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Abstract In areas of induced seismicity, earthquakes can be triggered by stress changes due to fluid injection and static deformation from fault slip. Here we present a method to distinguish between injection‐driven and earthquake‐driven triggering of induced seismicity by combining a calibrated, fully coupled, poroelastic stress model of wastewater injection with interpretation of a machine learning algorithm trained on both earthquake catalog and modeled stress features. We investigate seismicity from Paradox Valley, Colorado as an ideal test case: a single, high‐pressure injector that has induced thousands of earthquakes since 1991. Using feature importance analysis, we find that injection‐driven earthquakes are approximately 225% of the total catalog but act as background events that can trigger subsequent aftershocks. Injection‐driven events also have distinct spatiotemporal clustering properties with a larger b‐value, closer proximity to the well, and earlier occurrence in the injection history. Generalization of our technique can help characterize triggering processes in other regions where induced seismicity occurs.
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This content will become publicly available on December 1, 2026
Coulomb stress-based forecasting of injection-induced seismicity in Oklahoma and Kansas
Induced seismicity in Oklahoma and South Kansas has been widely attributed to wastewater disposal into the deep Arbuckle formation. However, the relative contributions of pore-pressure diffusion and poroelastic stress changes to earthquake triggering remain debated. In this study, we apply the Coulomb threshold rate-and-state seismicity forecasting model of Heimisson et al. (2022) to induced seismicity in the region from 2000 to 2024. Our model is informed by poroelastic stress changes resulting from wastewater injection between 1995 and 2024 and is benchmarked against existing seismicity forecast models. Despite its simplicity, our model accurately reproduces the onset, peak, and decline of seismicity, demonstrating strong agreement with the observed earthquake activity in space and time. It provides robust constraints on permeability, yielding a range consistent with previously reported values. Based on the fit to the data, the model informed by poroelastic stress changes performs better. However, regardless of the assumed mechanism, both models yield similarly reliable seismicity forecasts, indicating that the choice of mechanism has a limited impact on forecasting performance. Finally, we estimate the probability of an >= 5 event occurring between 2021 and 2024 to range from 7% to 18% and conclude that seismic risk will remain elevated if wastewater injection volumes into the Arbuckle persist at similar levels in the coming years.
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- Award ID(s):
- 1822214
- PAR ID:
- 10655489
- Publisher / Repository:
- Elsevier
- Date Published:
- Journal Name:
- Earth and Planetary Science Letters
- Volume:
- 671
- Issue:
- C
- ISSN:
- 0012-821X
- Page Range / eLocation ID:
- 119677
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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