Date of Award

Spring 5-2014

Author's School

School of Engineering & Applied Science

Author's Department

Mechanical Engineering & Materials Science

Degree Name

Master of Science (MS)

Degree Type

Thesis

Abstract

With rising concerns surrounding CO2 emissions from fossil fuel power plants, there has been a strong emphasis on the development of safe and economical Carbon Capture Utilization and Storage (CCUS) technology. Two methods that show the most promise are Enhanced Gas Recovery (EGR) and Enhanced Geothermal Systems (EGS). In Enhanced Gas Recovery a depleted or depleting natural gas reservoir is re-energized with high pressure CO2 to increase the recovery factor of the gas. As an additional benefit following the extraction of natural gas, the reservoir would serve as a long-term storage vessel for the captured carbon. CO2 based Enhanced Geothermal Systems seek to increase the heat extracted from a given geothermal reservoir by using CO2 as a working fluid. Carbon sequestration is accomplished as a result of fluid losses throughout the life of the geothermal system. Although these technologies are encouraging approaches to help in the mitigation of anthropogenic CO2 emissions, the detailed mechanisms involved are not fully understood. There remain uncertainties in the efficiency of the systems over time, and the safety of the sequestered CO2 due to leakage. In addition, the efficiency of both natural gas extraction in EGR and heat extraction in EGS are highly dependent on the injection rate and injection pressure. Before large scale deployment of these technologies, it is important to maximize the extraction efficiency and sequestration capacity by optimizing the injection parameters. In this thesis, numerical simulations of subsurface flow in EGR and EGS are conducted using the DOE multiphase flow solver TOUGH2 (Transport of Unsaturated Groundwater and Heat). A previously developed multi-objective optimization code based on a genetic algorithm is modified for applications to EGR and EGS. For EGR study, a model problem based on a benchmark-study that compares various mathematical and numerical models for CO2 storage is considered. For EGS study a model problem based on previous studies (with parameters corresponding to the European EGS site at Soultz) is considered. The simulation results compare well with the computations of other investigators and give insight into the parameters that can influence the simulation accuracy. Optimizations for EGR and EGS problems are carried out with a genetic algorithm (GA) based optimizer combined with TOUGH2, designated as GA-TOUGH2. Validation of the optimizer was achieved by comparison of GA based optimization studies with the brute-force run of large number of simulations. Using GA-TOUGH2, optimal time-independent and time-dependent injection profiles were determined for both EGR and EGS. Optimization of EGR problem resulted in a larger natural gas production rate, a shorter total operation time, and an injection pressure well below the fracture pressure. Optimization of EGS problem resulted in a precise management of the production temperature profile, heat extraction for the entire well life, and more efficient utilization of CO2. The results of these studies will hopefully pave the way for future GA-TOUGH2 based optimization studies to improve the modeling of CCUS projects.

Language

English (en)

Chair

Ramesh Kumar Agarwal

Committee Members

Kenneth Jerina

Comments

Permanent URL: https://doi.org/10.7936/K7D50JXD

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