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Numerical Modeling of Deep Geothermal Energy Reservoirs

Ahmadi Hosseini, Adel | 2019

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 52139 (09)
  4. University: Sharif University of Technology
  5. Department: Civil Engineering
  6. Advisor(s): Pak, Ali
  7. Abstract:
  8. Geothermal energy is one of the most important sources of energy that is increasingly becoming more popular all over the world. In this study, the performance of deep geothermal energy as a form of geothermal energy was evaluated using a numerical modeling approach. To do so, first, the thermo-hydraulic behavior of geothermal reservoirs was studied to help achieve the most efficient arrangement for production and injection wells. The results show that to optimize production and injection wells, there are two factors to consider. Firstly, the distance between production and injection wells must be high. Secondly, the production wells must be uniformly distributed throughout the reservoir so that the cold input fluid is more widely distributed into the geothermal reservoir. Furthermore, a large dataset is developed using this model, which is then used to train an artificial neural network. The artificial neural network can predict the performance of deep geothermal reservoir behavior with high precision. After that, to further study the geomechanical effects in geothermal reservoirs the Thermo-Hydraulic process was extended to a Thermo-Hydro-Mechanical process. Using this approach, deformations of the reservoir and the subsidence as a result of utilizing them was investigated. The results indicate the significant effects of thermal expansion compared to pressure changes in the deformation land ground subsidence
  9. Keywords:
  10. Geothermal Energy ; Deep Geothermal Reservoir ; Geometry Optimization ; Subsidence Phenomenon ; Artificial Neural Network

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