. The injection sequences and the corresponding particle size distributions of different DPG slugs are optimized based on the plugging efficiency and the migration depths of DPGs in a sandpack. Among the injection schemes tested, the optimal scheme is the one that comprises three DPG slugs with matching coefficients of 0.72, 0.78, and 0.46, respectively. These optimal DPG slugs can migrate into the deeper parts of the sandpack as well as yield a high plugging efficiency by forming bridging-plugging in the porous media. This study provides a new approach of achieving in-depth profile control by optimizing the injection sequence and particle size distribution of DPGs.

Automated summary

This study investigates the feasibility of achieving in-depth profile control by striking a balance between the plugging efficiency and migration depths of dispersed particle gels (DPGs) in a given porous media. Different DPG suspensions with varying particle size distributions are sequentially injected into sandpacks. The optimal scheme comprises three DPG slugs with matching coefficients of 0.72, 0.78, and 0.46, respectively, which can migrate into deeper parts of the sandpacks and yield a high plugging efficiency. This study provides a new approach of achieving in-depth profile control by optimizing the injection sequence and particle size distribution of DPGs.