arXiv subjects

Samuel J. Jackson

Publications and source records attributed to Samuel J. Jackson.

6 recordsLinked to original sources

arXiv2025

Unstable drainage dynamics during multiphase flow across capillary heterogeneities

We use novel, fast 4D Synchrotron X-ray imaging with large field-of-view to reveal pore- and macro-scale drainage dynamics during gas-brine flow through a layered sandstone rock sample. We show that a single centimetre-scale layer, similar in pore size distribution to the surrounding rock but with reduced connectivity, temporarily inhibits and redirects gas flow, acting as a capillary barrier. Subtle variations in gas invasion upstream of the barrier lead to different downstream migration pathways over repeated experiments, resulting in unstable and unpredictable drainage behaviour, with breakthrough times varying by up to a factor of four. The results show that heterogeneity in pore-scale connectivity can amplify variability in macroscopic flow, challenging deterministic assumptions in existing continuum models. By linking structural heterogeneity to flow instability, this work underscores the need for probabilistic modelling approaches in multiphase flow and highlights broader implications for managing fluid transport in natural and engineered porous systems.

physics.flu-dyn↗

arXiv2025

Rate dependency of capillary heterogeneity trapping for CO2 storage

In this paper, we experimentally quantify and analytically model rate dependent capillary heterogeneity trapping. Capillary heterogeneity trapping enhances non-wetting fluid trapping beyond pore-scale residual trapping through the isolation of non-wetting phase upstream of heterogeneities in the continuum capillary pressure characteristics. Whilst residual trapping is largely insensitive to the range of flow regimes prevalent in engineered reservoir settings, continuum theory anticipates that capillary heterogeneity trapping will be more sensitive to the balance of viscous and capillary forces that occur. We perform steady-state drainage and imbibition multiphase flow experiments at varying flow rate on a layered Bentheimer sample with in-situ medical X-ray CT scanning to quantify saturation. Saturation discontinuities are observed upstream of capillary pressure barriers as a result of capillary pressure discontinuities, trapping the non-wetting phase at a saturation greater than pore-scale residual trapping alone. We confirm the flow rate dependence predicted by theory whereby the relationship between the initial and residual saturations approach a 1:1 dependence as flow rate is decreased. We develop a one-dimensional analytical model to quantify the proportion of capillary heterogeneity trapping in the system and the dimensionless trapping length scale, which agrees with the experimental data and allows for rapid estimates of trapping up to the field-scale.

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arXiv2023

The FluidFlower International Benchmark Study: Process, Modeling Results, and Comparison to Experimental Data

Successful deployment of geological carbon storage (GCS) requires an extensive use of reservoir simulators for screening, ranking and optimization of storage sites. However, the time scales of GCS are such that no sufficient long-term data is available yet to validate the simulators against. As a consequence, there is currently no solid basis for assessing the quality with which the dynamics of large-scale GCS operations can be forecasted. To meet this knowledge gap, we have conducted a major GCS validation benchmark study. To achieve reasonable time scales, a laboratory-size geological storage formation was constructed (the "FluidFlower"), forming the basis for both the experimental and computational work. A validation experiment consisting of repeated GCS operations was conducted in the FluidFlower, providing what we define as the true physical dynamics for this system. Nine different research groups from around the world provided forecasts, both individually and collaboratively, based on a detailed physical and petrophysical characterization of the FluidFlower sands. The major contribution of this paper is a report and discussion of the results of the validation benchmark study, complemented by a description of the benchmarking process and the participating computational models. The forecasts from the participating groups are compared to each other and to the experimental data by means of various indicative qualitative and quantitative measures. By this, we provide a detailed assessment of the capabilities of reservoir simulators and their users to capture both the injection and post-injection dynamics of the GCS operations.

physics.geo-ph↗

arXiv2022

Deep learning of multi-resolution X-Ray micro-CT images for multi-scale modelling

Field-of-view and resolution trade-offs in X-Ray micro-computed tomography (micro-CT) imaging limit the characterization, analysis and model development of multi-scale porous systems. To this end, we developed an applied methodology utilising deep learning to enhance low resolution images over large sample sizes and create multi-scale models capable of accurately simulating experimental fluid dynamics from the pore (microns) to continuum (centimetres) scale. We develop a 3D Enhanced Deep Super Resolution (EDSR) convolutional neural network to create super resolution (SR) images from low resolution images, which alleviates common micro-CT hardware/reconstruction defects in high-resolution (HR) images. When paired with pore-network simulations and parallel computation, we can create large 3D continuum-scale models with spatially varying flow & material properties. We quantitatively validate the workflow at various scales using direct HR/SR image similarity, pore-scale material/flow simulations and continuum scale multiphase flow experiments (drainage immiscible flow pressures and 3D fluid volume fractions). The SR images and models are comparable to the HR ground truth, and generally accurate to within experimental uncertainty at the continuum scale across a range of flow rates. They are found to be significantly more accurate than their LR counterparts, especially in cases where a wide distribution of pore-sizes are encountered. The applied methodology opens up the possibility to image, model and analyse truly multi-scale heterogeneous systems that are otherwise intractable.

physics.geo-ph↗

arXiv2021

A comparative study of paired versus unpaired deep learning methods for physically enhancing digital rock image resolution

X-ray micro-computed tomography (micro-CT) has been widely leveraged to characterise pore-scale geometry in subsurface porous rock. Recent developments in super resolution (SR) methods using deep learning allow the digital enhancement of low resolution (LR) images over large spatial scales, creating SR images comparable to the high resolution (HR) ground truth. This circumvents traditional resolution and field-of-view trade-offs. An outstanding issue is the use of paired (registered) LR and HR data, which is often required in the training step of such methods but is difficult to obtain. In this work, we rigorously compare two different state-of-the-art SR deep learning techniques, using both paired and unpaired data, with like-for-like ground truth data. The first approach requires paired images to train a convolutional neural network (CNN) while the second approach uses unpaired images to train a generative adversarial network (GAN). The two approaches are compared using a micro-CT carbonate rock sample with complicated micro-porous textures. We implemented various image based and numerical verifications and experimental validation to quantitatively evaluate the physical accuracy and sensitivities of the two methods. Our quantitative results show that unpaired GAN approach can reconstruct super-resolution images as precise as paired CNN method, with comparable training times and dataset requirement. This unlocks new applications for micro-CT image enhancement using unpaired deep learning methods; image registration is no longer needed during the data processing stage. Decoupled images from data storage platforms can be exploited more efficiently to train networks for SR digital rock applications. This opens up a new pathway for various applications of multi-scale flow simulation in heterogeneous porous media.

eess.IV↗

arXiv2021

The effect of viscosity ratio and Peclet number on miscible viscous fingering in a Hele-Shaw cell: A combined numerical and experimental study

The results from a series of well characterised, unstable, miscible displacement experiments in a Hele Shaw cell with a quarter five-spot source-sink geometry are presented, with comparisons to detailed numerical simulation. We perform repeated experiments at adverse viscosity ratios from 1 - 20 and Peclet numbers from 10$^4$ - 10$^6$ capturing the transition from 2D to 3D radial fingering and experimental uncertainty. The open-access dataset provides time-lapse images of the fingering patterns, transient effluent profiles, and meta-information for use in model validation. We find the complexity of the fingering pattern increases with viscosity ratio and Peclet number, and the onset of fingering is delayed compared to linear displacements, likely due to Taylor dispersion stabilisation. The transition from 2D to 3D fingering occurs at a critical Peclet number that is consistent with recent experiments in the literature. 2D numerical simulations with hydrodynamic dispersion and different mesh orientations provide good predictions of breakthrough times and sweep efficiency obtained at intermediate Peclet numbers across the range of viscosity ratios tested, generally within the experimental uncertainty. Specific finger wavelengths, tip shapes, and growth are hard to replicate; model predictions using velocity dependent longitudinal dispersion or simple molecular diffusion bound the fingering evolution seen in the experiments, but neither fully capture both fine-scale and macroscopic measures. In both cases simulations predict sharper fingers than the experiment. A weaker dispersion stabilisation seems necessary to capture the experimental fingering at high viscosity ratio, which may also require anisotropic components. 3D models with varying dispersion formulations should be explored in future developments to capture the full range of effects at high viscosity ratio and Peclet number.

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