Combination of MRI and SEM to Assess Changes in the Chemical Properties and Permeability of Porous Media due to Barite Precipitation

A radiochemical lab-on-a-chip paired with computer vision to unlock the crystallization kinetics of (Ba,Ra)SO4

(Ra,Ba)SO4 solid solutions are commonly encountered as problematic scales in subsurface energy-related applications, e.g., geothermal systems, hydraulic fracturing, conventional oil and gas, etc. Despite its relevance, its crystallization kinetics were never determined because of radium (226), high radioactivity (3.7 × 1010 Bq g-1), and utilization in contemporary research, therefore constrained to trace amounts (< 10-8 M) with the composition of BaxRa1-xSO4 commonly restricted to x > 0.99. What if lab-on-a-chip technology could create new opportunities, enabling the study of highly radioactive radium beyond traces to access new information? In this work, we developed a lab-on-a-chip experiment paired with computer vision to evaluate the crystal growth rate of (Ba,Ra)SO4 solid solutions. The computer vision algorithm enhances experimental throughput, yielding robust statistical insights and further advancing the efficiency of such experiments. The 3D analysis results of the precipitated crystals using confocal Raman spectroscopy suggested that {210} faces grew twice as fast as {001} faces, mirroring a common observation reported for pure barite. The crystal growth rate of (Ba0.5Ra0.5)SO4 follows a second-order reaction with a kinetic constant equal to (1.23 ± 0.09) × 10-10 mol m-2 s-1.

A Lab on a Chip Experiment for Upscaling Diffusivity of Evolving Porous Media

Reactive transport modelling is a powerful tool to assess subsurface evolution in various energy-related applications. Upscaling, i.e., accounting for pore scale heterogeneities into larger scale analyses, remains one of the biggest challenges of reactive transport modelling. Pore scale simulations capturing the evolutions of the porous media over a wide range of Peclet and Damköhler number in combination with machine learning are foreseen as an efficient methodology for upscaling. However, the accuracy of these pore scale models needs to be tested against experiments. In this work, we developed a lab on a chip experiment with a novel micromodel design combined with operando confocal Raman spectroscopy, to monitor the evolution of porous media undergoing coupled mineral dissolution and precipitation processes due to diffusive reactive fluxes. The 3D-imaging of the porous media combined with pore scale modelling enabled the derivation of upscaled transport parameters. The chemical reaction tested involved the replacement of celestine by strontianite, whereby a net porosity increase is expected because of the smaller molar volume of strontianite. However, under our experimental conditions, the accessible porosity and consequently diffusivity decreased. We propose a transferability of the concepts behind the Verma and Pruess relationship to be applied to also describe changes of diffusivity for evolving porous media. Our results highlight the importance of calibrating pore scale models with quantitative experiments prior to simulations over a wide range of Peclet and Damköhler numbers of which results can be further used for the derivation of upscaled parameters.

A lab-on-a-chip approach integrating in-situ characterization and reactive transport modelling diagnostics to unravel (Ba,Sr)SO4 oscillatory zoning

The co-precipitation of sulphate minerals such as celestine and barite is widely studied because their formation is ubiquitous in natural and anthropogenic systems. Co-precipitation in porous media results in crystallization of solid solutions yielding characteristics such as oscillatory zoning that are rarely observed in bulk solution or in batch experiments. In the past, the precipitation of compositionally-zoned (Ba,Sr)SO₄ crystals was observed post-mortem in macroscopic silica gel counter-diffusion experiments. Their formation was originally explained by the difference in the solubility products of the end-members combined with diffusion-limited transport of solutes to the mineral-fluid interface, while a later study favored the idea of kinetically controlled reactions. With recent advances combining in-operando microfluidic experiments and reactive transport modelling, it is now possible to verify hypotheses on the driving forces of transport-coupled geochemical processes. We developed a “lab on a chip” experiment that enabled the systematic study of the nucleation and growth of oscillatory-zoned (Ba,Sr)SO₄ crystals in a microfluidic reactor. The compositions of the solid solutions were determined by in-situ Raman spectroscopy. Our investigation shows (1) that the composition of the nucleating phases can be approximated using classical nucleation theory, (2) that the oscillatory zoning is not solely controlled by the limited diffusional transport of solutes, and (3) that nucleation kinetics plays a major role in the switch between different stoichiometric compositions. The zoning phenomena is governed by the complex interplay between the diffusion of reactants and the crystallization kinetics as well as other factors, e.g. surface tension and lattice mismatch.

Barite Scaling Potential Modelled for Fractured-Porous Geothermal Reservoirs

Barite scalings are a common cause of permanent formation damage to deep geothermal reservoirs. Well injectivity can be impaired because the ooling of saline fluids reduces the solubility of barite, and the continuous re-injection of supersaturated fluids forces barite to precipitate in the host rock. Stimulated reservoirs in the Upper Rhine Graben often have multiple relevant flow paths in the porous matrix and fracture zones, sometimes spanning multiple stratigraphical units to achieve the economically necessary injectivity. While the influence of barite scaling on injectivity has been investigated for purely porous media, the role of fractures within reservoirs consisting of both fractured and porous sections is still not well understood. Here, we present hydro-chemical simulations of a dual-layer geothermal reservoir to study the long-term impact of barite scale formation on well injectivity. Our results show that, compared to purely porous reservoirs, fractured porous reservoirs have a significantly reduced scaling risk by up to 50%, depending on the flow rate ratio of fractures. Injectivity loss is doubled, however, if the amount of active fractures is increased by one order of magnitude, while the mean fracture aperture is decreased, provided the fractured aquifer dictates the injection rate. We conclude that fractured, and especially hydraulically stimulated, reservoirs are generally less affected by barite scaling and that large, but few, fractures are favourable. We present a scaling score for fractured-porous reservoirs, which is composed of easily derivable quantities such as the radial equilibrium length and precipitation potential. This score is suggested for use approximating the scaling potential and its impact on injectivity of a fractured-porous reservoir for geothermal exploitation.

Full-Harmonics Phasor Analysis: Unravelling Multiexponential Trends in Magnetic Resonance Imaging Data

Phasor analysis is a robust, nonfitting, method for the study of multiexponential decays in lifetime imaging data, routinely used in Fluorescence Lifetime Imaging Microscopy (FLIM) and only recently validated for Magnetic Resonance Imaging (MRI). In the established phasor approach, typically only the first Fourier harmonic is used to unravel time-domain exponential trends and their intercorrelations across image voxels. Here, we demonstrate the potential of full-harmonics (FH) phasor analysis by using all frequency-domain data points in simulations and quantitative MRI (qMRI) T₂ measurements of phantoms with bulk liquids or liquid-filled porous particles and of a human brain. We show that FH analysis, while of limited advantage in FLIM due to the correlated nature of shot noise, in MRI outperforms single-harmonic phasor in unravelling multiple physical environments and partial-volume effects otherwise undiscernible. We foresee application of FH phasor to, e.g., big-data analysis in qMRI of biological or other multiphase systems, where multiparameter fitting is unfeasible.

Microfluidic flow-through reactor and 3D Raman imaging for in situ assessment of mineral reactivity in porous and fractured porous media

An in-depth understanding of dissolution and precipitation of minerals in porous and fractured porous media and the complex feedback on the transport of fluids is essential for various subsurface applications. In this context, we developed a novel non-destructive "lab-on-chip" approach for quantitative in situ assessments of mineralogical changes in porous media. Our experimental approach involves a microfluidic flow-through reactor of reactive homogeneous and heterogeneous (fractured) porous media coupled with high-resolution imaging. Here, the reactive medium consists of compacted celestine grains seeded in a reservoir within the microfluidic chip. This medium reacts with a barium chloride solution injected into the microreactor at a constant flow rate, leading to the dissolution of celestine and growth of barite. Various seeding processes of the mineral grains allow the creation of homogeneous reactive porous media or the introduction of large heterogeneities such as fractures. Hence, our approach enables high-resolution investigations of reactive transport in fractured porous media. The use of confocal Raman spectroscopic techniques enables the spatio-temporal visualization of the mineral transformation at the pore-scale in two- and three-dimensions. Moreover, advanced pore-scale modelling correlates the hydrological heterogeneities to the geochemical observations in the micro-reactor, which explains the observed discrepancies between homogeneous and heterogeneous reactive media. Eventually, the proposed methodology can be applied to other chemical systems to provide new insights into hydro-geochemical coupling in porous and fractured porous media as well as high-fidelity datasets to benchmark reactive transport codes that are currently under development.

Nature-Inspired Optimization Algorithms for the 3D Reconstruction of Porous Media

One of the most challenging problems that are still open in the field of materials science is the 3D reconstruction of porous media using information from a single 2D thin image of the original material. Such a reconstruction is only feasible subject to some important assumptions that need to be made as far as the statistical properties of the material are concerned. In this study, the aforementioned problem is investigated as an explicitly formulated optimization problem, with the phase of each porous material point being decided such that the resulting 3D material model shows the same statistical properties as its corresponding 2D version. Based on this problem formulation, herein for the first time, several traditional (genetic algorithms—GAs, particle swarm optimization—PSO, differential evolution—DE), as well as recently proposed (firefly algorithm—FA, artificial bee colony—ABC, gravitational search algorithm—GSA) nature-inspired optimization algorithms were applied to solve the 3D reconstruction problem. These algorithms utilized a newly proposed data representation scheme that decreased the number of unknowns searched by the optimization process. The advantages of addressing the 3D reconstruction of porous media through the application of a parallel heuristic optimization algorithm were clearly defined, while appropriate experiments demonstrating the greater performance of the GA algorithm in almost all the cases by a factor between 5%–84% (porosity accuracy) and 3%–15% (auto-correlation function accuracy) over the PSO, DE, FA, ABC, and GSA algorithms were undertaken. Moreover, this study revealed that statistical functions of a high order need to be incorporated into the reconstruction procedure to increase the reconstruction accuracy.