Multiscale experimental–numerical study of alkali-free SP flooding with sensitivity analysis in a venezuelan extra-heavy oil reservoir

The recovery of extra-heavy oil remains challenging due to extremely high viscosity, unfavorable mobility ratios, and poor sweep efficiency during conventional waterflooding. This study investigates the performance of an alkali-free surfactant–polymer (SP) flooding process as a chemical enhanced oil recovery (CEOR) method for reservoirs in the Orinoco Oil Belt (OOB). The main objective is to evaluate the effectiveness of simultaneous SP injection in improving oil displacement and recovery in extra-heavy oil systems. A series of laboratory core flooding experiments were conducted using Bentheimer sandstone and reservoir rock samples representative of the OOB under reservoir-representative conditions (9°API crude oil, viscosity 4500 cP, temperature 50°C). Different injection strategies were tested, including water flooding, sequential surfactant–polymer (S + P) flooding, and simultaneous SP flooding. Since the number of laboratory experiments is inherently limited by experimental resources such as core material, testing time, and operational constraints, numerical tests were used as a complementary tool to reproduce experimental observations and explore additional injection scenarios beyond those tested experimentally. The experimental results demonstrate that simultaneous SP flooding significantly improves recovery performance, achieving oil recoveries of up to 94%, compared with 21% for water flooding and 67% for sequential S + P injection. The numerical results indicate that the synergistic effects of surfactant-induced interfacial tension (IFT) reduction and polymer-driven mobility control promote a more stable displacement front and improved sweep efficiency. Field-scale numerical tests based on calibrated core-scale models further suggest that optimized SP flooding could provide approximately 12.6% incremental recovery under representative reservoir conditions. In addition, sensitivity analysis highlights the critical role of key parameters such as polymer concentration, injection rate, and resistance factor in controlling displacement efficiency and recovery, providing a basis for optimizing injection design and quantifying uncertainty. The novelty of this study lies in the integrated experimental–modeling workflow, where laboratory core flooding experiments form the primary basis for evaluating alkali-free SP flooding performance, while numerical modeling serves to extend and interpret experimental findings. By incorporating sensitivity analysis into this workflow, the study further enables systematic evaluation of parameter uncertainty and supports robust optimization of CEOR strategies prior to field implementation in extra-heavy oil reservoirs.