Inhomogeneous rock compositions and varying dissolution rates affect evolution and shape of leaching zones in potash seams

Author(s):  
Svenja Steding ◽  
Thomas Kempka ◽  
Axel Zirkler ◽  
Michael Kühn

<p>Salt deposits host an important industrial raw material and provide storage capacities for energy and nuclear waste. However, leaching zones can seriously endanger the development and utilisation of salt deposits for these purposes, especially if these occur in potash seams. Their increased solubility enables even NaCl-saturated solutions, if present, to deeply penetrate these seams. The resulting salt dissolution processes generate fluid flow paths and affect the mechanical rock integrity. To model the timely evolution of leaching zones and to assess their hazard potential, a reactive transport model has been developed, taking into account not only the complex dissolution and precipitation behaviour of potash salts, but also the resulting porosity and permeability changes as well as density-driven chemical species transport. Additionally, the model makes use of an approach to describe transport and chemical reactions at the interface between impermeable (dry) salt rocks and permeated leaching zones (Steding et al., 2021). In the present study, we focus on the effect of heterogeneity of the mineral distribution within potash seams and on the influence of mineral- and saturation-dependent dissolution rates.</p><p>The applied reactive transport model is based on a coupling of the geochemical module PHREEQC (Parkhurst & Appelo, 2013) with the TRANSport Simulation Environment (Kempka, 2020) as well as the newly developed extension of an interchange approach (Steding et al., 2021). A numerical model has been developed and applied to simulate the leaching process of a carnallite-bearing potash seam due to natural density-driven convection. The results show that both, the mineral composition and dissolution rate of the original salt rock, strongly influence the shape and evolution of the leaching zone (Steding et al., 2021).</p><p>In nature, strong variations of the mineralogy occur within potash seams with random or stratified distributions. Furthermore, dissolution rates depend on the mineral itself as well as on its saturation state. Both may considerably influence the growth rate of a leaching zone. Therefore, the reactive transport model has been extended by mineral- and saturation-dependent dissolution rates. A scenario analysis has been undertaken to compare the impact of homogeneous and heterogeneous rock compositions. For that purpose, the carnallite content in the potash seam was varied from 5 to 25 wt. % including different stratifications and random distributions. The simulations were classified by means of the Péclet and Damköhler numbers, and the long-term behaviour as well as hazard potential are discussed.</p><p> </p><p>References:</p><p>Parkhurst, D.L.; Appelo, C.A.J. (2013). Description of Input and Examples for PHREEQC Version 3 - a Computer Program for Speciation, Batch-reaction, One-dimensional Transport, and Inverse Geochemical Calculations. In Techniques and Methods; Publisher: U.S. Geological Survey; Book 6, 497 pp</p><p>Kempka, T. (2020). Verification of a Python-based TRANsport Simulation Environment for density-driven fluid flow and coupled transport of heat and chemical species. Adv. Geosci. 54, 67–77. </p><p>Steding, S.; Kempka, T.; Zirkler, A.; Kühn, M. (2021). Spatial and temporal evolution of leaching zones within potash seams reproduced by reactive transport simulations. Water 13, 168. </p>

2020 ◽  
Author(s):  
Thomas Kempka

<p>Many different scientific open-source and commercial black-box software packages are available for the simulation of fluid flow and transport processes in the geological subsurface. Unfortunately, most of these simulators are limited by tightly integrated chemical modules with insufficient capabilities or the general lack of flexible interfaces applicable for an efficient coupling of third-party chemical libraries. Furthermore, most available open-source numerical frameworks are too complex to be used for educating geosciences students in numerical modelling techniques beyond the general application of ready-for-use simulators to specific modelling challenges. Taking into consideration that the development of a critical perspective of an emerging modeller requires fundamental analysis and understanding of common numerical modelling approaches and pitfalls, scientific source codes written in lower-level programming languages (e.g., FORTRAN, C++ or C) are per se less comprehensible compared to higher-level language implementations (e.g., Python). Hereby, the general lack of proper source code documentation, observed in many scientific open-source numerical codes additionally reduces code readability, and thus hinders code further development by third parties.<br>To overcome many of these limitations, the TRANsport Simulation Environment (TRANSE) has been developed based on the finite difference method. It allows for a highly flexible integration and coupling of arbitrary processes with thermodynamic and chemical libraries to consider chemical reactions and fluid equations of state. To date, TRANSE solves the pressure-based and density-driven formulation of the Darcy flow equation, coupled with the equations for transport of heat and chemical species on structured grids by simple explicit, weighted semi-implicit or fully-implicit numerical schemes, and is composed of less than 1,000 lines of Python code. A flux-corrected advection scheme can be employed in addition to pure upwinding to minimise numerical dispersion in transport problems dominated by high Péclet numbers.<br>Just-in-time compilation by means of the Python Numba library results in computational times in the order of equivalent lower-level language implementations (e.g., FORTRAN, C or C++), while CPU-based parallelisation allows for the realisation of high spatial model discretisations. Chemical libraries coupled to TRANSE can be easily parallelised to increase the overall computational efficiency, whereby the latter is especially relevant as chemistry usually represents the main computational bottleneck in reactive transport simulations. Python’s numpy library is used to enable fast and efficient model parametrisation as well as simulation runtime control, whereby the Matplotlib library is employed for automated visualisation. More sophisticated visualisation and post-processing are achieved by using the EVTK library for exporting VTK-compatible data to the interactive software packages VisIt, Mayavi or Paraview. <br>The present contribution demonstrates the basic validity of the code implementation by comparison against standard numerical model benchmarks for heat (1D heat diffusion) and fluid flow (Theis problem), advective transport (rotating cone test), density-driven fluid flow (Henry’s and Elder’s problems) as well as available density- and viscosity-driven hydrothermal convection in porous media. A fully coupled application example considering reactive transport of gaseous chemical species at high temperatures is presented.</p>


Geofluids ◽  
2017 ◽  
Vol 2017 ◽  
pp. 1-7
Author(s):  
Jixiang Huo ◽  
Fuheng Ma ◽  
Hanzhou Song

Pyrite existed widely in nature and its oxidative dissolution might lead groundwater to become acidic, which was harmful to the environment and indeed to artificial building materials. The reactive transport model was a useful tool to predict the extent of such pollution. However, the chemical species were coupled together in the form of a reaction term, which might lead the equations to be nonlinear and thus difficult to solve. A decoupling approach was presented: linear algebraic manipulations of the stoichiometric coefficients of the chemical reactions for the purpose of reducing the number of equation variables and simplifying the reactive source were used. Then the original and decoupled models were solved separately, by both a direct solver and an iterative solver. By comparing the solution times of two models, it was shown that the decoupling approach could enhance the computational efficiency, especially in situations using denser meshes. Using a direct solver, more solution time was saved than when using an iterative version.


2020 ◽  
Vol 54 ◽  
pp. 67-77
Author(s):  
Thomas Kempka

Abstract. Numerical simulation has become an inevitable tool for improving the understanding on coupled processes in the geological subsurface and its utilisation. However, most of the available open source and commercial modelling codes do not come with flexible chemical modules or simply do not offer a straight-forward way to couple third-party chemical libraries. For that reason, the simple and efficient TRANsport Simulation Environment (TRANSE) has been developed based on the Finite Difference Method in order to solve the density-driven formulation of the Darcy flow equation, coupled with the equations for transport of heat and chemical species. Simple explicit, weighted semi-implicit or fully-implicit numerical schemes are available for the solution of the system of partial differential equations, whereby the entire numerical code is composed of less than 1000 lines of Python code, only. A diffusive flux-corrected advection scheme can be employed in addition to pure upwinding to minimise numerical diffusion in advection-dominated transport problems. The objective of the present study is to verify the numerical code implementation by means of benchmarks for density-driven fluid flow and advection-dominated transport. In summary, TRANSE exhibits a very good agreement with established numerical simulation codes for the benchmarks investigated here. Consequently, its applicability to numerical density-driven flow and transport problems is proven. The main advantage of the presented numerical code is that the implementation of complex problem-specific couplings between flow, transport and chemical reactions becomes feasible without substantial investments in code development using a low-level programming language, but the easy-to-read and -learn Python programming language.


2016 ◽  
Vol 50 (13) ◽  
pp. 7010-7018 ◽  
Author(s):  
Yiwei Cheng ◽  
Christopher G. Hubbard ◽  
Li Li ◽  
Nicholas Bouskill ◽  
Sergi Molins ◽  
...  

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