European Geosciences Union General Assembly

p. 1

Presentation's date: 2019-04-09

Abstract:

The engineered injection – extraction (EIE) system through multiple wells was born with the idea to promotethe mixing and therefore the chemical reactions and the dilution in aquifers. But EIE has been mostly numeri-cally tested in multigaussian fields, which is the standard geostatistical field to describe the heterogeneity of theporous medium and therefore the spatial distribution of the logarithm of the hydraulic conductivity (K). However,this geostatistical model does not take into account the hydraulic connectivity of high-K zones, grouping the ex-treme values into disconnected bodies and only connecting structures of intermediate-K values. On the other hand,non-multigaussian fields can generate geological bodies of extreme K values that concentrate flow and inducechanneling. It turns out that, in real life, in situ remediation methods (e.g. injection of a treatment solution) areusually inefficient due to the presence of preferential paths generated by the heterogeneity of the porous medium,resulting in isolated low-K zones inaccessible to the treatment solution. In this work, we propose to use the chaoticflow, induced by the EIE, as a tool to break these preferential paths, making the aquifer behave as a chemical reac-tor in the zone enclosed by the wells. Importantly, if preferential paths can be controlled by using chaotic flow, theuncertainty of the remediation methods will be diminished. To study this, we compare the evolution of the dilutionindex obtained with multigaussian fields and with non-multigaussian fields of similar statistical properties]]>

Water resources research

Vol. 53, num. 11, p. 9019

DOI: 10.1002/2017WR021064

Date of publication: 2017-11

Abstract:

In recent years, a large body of the literature has been devoted to study reactive transport of solutes in porous media based on pure Lagrangian formulations. Such approaches have also been extended to accommodate second-order bimolecular reactions, in which the reaction rate is proportional to the concentrations of the reactants. Rather, in some cases, chemical reactions involving two reactants follow more complicated rate laws. Some examples are (1) reaction rate laws written in terms of powers of concentrations, (2) redox reactions incorporating a limiting term (e.g., Michaelis-Menten), or (3) any reaction where the activity coefficients vary with the concentration of the reactants, just to name a few. We provide a methodology to account for complex kinetic bimolecular reactions in a fully Lagrangian framework where each particle represents a fraction of the total mass of a specific solute. The method, built as an extension to the second-order case, is based on the concept of optimal Kernel Density Estimator, which allows the concentrations to be written in terms of particle locations, hence transferring the concept of reaction rate to that of particle location distribution. By doing so, we can update the probability of particles reacting without the need to fully reconstruct the concentration maps. The performance and convergence of the method is tested for several illustrative examples that simulate the Advection-Dispersion-Reaction Equation in a 1-D homogeneous column. Finally, a 2-D application example is presented evaluating the need of fully describing non-bilinear chemical kinetics in a randomly heterogeneous porous medium.

This is the peer reviewed version of the following article: Sole-Mari, G., Fernàndez-Garcia, D., Rodríguez-Escales, P., & Sanchez-Vila, X. (2017). A KDE-based random walk method for modeling reactive transport with complex kinetics in porous media. Water Resources Research, 53, 9019–9039, which has been published in final form at https://doi.org/10.1002/2017WR021064. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving.]]>

International Conference on Porous Media & Annual Meeting

p. 1

Presentation's date: 2017-05-10

Abstract:

In recent years a large body of literature has been devoted to study reactive transport of solutes in porous media based on pure Lagrangian formulations. Such approaches have also been extended to accommodate bimolecular reactions provided the kinetic term can be written as proportional to the product of the concentration of the two reactants. Rather, in some cases, reactive transport in bimolecular reactions involves more complicated rate laws that are not linear with respect to the concentration of the reactants. Some examples are (1) reaction rate laws written in terms of powers of concentrations, (2) redox reactions following a Michaelis-Menten rate law, or (3) any reaction where the activity coefficients vary with the concentration of the reactants, just to name a few. We provide a methodology to account for non-linear reactions in a fully Lagrangian approach where each particle represents an amount of mass of a specific solute. The method, built as an extension to the first-order case, is based on the concept of optimal Kernel Density Estimator, which allows the concentrations to be written in terms of particle locations hence transferring the concept of reaction rate to particle location distribution. By doing so, we can update the probability of particles reacting without the need to reconstruct the concentration maps. The methodology is implemented in a 1D model to reproduce the Advection-Dispersion-Reaction Equation (ADRE), and its performance is tested for several hypothetical case examples. The results show convergence towards the finite-difference solution as the number of particles is increased.]]>