This thesis investigates the feasibility of converting spent oil and gas wells for use in geothermal power generation. A novel approach to heat exchange with the ground was proposed whereby two directionally drilled (L-shaped) wells are connected to create a continuous loop. A Computational Fluid Dynamics (CFD) model was developed that simulates flow through the connected wells and the associated heat exchange with the ground. The model consisted of a coupled fluid-solid domain; 1D fluid flow was explicitly coupled to the 2D cylindrical solid domain using a convection boundary condition. Temperatures in the solid domain were resolved using an Alternating Direction Implicit (ADI) solver, which suited the largely unidirectional nature of the heat transfer problem. Fluid temperatures were solved for using a Tri-Diagonal Matrix Algorithm (TDMA). The results from a series of simulations demonstrated that geothermal power generation from abandoned wells is feasible under certain conditions. The findings of this research show that the correct selection of a well, considering geothermal gradient, well diameter, and ambient temperatures (impacting the inlet temperature), will significantly influence the level of power production. Further, the simulations show that it is necessary to optimize the flow rate for the given well conditions. The research indicates that the addition of insulation to a portion of the system can lead to modest improvements in power when the system is operated continuously. In contrast, it was found that insulation was necessary for the viability of intermittent use, which would allow the system to meet the demand for peak power generation. The simulations demonstrated that the proposed system could produce approximately 200 kW to 300 kW of electricity. / Thesis / Master of Applied Science (MASc)
Identifer | oai:union.ndltd.org:mcmaster.ca/oai:macsphere.mcmaster.ca:11375/21455 |
Date | 06 1900 |
Creators | Harris, Brianna |
Contributors | Lightstone, Marilyn, Mechanical Engineering |
Source Sets | McMaster University |
Language | English |
Detected Language | English |
Type | Thesis |
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