Challenges in adjoint-based optimization of a foam EOR process

Zanganeh, Maryam Namdar; Kraaijevanger, J. F. B. M.; Buurman, H. W.; Rossen, W.R.

doi:10.1007/s10596-014-9412-4

Cited by 16 publications

(9 citation statements)

References 23 publications

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“…Accurate modeling of near-wellbore mobility changes requires very fine grid refinement, as discussed previously (see also Leeftink et al 2015;Al Ayesh et al 2017). Similar resolution is needed to represent shock fronts (Zanganeh et al 2014). However, grid refinement will not be sufficient if the foam model itself does not adequately represent foam mobility.…”

Section: Discussionmentioning

confidence: 99%

Modeling of Liquid Injectivity in Surfactant-Alternating-Gas Foam Enhanced Oil Recovery

et al. 2019

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Surfactant alternating gas (SAG) is often the injection strategy used for injecting foam into a reservoir. However, liquid injectivity can be very poor in SAG, and fracturing of the well can occur. Coreflood studies of liquid injectivity directly following foam injection have been reported. We conducted a series of coreflood experiments to study liquid injectivity under conditions more like those near an injection well in a SAG process in the field (i.e., after a period of gas injection). Our previous experimental results suggest that the injectivity in a SAG process is determined by propagation of several banks. However, there is no consistent approach to modeling liquid injectivity in a SAG process. The Peaceman equation is used in most conventional foam simulators for estimating the wellbore pressure and injectivity. In this paper, we propose a modeling approach for gas and liquid injectivity in a SAG process on the basis of our experimental findings. The model represents the propagation of various banks during gas and liquid injection. We first compare the model predictions for linear flow with the coreflood results and obtain good agreement. We then propose a radial-flow model for scaling up the core-scale behavior to the field. The comparison between the results of the radial-propagation model and the Peaceman equation shows that a conventional simulator based on the Peaceman equation greatly underestimates both gas and liquid injectivities in a SAG process. The conventional simulator cannot represent the effect of gas injection on the subsequent liquid injectivity, especially the propagation of a relatively small region of collapsed foam near an injection well. The conventional simulator's results can be brought closer to the radial-flow-model predictions by applying a constant negative skin factor. The work flow described in this study can be applied to future field applications. The model we propose is based on a number of simplifying assumptions. In addition, the model would need to be fitted to coreflood data for the particular surfactant formulation, porous medium, and field conditions of a particular application. The adjustment of the simulator to better fit the radial-flow model also would depend, in part, on the grid resolution of the near-well region in the simulation.

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Section: Discussionmentioning

confidence: 99%

Modeling of Liquid Injectivity in Surfactant-Alternating-Gas Foam Enhanced Oil Recovery

et al. 2019

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“…Foam is sensetive to several parameters including oil and water saturation, surfactant concentration and chemical formulation, flow rate, reservoir heterogeneity and salinity. Thus, it is of extreme importance to design the surfactant injection process in a way that produces strong lamellae, which can propagate and survive at the reservoir conditions (Zanganeh, 2011). Although the ideal surfactant formulation is the one able to perform the dual role of IFT reduction, as well as stable foam generation and propagation, based on the present studies, it is hard to achieve.…”

Section: Foam Enhanced Co 2 -Eor Issues and Concernsmentioning

confidence: 81%

Foam assisted CO2-EOR; Concepts, Challenges and Applications

et al. 2013

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Foam assisted CO 2 enhanced oil recovery has attracted increasing attention of oil companies (operators and service companies) and research institutions mainly due to the potentially high benefit of foam on CO 2 -EOR. Miscible and immiscible CO 2 flooding projects are respectively proven and potential EOR methods. Both methods have suffered from limited efficiency due to gravity segregation, gas override, viscous fingering and channeling through high permeability streaks. Numerous theoretical and experimental studies as well as field applications have indicated that foaming of CO 2 reduces its mobility, thereby helping to control the above negative effects. However, there are still various conceptual and operational challenges, which may compromise the success and application of foam assisted CO 2 -EOR. This paper presents a critical survey of the foam assisted CO 2 -EOR process to reveal its strengths, highlight knowledge gaps and suggest ways. The oil recovery mechanisms involved in CO 2 foam flood, the effect of gaseous and soluble CO 2 on the process, synergic effect of foaming agent and ultra-low IFT surfactants, logistic and operational concerns, etc. were identified as among the main challenges for this process. Moreover, the complex flow behaviour of CO 2 , oil, micro-emulsion and brine system dictates a detailed study of the physical-chemical aspects of CO 2 foam flow for a successful design. Unavailability of reliable predictive tools due to the less understood concepts and phenomena adds more challenges to the process results and application justifications. The study highlights the recent achievements and analysis about foam application and different parameters, which cannot be avoided for a successful foam assisted CO 2 flood design and implementation. Accordingly, the study also addresses prospects and suggests necessary guidelines to be considered for the success of CO 2 foam projects. SPE 165280sweep efficiency in CO 2 -floods can be high, and the displacement efficiency of a miscible CO 2 flood often exceeds 90%. However, the sweep efficiency of CO 2 processes is often poor. Limitations of the current CO 2 -EORCO 2 would be much more widely used if it were abundantly available (Orr Jr., 2003). Natural sources, by-product of gas treatment units, and combustion processes could be supply sources of CO 2 . However, the present technologies of CO 2 capture and pressurization require energy which would result in a decreased overall energy efficiency and added cost. To recover additional oil in a CO 2 -EOR process, CO 2 is generally injected into the reservoir as a supercritical fluid (Sc-CO 2 ). Sc-CO 2 viscosity is lower than water and most crude oils, which can lead to a number of conformance and mobility issues, and instability in the displacement front, as shown in Fig. 1. Due to the adverse mobility ratio, fingers of CO 2 grow from the displacement front, and cause premature breakthrough, and inefficient CO 2 utilization. Furthermore, the tendency of lower density CO 2 to migrate toward the upper p...

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“…The low frequency temporal oscillations have been studied in the literature [1,2,40,41]. It has been shown in these works that the temporal oscillations occur as the front crosses a grid cell.…”

Section: The Numerical Solutions Depicted Inmentioning

confidence: 99%

Numerical artifacts in the discontinuous Generalized Porous Medium Equation: How to avoid spurious temporal oscillations

Maddix¹,

Sampaio²,

Gerritsen³

2018

Journal of Computational Physics

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Numerical discretizations of the Generalized Porous Medium Equation (GPME) with discontinuous coefficients are analyzed with respect to the formation of numerical artifacts. In addition to the degeneracy and self-sharpening of the GPME with continuous coefficients, detailed in [1], increased numerical challenges occur in the discontinuous coefficients case. These numerical challenges manifest themselves in spurious temporal oscillations in second order finite volume discretizations with both arithmetic and harmonic averaging. The integral average, developed in [2], leads to improved solutions with monotone and reduced amplitude temporal oscillations. In this paper, we propose a new method called the Shock-Based Averaging Method (SAM) that incorporates the shock position into the numerical scheme. The shock position is numerically calculated by discretizing the theoretical speed of the front from the GPME theory. The speed satisfies the jump condition for integral conservation laws. SAM results in a non-oscillatory temporal profile, producing physically valid numerical results. We use SAM to demonstrate that the choice of averaging alone is not the cause of the oscillations, and that the shock position must be a part of the numerical scheme to avoid the artifacts.

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Challenges in adjoint-based optimization of a foam EOR process

Cited by 16 publications

References 23 publications

Modeling of Liquid Injectivity in Surfactant-Alternating-Gas Foam Enhanced Oil Recovery

Modeling of Liquid Injectivity in Surfactant-Alternating-Gas Foam Enhanced Oil Recovery

Foam assisted CO2-EOR; Concepts, Challenges and Applications

Numerical artifacts in the discontinuous Generalized Porous Medium Equation: How to avoid spurious temporal oscillations

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