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\begin{document}

\title{Stress-Based and Convolutional Forecasting of Injection-Induced
Seismicity: Application to The Otaniemi Geothermal Reservoir Stimulation}



\author[1]{Taeho James Kim}%
\author[2]{Jean-Philippe Avouac}%
\affil[1]{Affiliation not available}%
\affil[2]{California Institute of Technology}%


\vspace{-1em}



  
  \date{May 17, 2024}


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\begin{abstract}
Induced seismicity observed during Enhanced Geothermal Stimulation (EGS)
at Otaniemi, Finland is modelled using both statistical and physical
approaches. The physical model produces simulations closest to the
observations when assuming rate-and-state friction for shear failure
with diffusivity matching the pressure build-up at the well-head at
onset of injections. Rate-and-state friction implies a time dependent
earthquake nucleation process which is found to be essential in
reproducing the spatial pattern of seismicity. This implies that
permeability inferred from the expansion of the seismicity triggering
front (Shapiro, 1997) can be biased. We suggest a heuristic method to
account for this bias that is independent of the earthquake magnitude
detection threshold. Our modelling suggests that the Omori law decay
during injection shut-ins results mainly from stress relaxation by pore
pressure diffusion. During successive stimulations, seismicity should
only be induced where the previous maximum of Coulomb stress changes is
exceeded. This effect, commonly referred to as the Kaiser effect, is not
clearly visible in the data from~ Otaniemi. The different injection
locations at the various stimulation stages may have resulted in
sufficiently different effective stress distributions that the effect
was muted. We describe a statistical model whereby seismicity rate is
estimated from~ convolution of the injection history with a kernel which
approximates earthquake triggering by fluid diffusion. The statistical
method has superior computational efficiency to the physical model and
fits the observations as well as the physical model. This approach is
applicable provided the Kaiser effect is not strong, as was the case in
Otaniemi.~~%
\end{abstract}%



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