Skip to main content
Log in

A Note on Upscaling Retardation Factor in Hierarchical Porous Media with Multimodal Reactive Mineral Facies

  • Published:
Transport in Porous Media Aims and scope Submit manuscript

Abstract

We present a model for upscaling the time-dependent effective retardation factor, \({\widetilde{R}}(t)\), in hierarchical porous media with multimodal reactive mineral facies. The model extends the approach by Deng et al. (Chemosphere 91(3):248–257, 2013) in which they expanded a Lagrangian-based stochastic theory presented by Rajaram (Adv Water Resour 20(4):217–230, 1997) in order to describe the scaling effect of \(\widetilde{R}(t)\). They used a first-order linear approximation in deriving their model to make the derivation tractable. Importantly, the linear approximation is known to be valid only to variances of 0.2. In this note, we show that the model can be derived with a higher-order approximation, which allows for representing variances from 0.2 to 1.0. We present the derivation and use the resulting model to recalculate \(\widetilde{R}(t)\) for the scenario examined by Deng et al. (2013).

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2

References

  • Bellin, A., Salandin, P., Rinaldo, A.: Simulation of dispersion in heterogeneous porous formations: statistics, first-order theories, convergence of computations. Water Resour. Res. 28(9), 2211–2227 (1992)

    Article  Google Scholar 

  • Bellin, A., Rinaldo, A., Bosma, W.J.P., Zee, S.E., Rubin, Y.: linear equilibrium adsorbing solute transport in physically and chemically heterogeneous porous formations: 1. Analytical solutions. Water Resour. Res. 29(12), 4019–4030 (1993)

    Article  Google Scholar 

  • Bellin, A., Rinaldo, A.: Analytical solutions for transport of linearly adsorbing solutes in heterogeneous formations. Water Resour. Res. 31(6), 1505–1511 (1995)

    Article  Google Scholar 

  • Bosma, W.J.P., Bellin, A., Zee, S.E., Rinaldo, A.: Linear equilibrium adsorbing solute transport in physically and chemically heterogeneous porous formations: 2. Numerical results. Water Resour. Res. 29(12), 4031–4043 (1993)

    Article  Google Scholar 

  • Burr, D.T., Sudicky, E.A., Naff, R.L.: Nonreactive and reactive solute transport in three-dimensional heterogeneous porous media: mean displacement, plume spreading and uncertainty. Water Resour. Res. 30(3), 791–815 (1994)

    Article  Google Scholar 

  • Brusseau, M.L., Srivastava, R.: Nonideal transport of reactive solutes in heterogeneous porous media: 2. Quantitative analysis of the Borden natural-gradient field experiment. J. Contam. Hydrol. 28(2), 115 (1997)

    Article  Google Scholar 

  • Dai, Z., Ritzi, R.W., Huang, C., Rubin, Y., Dominic, D.F.: Transport in heterogeneous sediments with multimodal conductivity and hierarchical organization across scales. J. Hydrol. 294(1), 68–86 (2004)

    Article  Google Scholar 

  • Deng, H., Dai, Z., Wolfsberg, A.V., Ye, M., Stauffer, P.H., Lu, Z., Kwicklis, E.: Upscaling retardation factor in hierarchical porous media with multimodal reactive mineral facies. Chemosphere 91(3), 248–257 (2013)

    Article  Google Scholar 

  • Garabedian, S.P., Gelhar, L.W., Celia, M.A.: Large-Scale Dispersive Transport in Aquifers: Field Experiments and Reactive Transport Theory. Technical report 315, Ralph M. Parsons Laboratory, Massachusetts Institute of Technology (1988)

  • Gelhar, L.W., Axness, C.L.: Three-dimensional stochastic analysis of macrodispersion in aquifers. Water Resour. Res. 19(1), 161–180 (1983)

    Article  Google Scholar 

  • Gelhar, L.W.: Stochastic Subsurface Hydrology. Prentice-Hall, Englewood Cliffs (1993)

    Google Scholar 

  • Glimm, J., Lindquist, W.B., Pereira, F., Zhang, Q.: A theory of macrodispersion for the scale-up problem. Transp. Porous Media 13(1), 97–122 (1993)

    Article  Google Scholar 

  • Hsu, K.C., Zhang, D., Neuman, S.P.: Higher-order effects on flow and transport in randomly heterogeneous porous media. Water Resour. Res. 32(3), 571–582 (1996)

    Article  Google Scholar 

  • Rajaram, H.: Time and scale-dependent effective retardation factors in heterogeneous aquifers. Adv. Water Resour. 20(4), 217–230 (1997)

    Article  Google Scholar 

  • Ritzi, W.R., Dai, Z., Dominic, D.F., Rubin, Y.N.: Spatial correlation of permeability in cross-stratified sediment with hierarchical architecture. Water Resour. Res. 40, W03513 (2004). doi:10.1029/2003WR002420

    Google Scholar 

  • Roberts, P.V., Goltz, M.N., Mackay, D.M.: A natural gradient experiment on solute transport in a sand aquifer: 3. Retardation estimates and mass balances for organic solutes. Water Resour. Res. 22(13), 2047–2058 (1986). doi:10.1029/WR022i013p02047

    Article  Google Scholar 

  • Soltanian, M.R, Ritzi, R., Dai, Z., Huang, C., Dominic, D.: Transport of kinetically sorbing solutes in heterogeneous sediments with multimodal conductivity and hierarchical organization across scales. Stoch. Environ. Res. Risk Assess. 1–18 (2014). doi:10.1007/s00477-014-0922-3

  • Soltanian, M.R., Ritzi, R., Dai, Z., Huang, C.: Reactive solute transport in physically and chemically heterogeneous porous media with multimodal reactive mineral facies: the Lagrangian approach. Chemosphere 122, 235–244 (2015). doi:10.1016/j.chemosphere.2014.11.064

    Article  Google Scholar 

  • Yoram, R.: Applied stochastic hydrogeology. Oxford University Press, New york (2003)

    Google Scholar 

Download references

Acknowledgments

Mohamad Reza Soltanian was supported by the National Science Foundation under Grant EAR-0810151, and also by a Graduate Fellowship from the College of Science and Mathematics at Wright State University. Any opinions, findings, and conclusions or recommendations expressed in this article are those of the authors and do not necessarily reflect those of the National Science Foundation or other supporting institutions. The manuscript was improved based on reviews by Timothy Ginn and six other anonymous reviewers.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Mohamad Reza Soltanian.

Appendix: Derivation of Cross-Covariance of \(v_1\) and \(R\)

Appendix: Derivation of Cross-Covariance of \(v_1\) and \(R\)

The derivation of \(C_{v_1 R} (\xi )\) by Deng et al. (2013) is presented here for ease of reference. The \(C_{v_1 R} (\xi )\) is found by taking the Fourier transform of the Eq. (18). Here we consider a unimodal porous media with the spectral density function \(S_{ff} (k)\) as in Eq. (19). Note that the same integration method is used three times for the three exponential terms in Eq. (20). The \(C_{v_1 R} (\xi )\) is found by:

(23)

We set \(I\) equal to the integration part in (23). Therefore,

(24)

One can use a spherical coordinate system and define the following:

$$\begin{aligned} k_1= & {} k \cos \,\beta \end{aligned}$$
(25)
$$\begin{aligned} k_1/k= & {} \cos \,\beta \cos \,\chi +\sin \,\theta \sin \,\chi \cos \,\alpha \end{aligned}$$
(26)
$$\begin{aligned} \hbox {d}k_1 \hbox {d}k_2 \hbox {d}k_3= & {} k^{2}\sin \,\theta \,\hbox {d}k\,\hbox {d}\alpha \,\hbox {d}\theta \end{aligned}$$
(27)

where \(\chi \) is the angle between the separation vector \(\xi \) and the direction of mean flow \(k_1\), and \(\theta \) is the angle between \(\xi \) and \(\kappa \). The \(\chi \) and \(\xi \) are coordinates of the covariance function. The \(k,\theta \), and \(\alpha \) are spherical coordinates in wave number space. Substituting (25), (26), and (27) into (24) gives:

$$\begin{aligned} I= & {} \frac{\sigma _f^2 }{\lambda \pi ^{2}}\int \limits _{k=0}^\infty \int \limits _{\alpha =0}^{2\pi } \int \limits _{\theta =0}^\pi \left\{ \left[ 1-\cos ^{2}\theta \cos ^{2}\chi -\sin ^{2}\theta \sin ^{2}\chi \cos ^{2}\theta \right. \right. \nonumber \\&\left. \left. \quad -\,2\cos \theta \cos \chi \sin \theta \sin \chi \cos \alpha \right] \frac{k^{2}\lambda ^{4}}{\left( 1+k^{2}\lambda ^{2}\right) ^{2}}\hbox {e}^{ik\xi \cos \theta }\sin \theta \,\hbox {d}k\,\hbox {d}\theta \,\hbox {d}\alpha \right\} \end{aligned}$$
(28)

One can let \(\cos \theta =y\) and use the relationship of \(\hbox {e}^{ik\xi y}=\cos k\xi y+i \sin k\xi y\) to change the (28) to the following expression:

$$\begin{aligned} I= & {} \frac{\sigma _f^2 }{\lambda \pi ^{2}}\int \limits _{k=0}^\infty {\int \limits _{\alpha =0}^{2\pi } } \nonumber \\&\quad \times \,\int \limits _{y=-1}^1 \left\{ \left[ \left( 1\!-\!y^{2}\cos ^{2}\chi \right) \!-\!\left( 1\!-\!y^{2}\right) \sin ^{2}\chi \sin ^{2}\alpha \right] \frac{k^{2}\lambda ^{4}}{\left( 1\!+\!k^{2}\lambda ^{2}\right) ^{2}}\cos k\xi y\right\} \hbox {d}k\,\hbox {d}y\,\hbox {d}\alpha \quad \quad \nonumber \\ \end{aligned}$$
(29)

Deng et al. (2013) integrated (29) by presenting the following integrals:

$$\begin{aligned}&\displaystyle I_a = \int \limits _0^\infty {\frac{k^{2}\lambda ^{4}}{\left( 1+k^{2}\lambda ^{2}\right) ^{2}}\cos k\xi y}\hbox {d}k=\frac{\pi }{4}\lambda \left( 1-\frac{\left| {\xi y} \right| }{\lambda }\right) \hbox {e}^{-\frac{\left| {\xi y} \right| }{\lambda }} \end{aligned}$$
(30)
$$\begin{aligned}&\displaystyle I_b =\int \limits _0^{2\pi } {(1-y^{2})} \sin ^{2}\chi \cos ^{2}\alpha \hbox {d}\alpha =\pi \left( 1-y^{2}\right) \sin ^{2}\chi \end{aligned}$$
(31)
$$\begin{aligned}&\displaystyle I_c =\int \limits _0^{2\pi } {\left( 1-y^{2}\cos ^{2}\chi \right) }\hbox {d}\alpha =2\pi \left( 1-y^{2}\cos ^{2}\chi \right) = \pi \left( 2-2y^{2}\cos ^{2}\chi \right) \end{aligned}$$
(32)

Substituting (30), (31), and (32) into (29) gives:

$$\begin{aligned} I= \frac{\sigma _f^2 }{4}\int \limits _{y=-1}^1 \left\{ \left[ \left( 2-2y^{2}\cos ^{2}\chi \right) -\left( 1-y^{2}\right) \sin ^{2}\chi \right] \left( 1-\frac{\left| {\xi y} \right| }{\lambda }\right) \hbox {e}^{-\frac{\left| {\xi y} \right| }{\lambda }}\right\} \hbox {d}y \end{aligned}$$
(33)

Then, one can expand (33) as:

$$\begin{aligned} I= & {} \frac{\sigma _f^2 }{2}\left\{ \int \limits _0^1 {\left( 1+\cos ^{2}\chi \right) } \hbox {e}^{-\frac{\xi y}{\lambda }}\hbox {d}y+\int \limits _0^1 {\left( 1-3\cos ^{2}\chi \right) } y^{2}\hbox {e}^{-\frac{\xi y}{\lambda }}\hbox {d}y\right. \nonumber \\&\left. \quad -\,\int \limits _0^1 {\frac{\xi }{\lambda }\left( 1+\cos ^{2}\chi \right) } y \hbox {e}^{-\frac{\xi y}{\lambda }}\hbox {d}y-\int \limits _0^1 {\frac{\xi }{\lambda }\left( 1-3\cos ^{2}\chi \right) } y^{3}\hbox {e}^{-\frac{\xi y}{\lambda }}\hbox {d}y\right\} \nonumber \\= & {} \frac{\sigma _f^2 }{2}\left( I_1 +I_2 -I_3 -I_4\right) \end{aligned}$$
(34)

Next, one can find \(I_1,I_2,I_3\), and \(I_4\) as (Deng et al. 2013):

$$\begin{aligned} I_1= & {} \int \limits _0^1 {\left( 1+\cos ^{2}\chi \right) } \hbox {e}^{-\frac{\xi y}{\lambda }}\hbox {d}y=-\frac{\lambda }{\xi }\left( 1+\cos ^{2}\chi \right) \left( \hbox {e}^{-\frac{\xi }{\lambda }}-1\right) \nonumber \\ \end{aligned}$$
(35)
$$\begin{aligned} I_2= & {} \int \limits _0^1 {\left( 1-3\cos ^{2}\chi \right) } y^{2}\hbox {e}^{-\frac{\xi y}{\lambda }}\hbox {d}y\nonumber \\= & {} \left( 3\cos ^{2}\chi -1\right) \left[ \left( \frac{\lambda }{\xi }\right) \hbox {e}^{-\frac{\xi }{\lambda }}+2\left( \frac{\lambda }{\xi }\right) ^{2}\hbox {e}^{-\frac{\xi }{\lambda }}+2\left( \frac{\lambda }{\xi }\right) ^{3}\left( \hbox {e}^{-\frac{\xi }{\lambda }}-1\right) \right] \end{aligned}$$
(36)
$$\begin{aligned} I_3= & {} \int \limits _0^1 {\frac{\xi }{\lambda }\left( 1+\cos ^{2}\chi \right) } y \hbox {e}^{-\frac{\xi y}{\lambda }}\hbox {d}y\nonumber \\= & {} -\left( 1+\cos ^{2}\chi \right) \left[ \hbox {e}^{-\frac{\xi }{\lambda }}+\left( \frac{\lambda }{\xi }\right) \left( \hbox {e}^{-\frac{\xi }{\lambda }}-1\right) \right] \end{aligned}$$
(37)
$$\begin{aligned} I_4= & {} \int \limits _0^1 {\frac{\xi }{\lambda }\left( 1-3\cos ^{2}\chi \right) } y^{3} \hbox {e}^{-\frac{\xi y}{\lambda }}\hbox {d}y\nonumber \\= & {} \left( 3\cos ^{2}\chi -1\right) \left[ \hbox {e}^{-\frac{\xi }{\lambda }}+3\left( \frac{\lambda }{\xi }\right) \hbox {e}^{-\frac{\xi }{\lambda }}+6\left( \frac{\lambda }{\xi }\right) ^{2}\hbox {e}^{-\frac{\xi }{\lambda }}+6\left( \frac{\lambda }{\xi }\right) ^{3}\left( \hbox {e}^{-\frac{\xi }{\lambda }}-1\right) \right] \qquad \end{aligned}$$
(38)

Substituting (35), (36), (37), and (38) into (34), which in turn goes into (23), finally gives:

$$\begin{aligned} C_{v_1 R} (\xi )= & {} \frac{\rho _\mathrm{b}}{n^{2}}K^\mathrm{G}K_\mathrm{d}^\mathrm{G}\textit{Ja} \frac{\sinh (\sigma _w)}{\sigma _w}\frac{\sigma _f^2 }{2}\left\{ \left( 1+\cos ^{2}\chi \right) \hbox {e}^{-\frac{\xi }{\lambda }}+\left( 1-3\cos ^{2}\chi \right) \right. \nonumber \\&\left. \times \left[ \hbox {e}^{-\frac{\xi }{\lambda }}+2\left( \frac{\lambda }{\xi }\right) \hbox {e}^{-\frac{\xi }{\lambda }}+4\left( \frac{\lambda }{\xi }\right) ^{2}\hbox {e}^{-\frac{\xi }{\lambda }}+4\left( \frac{\lambda }{\xi }\right) ^{3}\left( \hbox {e}^{-\frac{\xi }{\lambda }}-1\right) \right] \right\} \end{aligned}$$
(39)

when the separation vector is parallel to the flow direction, \(\chi =0\) and \(\cos ^{2}\chi =1\), then:

$$\begin{aligned} C_{v_1 R} (\xi )= & {} \frac{\rho _\mathrm{b}}{n^{2}}K^\mathrm{G}K_\mathrm{d}^\mathrm{G}\textit{Ja} \frac{\sinh (\sigma _w)}{\sigma _w}\sigma _f^2 \nonumber \\&\times \left[ 4\left( \frac{\lambda }{\xi }\right) ^{3}\left( 1-\hbox {e}^{-\frac{\xi }{\lambda }}\right) -4\left( \frac{\lambda }{\xi }\right) ^{2}\hbox {e}^{-\frac{\xi }{\lambda }}-2\left( \frac{\lambda }{\xi }\right) \hbox {e}^{-\frac{\xi }{\lambda }}\right] \quad \quad \end{aligned}$$
(40)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Soltanian, M.R., Ritzi, R., Huang, C.C. et al. A Note on Upscaling Retardation Factor in Hierarchical Porous Media with Multimodal Reactive Mineral Facies. Transp Porous Med 108, 355–366 (2015). https://doi.org/10.1007/s11242-015-0480-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11242-015-0480-2

Keywords

Navigation