IN SITU CO₂ GENERATION: NUMERICAL STUDY IN GEOTHERMAL SYSTEMS AND EXPERIMENTAL ASSESSMENT FOR ENHANCED OIL RECOVERY

Abstract

Chapter 1 introduces geothermal energy as a clean, renewable source with the potential to provide steady power and support global climate goals. As investment in geothermal grows, low-to-moderate temperature reservoirs that more common than high-temperature ones are gaining attention for both power generation and direct-use applications. The type of use depends largely on reservoir temperature, as outlined in the Lindal diagram. As geothermal development expands, accurately tracking the movement of the thermal front during cold-water injection becomes increasingly important. Unable to track this movement accurately can lead to inefficient heat extraction and poor reservoir management. Tracers have emerged as a promising tool to address this challenge, as they offer a way to monitor subsurface flow paths and thermal front propagation more efficiently. Among various tracer types, temperature-dependent reactive tracers are the most effective due to their sensitivity to temperature changes. However, many existing reactive tracers face limitations in high-temperature reservoirs due to their chemical formulations stability. These challenges have led to growing interest in identifying new tracers that are both stable and responsive under reservoir conditions. This research proposes urea as a temperature-dependent reactive tracer with strong potential for geothermal applications. Its predictable hydrolysis behavior, high solubility, and low cost make it a practical choice for field-scale use. The study is built around three core questions: whether urea can reliably track the thermal front, how its performance is affected by reservoir and operational parameters, and how it compares to existing reactive tracers. Together, these questions guide the work that follows, laying the foundation for simulation-based evaluation of urea’s behavior in geothermal systems. The second chapter of this dissertation focuses on the foundational step of building a reliable and representative numerical model for simulating geothermal reservoir behavior, when exposed to cold-water injection. Numerical simulation is a powerful tool for studying heat extraction, but it naturally involves errors from time and space discretization, such as numerical dispersion that can cause inaccuracy in the results. Thus, if not properly controlled, these errors can distort the simulation of thermal front movement and lead to incorrect predictions of reservoir performance. This chapter addresses these issues by evaluating how grid block size and time-step selection influence the accuracy and efficiency of the model. A key objective is to have the right balance between minimizing numerical dispersion and maintaining manageable running time. The study also emphasizes the importance of applying realistic boundary conditions, to ensure that simulation results are physically relevant to real reservoir situations. Beyond numerical sensitivity, this chapter focuses also on refining reaction parameters related to urea hydrolysis, and ensuring consistency in thermal energy in place calculations. Together, these efforts are aimed at improving model calibration and laying a solid floor for the subsequent simulation chapter that builds upon this base framework. Chapter 3 explores the use of urea as a temperature-dependent reactive tracer for tracking thermal front movement in geothermal reservoirs. Using CMG STARS, urea was simulated under varying temperatures and injection rates. Results showed that its effectiveness depends on in-situ flow velocity, reaction kinetics, and reservoir temperature. urea performed best between 70–90 °C, providing a clear signal at the production well. Its intermediate reaction rate allowed better thermal tracking than both slower and faster-reacting tracers, making it suitable for moderate-temperature systems. To validate the simulation and assess a common temperature estimation method, Hawkins et al. (2021) correlation was applied. This helped to identify whether the method tends to overestimate reservoir temperatures under urea conditions, which offers additional insight into its reliability for geothermal applications. Chapter 4 explores the phase behavior of surfactant formulations designed for further application that will be tested in the future for enhanced oil recovery (EOR) in tight shale formations with the addition of urea. The goal was to identify systems capable of forming stable Type III microemulsions and achieving ultra-low interfacial tension (IFT), which are essential for mobilizing trapped oil. Petrostep S2, a thermally stable internal olefin sulfonate (IOS) surfactant, was tested for the first time in this context, within a shale + urea framework. The working hypothesis was that S2, when paired with co-surfactants and under optimal salinity, could promote favorable microemulsion formation and support both IFT reduction and wettability alteration at elevated temperatures. A series of formulations were evaluated across temperatures of 25 °C, 50 °C, and 90 °C, focusing on high-temperature performance. Co-surfactants including Alfoterra, SDBS, and Calfax were combined with S2 at various ratios, and salinity was systematically varied to track microemulsion transitions. Visual phase behavior screening was used to detect the formation of Winsor phases, especially Type III systems. The Chun-Huh correlation was applied to estimate IFT based on observed solubilization parameters. Among the tested systems, a 50:50 blend of S2 and SDBS at 17% NaCl showed the most promising behavior, forming a stable middle-phase microemulsion with theoretically ultra-low IFT. This formulation was selected for further flowthrough evaluation in one-dimensional sand pack experiments in the subsequent chapter, allowing comparison of its oil recovery potential against previously tested urea-based in-situ CO₂ systems. Nevertheless, binary systems with Calfax 16L-35 demonstrated similar behavior but at slightly high salt concentrations. Chapter 5 builds on the findings of Chapter 4 by applying the optimal surfactant formulation in combination with urea under dynamic flowthrough conditions. Using 1D sand pack experiments, the study investigates the performance of this coupled system for EOR in sandstone medium. Upon injection, urea decomposes at elevated temperatures to generate CO₂ and NH₃. The CO₂ partitions into the oil phase, reducing viscosity and swelling the oil, while NH₃ promotes wettability alteration through interaction with the rock surface. The addition of the ultra-low IFT surfactant formulation further enhances oil mobility by significantly reducing interfacial tension. This combined approach depends on multiple recovery mechanisms; viscosity reduction, wettability alteration, and interfacial control, working together to improve oil displacement efficiency. Although earlier studies have reported the benefits of urea-based systems in various formations, they typically used surfactants with only moderate IFT reduction. This chapter explores the synergy between urea and ultra-low IFT surfactants, offering new insights into their potential for boosting recovery in tight reservoir conditions in future work.