Finite element simulation of a highly water-saturated gas reservoir in northwestern Argentina to forecast its geothermal potential

"A wide availability of in field Oil & Gas facilities which still have a marginal productive life can be a good opportunity to produce geothermal energy. The challenge is to make good decisions about the company’s assets to include geothermal energy as a candidate in their project portfolio. The self-sustainability of this type of energy production must be ensured by accurate forecasts of the net-energy balance. A geothermal energy production cycle must ensure the best selection of production and injection wells saving energy during their productive lives of the project. A first approach to the simulation of geological faults,lithological heterogeneities of rocks and their interaction with the wells is the basis for the later detailed understanding of the geothermal water cycle. Finite element simulation (FEM) it is a fast tool to understand how the key variables such as ”injection and production flow rates”, ”well-to-well interference” and ”well-to-reservoir heterogeneities interactions” can change the energy consumption needed for geothermal energy production. The role of the key parameters can be easily adjusted to make quick comparisons between different prospects before any detailed engineering is performed. The simulation performed in this thesis has shown a geothermal harvest gain of 58%, when a combination of the more advantageous properties of the geothermal system were used, in comparison with the case represented by the less efficient properties combination.Thanks to the FEM simulation, a detailed interpretation of the peculiarities of production and temperature development shows that not always the more productive case is the most efficient one. The present work presents a method to get a preliminar model of the energy production potential in a water-flooded hydrocarbon reservoir." Tesis Energía y Ambiente (maestría) - Instituto Tecnológico de Buenos Aires, Buenos Aires - Karlsruher Institut für Technologie, Karlsruhe, 2018