5 research outputs found
Autonomous decision-making against induced seismicity in deep fluid injections
The rise in the frequency of anthropogenic earthquakes due to deep fluid
injections is posing serious economic, societal, and legal challenges to
geo-energy and waste-disposal projects. We propose an actuarial approach to
mitigate this risk, first by defining an autonomous decision-making process
based on an adaptive traffic light system (ATLS) to stop risky injections, and
second by quantifying a "cost of public safety" based on the probability of an
injection-well being abandoned. The ATLS underlying statistical model is first
confirmed to be representative of injection-induced seismicity, with examples
taken from past reservoir stimulation experiments (mostly from Enhanced
Geothermal Systems, EGS). Then the decision strategy is formalized: Being
integrable, the model yields a closed-form ATLS solution that maps a risk-based
safety standard or norm to an earthquake magnitude not to exceed during
stimulation. Finally, the EGS levelized cost of electricity (LCOE) is
reformulated in terms of null expectation, with the cost of abandoned
injection-well implemented. We find that the price increase to mitigate the
increased seismic risk in populated areas can counterbalance the heat credit.
However this "public safety cost" disappears if buildings are based on
earthquake-resistant designs or if a more relaxed risk safety standard or norm
is chosen.Comment: 8 pages, 4 figures, conference (International Symposium on Energy
Geotechnics, 26-28 September 2018, Lausanne, Switzerland