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Horizontal miscible displacements through porous media: the interplay between viscous fingering and gravity segregation

Published online by Cambridge University Press:  26 January 2022

Japinder S. Nijjer*
Affiliation:
Molecular Cellular and Developmental Biology, Yale University, 260 Whitney Avenue, New Haven 06511, USA
Duncan R. Hewitt
Affiliation:
Department of Mathematics, University College London, 25 Gordon Street, London WC1H 0AY, UK
Jerome A. Neufeld
Affiliation:
Department of Applied Mathematics and Theoretical Physics, University of Cambridge, Wilberforce Road, Cambridge CB3 0WA, UK Department of Earth Sciences, University of Cambridge, Downing Street, Cambridge CB2 3EQ, UK BP Institute, University of Cambridge, Bullard Laboratories, Madingley Road, Cambridge CB3 0EZ, UK
*
Email address for correspondence: japinder.nijjer@yale.edu

Abstract

We consider miscible displacements in two-dimensional homogeneous porous media where the displacing fluid is less viscous and has a different density than the displaced fluid. We find that the dynamics evolve through nine possible regimes depending on the viscosity ratio, strength of density variations and the strength of the background flow, as characterized by the Péclet number. At early times the interface is dominated by longitudinal diffusion before undergoing a transition to a slumping regime where vertical flow is important. At intermediate times, vertical flow and diffusion can be neglected and there are three different limiting solutions: a fingering limit; an injection-driven gravity-current limit; and a density-driven gravity-current limit. Finally at late times, transverse diffusion becomes important and there is a transition from an apparent shutdown regime to a viscously enhanced Taylor-slumping regime. In each of the regimes, the dominant scalings are identified and reduced-order models for the evolution of the concentration field are developed. Lastly, three case studies are considered to illustrate the dominant physical balances in the geophysically relevant setting of geological $\textrm {CO}_2$ storage.

Information

Type
JFM Papers
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
Copyright
© The Author(s), 2022. Published by Cambridge University Press
Figure 0

Figure 1. A schematic of the model geometry. The porous medium is infinite in the $\hat {x}$ direction, and finite, with width $a$, in the $\hat {y}$ direction. The medium is initially saturated with a fluid of density $\rho _2$ and viscosity $\mu _2$ and another fully miscible fluid, with density $\rho _1$ and viscosity $\mu _1$ is injected at the left boundary. We assume that the injected fluid is introduced in a purely horizontal manner and at a constant two-dimensional (2-D) volumetric flow rate $Q$.

Figure 1

Figure 2. Evolution of the concentration field for $R=0$ and $(G,\textit {Pe}) = (3,100)$. (ae) Plots of the concentration field versus $x/h(t)$ and $y$ at (a) $t=1\times 10^{-4}$, (b) $t=0.036$, (c) $t=0.83$, (d) $t=57$ (e) $t=8000$. (f) Evolution of the spreading length, $h$, as a function of time, $t$. The dots correspond to the snapshots in panels (ae) and the dashed lines correspond to the theoretical predictions from Szulczewski & Juanes (2013).

Figure 2

Figure 3. Evolution of the concentration field for $G=0$ and $(R,\textit {Pe}) = (2.5,500)$. (ae) Plots of the concentration field versus $x/h(t)$ and $y$ at (a) $t=2\times 10^{-2}$, (b) $t=2.6$, (c) $t=15$, (d) $t=170$ (e) $t=525$. (f) Evolution of the spreading length, $h$, as a function of time, $t$. The dots correspond to snapshots in panels (ae) and the dashed lines correspond to the theoretical predictions from Nijjer, Hewitt & Neufeld (2018).

Figure 3

Figure 4. Colourmaps of the concentration field for $(R,\textit {Pe}) = (2,500)$ and (a,c,e,g) $G =0.025$, (b,d,f,h) ${G=2}$. The snapshots are taken at times (a,b) $t=0.05$, (c,d) $t=2$, (e,f) $t=30$ and (g,h) $t=500$. Evolution of (i) the spreading length, $h$ and (j) the Nusselt number, $\textit {Nu}$, for the same parameters as in (ah).

Figure 4

Figure 5. Colourmaps of the concentration field in the slumping regime for $(R,\textit {Pe}) = (1,4000)$ and $(G,t)=\,$ (a) $(0.02,0.6)$ and (b) $(2,0.07)$.

Figure 5

Figure 6. Plots of $h(t)$ for $\textit {Pe} = 100$ and different $G$ and $R$ as labelled. The raw data is plotted in (a). In (b) the spreading length is rescaled by the predicted scalings for the small-$G$ slumping limit. The dotted lines denote simulations with $G=0$ and $R=\{0.5,1,2\}$. In (c) the spreading length is rescaled by the predicted scalings for the large-$G$ slumping limit. The dotted lines denote simulations with $R=0$ and $G = \{1,2,4\}$.

Figure 6

Figure 7. Evolution of the transversely averaged concentration (or equivalently the height of the current above the base) found by solving (4.7) for (a) small times, $(R,G) = (2,8)$ and $t$ ranging logarithmically from $0.03$ to $1$ and (b) large times, $(R,G) = (2,2)$ and $t$ ranging logarithmically from $1$ to $32$. The small-time asymptotic limit found by solving (4.8) and large-time asymptotic limit (4.10) are given by dashed black lines.

Figure 7

Figure 8. Plot of the transversely averaged concentration for (a) small times, $(R,\textit {Pe},G,t) = (1,4000,14,1)$ and (b) large times $(R,\textit {Pe},G,t) = (2,4000,0.5,10)$ from the 2-D numerical simulations (black lines). The coloured lines represent the four different model solutions: the full one-dimensional (1-D) sharp-interface model (4.7); the small-time limit of the sharp-interface model (4.8); the large-time limit of the sharp-interface model (4.10); and the diffuse-interface model (A 1) with (4.5). The size of the diffuse region $l=0.03$ is chosen to fit the full 2-D numerical simulations.

Figure 8

Figure 9. Plot of $h(t)$ for $(R,\textit {Pe}) = (1,4000)$ and different values of $G$ in the intermediate-time regime. (b) Plot of the spreading rate $\dot {h}$ calculated by least-squares fitting a function of the form $h=h_0+\dot {h}t$ to the numerical results for $t$ in the range $5 \leqslant t \leqslant 10$, for $\textit {Pe}=4000$ and different $G$ and $R$. The theoretical predictions for (a$h$ and (b) $\dot {h}$ are found from the solution (4.10) with either $M = \textrm {e}^{R}$ or $M = \textrm {e}^{R}\mathrm {erf}(\sqrt {R})/\mathrm {erfi}(\sqrt {R})$, given by dashed and dot–dashed lines, respectively.

Figure 9

Figure 10. Stable versus unstable displacements for (a) $\textit {Pe} = 4000$ and (b) $R=2$. Filled circles denote simulations where no fingers were observed during the entire length of the simulations, while unfilled circles denote simulations where fingers were observed for at least some portion of the simulation. Dashed lines show the stability boundary $G=5\times 10^{-5} R^{2}\textit {Pe}$.

Figure 10

Figure 11. Colourmaps (with overlain contours) of the (a,b) concentration field, (c,d) concentration deviations $c'$ and (e,f) streamwise velocity, $u$ for (a,c,e) $(R,\textit {Pe},G,t) = (1.5,1000,0.1,1000)$ (small $G$) and (b,d,f) $(R,\textit {Pe},G,t) = (1.5,100,10,1000)$ (large $G$). Panels (a,c,e) correspond to flow in the shutdown regime and (b,d,f) correspond to flow in the viscously enhanced Taylor slumping regime. Note that the aspect ratio of the figures is compressed, so variations in the $x$-direction seem more pronounced than they actually are.

Figure 11

Figure 12. (a) Evolution of $\bar {c}$ for $(R,\textit {Pe},G) = (1.5,1000,0.3)$ and $t$ spaced evenly from $150$ to $900$. (b) Plot of $\bar {c}(x)$ at $t=1000$ for $R$ ranging from $0.5$ to $2.5$, $G$ ranging from $0.01$ to $0.8$ and $\textit {Pe}$ ranging from $300$ to $1000$. (c) Plot of $\textit {Nu}(t)$ for $(R,\textit {Pe},G) = (1.5,1000,0.3)$. The solid and dashed black lines denote theoretical predictions with $K=0.5$ and $K=0.6$, respectively.

Figure 12

Figure 13. (a) The similarity solution of (4.25) for $R = {0,0.5,1,1.5,2,2.5,3}$. The analytical solution for $R=0$ is given by the black line (Szulczewski & Juanes 2013). (b) The evolution of $\bar {c}$ for $(R,\textit {Pe},G)=(3,10,10)$ at $t=\{1000, 2000, 4000\}$. The theoretical predictions, found by solving (4.24), are denoted by dotted lines.

Figure 13

Figure 14. Representative plots of the scaling exponent of the spreading length, $\delta$, found by locally fitting a power law of the form $h=At^{\delta }$, for $R=1.5$ and (a) $\textit {Pe} = 100$, (b) $\textit {Pe} = 1000$. The regime boundaries (black lines) divide the (I) early-time diffusive, (II) large-$G$ slumping, (III) small-$G$ slumping and viscous fingering, (IV) density-driven gravity current, (V) injection-driven gravity current, (VI) shutdown, (VII) central-finger and boundary-finger and (VIII) viscously enhanced Taylor-slumping regimes. Over long times, the interface evolves through longitudinal diffusion (regime IX not shown).

Figure 14

Figure 15. Evolution of the displacement front in the three case studies. The black dots denote the time since injection at Sleipner, the total injection time at In Salah, and time until breakthrough at Salt Creek.

Figure 15

Table 1. Characteristic advective time scale $t_{{dim}}$ and dimensionless variables $G,R,\textit {Pe}$ for the three carbon dioxide sequestration case studies.