Date

2020-9

Author

Abukubu, Alfred Ejiro

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Enhanced oil recovery (EOR) involves the implementation of various techniques for increasing oil recovery, which typically involves injection of an agent that help to increase the oil flow. Steam injection is a common method to increase the recovery from heavy-oil reservoirs, which contain oil that has very high viscosity that may not be produced at economic rates due to inability to flow by viscous forces. Using concentrating solar power (CSP) as a renewable-energy system is one means to attain this objective, with a reduction in CO2 emissions and fuel usage in generating steam, and could be at a lower cost than burning natural gas. The objective of this study to develop a coupled solar-energy/steam-injection forecasting tool to understand the impact of certain designs and natural parameters on the process. The study would use an existing data driven screening tool (artificial neural network), trained with numerical-simulation results, to optimize the steam-injection efficiency. Then solar-energy and steam-injection models, are going to be integrated so that both models can communicate. In the entirety of the project, economic indicators such as steam cost, capital investments for solar system would be reflected amongst other operational parameters to present a more realistic analysis. Finally, integrated models will be organized in a graphical-user-interface (GUI) input/output type application to convert the coupled models into a user-friendly screening tool, easy to use and understand by an investor or an engineer.

Subject Keywords

Genetic Algorithm, Optimization, Cyclic Steam Injection, Enhanced Oil Recovery, Solar-Steam

URI

https://hdl.handle.net/11511/69232

Collections

Northern Cyprus Campus, Thesis