Deciphering pore-level precipitation mechanisms

Abstract

Mineral precipitation and dissolution in aqueous solutions has a significant effect on solute transport and structural properties of porous media. The understanding of the involved physical mechanisms, which cover a large range of spatial and temporal scales, plays a key role in several geochemical and industrial processes. Here, by coupling pore scale reactive transport simulations with classical nucleation theory, we demonstrate how the interplay between homogeneous and heterogeneous precipitation kinetics along with the non-linear dependence on solute concentration affects the evolution of the system. Such phenomena are usually neglected in pure macroscopic modelling. Comprehensive parametric analysis and comparison with laboratory experiments confirm that incorporation of detailed microscale physical processes in the models is compulsory. This sheds light on the inherent coupling mechanisms and bridges the gap between atomistic processes and macroscopic observations.

Figure 1

Experiment, underlying processes and modelling. (a) BSE-SEM image of the reacted sample with highlighted characteristic features (HON - HET). (b) Energy barriers and formation of critical nuclei according to CNT. The computational voxel represents a volume in the bulk where conditions for HON precipitation are met. (c) Evolution of HON and HET precipitation is affected by the transport of solutes within the porous medium and vice versa. Colors represent velocity magnitude and white streamlines the preferential flow paths of a generic transport process calculated using the lattice Boltzmann (LB) method. (d) Visualization of a model prediction where celestine crystals are depicted in blue and newly formed baryte HON precipitates are in dark yellow, HET in light yellow.

Figure 2

Interplay of precipitation mechanisms. (a) Supersaturation - nucleation time diagram including as inset the initial celestine distribution. Saturation index is calculated with respect to baryte. (b) Baryte and celestine volumetric fraction after 140 hours of reaction at SI = 4.08, 3.96, 3.8 and 3.6 (top to bottom). Colored arrows represent the predicted evolution of the system for the respective SI, highlighting the interplay of the precipitation mechanisms.

Figure 3

Evolution of precipitation versus time during 140 h. (a) Conversion of small celestine crystals to baryte as a function of reaction time (in black) including a nucleation kinetics sensitivity analysis (color), (b) partitioning of amounts of epitaxially grown- and nano-crystalline- baryte after 140 h for the different cases.

Figure 4

Temporal evolution of the epitaxially grown baryte rim. Higher values of SI result in thinner and slower growth of baryte rims (HET) due to accelerated nano-crystalline formation (HON). Different colors represent the temporal evolution in hours. For SI = 3.96 the average baryte rim thickness is predicted to be L _sim = 4.5 μm and is in very good agreement with the post-mortem analysis of the reactive experiment which measures L _exp = 4.2 μm.

Figure 5

Schematic of the laboratory experiment. A zone of celestine grains (SrSO₄) is positioned between two layers of quartz (SiO₂). Barium chloride BaCl₂ rich solution is injected from the inlet on the left side and causes the dissolution of celestine. Baryte precipitation changes the topology and hydrodynamic properties of the former celestine zone. Post mortem microscopic characterization the reacted zone allows identifying the involved precipitation mechanisms.