340 research outputs found

    Event-based contact angle measurements inside porous media using time-resolved micro-computed tomography

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    Hypothesis: Capillary-dominated multiphase flow in porous materials is strongly affected by the pore walls' wettability. Recent micro-computed tomography (mCT) studies found unexpectedly wide contact angle distributions measured on static fluid distributions inside the pores. We hypothesize that analysis on time-resolved mCT data of fluid invasion events may be more directly relevant to the fluid dynamics. Experiment: We approximated receding contact angles locally in time and space on time-resolved mCT datasets of drainage in a glass bead pack and a limestone. Whenever a meniscus suddenly entered one or more pores, geometric and thermodynamically consistent contact angles in the surrounding pores were measured in the time step just prior to the displacement event. We introduced a new force-based contact angle, defined to recover the measured capillary pressure in the invaded pore throat prior to interface movement. Findings: Unlike the classical method, the new geometric and force-based contact angles followed plausible, narrower distributions and were mutually consistent. We were unable to obtain credible results with the thermodynamically consistent method, likely because of sensitivity to common imaging artifacts and neglecting dissipation. Time-resolved mCT analysis can yield a more appropriate wettability characterization for pore scale models, despite the need to further reduce image analysis uncertainties. (C) 2020 The Authors. Published by Elsevier Inc

    Two-phase flow in rocks : new insights from multi-scale pore network modeling and fast pore scale visualization

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    Many geological applications involve the flow of multiple fluids through porous geological materials, e.g. environmental remediation of polluted ground water resources, carbon dioxide storage in geological reservoirs and petroleum recovery. Commonly, to model these applications, the geological materials in question are treated as continuous porous media with effective material properties. Since these properties are a manifestation of what goes on in the pores of the material, we have to study the transport processes at the pore scale to understand why and how they vary over space and time in different rocks and under different conditions. As the high cost of acquiring and testing samples in many of these applications is often a limiting factor, numerical modelling at the pore scale is becoming a key technology to gain new insights in this field. This could be crucial in reducing uncertainties in field scale projects. The work presented in this thesis focuses on the investigation of two-phase flow in sedimentary rocks, and is an integrated numerical and experimental study. It deals primarily with two outstanding issues. First, image-based pore scale simulation methods have difficulties with representing the multiple pore scales in rocks with wide pore size distributions, due to a trade-off in the size and resolution of both modeling and imaging methods. Therefore, performing two-phase flow simulations in a number of important rock types, such as many carbonates and tight, clay-baring sandstones has remained an outstanding challenge. To tackle this problem, a new numerical model was developed to calculate capillary pressure, relative permeability and resistivity index curves during drainage and imbibition processes in such materials. The multi-scale model was based on information obtained from 3D micro-computed tomography images of the internal pore structure, complemented with information on the pores that are unresolved with this technique. In this method, pore network models were first extracted from resolved pores in the images, by using a maximal ball network extraction algorithm. Then, pores which touched regions with unresolved porosity were connected with a special type of network element called micro-links. In the quasi-static simulations that were performed on these network models, the micro-links carried average properties of the unresolved porosity. In contrast to most previous models, the new approach to taking into account unresolved porosity therefore allowed efficient simulations on images of complex rocks, with sizes comparable to single-scale pore network models. It was able to reproduce most of the behaviour of a fully resolved pore network model, for both drainage and imbibition processes, and for different pore scale wettability distributions (water-wet, oil-wet and different mixed-wet distributions). Furthermore, simulations on images of carbonate rocks showed good agreement to experiments. A sensitivity study on carbonate rocks and tight, clay-bearing sandstones produced results that were in qualitative agreement with experiments, and allowed to analyse how the two-phase flow behaviour of these rocks is influenced by their pore scale properties. The second issue which is treated in this thesis is related to the validation of pore scale models. Comparing predicted effective properties to experimentally measured values is useful and necessary, but is complicated by the typical difference in size between the model and the experiment. Furthermore, it does not always give a clear indication of the reasons for an observed mismatch between models and experiments. Comparing two-phase flow models to pore scale experiments in which the evolution of the fluid distributions is visualized is thus extremely useful. However, this requires to image the two-phase flow process while it is taking place in a rock, and it is necessary to do this with time resolutions on the order of tens of seconds and spatial resolutions on the order of micrometers. Previous experimental approaches used synchrotron beam lines to achieve this. In this thesis, we show that such experiments are also possible using laboratory-based micro-computed tomography scanners, which are orders of magnitude cheaper and therefore more accessible than synchrotrons. An experiment in which kerosene was pumped into a water-saturated sandstone is presented, showing that individual Haines jumps (pore filling events) could be visualized during this drainage process. Because the image quality is lower than at synchrotrons, care had to be taken to adapt the image analysis work flow to deal with high image noise levels. The work flow was designed to allow to track the fluid filling state of individual pores. The results indicate that the dynamic effects due to viscous and inertial forces during Haines jumps do not significantly impact the evolution of the fluid distributions during drainage, which may thus be adequately described by quasi-static models

    A multi-scale approach to determine the REV in complex carbonate rocks

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    Complex porous carbonates display heterogeneity at different scales, influencing their reservoir properties (e.g. porosity) especially since different porosity types may exist on different spatial scales. This requires a quantitative geometric description of the complex (micro)structure of the rocks. Modern computer tomography techniques permit acquiring detailed information concerning the porosity network at different scales. These datasets allow evolvement to a more objective pore classification based on mathematical parameters. However computational limitations in complex reservoir models do not allow incorporating heterogeneities on small scales (e.g. sub-meter scale) in full-field reservoir simulations [Nordahl and Ringrose, 2008]. The suggested workflow allows characterizing different porosity networks in travertine rocks as well as establishing confidence intervals regarding the Representative Elementary Volume (REV) of these samples. The results of this study prove that one has to be very critical when determining the REV of heterogeneous complex carbonate rocks, since they are influenced by both resolution and size of the dataset

    Using micro-CT in the context of self-healing polymers

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    Dynamic micro-CT analysis of fracture formation in rock specimens subjected to multi-phase fluid flow

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    In this study, fracture formation in rocks is being studied at the pore-scale through the combination of high-resolution X-ray CT scanning with custom-made add-on modules. The Deben CT5000 system, an in-situ load cell, was used at the scanners at the Centre for X-ray Tomography at Ghent University (UGCT), providing information on mechanical properties of the tested rocks. Micro-CT scans made at the High Energy CT system Optimised for Research (HECTOR) allowed the visualisation of the fracturesk and their formation as well as the analysis of porosity changes in the material, related to the changes in stress

    Visualization of self-healing materials by X-ray computed micro-tomography at UGCT

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    This work presents recent advancements in X-ray micro-computed tomography (XRMCT) of self-healing materials at Ghent University’s Centre for X-ray Tomography (UGCT). Results of XRMCT imaging in a self-healing polymer system are shown to demonstrate the use of XRMCT in self-healing studies. Furthermore, two new XRMCT scanners are presented. The HECTOR scanner was designed for large samples and strongly attenuating samples, and is therefore well suited to study self-healing concrete. The EMCT scanner is well suited for dynamic self-healing experiments in a controlled environment

    Effect of an initial solution in iterative reconstruction of dynamically changing objects

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    Visualizing and analyzing dynamic processes in 3D is an emerging topic, e.g. in geosciences (Berg et al., 2009; Cnudde and Boone, 2013; Bultreys et al., accepted), which has only recently become possible due to fast, high-resolution CT scanning. However; dynamically changing objects pose a challenge in CT-imaging because the existing reconstruction algorithms, which reconstruct the sample volume from a number of scan images, presume an unchanging sample during the acquisition of the projection images. Movements or changes during the scan cause artefacts in the resulting volume. Furthermore, when fast processes are visualized, the acquisition time needs to be reduced, thus drastically decreasing the signal-to-noise ratio (SNR). To address these issues, an iterative reconstruction technique is applied, where an initial solution is provided to the algorithm. In this work, we present an evaluation of this method based on both simulations and real experimental data
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