Induced seismicity closed-form traffic light system for actuarial decision-making during deep fluid injections

Area of Science:

• Geophysics
• Risk Assessment
• Sustainable Energy

Background:

• Anthropogenic earthquakes from deep fluid injections pose significant risks to geo-energy and waste disposal projects.
• Current risk assessment methods are largely heuristic and rely on expert judgment, lacking quantitative rigor.

Purpose of the Study:

• To introduce a novel, data-driven Adaptive Traffic Light System (ATLS) for statistically modeling and managing induced seismicity risks.
• To provide an actuarial judgment of seismic risk based on earthquake magnitude and flow rates, complementing existing assessment tools.

Main Methods:

• Developed a statistical model for induced seismicity, incorporating a linear relationship between seismicity rate and flow rate, and a normal diffusion process for post-injection.
• Integrated this model into a closed-form Adaptive Traffic Light System (ATLS) solution.
• Validated the ATLS using data from six underground reservoir stimulation experiments, primarily from Enhanced Geothermal Systems.

Main Results:

• The proposed statistical model accurately represents the observed data from fluid injection experiments.
• The closed-form ATLS solution is transparent, robust, and demonstrated to consistently ensure the predefined safety target through simulations.
• The system provides an actuarial risk assessment, mapping earthquake magnitude to risk levels.

Conclusions:

• The ATLS offers a reliable, data-driven approach to managing risks associated with induced seismicity in geo-energy operations.
• While simulations confirm the ATLS's effectiveness, further validation in diverse fluid injection environments is recommended due to the limited dataset used.
• This system enhances safety and predictability for projects involving deep fluid injections.