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Development and Validation of a New Model for In Situ Foam Generation Using Foamer Droplets Injection


Foam generation and transport in porous media are a proven method to improve the sweep efficiency of a flooding fluid in enhanced oil recovery process and increase the effectiveness of a treatment fluid in well intervention procedures. Foam in the porous media is often generated using surfactant alternating gas or co-injection. Although these operations result in good incremental production, the profit losses could be high due to surfactant retention and lack of water injection facilities in the target fields. One way of reducing foam generation operations expenses is by injecting the surfactant solution disperse throughout the gas phase in a process called “disperse foam.” Core-flooding experimental results have shown that disperse foam techniques reduce the surfactant retention and increase cumulative oil production. This increase means that not only the foam is being generated but also it is blocking the high mobility channels and enhancing the sweep efficiency. Additionally, the operational implementation in field operations is very simple and reduces significantly operational costs of the process. Because few laboratory core-flooding tests and field pilots have been executed using the disperse foam technique, there is a high level of uncertainty associated with the method. Besides, the models reported in the literature do not account for all the associated phenomena, including the surfactant droplets transfer between the gas and liquid phases, and the lamellae stability at low water saturation. For this reason, the development of a mechanistic disperse foam model is key to understand the phenomena associated with “disperse foam” operations. In this work, we use a previous foam mechanistic model to develop a disperse foam model that includes the physicochemical mechanisms of the foaming process a core scale. The model accounts for the foamer mass transference between the gas and liquid phases in a non-equilibrium state with a particle interception model, also accounts for the reversible and irreversible surfactant adsorption on the rock surface in dynamic conditions with a first-order kinetic model, and includes foam generation, coalescence and, transport using a population balance mechanistic model.

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a, b, c :

Velocity exponents in Eqs. (14)–(18)

b :

Inverse of the formation volume factor (Shrinkage)

C s :

Foamer concentration

C sg :

Foamer droplets dispersion ratio

J :

Diffusion flux

K :

Kinetic mass transfer term

K − 1, K1 :

Generation and coalescence parameters


Mass transfer

N :

Adsorbed mass fraction

n :

Foam texture, bubble density

Pc :

Capillary pressure

Pct :

Threshold capillary pressure

q :


rg, rc :

Generation and coalescence foams kinetics

Rs, Rv :

Dissolved gas in the oleic phase, volatilized gas–oil ratio

S :

Phase saturation

t :


u :

Darcy velocity

v :

Interstitial velocity

X :

Component concentration, Foam quality

α :

Foam model parameters

β :

Foam model parameters

ρ :

Phase density

ϕ :



Reference condition


Flowing foam


Gas phase


Flow direction








Surfactant (foamer)


Standard conditions


Trapped foam


Water phase


Pc ∞



* :

Limit value














Phase number


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Authors thank Equion, COLCIENCIAS and the Agencia Nacional de Hidorcarburos for financial support under Contract No. 273-2017. Authors also thank the Universidad Nacional de Colombia for logistic and financial support.

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Correspondence to Juan D. Valencia.

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Valencia, J.D., Ocampo, A. & Mejía, J.M. Development and Validation of a New Model for In Situ Foam Generation Using Foamer Droplets Injection. Transp Porous Med 131, 251–268 (2020).

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  • Foam EOR
  • Foam modeling
  • Disperse foamer
  • Foam generation
  • Coalescence