Investigation of Local Mixing and Its Influence on Core Scale Mixing (dispersion)

Investigation of Local Mixing and Its Influence on Core Scale Mixing (dispersion)
Author: Raman Kumar Jha
Publisher:
Total Pages: 424
Release: 2008
Genre:
ISBN:

Local displacement efficiency in miscible floods is significantly affected by mixing taking place in the medium. Laboratory experiments usually measure flow-averaged ("cup mixed") effluent concentration histories. The core-scale averaged mixing, termed as dispersion, is used to quantify mixing in flow through porous media. The dispersion coefficient has the contributions of convective spreading and diffusion lumped together. Despite decades of research there remain questions about the nature and origin of dispersion. The main objective of this research is to understand the basic physics of solute transport and mixing at the pore scale and to use this information to explain core-scale mixing behavior (dispersion). We use two different approaches to study the interaction between convective spreading and diffusion for a range of flow conditions and the influence of their interaction on dispersion. In the first approach, we perform a direct numerical simulation of pore scale solute transport (by solving the Navier Stokes and convection diffusion equations) in a surrogate pore space. The second approach tracks movement of solute particles through a network model that is physically representative of real granular material. The first approach is useful in direct visualization of mixing in pore space whereas the second approach helps quantify the effect of pore scale process on core scale mixing (dispersion). Mixing in porous media results from interaction between convective spreading and molecular diffusion. The converging-diverging flow around sand grains causes the solute front to stretch, split and rejoin. In this process the area of contact between regions of high and low solute concentrations increases by and order of magnitude. Diffusion tends to reduce local variations in solute concentration inside the pore body. If the fluid velocity is small, diffusion is able to homogenize the solute concentration inside each pore. On the other hand, in the limit of very large fluid velocity (or no diffusion) local mixing because of diffusion tends to zero and dispersion is entirely caused by convective spreading. Flow reversal provides insights about mixing mechanisms in flow through porous media. For purely convective transport, upon flow reversal solute particles retrace their path to the inlet. Convective spreading cancels and echo dispersion is zero. Diffusion, even though small in magnitude, causes local mixing and makes dispersion in porous media irreversible. Echo dispersion in porous media is far greater than diffusion and as large as forward (transmission) dispersion. In the second approach, we study dispersion in porous media by tracking movement of a swarm of solute particles through a physically representative network model. We developed deterministic rules to trace paths of solute particles through the network. These rules yield flow streamlines through the network comparable to those obtained from a full solution of Stokes' equation. In the absence of diffusion the paths of all solute particles are completely determined and reversible. We track the movement of solute particles on these paths to investigate dispersion caused by purely convective spreading at the pore scale. Then we superimpose diffusion and study its influence on dispersion. In this way we obtain for the first time an unequivocal assessment of the roles of convective spreading and diffusion in hydrodynamic dispersion through porous media. Alternative particle tracking algorithms that use a probabilistic choice of an out-flowing throat at a pore fail to quantify convective spreading accurately. For Fickian behavior of dispersion it is essential that all solute particles encounter a wide range of independent (and identically distributed) velocities. If plug flow occurs in the pore throats a solute particle can encounter a wide range of independent velocities because of velocity differences in pore throats and randomness of pore structure. Plug flow leads to a purely convective spreading that is asymptotically Fickian. Diffusion superimposed on plug low acts independently of convective spreading causing dispersion to be simply the sum of convective spreading and diffusion. In plug flow hydrodynamic dispersion varies linearly with the pore-scale Peclet number. For a more realistic parabolic velocity profile in pore throats particles near the solid surface of the medium do not have independent velocities. Now purely convective spreading is non-Fickian. When diffusion is non-zero, solute particles can move away from the low velocity region near the solid surface into the main flow stream and subsequently dispersion again becomes asymptotically Fickian. Now dispersion is the result of an interaction between convection and diffusion and its results in a weak non-linear dependence of dispersion on Peclet number. The dispersion coefficients predicted by particle tracking through the network are in excellent agreement with the literature experimental data. We conclude that the essential phenomena giving rise to hydrodynamic dispersion observed in porous media are (i) stream splitting of the solute front at every pore, thus causing independence of partical velocities purely by convection, (ii) a velocity gradient within throats and (iii) diffusion. Taylor's dispersion in a capillary tube accounts for only the second and third of these phenomena, yielding a quadratic dependence of dispersion on Peclet number. Plug flow in the bonds of a physically representative network accounts for the only the first and third phenomena, resulting in a linear dependence of dispersion upon Peclet number.

Dispersion Phenomena of Solutes and Particles and Their Applications in Porous Media

Dispersion Phenomena of Solutes and Particles and Their Applications in Porous Media
Author: Xiaoyan Meng
Publisher:
Total Pages: 0
Release: 2019
Genre:
ISBN:

Due to the special features, nanoparticles have seen various applications from drilling and completion as well as reservoir characterization to enhanced oil recovery (EOR). Not only does dispersion dominate solute and particle transport in both aquifers and hydrocarbon reservoirs, but also it imposes a significant impact on oil recovery during either chemical flooding or miscible gas injection processes for the injected agents. Considering the inherent heterogeneity and complex flow behaviour in porous media, therefore, it is of fundamental and practical importance to accurately describe dispersion of solutes and particles (including nanoparticles) in a uniform parallel-plate fracture and a circular tube. Also, this shall serve as a solid foundation for their applications to enhance oil recovery in fractured rocks and porous media. Besides, more efforts need to be extended to study solute and particle dispersion in porous media with different degrees of heterogeneity under various flow conditions. Using the moment analysis method and Green's function, mathematical formulations have been developed to determine dynamic dispersion coefficients for passive (i.e., chemically inert) and reactive (i.e., chemically active) particles flowing in a parallelplate fracture and a circular tube with fully-developed laminar flow under different source conditions across the full-time scale. These newly developed formulations have been verified for both solute and particle transport by agreeing well with analytical solutions and the random walk particle tracking (RWPT) simulations. Subsequently, the newly developed formulations for passive particles flowing in a parallel-plate fracture have been extended to match experimental measurements, while particle dispersion coefficients are notably less than those calculated by using the extended Taylor theory. For passive solutes and particles, at early times, dispersion coefficient is not only controlled by source condition, but also negatively correlated with center-of-mass velocity. After the critical time, source effect is negligible and all dispersion coefficients approach the values obtained through the extended Taylor theory. The relationship between particle size and dispersion coefficient for passive particles varies with time where they are positively correlated if Peclet number is larger than its critical value; otherwise, they are negatively correlated. As Damköhler number increases, for reactive particles, at long times, both reaction rate and center-of-mass velocity increase in magnitude, but dispersion coefficient decreases. At early times, however, those three parameters are not sensitive to Damköhler number. Consequently, reaction at the tube walls greatly affects concentration distribution. Coupling with the RWPT and pore-network modeling simulation, it is found that particle dispersion is greatly affected by particle size in a homogeneous model; however, for a heterogeneous model, throat velocity difference caused by heterogeneity plays an important role. In a homogeneous model, dispersion coefficient of particles (i.e., 7 dp 5 10   m) is overestimated without size exclusion, while the size-exclusion effects become more important as flow rate increases. In the heterogeneous models, however, size-exclusion effects of particles can be neglected. The dispersion difference between volumetric and uniform distributions increases with particle size and heterogeneity of the pore-network model. For a homogeneous model, dispersion coefficient with uniform distribution leads to a larger value than that with volumetric distribution; however, as heterogeneity increases, dispersion coefficient with volumetric distribution shows a larger value.

Computational Modelling of Multi-scale Solute Dispersion in Porous Media

Computational Modelling of Multi-scale Solute Dispersion in Porous Media
Author: Don Kulasiri
Publisher: BoD – Books on Demand
Total Pages: 246
Release: 2011-11-04
Genre: Computers
ISBN: 9533077263

This research monograph presents a mathematical approach based on stochastic calculus which tackles the "cutting edge" in porous media science and engineering - prediction of dispersivity from covariance of hydraulic conductivity (velocity). The problem is of extreme importance for tracer analysis, for enhanced recovery by injection of miscible gases, etc. This book explains a generalised mathematical model and effective numerical methods that may highly impact the stochastic porous media hydrodynamics. The book starts with a general overview of the problem of scale dependence of the dispersion coefficient in porous media. Then a review of pertinent topics of stochastic calculus that would be useful in the modeling in the subsequent chapters is succinctly presented. The development of a generalised stochastic solute transport model for any given velocity covariance without resorting to Fickian assumptions from laboratory scale to field scale is discussed in detail. The mathematical approaches presented here may be useful for many other problems related to chemical dispersion in porous media.

The Mathematics of Diffusion

The Mathematics of Diffusion
Author: John Crank
Publisher: Oxford University Press
Total Pages: 428
Release: 1979
Genre: Mathematics
ISBN: 9780198534112

Though it incorporates much new material, this new edition preserves the general character of the book in providing a collection of solutions of the equations of diffusion and describing how these solutions may be obtained.