Loading...

Modeling of CO2 solubility in brine by using neural networks

Sadeghi, M. A ; Sharif University of Technology | 2012

552 Viewed
  1. Type of Document: Article
  2. Publisher: European Association of Geoscientists and Engineers, EAGE , 2012
  3. Abstract:
  4. CO2 sequestration in geological formations, such as aquifers, is known to be the best short-term solution to CO2 mitigation. Accurate description of CO2 solubility in brine is important for evaluating the capacity of aquifers to sequester CO2. Currently, EOS-based models are widely used in reservoir compositional simulators for this purpose. However, most of these models involve complex and iterative calculations which take too much time in case of large-scale flow simulation of geological CO2 storage. In this study, a neural network model is presented for prediction of CO2 solubility in brine which is highly accurate with less computational overhead
  5. Keywords:
  6. Aquifers ; Hydrogeology ; Solubility ; CO2 sequestration ; Compositional simulators ; Computational overheads ; Geological formation ; Iterative calculation ; Large-scale flows ; Neural network model ; Short-term solutions ; Carbon dioxide
  7. Source: Saint Petersburg 2012 - Geosciences: Making the Most of the Earth's Resources, 2 April 2012 through 5 April 2012 ; April , 2012