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An Ensemble Approach to Characterizing Trailing Induced Seismicity

Description: 

Earthquakes caused by human activities can pose significant risks, and lingering seismicity that trails the stopped anthropogenic operation is a particular challenge for risk management. To address this concern, we characterize cases where induced seismicity stops. Five competing models are fit to 56 trailing seismicity cases that span injection operations including: hydraulic fracturing, enhanced geothermal systems, wastewater disposal, and gas storage. Models are ranked based on a suite of statistical performance metrics. We find that the Omori and Stretched Exponential models are typically the best fitting; however, since there are cases where each model is best, we advocate for the use of an ensemble. We discuss a framework for a weighted ensemble that updates based on model performance and then demonstrate with a post hoc ‘forecast’ of trailing seismicity. We also find some cases (~23%) that misfit all the models. Residual analysis of these outlier cases shows common themes, including productive trailing sequences that abruptly cease. Such outliers suggest room for more physically motivated models that can encompass phenomenon such as operator mitigation, stress shadows, or poroelasticity. The results of our study provide a quantitative framework for quantifying trailing seismicity, including both forecasting, and observable mitigation criteria.

Session: De-risking Deep Geothermal Projects: Geophysical Monitoring and Forecast Modeling Advances

Type: Oral

Date: 4/18/2023

Presentation Time: 08:45 AM (local time)

Presenting Author: Ryan Schultz

Student Presenter: No

Invited Presentation: 

Authors