A proxy model for determining reservoir pressure and temperature for geothermal wells

Aydin H., AKIN S., Senturk E.

Geothermics, vol.88, 2020 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 88
  • Publication Date: 2020
  • Doi Number: 10.1016/j.geothermics.2020.101916
  • Journal Name: Geothermics
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, PASCAL, Aerospace Database, Agricultural & Environmental Science Database, Aquatic Science & Fisheries Abstracts (ASFA), CAB Abstracts, Communication Abstracts, Compendex, Environment Index, Geobase, Greenfile, INSPEC, Metadex, Civil Engineering Abstracts
  • Keywords: Alasehir field, Wellbore simulation, Geothermal energy, Artificial neural network, Proxy model, Non condensable gases, ARTIFICIAL NEURAL-NETWORKS, 2-PHASE FLOW, DROPS
  • Middle East Technical University Affiliated: Yes

Abstract

Estimating reservoir pressure and temperature is one of the challenges of geothermal reservoir engineering. A new proxy model has been developed to estimate reservoir pressure and temperature using wellhead pressure, temperature and non-condensable gas (NCG) amount. An exhaustive set of wellhead data covering a range of possible wellhead pressure, temperature and NCG data is used in a calibrated wellbore simulator, which is then used to create a knowledgebase to train an artificial neural network (ANN) model. The developed ANN model tested using numerical simulation model results coupled with a wellbore simulator. It is observed that the ANN model can accurately estimate reservoir pressure and temperature for various production scenarios in liquid phase reservoir.