Surfactant flooding is a promising enhanced oil recovery (EOR) method for mobilizing residual oil after primary recovery and conventional waterflooding. Its performance is highly sensitive to reservoir chemistry, particularly in associated gas reservoirs where CO₂, H₂S, and CH₄ may alter aqueous-phase behavior, surfactant stability, adsorption, and chemical transport. This study evaluates salinity-controlled surfactant flooding performance in a synthetic three-dimensional associated gas–oil reservoir using a simulation-guided diagnostic workflow. The model examines surfactant transport, adsorption, oil rate response, and block-level oil saturation across ultralow-, low-, and moderate-to-high-salinity ranges. Performance was evaluated using field oil production rate (FOPR), cumulative field oil production (FOPT), block oil saturation (BOSAT), block total surfactant concentration (BTCNFSUR), and block total adsorbed surfactant (BTADSUR). Because the simulation does not independently vary gas composition, the results should be interpreted as salinity effects under an associated gas reservoir setting rather than as isolated gas composition effects. The strongest sustained production response occurred in the ultralow- to low-salinity cases, especially 400 ppm and 1000 ppm, where surfactant propagation was more stable and late-time FOPR recovery was stronger. The 15,000 ppm case was the best performer only within the moderate-salinity group and should not be interpreted as the global optimum across all salinity cases. Above 25,000 ppm, FOPR declined to approximately 50–60 Sm³/day, while BOSAT remained high in poorly swept layers, indicating channelized flow, localized chemical contact, and greater retention risk. The results show that salinity compatibility is a dominant control on surfactant flood efficiency and that salinity screening is necessary before applying surfactant flooding in gas-rich reservoirs.

Bullheading is a well control technique where heavy kill fluid is pumped down a wellbore to force a gas influx back into the formation, but poor estimation of the required injection pressure has historically led to failed interventions, most notably during the Macondo/Deepwater Horizon blowout. This study numerically simulates bullheading operations in a deepwater reservoir setting using the Petrel E&P platform, focusing on bottomhole pressure (BHP) behavior and the injection pressure needed to displace an influx. A vertical-well grid model representative of deepwater turbidite reservoirs was built, and a sensitivity analysis was performed across five reservoir/operational parameters, namely horizontal permeability, vertical permeability, porosity, net-to-gross (NTG) ratio, rock compressibility, and injection rate, using thirty-nine simulation cases. Horizontal permeability and NTG ratio were found to have the greatest influence on injection pressure, followed by porosity and rock compressibility, while vertical permeability showed no measurable effect. Injection rate, the only field-controllable variable, showed a strong direct relationship with both BHP and injection pressure. A subsequent uncertainty and cluster analysis using horizontal permeability and NTG ratio identified representative low, mid, and high pressure scenarios. These results indicate that reservoir characterization, particularly of horizontal permeability and NTG is critical to accurately predicting injection pressure for safe bullheading design in deepwater wells, and that simulation outputs should be validated against downhole pressure gauge data to reduce estimation uncertainty.