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Published May 28, 2021 | Published + Supplemental Material + Submitted
Journal Article Open

Constraining Fault Friction and Stability With Fluid-Injection Field Experiments

Abstract

While the notion that injecting fluids into the subsurface can reactivate faults by reducing frictional resistance is well established, the ensuing evolution of the slip is still poorly understood. What controls whether the induced slip remains stable and confined to the fluid-affected zone or accelerates into a runaway earthquake? Are there observable indicators of the propensity to earthquakes before they happen? Here, we investigate these questions by modeling a unique fluid-injection experiment on a natural fault with laboratory-derived friction laws. We show that a range of fault models with diverging stability with sustained injection reproduce the slip measured during pressurization. Upon depressurization, however, the most unstable scenario departs from the observations, suggesting that the fault is relatively stable. The models could be further distinguished with optimized depressurization tests or spatially distributed monitoring. Our findings indicate that avoiding injection near low-residual-friction faults and depressurizing during slip acceleration could help prevent large-scale earthquakes.

Additional Information

© 2021 American Geophysical Union. Issue Online: 24 May 2021; Version of Record online: 24 May 2021; Accepted manuscript online: 11 May 2021; Manuscript accepted: 05 May 2021; Manuscript revised: 30 April 2021; Manuscript received: 07 October 2020. This study was supported by the National Science Foundation (Grants EAR 1151926 and EAR 1724686), the NSF-IUCRC Center for Geomechanics and Mitigation of Geohazards (projects GMG-4.1, GMG-4.2), the National Sciences and Engineering Research Council of Canada (PGSD-3-517078-2018), and the French government through the UCAJEDI Investments in the Future project managed by the National Research Agency (ANR) with the reference number ANR-15-IDEX-01. The computations presented here were conducted on the Caltech High Performance Cluster. The authors thank Jean-Philippe Avouac, Pathikrit Bhattacharya, Yves Guglielmi, and Robert C. Viesca for helpful discussions as well as Valère Lambert and Oliver Stephenson for help with the simulation code. We would also like to thank the editor Germán Prieto as well as Eric Dunham and one anonymous reviewer for their constructive comments which have led to an improved manuscript. The authors declare no competing interests. Data Availability Statement: The data supporting the analysis and conclusions are given in Figures and Tables, in the main text, and supplementary materials. Model outputs and the experimental data from the Guglielmi et al. (2015) field experiment are accessible through the CaltechDATA repository (https://data.caltech.edu/records/1891). Data from the field experiment as reported in Guglielmi et al. (2015) can be found in the supplementary materials.

Attached Files

Published - 2020GL091188.pdf

Submitted - essoar.10504514.2.pdf

Supplemental Material - 2020gl091188-sup-0001-supporting_information_si-s01.pdf

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Additional details

Created:
August 22, 2023
Modified:
October 23, 2023