175 research outputs found

    A model of dispersive transport across sharp interfaces between porous materials

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    Recent laboratory experiments on solute migration in composite porous columns have shown an asymmetry in the solute arrival time upon reversal of the flow direction, which is not explained by current paradigms of transport. In this work, we propose a definition for the solute flux across sharp interfaces and explore the underlying microscopic particle dynamics by applying Monte Carlo simulation. Our results are consistent with previous experimental findings and explain the observed transport asymmetry. An interpretation of the proposed physical mechanism in terms of a flux rectification is also provided. The approach is quite general and can be extended to other situations involving transport across sharp interfaces.Comment: 4 pages, 4 figure

    Prediction of the absolute hydraulic conductivity function from soil water retention data

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    For modeling flow and transport processes in the soil–plant–atmosphere system, knowledge of the unsaturated hydraulic properties in functional form is mandatory. While much data are available for the water retention function, the hydraulic conductivity function often needs to be predicted. The classical approach is to predict the relative conductivity from the retention function and scale it with the measured saturated conductivity, Ks. In this paper we highlight the shortcomings of this approach, namely, that measured Ks values are often highly uncertain and biased, resulting in poor predictions of the unsaturated conductivity function. We propose to reformulate the unsaturated hydraulic conductivity function by replacing the soil-specific Ks as a scaling factor with a generally applicable effective saturated tortuosity parameter τs and predicting total conductivity using only the water retention curve. Using four different unimodal expressions for the water retention curve, a soil-independent general value for τs was derived by fitting the new formulation to 12 data sets containing the relevant information. τs was found to be approximately 0.1. Testing of the new prediction scheme with independent data showed a mean error between the fully predicted conductivity functions and measured data of less than half an order of magnitude. The new scheme can be used when insufficient or no conductivity data are available. The model also helps to predict the saturated conductivity of the soil matrix alone and thus to distinguish between the macropore conductivity and the soil matrix conductivity.</p

    Multiscale pore-network reconstruction of a fine-textured heterogeneous soil.

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    Abstract Digital samples offer many opportunities to study subsurface fluid flow and contaminant transport processes. The pore size distribution of especially fine-textured porous media often covers many orders of magnitude in the length scale, which makes accurate microCT scanning and modeling of the underlying processes difficult. When a single-resolution image is not capable of capturing all relevant details of a sample, one should scan the sample, or selected parts of it, at different resolutions. Combining multiple resolutions into one single sample for subsequent pore-scale modeling is generally not possible due to limitations in computer memory and speed, thus making it necessary to create a simpler sample containing relevant information from the parent networks. We imaged four samples using different resolutions to capture the multiscale heterogeneity of a fine-textured soil and combined them into one overall digital sample based on the original pore networks. The parent networks were characterized using their geometrical properties, correlations between these properties, and connectivity functions describing the network topologies. Our approach creates stochastic networks of arbitrary size with the same flow properties as the parent network. The method, implemented using the PoreStudio pore network model, repeatedly integrates information at two subsequent scales, with the resulting digital sample having the same hydraulic properties as the original samples. The procedure leads to more useful three-dimensional digital models, facilitating basic analyses of underlying pore size distributions. Porosity calculations were compared with direct measurements, while those for the hydraulic conductivity were compared with estimates based on the particle size distribution and nearby field data

    Impacts of Mineralogy on Petrophysical Properties

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    Because of their extreme heterogeneity at multiple scales, carbonate rocks present a great challenge for studying and managing oil reservoirs. Depositional processes and diagenetic alterations of carbonates may have produced very complex pore structures and, consequently, variable fluid storage and flow properties of hydrocarbon reservoirs. To understand the impact of mineralogy on the pore system, we analyzed four carbonate rock samples (coquinas) from the Morro do Chaves Formation in Brazil. For this study, we used thin sections and XRD for their mineralogical characterization, together with routine core analysis, NMR, MICP and microCT for the petrophysical characterizations. The samples revealed very similar porosity values but considerably different permeabilities. Samples with a relatively high quartz content (terrigenous material) generally had lower permeabilities, mostly caused by more mineral fragmentation. Samples with little or no quartz in turn exhibited high permeabilities due to less fragmentation and more diagenetic actions (e.g., dissolution of shells). Results confirm that carbonate minerals are very susceptible to diagenesis, leading to modifications in their pore body and pore throat sizes, and creating pores classified as moldic and vug pores, or even clogging them. For one of the samples, we acquired detailed pore skeleton information based on microCT images to obtain a more complete understanding of its structural characteristics

    Effects of carbonated water injection on the pore system of a carbonate rock (coquina)

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    CO2 injection is a well-known Enhanced Oil Recovery (EOR) technique that has been used for years to improve oil extraction from carbonate rock and other oil reservoirs. Optimal functioning of CO2 injection requires a thorough understanding of how this method affects the petrophysical properties of the rocks. We evaluated pore-scale changes in these properties, notably porosity and absolute permeability, following injection of CO2-saturated water in two coquina outcrop samples from the Morro do Chaves Formation in Brazil. The coquinas are close analogues of Pre-salt oil reservoirs off the coast of southern Brazil. The effects of carbonated water injection were evaluated using a series of experimental and numerical steps before and after coreflooding: cleaning, basic petrophysics, microtomography (microCT) imaging, nuclear magnetic resonance (NMR) analyses, and pore network modeling (PNM). Our study was motivated by an earlier experiment which did not show the development of a wormhole in the center of the sample, with a concomitant increase in permeability of the coquina as often noted in the literature. We instead observed a substantial decrease in the absolute permeability (between 71 and 77%), but with little effect on the porosity and no wormhole formation. While all tests were carried out on both samples, here we present a comprehensive analysis for one of the samples to illustrate changes at the pore network level. Different techniques were used for the pore-scale analyses, including pore network modeling using PoreStudio, and software developed by the authors to enable a statistical analysis of the pore network. Results provided much insight in how injected carbonated water affects the pore network of carbonate rocks
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