Machine Learning Application to CO2 Foam Rheology

Conventional foam modelling techniques require tuning of too many parameters and long computational time in order to provide accurate predictions. Therefore, there is a need for alternative methodologies for the efficient and reliable prediction of the foams’ performance. Foams are susceptible to various operational conditions and reservoir parameters. This research aims to apply machine learning (ML) algorithms to experimental data in order to correlate important affecting parameters to foam rheology. In this way, optimum operational conditions for CO2 foam enhanced oil recovery (EOR) can be determined. In order to achieve that, five different ML algorithms were applied to experimental rheology data from various experimental studies. It was concluded that the Gradient Boosting (GB) algorithm could successfully fit the training data and give the most accurate predictions for unknown cases.

Foaming and rheological properties of aqueous solutions: an interfacial study

Although aqueous foam is composed of simple fluids, air and water, it shows a complex rheological behavior. It exhibits solid-like behavior at low shear and fluid-like behavior at high shear rate. Therefore, understanding such behavior is important for many industrial applications in foods, pharmaceuticals, and cosmetics. Additionally, air–water interface of bubble surface plays an important role in the stabilizing mechanism of foams. Therefore, the rheological properties associated with the aqueous foam highly depend on its interfacial properties. In this review, a systematic study of aqueous foam are presented primarily from rheology point of view. Firstly, foaming agents, surfactants and particles are described; then foam structure was explained, followed by change in structure under applied shear. Finally, foam rheology was linked to interfacial rheology for the interface containing particles whose surface properties were altered by surfactants.

The Effect of Salt on Stability of Aqueous Foams

The properties of foams are often affected by environmental variables such as salt contamination. The objective of this study is to investigate the impact of salt on the drainage behavior of aqueous foams. To accomplish this objective, drainage experiments were conducted on aqueous foams. Test variables were foam quality (40–65%), and salt content (0% to 18%), and type. To investigate drainage, the foam was generated in a flow loop and trapped in a vertical test section. Then, the pressure profile in the foam column was measured using ten pressure sensors. Foam drainage is determined as a function of time using measured pressure profiles. The results show that the drainage of NaCl-containing foams decreased with foam quality, whereas the CaCl2-containing foams did not exhibit a clear trend with foam quality. The effect of salt content on foam rheology was minimal.

Probing Methane Foam Transport in Heterogeneous Porous Media: An Experimental and Numerical Case Study of Permeability-Dependent Rheology and Fluid Diversion at Field Scale

Summary This paper advances the understanding of foam transport in heterogeneous porous media for enhanced oil recovery (EOR). Specifically, we investigate the dependence of methane foam rheology on the rock permeability at the laboratory scale and then extend the observations to the field scale with foam modeling techniques and reservoir simulation tools. The oil recovery efficiency of conventional gasflooding, waterflooding, and water-alternating-gas (WAG) processes can be limited by constraints such as bypassing effects (including both viscous fingering and channeling mechanisms) and gravity override. The problem can be more severe if the reservoir is highly fractured or heterogeneously layered in the direction of flow. Foam offers the promise to address the three issues simultaneously by better controlling the mobility of injected fluids. However, limited literature data of foam-flooding experiments were reported using actual reservoir cores at harsh conditions. In this paper, a series of methane (CH4) foam-flooding experiments were conducted in three different actual cores from a proprietary reservoir at an elevated temperature. It is found that foam rheology is significantly correlated with the rock permeability. To quantify the mobility control offered by foam, we calculated the apparent viscosity on the basis of the measured pressure drop at steady state. Interestingly, the apparent viscosity was found to be selectively higher in the high-permeability cores compared with that in the low-permeability zones. We parameterized our system using a texture-implicit-local-equilibrium model (STARS™ simulator, Computer Modelling Group, Calgary, Alberta, Canada) to illustrate the dependence of foam parameters on rock permeability. In addition, we created a two-layered model reservoir using an in-house simulator called modular reservoir simulator (MoReS; Shell Research, Rijswijk, The Netherlands) to elucidate the role of different driving forces for fluid diversion at the field level. We took into consideration the combined effect of gravitational, viscous force, and capillary forces in our simulation. We show that the gravitational forces prevent the gas from sweeping the lower part of the reservoir. However, the poor sweep can be ameliorated by intermittent surfactant injection to generate foam. In addition, the capillary force which hinders the gas (nonwetting phase) from entering the low-permeability region can be effectively leveraged to redistribute the fluids in the porous media, resulting in better sweep efficiency. We conclude that foam if properly designed can effectively improve the conformance of the WAG EOR in the presence of reservoir heterogeneity.

Effect of surfactant redistribution on the flow and stability of foam films

The viscous froth model for two-dimensional (2D) dissipative foam rheology is combined with Marangoni-driven surfactant redistribution on a foam film. The model is used to study the flow of a 2D foam system consisting of one bubble partially filling a constricted channel and a single spanning film connecting it to the opposite channel wall. Gradients of surface tension arising from film deformation induce tangential flow that redistributes surfactant along the film. This redistribution, and the consequent changes in film tension, inhibit the structure from undergoing a foam-destroying topological change in which the spanning film leaves the bubble behind; foam stability is thereby increased. The system’s behaviour is categorized by a Gibbs–Marangoni parameter, representing the ratio between the rate of motion in tangential and normal directions. Larger values of the Gibbs–Marangoni parameter induce greater variation in surface tension, increase the rate of surfactant redistribution and reduce the likelihood of topological changes. An intermediate regime is, however, identified in which the Gibbs–Marangoni parameter is large enough to create a significant gradient of surface tension but is not great enough to smooth out the flow-induced redistribution of surfactant entirely, resulting in non-monotonic variation in the bubble height, and hence in foam stability.