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Coulomb stress-based forecasting of injection-induced seismicity in Oklahoma and Kansas

Research output: Contribution to journal › Article › peer-review

Abstract

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 Mw ≥ 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.

Original languageEnglish
Article number119677
Pages (from-to)1-14
Number of pages14
JournalEarth and Planetary Science Letters
Volume671
Early online date15 Oct 2025
DOIs
Publication statusPublished (in print/issue) - 1 Dec 2025

Bibliographical note

Publisher Copyright:
Copyright © 2025. Published by Elsevier B.V.

Data Availability Statement

Data used in this study are publicly available.

Funding

We thank Mateo Acosta, Qian Shi, Lei Jin, Stefan Hussenoeder and Josimar Alves Da Silva for discussions regarding the implementation of our model. This study was supported by the center of Geomechanics and Mitigation of Geohazards thanks to the enhancement project funded by ExxonMobil Technology and Engineering Company.

    UN SDGs

    This output contributes to the following UN Sustainable Development Goals (SDGs)

    1. SDG 9 - Industry, Innovation, and Infrastructure
      SDG 9 Industry, Innovation, and Infrastructure
    2. SDG 11 - Sustainable Cities and Communities
      SDG 11 Sustainable Cities and Communities
    3. SDG 13 - Climate Action
      SDG 13 Climate Action

    Keywords

    • Induced seismicity
    • Forecast
    • Poroelasticity

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