A double-continuum transport model for segregated porous media: Derivation and sensitivity analysis-driven calibration

Ceriotti, Giulia; Russian, Anna; Bolster, Diogo; Porta, Giovanni

doi:10.1016/j.advwatres.2019.04.003

Cited by 14 publications

(6 citation statements)

References 70 publications

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“…However, in this study, such parameterizations were derived from high‐fidelity models that required Lagrangian particle tracking statistics. How to parameterize the modified Bernoulli models from field observations remains unclear and requires further investigation, although detailed geostatical measures may aid in that regard (Ceriotti et al, ). Furthermore, the conclusions of this study are drawn from networks with only three percolation lengths and where fracture radii are sampled from a power law distribution that spans a single order of magnitude and has a constant

α

exponent, and so our conclusions may not reflect universal behavior.…”

Section: Discussionmentioning

confidence: 99%

Characterizing the Influence of Fracture Density on Network Scale Transport

et al. 2020

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The topology of natural fracture networks is inherently linked to the structure of the fluid velocity field and transport therein. Here we study the impact of network density on flow and transport behaviors. We stochastically generate fracture networks of varying density and simulate flow and transport with a discrete fracture network model, which fully resolves network topology at the fracture scale. We study conservative solute trajectories with Lagrangian particle tracking and find that as fracture density decreases, solute channelization to large local fractures increases, thereby reducing plume spreading. Furthermore, in sparse networks mean particle travel distance increases and local network features, such as velocity zones where flow is counter to the primary pressure gradient, become increasingly important for transport. As the network density increases, network statistics homogenize and such local features have a reduced impact. We quantify local topological influence on transport behavior with an effective tortuosity parameter, which measures the ratio of total advective distance to linear distance at the fracture scale; large tortuosity values are correlated to slow-velocity regions. These large tortuosity, slow-velocity regions delay downstream transport and enhance tailing on particle breakthrough curves. Finally, we predict transport with an upscaled, Bernoulli spatial Markov random walk model and parameterize local topological influences with a novel tortuosity parameter. Bernoulli model predictions improve when sampling from a tortuosity distribution, as opposed to a fixed value as has previously been done, suggesting that local network topological features must be carefully considered in upscaled modeling efforts of fracture network systems. and topology, and the corresponding flow field. The flow field within an individual fracture is typically highly correlated, commonly causing solute velocity to display persistent, low variability behavior over the in-fracture scale; consequently, the greatest Lagrangian accelerations occur at fracture intersections . As the fracture density increases, solute encounters more intersections on average, and the velocity correlation scale decreases. Furthermore, strong preferential flow paths form within interconnected networks of large fractures and channel a significant portion of mass, enabling solute to persist at high velocities for distances greater than the single fracture scale Sherman et al., 2019). This channelization becomes enhanced in sparse networks, where particles encounter fewer intersections, enabling them to persist on single fractures for longer distances. Resolving all these intranetwork features in 3-D DFN models is still computationally costly, and so upscaled modeling approaches, which account for network variability through effective parameter schemes, while maintaining a parsimonious framework, present an attractive alternative. However, how to properly parameterize network properties, such as velocity correlation and geometry, and inco...

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α

exponent, and so our conclusions may not reflect universal behavior.…”

Section: Discussionmentioning

confidence: 99%

Characterizing the Influence of Fracture Density on Network Scale Transport

et al. 2020

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“…The average pore size is equal to 0.05 mm . The resulting velocity field in the porous space is also power law-distributed and spans 5 orders of magnitude, consistent with those observed in natural sediments, e.g., sandstone. , …”

Section: Methodsmentioning

confidence: 99%

“…52 The resulting velocity field in the porous space is also power law-distributed 39 and spans 5 orders of magnitude, consistent with those observed in natural sediments, e.g., sandstone. 40,41 Using classical soft lithography, the porous geometry (Figure 1A) was printed onto a microfluidic master with a thickness of h = 50 μm (i.e., similar to the average pore-throat size l pt ). This was used to mold PDMS chip replicates (Sylgard 184 Silicone Elastomer mixed with 10 w/w % of a curing agent; supplier: Dow Corning, Midland, MI).…”

Section: ■ Introductionmentioning

confidence: 99%

Morphology and Size of Bacterial Colonies Control Anoxic Microenvironment Formation in Porous Media

Ceriotti

Borisov

Berg

et al. 2022

Environ. Sci. Technol.

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Bacterial metabolisms using electron acceptors other than oxygen (e.g., methanogenesis and fermentation) largely contribute to element cycling and natural contaminant attenuation/mobilization, even in well-oxygenated porous environments, such as shallow aquifers. This paradox is commonly explained by the occurrence of small-scale anoxic microenvironments generated by the coupling of bacterial respiration and dissolved oxygen (O 2 ) transport by pore water. Such microenvironments allow facultative anaerobic bacteria to proliferate in oxic environments. Microenvironment dynamics are still poorly understood due to the challenge of directly observing biomass and O 2 distributions at the microscale within an opaque sediment matrix. To overcome these limitations, we integrated a microfluidic device with transparent O 2 planar optical sensors to measure the temporal behavior of dissolved O 2 concentrations and biomass distributions with time-lapse videomicroscopy. Our results reveal that bacterial colony morphology, which is highly variable in flowing porous systems, controls the formation of anoxic microenvironments. We rationalize our observations through a colony-scale Damkoḧler number comparing dissolved O 2 diffusion and a bacterial O 2 uptake rate. Our Damkoḧler number enables us to predict the pore space fraction occupied by anoxic microenvironments in our system for a given bacterial organization.

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“…These authors suggest that evaluation of the block geometry, matrix permeability, as well as an appropriate use of relative permeability and capillary pressure correlations can significantly affect the evaluation of the flow transfer between the two continua. Ceriotti et al (2019) focus on the formulation, calibration, and validation of a dual-continuum model for solute transport in porous media. In this context, the authors suggest that relying on sensitivity analysis techniques to diagnose the behavior of a given simulation model can be an efficient tool to design ad-hoc metrics for model calibration.…”

Section: Introductionmentioning

confidence: 99%

Sensitivity-based Parameter Calibration of Single- and Dual-continuum Coreflooding Simulation Models

et al. 2022

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Our study is keyed to the development of a viable framework for the stochastic characterization of coreflooding simulation models under two- and three-phase flow conditions taking place within a core sample in the presence of preferential flow of the kind that can be associated with the presence of a system of fractures. We do so considering various modeling strategies based on (spatially homogeneous or heterogeneous) single- and dual-continuum formulations of black-oil computational models and relying on a global sensitivity-driven stochastic parameter calibration. The latter is constrained through a set of data collected under a water alternating gas scenario implemented in laboratory-scale coreflooding experiments. We set up a collection of Monte Carlo (MC) numerical simulations while considering uncertainty encompassing (a) rock attributes (i.e., porosity and absolute permeability), as well as (b) fluid–fluid/ fluid–solid interactions, as reflected through characteristic parameters of relative permeability and capillary pressure formulations. Modern moment-based global sensitivity indices are evaluated on the basis of the MC model responses, with the aim of (i) quantifying sensitivity of the coreflooding simulation results to variations of the input uncertain model parameters and (ii) assessing the possibility of reducing the dimensionality of model parameter spaces. We then rest on a stochastic inverse modeling approach grounded on the acceptance–rejection sampling (ARS) algorithm to obtain probability distributions of the key model parameters (as identified through our global sensitivity analyses) conditional to the available experimental observations. The relative skill of the various candidate models to represent the system behavior is quantified upon relying on the deviance information criterion. Our findings reveal that amongst all tested models, a dual-continuum formulation provides the best performance considering the experimental observations available. Only a few of the parameters embedded in the dual-continuum formulation are identified as major elements significantly affecting the prediction (and associated uncertainty) of model outputs, petrophysical attributes and relative permeability model parameters having a stronger effect than parameters related to capillary pressure.

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A double-continuum transport model for segregated porous media: Derivation and sensitivity analysis-driven calibration

Cited by 14 publications

References 70 publications

Characterizing the Influence of Fracture Density on Network Scale Transport

Characterizing the Influence of Fracture Density on Network Scale Transport

Morphology and Size of Bacterial Colonies Control Anoxic Microenvironment Formation in Porous Media

Sensitivity-based Parameter Calibration of Single- and Dual-continuum Coreflooding Simulation Models

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