Enhancing CO2 Foam Viscosity and Stability at Harsh Reservoir Conditions Through the Synergetic Interactions of Surfactant and Polymer

Abstract

The injection of foam into petroleum reservoirs has attracted special interest in the last decades. Some applications include; fracturing, stimulation, and gas mobility control during gas EOR processes. Utilizing foam in well stimulation is promising as it consumes less water than water-based fracturing fluid, is less damaging to the formation, and provides an effective proppant carrying capacity and transportation. This paper studies the synergic effects of surfactant-polymer system on the rheology and stability of foamed acid at high temperature. A modified high-pressure, high-temperature (HPHT) foam rheometer was utilized to measure the apparent viscosity of CO2-foamed acid at 1,000 psi and 120 ℃. Additionally, a novel HPHT foam analyzer was used to characterize the following parameters; foamability, foam stability, foam structure, bubble count, and size under the same conditions. HPHT foam analyzer allows detecting the height and structure of foam all together as a function of the foam decay. Surfactant screening showed that Armovis is thermally stable at high temperatures and therefore was used in this work. Results showed that the polymer enhanced the foamed fluid viscosity significantly. The apparent foam viscosity increased by 43 %, once 0.5 wt% of superpusher polymer was synergic with 1 % Armovis-surfactant. The results of the HPHT foam analyzer indicated that the Armovis/polymer system is thermally stable and capable of resisting high salinity. The foam half-life improved by 12 times when 0.5 wt% of the polymer was added. Also, the bubble growth rate reduced remarkably, this improvement was due to the adsorption of surfactant and polymer molecules at the gas/liquid interface, which resulted in the reduction of gas permeability through the liquid film. This study investigates the synergy of polymer (superpusher SAV 522) and foamer (Armovis) in enhancing CO2 foam viscosity and stability at high pressure, temperature, and salinity. Furthermore, the surfactant-polymer systems evaluated can be investigated and used as stimulation fluid systems at temperatures up to 120 °C.

Prediction of Foam Rheology Models Parameters Utilizing Machine Learning Tools

“…The performance of foam viscosity is strongly related to the bubble size, bubble density, and bubble shapes and its response to the deformation in the dynamic state . Additionally, the experimental studies showed that foam viscosity varied with many parameters, including foam quality, pressure, temperature, shear rate, salinity, and additives. − …”