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\begin{document}

\title{A discrete fracture hybrid model for forecasting diffusion-induced
seismicity and power generation in Enhanced Geothermal Systems}



\author[1]{Dimitrios Karvounis}%
\author[2]{Stefan Wiemer}%
\affil[1]{Swiss Seismological Service, ETH Zurich,}%
\affil[2]{Swiss Seismological Service, ETH Zurich}%


\vspace{-1em}



  
  \date{May 25, 2024}


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\begin{abstract}
We describe a three-dimensional discrete fracture hybrid model (DFHM)
that returns forecasts of both induced seismicity and of power
generation in an Enhanced Geothermal System (EGS). Our model considers
pore-pressure increase as the mechanism driving induced seismicity,
similarly to other hybrid models, but it employs discrete fracture
modelling for flow and heat that allows accurate and realistic transient
solutions of pore pressure and temperature in fractured reservoirs.
Earthquakes and flow are thus considered as closely coupled processes.
In the DFHM model, the creation phase of an EGS is described as a
Markovian process with a transitional probability that encapsulates the
irreducible uncertainty with regards to induced seismicity. We
conditioned this transitional probability on field observations from the
2006 EGS project in Basel, achieving a good match with observations of
seismicity evolution. Specifically, our model effectively reproduces and
explains the observed long-term exponential decay of seismicity after
the well was shut in, suggesting that pore pressure diffusion in a
critically stressed fractured reservoir is sufficient to explain
long-lasting post-injection seismic activity as observed in Basel. We
then investigate alternative injection scenarios, using Monte Carlo
simulations to capture the uncertainties in fault locations and
stressing conditions. We show that the number of induced events depends
not only on the total injected volume but also on the injection
strategy. We demonstrate that multi-stage injection schemes are superior
to single-stage ones, since the former are associated with less seismic
risk and can generate at least the same revenue in the long term.%
\end{abstract}%



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