Energies (Jan 2021)

Coupled Thermo–Hydro–Mechanical–Seismic Modeling of EGS Collab Experiment 1

  • Jianrong Lu,
  • Ahmad Ghassemi

DOI
https://doi.org/10.3390/en14020446
Journal volume & issue
Vol. 14, no. 2
p. 446

Abstract

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An important technical issue in the enhanced geothermal system (EGS) is the process of fracture shear and dilation, fracture network propagation and induced seismicity. EGS development requires an ability to reliably predict the fracture network’s permeability evolution. Laboratory and field studies such as EGS Collab and Utah FORGE, and modeling simulations provide valuable lessons for successful commercial EGS design. In this work we present a modeling analysis of EGS Collab Testbed Experiment 1 (May 24, Stim-II ≅ 164 Notch) and interpret the stimulation results in relation to the creation of a fracture network. In doing so, we use an improved 3D discrete fracture network model coupled with a 3D thermo-poroelastic finite element model (FEM) which can consider fracture network evolution and induced seismicity. A dual-scale semi-deterministic fracture network is generated by combining data from image logs, foliations/micro-fractures, and core. The natural fracture properties (e.g., length and asperity) follow a stochastic distribution. The fracture network propagation under injection is considered by an ultrafast analytical approach. This coupled method allows for multiple seismic events to occur on and around a natural fracture. The uncertainties of seismic event clouds are better constrained using the energy conservation law. Numerical simulations show that the simulated fracture pressure profiles reasonably follow the trend observed in the field test. The simulations support the concept that a natural fracture was propagated from the injection well connecting with the production well via intersection and coalescence with other natural fractures consistent with plausible flow paths observed on the field. The fracture propagation profiles from numerical modeling generally match the field observation. The distribution of simulated micro-seismicity have good agreement with the field-observed data.

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