Local Equilibrium Mechanistic Simulation of CO2-Foam Flooding

Mechanistic modeling of the non-Newtonian CO2-foam flow in porous media is a challenging task that is computationally expensive due to abrupt gas mobility changes. The objective of this paper is to present a local equilibrium (LE) CO2-foam mechanistic model, which could alleviate some of the computational cost, and its implementation in the Matlab Reservoir Simulation Tool (MRST). Interweaving the LE-foam model into MRST enables users quick prototyping and testing of new ideas and/or mechanistic expressions. We use MRST, the open source tool available from SINTEF, to implement our LE-foam model. The model utilizes MRST automatic differentiation capability to compute the fluxes as well as the saturations of the aqueous and the gaseous phases at each Newton iteration. These computed variables and fluxes are then fed into the LE-foam model that estimates the bubble density (number of bubbles per unit volume of gas) in each grid block. Finally, the estimated bubble density at each grid block is used to readjust the gaseous phase mobility until convergence is achieved. Unlike the full-physics model, the LE-foam model does not add a population balance equation for the flowing bubbles. The developed LE-foam model, therefore, does not add much computational cost to solving a black oil system of equations as it uses the information from each Newton iteration to adjust the gas mobility. Our model is able to match experimental transient foam flooding results from the literature. The chosen flowing foam fraction (Xf) formula dictates to a large extent the behavior of the solution. An appropriate formula for Xf needs to be chosen such that our simulations are more predictive. The work described in this paper could help in prototyping various ideas about generation and coalescence of bubbles as well as any other correlations used in any population balance model. The chosen model can then be used to predict foam flow and estimate economic value of any foam pilot project.

Three dimensional modelling of aluminum foam through computed tomography scan technique

Purpose This study aims to generate different three-dimensional (3D) foam models using computer tomography (CT) scan and solid continuum techniques. The generated foam models were used to study deformation mechanism and the elastic-plastic behaviour with the existing experimental foam behaviour. Design/methodology/approach CT scan model was generated by combing 2D images of foam in MIMICS software. Afterwards, it was imported in ABAQUS/CAE software. However, solid continuum model was generated in ABAQUS/CAE software by using crushable foam properties. Then, the generated foam models were sets boundary conditions for a compression test. Findings CT scans capture the actual morphology of foam sample which may directly an image based finite element foam model. The sectional views of both the models were used to observe deformation mechanism on compression. The real compressive behaviour of foam was visualised in CT-Scan foam model. It was observed that CT-scan model was the more accurate modelling method than crushable foam model. Originality/value The internal structure of foam is very complex and difficult to analyse. Therefore, CT-scanning may be the accurate method for capturing the macro-level detailing of foam structure. A CT-scan foam model can be used for multiple times for mechanical analysis using a simulation software, which may reduce the manufacturing and the experimental cost and time.

Simulation of Foam Enhanced-Oil-Recovery Processes Using Operator-Based Linearization Approach

Summary Foam injection is a promising enhanced-oil-recovery (EOR) technology that significantly improves the sweep efficiency of gas injection. Simulation of foam/oil displacement in reservoirs is an expensive process for conventional simulation because of the strongly nonlinear physics, such as multiphase flow and transport with oil/foam interactions. In this work, an operator-based linearization (OBL) approach, combined with the representation of foam by an implicit-texture (IT) model with two flow regimes, is extended for the simulation of the foam EOR process. The OBL approach improves the efficiency of the highly nonlinear foam-simulation problem by transforming the discretized nonlinear conservation equations into a quasilinear form using state-dependent operators. The state-dependent operators are approximated by discrete representation on a uniform mesh in parameter space. The numerical-simulation results are validated by using three-phasefractional-flow theory for foam/oil flow. Starting with an initial guess depending on the fitting of steady-state experimental data with oil, the OBL foam model is regressed to experimental observations using a gradient-optimization technique. A series of numerical validation studies is performed to investigate the accuracy of the proposed approach. The numerical model shows good agreement with analytical solutions at different conditions and with different foam parameters. With finer grids, the resolution of the simulation is better, but at the cost of more expensive computations. The foam-quality scan is accurately fitted to steady-state experimental data, except in the low-quality regime. In this regime, the used IT foam model cannot capture the upward-tilting pressure gradient (or apparent viscosity) contours. 1D and 3D simulation results clearly demonstrate two stages of foam propagation from inlet to outlet, as seen in the computed-tomography (CT) coreflood experiments: weak foam displaces most of the oil, followed by a propagation of stronger foam at lower oil saturation. OBL is a direct method to reduce nonlinearity in complex physical problems, which can significantly improve computational performance. Taking its accuracy and efficiency into account, the data-drivenOBL-based approach could serve as a platform for efficient numerical upscaling to field-scaleapplications.

Amine Structure-Foam Behavior Relationship and Its Predictive Foam Model Used for Amine Selection for Design of Amine-based Carbon Dioxide (CO2) Capture Process

Background: The use of an amine solution to capture CO2 from flue gases is one of the methods applied commercially to clean up the exhaust gas stream of a power plant. One of the issues in this process is foaming which should be known in order to select a suitable amine for design. Objectives: In this work, all possible types of amines used for CO2 capture, namely, alkanolamines, sterically hindered alkanolamines, multi-alkylamines and cyclic amines, were investigated to elucidate their chemical structure–foaming relationships. Methods: Foam volume produced by each type of 2M amine solution with its equilibrium CO2 loading was measured at 40°C using 94 mL/min of N2 flow. Results: Amines with a higher number or a longer chain of the alkyl group exhibited higher foam volume because of alkyl group’s ability to decrease the surface tension while increasing the viscosity of the solution. An increase in the number of hydroxyl or amino groups in the amine led to the reduction of foam formation due to the increase in surface tension and a decrease in viscosity of the solution. The predictive foam models for non-cyclic and cyclic-amines developed based on the structural variations, surface tension and viscosity of 29 amines predicted the foam volume very well with average absolute deviations (AAD) of 12.7 and 0.001%, respectively. The model accurately predicted the foam volume of BDEA, which was not used in model development with 13.3 %AD. Conclusion: This foam model is, therefore, indispensable in selecting a suitable amine for an amine-based CO2 capture plant design and operation.