The transition to efficient, affordable, reliable, and clean sources of energy is one of the major challenges of this century. Despite advances in renewable energy technologies, fossil fuels remain the primary source of energy, and are expected to remain so for decades to come. Natural gas, a relatively cleaner fossil fuel vital to many industries such as power generation, is expected to play a more prominent role in the global energy mix. However, with the decline in conventional gas discoveries, it is crucial to improve recovery from mature reservoirs to satisfy the growing demand for energy. On the other hand, the combustion of fossil fuels significantly contributes to carbon dioxide (CO2) emissions and climate change, an issue of major concern. CO2-based enhanced gas recovery (EGR) is a useful method to improve gas recovery, and simultaneously store CO2 securely in depleted gas reservoirs, therefore reducing net CO2 emissions. However, CO2 injection for EGR has a drawback of excess mixing with the methane therefore reducing the quality of gas produced, and leading to early breakthrough. Although this issue has been identified as a major obstacle in CO2-based EGR, few strategies have been suggested to mitigate this problem. In this study, we propose a novel hybrid EGR method to reduce mixing and delay breakthrough. We propose the injection of a slug of carbonated water before beginning CO2 injection. Carbonated water hinders CO2-methane mixing, and reduces CO2 mobility therefore delaying breakthrough. We use reservoir simulation to assess the feasibility and benefit of the proposed method. Through a structured design of experiments (DoE) framework, we perform sensitivity analysis, uncertainty quantification, and optimization to identify the ideal operation and transition conditions. We show that the proposed method has an overall benefit for up to ~3% pore volumes of carbonated water injected. The proposed method is mainly influenced by the heterogeneity of the reservoir, slug volume injected, and production rates. Through Monte Carlo simulation we show that high recovery factors and storage ratios can be achieved while keeping recycled CO2 ratios low. These results are encouraging and highlight the overall benefit of the proposed hybrid EGR method.

Permanently sequestering carbon dioxide (CO2) in gas-bearing shale formations is beneficial in that it can mitigate greenhouse gas emissions as well as enhance gas recovery in production wells. This is possible due to the sorption properties of the organic material within shales and their greater affinity for CO2 over methane. The phenomenon of preferentially adsorbing CO2 while desorbing methane has been proven in coalbed reservoirs successfully, and is feasible for shale formations. The objective of this thesis is to explore the potential for enhanced gas recovery from gas-bearing shale formations by injecting CO2 into a targeted shale formation. With the advancement of technologies in horizontal drilling combined with hydraulic fracturing, shale gas has become a significant source of energy throughout the United States. With over 6,000 trillion cubic feet (Tcf) of theoretical gas-in-place, Appalachia has proven a major basin for gas production from organic shales. With its extensive shale reserves and lack of conventional reservoirs typically used for CO2 storage, Appalachia's unconventional reservoirs are favorable candidates for CO2 storage with enhanced gas recovery. Enhancing gas recovery not only increases reserves, but extends the life of mature wells and fields throughout the basin. As part of this research, 510 tons of CO2 were successfully injected into a horizontal production well completed in the Chattanooga shale formation, a late Devonian shale, in Morgan County, Tennessee. An extensive monitoring program was implemented during the pre-injection baseline, injection, soaking, and flowback phases of the test. Multiple fluorinated tracers were used to monitor for potential CO2 breakthrough at offset production wells and to help account for the CO2 once the well was flowed back. Results from this test, once the well was put back into normal production state, confirm the injectivity and storage potential of CO2 in shale formations, as well as an increase in gas production rate and quality of gas produced. / Master of Science

A storage and enhanced coalbed methane (CO2-ECBM) test will store up to 20,000 tons of carbon dioxide in a stacked coal reservoir in southwest Virginia. The test involves two phases of CO2 injection operations. Phase I was conducted from July 2, 2015 to April 15, 2016, and injected a total of 10, 601 tons of CO2. After a reservoir soaking period of seven months, Phase II is scheduled to begin Fall 2016. The design of the monitoring program for the test considered several site-specific factors, including a unique reservoir geometry, challenging surface terrain, simultaneous CBM production activities which complicate the ability to attribute signals to sources. A multi-scale approach to the monitoring design incorporated technologies deployed over different, overlapping spatial and temporal scales selected for the monitoring program include dedicated observation wells, CO2 injection operations monitoring, reservoir pressure and temperature monitoring, gas and formation water composition from offset wells tracer studies, borehole liquid level measurement, microseismic monitoring, surface deformation measurement, and various well logs and tests. Integrated interpretations of monitoring results from Phase I of the test have characterized enhanced permeability, geomechanical variation with depth, and dynamic reservoir injectivity. Results have also led to the development of recommended injection strategy for CO2-ECBM operations. The work presented here describes the development of the monitoring program, including design considerations and rationales for selected technologies, and presents monitoring results and interpretations from Phase I of the test. / Ph. D.

Numerical modelling of subsurface processes, such as geotechnical, geohydrological or geothermal applications requires a realistic description of fluid parameters in order to obtain plausible results. Particularly for gases, the properties of a fluid strongly depend on the primary variables of the simulated systems, which lead to non-linerarities in the governing equations. This thesis describes the development, evaluation and application of a numerical model for non-isothermal flow processes based on thermodynamic principles. Governing and constitutive equations of this model have been implemented into the open-source scientific FEM simulator OpenGeoSys. The model has been verified by several well-known benchmark tests for heat transport as well as for single- and multiphase flow. To describe physical fluid behaviour, highly accurate thermophysical property correlations of various fluids and fluid mixtures have been utilized. These correlations are functions of density and temperature. Thus, the accuracy of those correlations is strongly depending on the precision of the chosen equation of state (EOS), which provides a relation between the system state variables pressure, temperature, and composition. Complex multi-parameter EOSs reach a higher level of accuracy than general cubic equations, but lead to very expansive computing times. Therefore, a sensitivity analysis has been conducted to investigate the effects of EOS uncertainties on numerical simulation results. The comparison shows, that small differences in the density function may lead to significant discrepancies in the simulation results. Applying a compromise between precision and computational effort, a cubic EOS has been chosen for the simulation of the continuous injection of carbon dioxide into a depleted natural gas reservoir. In this simulation, real fluid behaviour has been considered. Interpreting the simulation results allows prognoses of CO2 propagation velocities and its distribution within the reservoir. These results are helpful and necessary for scheduling real injection strategies. / Für die numerische Modellierung von unterirdischen Prozessen, wie z. B. geotechnische, geohydrologische oder geothermische Anwendungen, ist eine möglichst genaue Beschreibung der Parameter der beteiligten Fluide notwendig, um plausible Ergebnisse zu erhalten. Fluideigenschaften, vor allem die Eigenschaften von Gasen, sind stark abhängig von den jeweiligen Primärvariablen der simulierten Prozesse. Dies führt zu Nicht-linearitäten in den prozessbeschreibenden partiellen Differentialgleichungen. In der vorliegenden Arbeit wird die Entwicklung, die Evaluierung und die Anwendung eines numerischen Modells für nicht-isotherme Strömungsprozesse in porösen Medien beschrieben, das auf thermodynamischen Grundlagen beruht. Strömungs-, Transport- und Materialgleichungen wurden in die open-source-Software-Plattform OpenGeoSys implementiert. Das entwickelte Modell wurde mittels verschiedener, namhafter Benchmark-Tests für Wärmetransport sowie für Ein- und Mehrphasenströmung verifiziert. Um physikalisches Fluidverhalten zu beschreiben, wurden hochgenaue Korrelationsfunktionen für mehrere relevante Fluide und deren Gemische verwendet. Diese Korrelationen sind Funktionen der Dichte und der Temperatur. Daher ist deren Genauigkeit von der Präzision der verwendeten Zustandsgleichungen abhängig, welche die Fluiddichte in Relation zu Druck- und Temperaturbedingungen sowie der Zusammensetzung von Gemischen beschreiben. Komplexe Zustandsgleichungen, die mittels einer Vielzahl von Parametern an Realgasverhalten angepasst wurden, erreichen ein viel höheres Maß an Genauigkeit als die einfacheren, kubischen Gleichungen. Andererseits führt deren Komplexität zu sehr langen Rechenzeiten. Um die Wahl einer geeigneten Zustandsgleichung zu vereinfachen, wurde eine Sensitivitätsanalyse durchgeführt, um die Auswirkungen von Unsicherheiten in der Dichtefunktion auf die numerischen Simulationsergebnisse zu untersuchen. Die Analyse ergibt, dass bereits kleine Unterschiede in der Zustandsgleichung zu erheblichen Abweichungen der Simulationsergebnisse untereinander führen können. Als ein Kompromiss zwischen Einfachheit und Rechenaufwand wurde für die Simulation einer enhanced gas recovery-Anwendung eine kubische Zustandsgleichung gewählt. Die Simulation sieht, unter Berücksichtigung des Realgasverhaltens, die kontinuierliche Injektion von CO2 in ein nahezu erschöpftes Erdgasreservoir vor. Die Interpretation der Ergebnisse erlaubt eine Prognose über die Ausbreitungsgeschwindigkeit des CO2 bzw. über dessen Verteilung im Reservoir. Diese Ergebnisse sind für die Planung von realen Injektionsanwendungen notwendig

Numerical modelling of subsurface processes, such as geotechnical, geohydrological or geothermal applications requires a realistic description of fluid parameters in order to obtain plausible results. Particularly for gases, the properties of a fluid strongly depend on the primary variables of the simulated systems, which lead to non-linerarities in the governing equations. This thesis describes the development, evaluation and application of a numerical model for non-isothermal flow processes based on thermodynamic principles. Governing and constitutive equations of this model have been implemented into the open-source scientific FEM simulator OpenGeoSys. The model has been verified by several well-known benchmark tests for heat transport as well as for single- and multiphase flow. To describe physical fluid behaviour, highly accurate thermophysical property correlations of various fluids and fluid mixtures have been utilized. These correlations are functions of density and temperature. Thus, the accuracy of those correlations is strongly depending on the precision of the chosen equation of state (EOS), which provides a relation between the system state variables pressure, temperature, and composition. Complex multi-parameter EOSs reach a higher level of accuracy than general cubic equations, but lead to very expansive computing times. Therefore, a sensitivity analysis has been conducted to investigate the effects of EOS uncertainties on numerical simulation results. The comparison shows, that small differences in the density function may lead to significant discrepancies in the simulation results. Applying a compromise between precision and computational effort, a cubic EOS has been chosen for the simulation of the continuous injection of carbon dioxide into a depleted natural gas reservoir. In this simulation, real fluid behaviour has been considered. Interpreting the simulation results allows prognoses of CO2 propagation velocities and its distribution within the reservoir. These results are helpful and necessary for scheduling real injection strategies. / Für die numerische Modellierung von unterirdischen Prozessen, wie z. B. geotechnische, geohydrologische oder geothermische Anwendungen, ist eine möglichst genaue Beschreibung der Parameter der beteiligten Fluide notwendig, um plausible Ergebnisse zu erhalten. Fluideigenschaften, vor allem die Eigenschaften von Gasen, sind stark abhängig von den jeweiligen Primärvariablen der simulierten Prozesse. Dies führt zu Nicht-linearitäten in den prozessbeschreibenden partiellen Differentialgleichungen. In der vorliegenden Arbeit wird die Entwicklung, die Evaluierung und die Anwendung eines numerischen Modells für nicht-isotherme Strömungsprozesse in porösen Medien beschrieben, das auf thermodynamischen Grundlagen beruht. Strömungs-, Transport- und Materialgleichungen wurden in die open-source-Software-Plattform OpenGeoSys implementiert. Das entwickelte Modell wurde mittels verschiedener, namhafter Benchmark-Tests für Wärmetransport sowie für Ein- und Mehrphasenströmung verifiziert. Um physikalisches Fluidverhalten zu beschreiben, wurden hochgenaue Korrelationsfunktionen für mehrere relevante Fluide und deren Gemische verwendet. Diese Korrelationen sind Funktionen der Dichte und der Temperatur. Daher ist deren Genauigkeit von der Präzision der verwendeten Zustandsgleichungen abhängig, welche die Fluiddichte in Relation zu Druck- und Temperaturbedingungen sowie der Zusammensetzung von Gemischen beschreiben. Komplexe Zustandsgleichungen, die mittels einer Vielzahl von Parametern an Realgasverhalten angepasst wurden, erreichen ein viel höheres Maß an Genauigkeit als die einfacheren, kubischen Gleichungen. Andererseits führt deren Komplexität zu sehr langen Rechenzeiten. Um die Wahl einer geeigneten Zustandsgleichung zu vereinfachen, wurde eine Sensitivitätsanalyse durchgeführt, um die Auswirkungen von Unsicherheiten in der Dichtefunktion auf die numerischen Simulationsergebnisse zu untersuchen. Die Analyse ergibt, dass bereits kleine Unterschiede in der Zustandsgleichung zu erheblichen Abweichungen der Simulationsergebnisse untereinander führen können. Als ein Kompromiss zwischen Einfachheit und Rechenaufwand wurde für die Simulation einer enhanced gas recovery-Anwendung eine kubische Zustandsgleichung gewählt. Die Simulation sieht, unter Berücksichtigung des Realgasverhaltens, die kontinuierliche Injektion von CO2 in ein nahezu erschöpftes Erdgasreservoir vor. Die Interpretation der Ergebnisse erlaubt eine Prognose über die Ausbreitungsgeschwindigkeit des CO2 bzw. über dessen Verteilung im Reservoir. Diese Ergebnisse sind für die Planung von realen Injektionsanwendungen notwendig