Resolving experimental biases in the interpretation of diffusion experiments with a user-friendly numerical reactive transport approach

被引:3
|
作者
Tournassat, Christophe [1 ,2 ]
Steefel, Carl I. [1 ]
Fox, Patricia M. [1 ]
Tinnacher, Ruth M. [3 ]
机构
[1] Lawrence Berkeley Natl Lab, Earth & Environm Sci Area, Berkeley, CA USA
[2] Univ Orleans, Inst Sci Terre Orleans, BRGM, CNRS, Orleans, France
[3] Calif State Univ East Bay, Dept Chem & Biochem, Hayward, CA USA
来源
SCIENTIFIC REPORTS | 2023年 / 13卷 / 01期
基金
欧盟地平线“2020”;
关键词
TRACER DIFFUSION; HTO; CL-36(-); SORPTION; SODIUM; CLAY;
D O I
10.1038/s41598-023-42260-5
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
The reactive transport code CrunchClay was used to derive effective diffusion coefficients (D-e), clay porosities (epsilon), and adsorption distribution coefficients (K-D) from through-diffusion data while considering accurately the influence of unavoidable experimental biases on the estimation of these diffusion parameters. These effects include the presence of filters holding the solid sample in place, the variations in concentration gradients across the diffusion cell due to sampling events, the impact of tubing/dead volumes on the estimation of diffusive fluxes and sample porosity, and the effects of O-ring-filter setups on the delivery of solutions to the clay packing. Doing so, the direct modeling of the measurements of (radio)tracer concentrations in reservoirs is more accurate than that of data converted directly into diffusive fluxes. While the above-mentioned effects have already been described individually in the literature, a consistent modeling approach addressing all these issues at the same time has never been described nor made easily available to the community. A graphical user interface, CrunchEase, was created, which supports the user by automating the creation of input files, the running of simulations, and the extraction and comparison of data and simulation results. While a classical model considering an effective diffusion coefficient, a porosity and a solid/solution distribution coefficient (D-e-epsilon-K-D) may be implemented in any reactive transport code, the development of CrunchEase makes it easy to apply by experimentalists without a background in reactive transport modeling. CrunchEase makes it also possible to transition more easily from a D-e-epsilon-K-D modeling approach to a state-of-the-art process-based understanding modeling approach using the full capabilities of CrunchClay, which include surface complexation modeling and a multi-porosity description of the clay packing with charged diffuse layers.
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页数:13
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