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Inferring Maximum Magnitudes From the Ordered Sequence of Large Earthquakes

Description: 

The largest magnitude earthquake in a sequence is often used as a proxy for hazard estimates, as consequences are often predominately from this single event. In this paper, the statistical concept of order statistics is adapted to infer the maximum magnitude (M_MAX) of an earthquake catalogue. A suite tools developed here can discern M_MAXinfluences through hypothesis testing, quantify M_MAXthough maximum likelihood estimation, or select the best M_MAXprediction amongst several models. The efficacy of these tools is benchmarked against synthetic and real-data tests, demonstrating their utility. Ultimately, thirteen cases of induced seismicity spanning wastewater disposal, hydraulic fracturing, enhanced geothermal systems are tested for volume-based M_MAX. I find that there is no evidence of volume-based processes influencing any of these cases. To the contrary, all these cases are adequately explained by an unbounded magnitude distribution. These implications towards mitigating induced seismicity and inferring source processes are discussed. Overall, this suite of tools will be important for better understanding earthquakes and managing their risks.

Session: Induced Earthquakes: Source Characteristics, Mechanisms, Stress Field Modeling and Hazards [Poster Session]

Type: Poster

Date: 5/1/2024

Presentation Time: 08:00 AM (local time)

Presenting Author: Ryan

Student Presenter: No

Invited Presentation: 

Authors