Abstract
Induced seismicity due to fluid injection, including hydraulic fracturing, is an increasingly common phenomenon worldwide; yet, the mechanisms by which hydraulic fracturing causes fault activation remain unclear. Here we show that preexisting fracture networks are instrumental in transferring fluid pressures to larger faults on which dynamic rupture occurs. Studies of hydraulic fracturing-induced seismicity in North America have often used observations from regional seismograph networks at distances of 10s of km, and as such lack the resolution to answer some of the key questions about triggering mechanisms. To carry out a more detailed analysis of the mechanisms of fault activation, we use data from a dense sensor array located at a hydraulic-fracturing site in Alberta, Canada. The spatiotemporal distribution of event hypocenters, coupled with measurements of seismic anisotropy, reveal the presence of preexisting fracture corridors that allowed communication of fluid-pressure perturbations to larger faults, over distances of 1 km or more. The presence of preexisting permeable fracture networks can significantly increase the volume of rock affected by the pore-pressure increase, thereby increasing the probability of induced seismicity. This study demonstrates the importance of understanding the connectivity of preexisting natural fractures for assessing potential seismic hazards associated with hydraulic fracturing of shale formations and offers a detailed case exposition of induced seismicity due to hydraulic fracturing.
| Original language | English |
|---|---|
| Article number | e2020JB020311 |
| Journal | Journal of Geophysical Research: Solid Earth |
| Volume | 126 |
| Issue number | 3 |
| Early online date | 25 Jan 2021 |
| DOIs | |
| Publication status | Published - Mar 2021 |
Bibliographical note
Funding Information:The ToC2ME program was enabled by generous support from two companies. Continuous raw data (geophone and broadband recordings, network code TC2ME) are available through the IRIS Data Center, see also the ToC2ME GitHub: https://github.com/ToC2ME/. The seismicity catalog used to prepare the figures in this manuscript is available on Zenodo (Igonin,?2020). Financial support was provided by Chevron and the Natural Sciences and Engineering Research Council of Canada (NSERC) through the NSERC-Chevron Industrial Research Chair in Microseismic System Dynamics. James Verdon's contribution to this study was funded by the Natural Environment Research Council (NERC) under the UK Unconventional Hydrocarbons Project, Challenge 2 (Grant No. NE/R018162/1). Continuous geophone data were recorded under license from Microseismic Inc. for use of the BuriedArray method. TGS is sincerely thanked for providing the 3D multicomponent seismic data used in this analysis. CGG and Seisware are thanked for providing GeoSoftware used to display and interpret the seismic data. All sponsors of the Microseismic Industry Consortium are also sincerely thanked for their ongoing support. Nadine Igonin was supported through the NSERC PGS-D, the SEG Reba C. Griffin Memorial Scholarship, and this collaboration was funded through the NSERC MSFSS, which facilitated the lead author's visit to the University of Bristol. J. M. Kendall was funded by Natural Environment Research Council (NERC) under the UK Unconventional Hydrocarbons Project, Challenge 3 (Grant No. NE/R018006/1). James Verdon and J. M. Kendall were partially funded by the Bristol University Microseismic Projects (BUMPS), an industry funded consortium. We thank Tom Kettlety for his advice with the stress modeling portion of this paper. We thank Emerson Automation Solutions for the use of their Tempest reservoir modeling tools, and specifically Paul Childs for his helpful discussions as to the application of this software. Finally, we thank the reviewers and the editor for their suggestions for improving the manuscript.
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