788 research outputs found

    Doctor of Philosophy

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    dissertationThe objective of this dissertation is to estimate possible leakage pathways such as abandoned wells and fault zones in the deep subsurface for CO2 storage using inverse analysis. Leakage pathways through a cap rock may cause CO2 to migrate into the layers above cap rock. An inverse analysis using iTOUGH2 was applied to estimate possible leakage pathways using pressure anomalies in the overlying formation induced by brine and/or CO2 leaks. Prior to applying inverse analysis, sensitivity analysis and forward modeling were conducted. In addition, an inverse model was developed for single-phase flow and it was applied to the leakage pathway estimation in a brine/CO2 system. Migration of brine/CO2 through the leakage pathway was simulated in the generic homogeneous and heterogeneous domains. The increased pressure gradient due to CO2 injection continuously induced brine leaks through the leakage pathway. Capillary pressure was induced by the migration of CO2 along the leakage pathway saturated by brine. Pressure anomalies due to capillary pressures were propagated to the entire overlying formation. The sensitivity analysis was focused on how the hydrogeological properties affect the pressure signals at monitoring wells. Parameter estimation using the iTOUGH2 model was applied to detect locations of leakage pathways in homogeneous and heterogeneous model domains. For homogeneous models, the parameterization of uncertain permeability in an overlying formation could improve location estimation accuracy. Residual analysis illustrated that pressure anomalies in the overlying formation induced by leaks are critical information for the leakage pathway estimation. For heterogeneous models, the calibration of renormalized permeability values could reduce systematic modeling errors and should improve the leakage pathway location estimation accuracy. The weighting factors significantly influenced the accuracy of the leakage pathway estimation. The developed inverse model was applied to estimate the leakage pathway in a brine/CO2 system using pressure anomalies induced by only brine leaks. To estimate a possible leakage pathway, the developed inverse model calibrated each integrated parameter (of both cross-sectional area and vertical hydraulic conductivity) of initial guesses of the leakage pathway. This application can provide warning before the CO2 leaks, and will be useful in mitigating the risk of CO2 leaks

    Application of upscaling methods for fluid flow and mass transport in multi-scale heterogeneous media : A critical review

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    Physical and biogeochemical heterogeneity dramatically impacts fluid flow and reactive solute transport behaviors in geological formations across scales. From micro pores to regional reservoirs, upscaling has been proven to be a valid approach to estimate large-scale parameters by using data measured at small scales. Upscaling has considerable practical importance in oil and gas production, energy storage, carbon geologic sequestration, contamination remediation, and nuclear waste disposal. This review covers, in a comprehensive manner, the upscaling approaches available in the literature and their applications on various processes, such as advection, dispersion, matrix diffusion, sorption, and chemical reactions. We enclose newly developed approaches and distinguish two main categories of upscaling methodologies, deterministic and stochastic. Volume averaging, one of the deterministic methods, has the advantage of upscaling different kinds of parameters and wide applications by requiring only a few assumptions with improved formulations. Stochastic analytical methods have been extensively developed but have limited impacts in practice due to their requirement for global statistical assumptions. With rapid improvements in computing power, numerical solutions have become more popular for upscaling. In order to tackle complex fluid flow and transport problems, the working principles and limitations of these methods are emphasized. Still, a large gap exists between the approach algorithms and real-world applications. To bridge the gap, an integrated upscaling framework is needed to incorporate in the current upscaling algorithms, uncertainty quantification techniques, data sciences, and artificial intelligence to acquire laboratory and field-scale measurements and validate the upscaled models and parameters with multi-scale observations in future geo-energy research.© 2021 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)This work was jointly supported by the National Key Research and Development Program of China (No. 2018YFC1800900 ), National Natural Science Foundation of China (No: 41972249 , 41772253 , 51774136 ), the Program for Jilin University (JLU) Science and Technology Innovative Research Team (No. 2019TD-35 ), Graduate Innovation Fund of Jilin University (No: 101832020CX240 ), Natural Science Foundation of Hebei Province of China ( D2017508099 ), and the Program of Education Department of Hebei Province ( QN219320 ). Additional funding was provided by the Engineering Research Center of Geothermal Resources Development Technology and Equipment , Ministry of Education, China.fi=vertaisarvioitu|en=peerReviewed

    Modeling a geologically complex karst aquifer system, Hochifen-Gottesacker, Alps

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    Modelling the two-phase plume dynamics of CO2 leakage into open shallow waters

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    A numerical model of two-phase plume developments in a small scale turbulent ocean is proposed and designed as a fundamental study to predict the near field physicochemical impacts and biological risk to the marine ecosystem from CO2 leakage from potential carbon storage locations around the North Sea. New sub-models are developed for bubble formation and drag coefficients using in-situ measurements from videos of the Quantifying and monitoring potential ecosystem Impacts of geological Carbon Storage (QICS) experiment. Existing sub-models such as Sherwood numbers and plume interactions are also compared, verified and implemented into the new model. Observational data collected from the North Sea provides the ability to develop and verify a large eddy simulation turbulence model, limited to situations where the non-slip boundary wall may be neglected. The model is then tested to assimilate the QICS experiment, before being applied to potential leakage scenarios around the North Sea with key marine impacts from pCO2 and pH changes. The most serious leak is from a well blowout, with maximum pH changes of up to -2.7 and changes greater than -0.1 affecting areas up to 0.23 km2. Other scenarios through geological structures would be challenging to detect with pH changes below -0.27

    Tracing back the source of contamination

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    From the time a contaminant is detected in an observation well, the question of where and when the contaminant was introduced in the aquifer needs an answer. Many techniques have been proposed to answer this question, but virtually all of them assume that the aquifer and its dynamics are perfectly known. This work discusses a new approach for the simultaneous identification of the contaminant source location and the spatial variability of hydraulic conductivity in an aquifer which has been validated on synthetic and laboratory experiments and which is in the process of being validated on a real aquifer

    Characterizing flow pathways in a sandstone aquifer: Tectonic vs sedimentary heterogeneities

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    Sandstone aquifers are commonly assumed to represent porous media characterized by a permeable matrix. However, such aquifers may be heavy fractured when rock properties and timing of deformation favour brittle failure and crack opening. In many aquifer types, fractures associated with faults, bedding planes and stratabound joints represent preferential pathways for fluids and contaminants. In this paper, well test and outcrop-scale studies reveal how strongly lithified siliciclastic rocks may be entirely dominated by fracture flow at shallow depths (≤ 180 m), similar to limestone and crystalline aquifers. However, sedimentary heterogeneities can primarily control fluid flow where fracture apertures are reduced by overburden pressures or mineral infills at greater depths. The Triassic St Bees Sandstone Formation (UK) of the East Irish Sea Basin represents an optimum example for study of the influence of both sedimentary and tectonic aquifer heterogeneities in a strongly lithified sandstone aquifer-type. This fluvial sedimentary succession accumulated in rapidly subsiding basins, which typically favours preservation of complete depositional cycles including fine grained layers (mudstone and silty sandstone) interbedded in sandstone fluvial channels. Additionally, vertical joints in the St Bees Sandstone Formation form a pervasive stratabound system whereby joints terminate at bedding discontinuities. Additionally, normal faults are present through the succession showing particular development of open-fractures. Here, the shallow aquifer (depth ≤ 180 m) was characterized using hydro-geophysics. Fluid temperature, conductivity and flow-velocity logs record inflows and outflows from normal faults, as well as from pervasive bed-parallel fractures. Quantitative flow logging analyses in boreholes that cut fault planes indicates that zones of fault-related open fractures characterize ~ 50% of water flow. The remaining flow component is dominated by bed-parallel fractures. However, such sub-horizontal fissures become the principal flow conduits in wells that penetrate the exterior parts of fault damage zones, as well as in non-faulted areas. The findings of this study have been compared with those of an earlier investigation of the deeper St Bees Sandstone aquifer (180 to 400 m subsurface depth) undertaken as part of an investigation for a proposed nuclear waste repository. The deeper aquifer is characterized by significantly lower transmissivities. High overburden pressure and the presence of mineral infillings, have reduced the relative impact of tectonic heterogeneities on transmissivity here, thereby allowing matrix flow in the deeper part of the aquifer. The St Bees Sandstone aquifer contrasts the hydraulic behaviour of low-mechanically resistant sandstone rock-types. In fact, the UK Triassic Sandstone of the Cheshire Basin is low-mechanically resistant and flow is supported both by matrix and fracture. Additionally, faults in such weak-rocks are dominated by granulation seams representing flow-barriers which strongly compartmentalize the UK Triassic Sandstone in the Cheshire Basin

    Understanding and modelling of surface and groundwater interactions

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    The connections between surface water and groundwater systems remain poorly understood in many catchments throughout the world and yet they are fundamental to effectively managing water resources. Managing water resources in an integrated manner is not straightforward, particularly if both resources are being utilised, and especially in those regions that suffer problems of data scarcity. This study explores some of the principle issues associated with understanding and practically modelling surface and groundwater interactions. In South Africa, there remains much controversy over the most appropriate type of integrated model to be used and the way forward in terms of the development of the discipline; part of the disagreement stems from the fact that we cannot validate models adequately. This is largely due to traditional forms of model testing having limited power as it is difficult to differentiate between the uncertainties within different model structures, different sets of alternative parameter values and in the input data used to run the model. While model structural uncertainties are important to consider, the uncertainty from input data error together with parameter estimation error are often more significant to the overall residual error, and essential to consider if we want to achieve reliable predictions for water resource decisions. While new philosophies and theories on modelling and results validation have been developed (Beven, 2002; Gupta et al., 2008), in many cases models are not only still being validated and compared using sparse and uncertain datasets, but also expected to produce reliable predictions based on the flawed data. The approach in this study is focused on fundamental understanding of hydrological systems rather than calibration based modelling and promotes the use of all the available 'hard' and 'soft' data together with thoughtful conceptual examination of the processes occurring in an environment to ensure as far as possible that a model is generating sensible results by simulating the correct processes. The first part of the thesis focuses on characterising the 'typical' interaction environments found in South Africa. It was found that many traditional perceptual models are not necessarily applicable to South African conditions, largely due to the relative importance of unsaturated zone processes and the complexity of the dominantly fractured rock environments. The interaction environments were categorised into four main 'types' of environment. These include karst, primary, fractured rock (secondary), and alluvial environments. Processes critical to Integrated Water Resource Management (IWRM) were defined within each interaction type as a guideline to setting a model up to realistically represent the dominant processes in the respective settings. The second part of the thesis addressed the application and evaluation of the modified Pitman model (Hughes, 2004), which allows for surface and groundwater interaction behaviour at the catchment scale to be simulated. The issue is whether, given the different sources of uncertainty in the modelling process, we can differentiate one conceptual flow path from another in trying to refine the understanding and consequently have more faith in model predictions. Seven example catchments were selected from around South Africa to assess whether reliable integrated assessments can be carried out given the existing data. Specific catchment perceptual models were used to identify the critical processes occurring in each setting and the Pitman model was assessed on whether it could represent them (structural uncertainty). The available knowledge of specific environments or catchments was then examined in an attempt to resolve the parameter uncertainty present within each catchment and ensure the subsequent model setup was correctly representing the process understanding as far as possible. The confidence in the quantitative results inevitably varied with the amount and quality of the data available. While the model was deemed to be robust based on the behavioural results obtained in the majority of the case studies, in many cases a quantitative validation of the outputs was just not possible based on the available data. In these cases, the model was judged on its ability to represent the conceptualisation of the processes occurring in the catchments. While the lack of appropriate data means there will always be considerable uncertainty surrounding model validation, it can be argued that improved process understanding in an environment can be used to validate model outcomes to a degree, by assessing whether a model is getting the right results for the right reasons. Many water resource decisions are still made without adequate account being taken of the uncertainties inherent in assessing the response of hydrological systems. Certainly, with all the possible sources of uncertainty in a data scarce country such as South Africa, pure calibration based modelling is unlikely to produce reliable information for water resource managers as it can produce the right results for the wrong reasons. Thus it becomes essential to incorporate conceptual thinking into the modelling process, so that at the very least we are able to conclude that a model generates estimates that are consistent with, and reflect, our understanding (however limited) of the catchment processes. It is fairly clear that achieving the optimum model of a hydrological system may be fraught with difficulty, if not impossible. This makes it very difficult from a practitioner's point of view to decide which model and uncertainty estimation method to use. According to Beven (2009), this may be a transitional problem and in the future it may become clearer as we learn more about how to estimate the uncertainties associated with hydrological systems. Until then, a better understanding of the fundamental and most critical hydrogeological processes should be used to critically test and improve model predictions as far as possible. A major focus of the study was to identify whether the modified Pitman model could provide a practical tool for water resource managers by reliably determining the available water resource. The incorporation of surface and groundwater interaction routines seems to have resulted in a more robust and realistic model of basin hydrology. The overall conclusion is that the model, although simplified, is capable of representing the catchment scale processes that occur under most South African conditions
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