Item request has been placed! ×
Item request cannot be made. ×
loading  Processing Request

A semi-analytical formulation for thermo-mechanical advective-diffusive heat transport in DFN

Item request has been placed! ×
Item request cannot be made. ×
loading   Processing Request
  • معلومة اضافية
    • Contributors:
      Observatoire des Sciences de l'Univers de Rennes (OSUR); Géosciences Rennes (GR); Université de Rennes 1 (UR1); Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire des Sciences de l'Univers de Rennes (OSUR)-Centre National de la Recherche Scientifique (CNRS); Itasca Consultants; American Rock Mechanics Association (ARMA).
    • بيانات النشر:
      HAL CCSD
    • الموضوع:
      2021
    • Collection:
      Archive ouverte HAL (Hyper Article en Ligne, CCSD - Centre pour la Communication Scientifique Directe)
    • الموضوع:
    • نبذة مختصرة :
      International audience ; Modeling heat transfer in complex heterogeneous fractured system is key for geothermal energy applications. Discrete fracture network (DFN) modeling is the ideal framework to reproduce the advective part of the transport, which is determined by the fracture connectivity and heterogeneity. This approach in general sacrifices the representation of the rock matrix, disregarding both its diffusive heat exchange with the fractures and the effects of its thermo-mechanical deformation on the fracture aperture. Here we propose a new semi-analytic formulation that can be implemented in a DFN simulator with particle tracking approach. The contribution of the rock matrix in terms of diffusive heat exchange and thermal contraction/expansion is analytically evaluated, which respectively impact the advective heat transfer and the fracture aperture variation. The methodology enables investigating the reservoir behavior and optimizing the geothermal performance while keeping the computational effort within reasonable values. This allows exploring the uncertainty in cases when the characterization is poor, which is the spirit of the DFN modeling.
    • Relation:
      insu-03326683; https://hal-insu.archives-ouvertes.fr/insu-03326683; https://hal-insu.archives-ouvertes.fr/insu-03326683/document; https://hal-insu.archives-ouvertes.fr/insu-03326683/file/DeSimone_et_al_DFNE_2021_paper_last.pdf
    • Rights:
      info:eu-repo/semantics/OpenAccess
    • الرقم المعرف:
      edsbas.24711A8D