Reservoir condition pore-scale imaging of reaction

This thesis presents the first dynamic imaging of fluid/rock reaction using x- ray microtomography (μ-CT) and focuses on three series of experiments: (1) imaging a homogenous carbonate during dissolution using a laboratory scanner; (2) imaging heterogeneous carbonates at multiple flow rates using a synchrotron pink beam; (3) imaging the same rocks using a laboratory scanner at multiple reactive conditions incorporating effluent analysis. First the in situ reservoir condition imaging apparatus was adapted to image Ketton carbonate dynamically using a laboratory μ-CT scanner. 10 images were acquired over 2 1⁄2 hours. Porosity and surface area were measured from the images and permeability and connectivity were calculated using flow models. Ketton dissolved uniformly at these conditions although the effective reaction rate (reff) was 16 times lower than those measured in batch reactor experiments with no transport limitations. Second the experimental apparatus was used with fast synchrotron-based μ- CT to image two more complex carbonates, Estaillades and Portland Basebed at two different flow conditions. ~100 images were taken over 2 hours, which captured the complexity of dissolution. It was found that the type of dissolution is both pore structure and flow rate dependent. A new type of dissolution, channelling, is observed which has a reff up to 100 times lower than batch rates. Third, effluent analysis was incorporated into the experimental apparatus. All three rocks were imaged again at two separate reactive conditions. The reff was between 10 and 100 times lower than the batch rates, with the lowest rates in samples with the most channelized flow, confirming that transport limitations are the dominant mechanism in determining reff at the fluid/solid boundary. Effluent analysis confirmed that using the in situ, rather than the injected pH, to determine reff is valid in the uniform regime, but overestimates reff with channelling by an order of magnitude.Open Acces

Channeling: a new class of dissolution in complex porous media

The current conceptual model of mineral dissolution in porous media is comprised of three dissolution patterns (wormhole, compact, and uniform) - or regimes - that develop depending on the relative dominance of flow, diffusion, and reaction rate. Here, we examine the evolution of pore structure during acid injection using numerical simulations on two porous media structures of increasing complexity. We examine the boundaries between regimes and characterise the existence of a forth regime called channeling, where already existing fast flow pathways are preferentially widened by dissolution. Channeling occurs in cases where the distribution in pore throat size results in orders of magnitude differences in flow rate for different flow pathways. This focusing of dissolution along only dominant flow paths induces an immediate, large change in permeability with a comparatively small change in porosity, resulting in a porosity-permeability relationship unlike any that has been previously seen. This work demonstrates that our current conceptual model of dissolution regimes must be modified to include channeling for accurate predictions of dissolution in applications such as geologic carbon storage and geothermal energy production

Upscaling the porosity-permeability relationship of a microporous carbonate to the Darcy scale with machine learning

The permeability of a pore structure is typically described by stochastic representations of its geometrical attributes. Database-driven numerical solvers for large model domains can only accurately predict large-scale flow behaviour when they incorporate upscaled descriptions of that structure. The upscaling is particularly challenging for rocks with multimodal porosity structures such as carbonates, where several different types of structures are interacting. It is the connectivity both within and between these different structures that controls the porosity-permeability relationship at the larger length scales. Recent advances in machine learning combined with numerical modelling and structural analysis have allowed us to probe the relationship between structure and permeability more deeply. We have used this integrated approach to tackle the challenge of upscaling multimodal and multiscale porous media. We present a novel method for upscaling multimodal porosity-permeability relationships using machine learning based multivariate structural regression. A m-CT image of limestone was divided into sub-volumes and permeability was computed using the DBS model. The porosity-permeability relationship from Menke et al. was used to assign permeability values to the microporosity. Structural attributes of each sub-volume were extracted and then regressed against the solved permeability using an Extra-Trees regression model to derive an upscaled porosity-permeability relationship. Ten upscaled test cases were then modelled at the Darcy scale using the regression and benchmarked against full DBS simulations, a numerically upscaled Darcy model, and a K-C fit. We found good agreement between the full DBS simulations and both the numerical and machine learning upscaled models while the K-C model was a poor predictor in all cases

Subsurface hydrogen storage controlled by small-scale rock heterogeneities

Subsurface porous rocks have the potential to store large volumes of hydrogen (H$_2$) required for transitioning towards a H$_2$-based energy future. Understanding the flow and trapping behavior of H$_2$ in subsurface storage systems, which is influenced by pore-scale heterogeneities inherent to subsurface rocks, is crucial to reliably evaluate the storage efficiency of a geological formation. In this work, we performed 3D X-ray imaging and flow experiments to investigate the impact of pore-scale heterogeneity on H$_2$ distribution after its cyclic injection (drainage) and withdrawal (imbibition) from a layered rock sample, characterized by varying pore and throat sizes. Our findings reveal that even subtle variations in rock structure and properties significantly influence H$_2$ displacement and storage efficiency. During drainage, H$_2$ follows a path consisting of large pores and throats, bypassing the majority of the low permeability rock layer consisting of smaller pores and throats. This bypassing substantially reduces the H$_2$ storage capacity. Moreover, due to the varying pore and throat sizes in the layered sample, depending on the experimental flow strategy, we observe a higher H$_2$ saturation after imbibition compared to drainage, which is counterintuitive and opposite to that observed in homogeneous rocks. These findings emphasize that small-scale rock heterogeneity, which is often unaccounted for in reservoir-scale models, can play a vital role in the displacement and trapping of H$_2$ in subsurface porous media

Experimental investigation of solubility trapping in 3D printed micromodels

Understanding interfacial mass transfer during dissolution of gas in a liquid is vital for optimising large-scale carbon capture and storage operations. While the dissolution of CO2 bubbles in reservoir brine is a crucial mechanism towards safe CO2 storage, it is a process that occurs at the pore-scale and is not yet fully understood. Direct numerical simulation (DNS) models describing this type of dissolution exist and have been validated with semi-analytical models on simple cases like a rising bubble in a liquid column. However, DNS models have not been experimentally validated for more complicated scenarios such as dissolution of trapped CO2 bubbles in pore geometries where there are few experimental datasets. In this work we present an experimental and numerical study of trapping and dissolution of CO2 bubbles in 3D printed micromodel geometries. We use 3D printing technology to generate three different geometries, a single cavity geometry, a triple cavity geometry and a multiple channel geometry. In order to investigate the repeatability of the trapping and dissolution experimental results, each geometry is printed three times and three identical experiments are performed for each geometry. The experiments are performed at low capillary number representative of flow during CO2 storage applications. DNS simulations are then performed and compared with the experimental results. Our results show experimental reproducibility and consistency in terms of CO2 trapping and the CO2 dissolution process. At such low capillary number, our numerical simulator cannot model the process accurately due to parasitic currents and the strong time step constraints associated with capillary waves. However, we show that, for the single and triple cavity geometry

Time-resolved synchrotron X-ray micro-tomography datasets of drainage and imbibition in carbonate rocks

Multiphase flow in permeable media is a complex pore-scale phenomenon, which is important in many natural and industrial processes. To understand the pore-scale dynamics of multiphase flow, we acquired time-series synchrotron X-ray micro-tomographic data at a voxel-resolution of 3.28 μm and time-resolution of 38 s during drainage and imbibition in a carbonate rock, under a capillary-dominated flow regime at elevated pressure. The time-series data library contains 496 tomographic images (gray-scale and segmented) for the complete drainage process, and 416 tomographic images (gray-scale and segmented) for the complete imbibition process. These datasets have been uploaded on the publicly accessible British Geological Survey repository, with the objective that the time-series information can be used by other groups to validate pore-scale displacement models such as direct simulations, pore-network and neural network models, as well as to investigate flow mechanisms related to the displacement and trapping of the non-wetting phase in the pore space. These datasets can also be used for improving segmentation algorithms for tomographic data with limited projections

Characterization of Hantavirus N Protein Intracellular Dynamics and Localization

Hantaviruses are enveloped viruses that possess a tri-segmented, negative-sense RNA genome. The viral S-segment encodes the multifunctional nucleocapsid protein (N), which is involved in genome packaging, intracellular protein transport, immunoregulation, and several other crucial processes during hantavirus infection. In this study, we generated fluorescently tagged N protein constructs derived from Puumalavirus (PUUV), the dominant hantavirus species in Central, Northern, and Eastern Europe. We comprehensively characterized this protein in the rodent cell line CHO-K1, monitoring the dynamics of N protein complex formation and investigating co-localization with host proteins as well as the viral glycoproteins Gc and Gn. We observed formation of large, fibrillar PUUV N protein aggregates, rapidly coalescing from early punctate and spike-like assemblies. Moreover, we found significant spatial correlation of N with vimentin, actin, and P-bodies but not with microtubules. N constructs also co-localized with Gn and Gc albeit not as strongly as the glycoproteins associated with each other. Finally, we assessed oligomerization of N constructs, observing efficient and concentration-dependent multimerization, with complexes comprising more than 10 individual proteins

Limits for Recombination in a Low Energy Loss Organic Heterojunction

Donor–acceptor organic solar cells often show high quantum yields for charge collection, but relatively low open-circuit voltages (V$_{OC}$) limit power conversion efficiencies to around 12%. We report here the behavior of a system, PIPCP:PC$_{61}$BM, that exhibits very low electronic disorder (Urbach energy less than 27 meV), very high carrier mobilities in the blend (field-effect mobility for holes >10$^{-2}$ cm$^{2}$ V$^{-1}$ s$^{-1}$), and a very low driving energy for initial charge separation (50 meV). These characteristics should give excellent performance, and indeed, the V$_{OC}$ is high relative to the donor energy gap. However, we find the overall performance is limited by recombination, with formation of lower-lying triplet excitons on the donor accounting for 90% of the recombination. We find this is a bimolecular process that happens on time scales as short as 100 ps. Thus, although the absence of disorder and the associated high carrier mobility speeds up charge diffusion and extraction at the electrodes, which we measure as early as 1 ns, this also speeds up the recombination channel, giving overall a modest quantum yield of around 60%. We discuss strategies to remove the triplet exciton recombination channel.SMM, RHF, MKR, SAA, and JLB acknowledge support from the KAUST Competitive Research Grant Program. MKR, SAA, and JLB also acknowledge generous support of their work by KAUST and the Office of Naval Research Global (Award N62909­15­1­2003); they thank the KAUST IT Research Computing Team and Supercomputing Laboratory for providing computational and storage resources. NAR, MW, TQN, and GCB acknowledge support from the Department of the Navy, Office of Naval Research (Award Nos. N00014-14-1-0580 and N00014-16-1-25200. AS would like to acknowledge the funding and support from the India-UK APEX project. HLS acknowledges support from the Winton Programme for the Physics of Sustainability. MN and HS gratefully acknowledge financial support from the Engineering and Physical Sciences Research Council though a Programme Grant (EP/M005141/1)