Developments in understanding seismicity triggered by hydraulic fracturing

Atkinson, Gail M.; Eaton, David W.; Igonin, Nadine

doi:10.1038/s43017-020-0049-7

Cited by 159 publications

(109 citation statements)

References 135 publications

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“…Since HF‐induced seismicity commonly occurs on previously unmapped structures (Bao & Eaton, 2016; Peña Castro et al, 2020; Skoumal et al, 2019), further research is needed to explore ways to construct more complete fault maps. Ultimately, seismicity catalogs and fault knowledge on a regional scale are inherently incomplete, motivating studies such as this to identify factors that control the likelihood of HF‐induced seismicity (Atkinson et al, 2020).…”

Section: Discussionmentioning

confidence: 99%

Machine Learning‐Based Analysis of Geological Susceptibility to Induced Seismicity in the Montney Formation, Canada

Wozniakowska

Eaton

2020

Geophysical Research Letters

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We analyze data from 6,466 multistage horizontal hydraulic fracturing wells drilled into the Montney Formation over a large region in western Canada to evaluate the impact of geological, geomechanical, and tectonic characteristics on the distribution of hydraulic fracturing-induced seismicity. Logistic regression was used to obtain a machine learning estimate of the seismogenic activation potential of each well. Our results fit the observed spatial variability, including an enigmatic change in seismicity at 120°W that does not correlate with any change in industrial activity. Feature importance analysis provides insight into data types that have the greatest impact on the results. Based on current data, seismogenic activation potential is most strongly influenced by depth of injection and distance of the well to the Cordilleran thrust belt. Plain Language Summary A supervised machine learning model is applied within a zone of oil and gas development in western Canada to determine areas where hydraulic fracturing operations are more likely to induce earthquake activity. Geological characteristics are investigated to determine factors that exert the greatest influence on earthquake triggering during or within 3 months after hydraulic fracturing. Our results indicate that an enigmatic change in seismicity patterns at 120°W arises from a combination of parameters, including distance to the northern Canadian Rockies. These inferences may be useful for a general understanding of localization of induced seismicity.

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Section: Discussionmentioning

confidence: 99%

Machine Learning‐Based Analysis of Geological Susceptibility to Induced Seismicity in the Montney Formation, Canada

Wozniakowska

Eaton

2020

Geophysical Research Letters

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“…Underground mining, deep artificial water reservoirs, oil and gas extraction, geothermal power generation, and wastewater disposal have all resulted in cases of induced seismicity. As elaborated in this review, induced earthquakes have also been documented as being caused directly by HF stage stimulation (e.g., Atkinson et al, 2020).…”

Section: Introductionmentioning

confidence: 90%

Hydraulic Fracturing‐Induced Seismicity

Schultz

Skoumal

Brudzinski

et al. 2020

Reviews of Geophysics

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Hydraulic fracturing (HF) is a technique that is used for extracting petroleum resources from impermeable host rocks. In this process, fluid injected under high pressure causes fractures to propagate. This technique has been transformative for the hydrocarbon industry, unlocking otherwise stranded resources; however, environmental concerns make HF controversial. One concern is HF‐induced seismicity, since fluids driven under high pressure also have the potential to reactivate faults. Controversy has inevitably followed these HF‐induced earthquakes, with economic and human losses from ground shaking at one extreme and moratoriums on resource development at the other. Here, we review the state of knowledge of this category of induced seismicity. We first cover essential background information on HF along with an overview of published induced earthquake cases to date. Expanding on this, we synthesize the common themes and interpret the origin of these commonalities, which include recurrent earthquake swarms, proximity to well bore, rapid response to stimulation, and a paucity of reported cases. Next, we discuss the unanswered questions that naturally arise from these commonalities, leading to potential research themes: consistent recognition of cases, proposed triggering mechanisms, geologically susceptible conditions, identification of operational controls, effective mitigation efforts, and science‐informed regulatory management. HF‐induced seismicity provides a unique opportunity to better understand and manage earthquake rupture processes; overall, understanding HF‐induced earthquakes is important in order to avoid extreme reactions in either direction.

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“…The associated rise in induced seismicity appears highly clustered near some of these HF operations and cannot be fully accounted for by the deployment of denser seismic monitoring networks and more sensitive instruments (Atkinson et al, 2016; Cui & Atkinson, 2016; Schultz, Stern, Gu, et al, 2015). Furthermore, recent studies have demonstrated that the hazard related to induced seismicity, including HF, is potentially much greater than that of natural seismicity, particularly in areas characterized by low to moderate tectonic activity (Atkinson, 2017; Atkinson et al, 2020; Langenbruch et al, 2020; Lee et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

“…The low natural occurrence rate has allowed for a relatively straightforward identification of the recent surge in unnatural seismicity (e.g., Atkinson et al, 2016), in comparison to the situation in other regions (e.g., Schoenball et al, 2015). Moreover, the increased seismicity may be particularly consequential in low‐hazard regions where facilities were not designed for high seismic levels (Atkinson et al, 2020). These factors offer significant motivation to analyze the regional changes in earthquake space, time, and magnitude distributions statistically.…”

Section: Introductionmentioning

confidence: 99%

Statistical Modeling and Characterization of Induced Seismicity Within the Western Canada Sedimentary Basin

2020

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In western Canada, there has been an increase in seismic activity linked to anthropogenic energy-related operations including conventional hydrocarbon production, wastewater fluid injection and more recently hydraulic fracturing (HF). Statistical modeling and characterization of the space, time and magnitude distributions of the seismicity clusters is vital for a better understanding of induced earthquake processes and development of predictive models. In this work, a statistical analysis of the seismicity in the Western Canada Sedimentary Basin was performed across past and present time periods by utilizing a compiled earthquake catalogue for Alberta and eastern British Columbia. Specifically, the frequency-magnitude statistics were analyzed using the Gutenberg-Richter (GR) relation. The clustering of seismicity was studied using the Nearest-Neighbour Distance (NND) method and the Epidemic Type Aftershock Sequence (ETAS) model. The obtained results suggest that recent regional changes in the NND distributions, namely a disproportionate increase in loosely and tightly clustered seismic activity over time, are unnatural and likely due to the rise in HF operations for the development of unconventional resources. It is concluded that both these loosely and tightly clustered earthquake subpopulations differ measurably from what may be the region's tectonic seismic activity. Additionally, HF treatments have a greater probability of triggering swarm-like sequences that sharply spike the seismicity rate and are characterized by steeper frequencymagnitude distributions. Conventional production and wastewater disposal operations largely trigger loosely clustered activity with more typical magnitude-occurrence rates.

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Developments in understanding seismicity triggered by hydraulic fracturing

Cited by 159 publications

References 135 publications

Machine Learning‐Based Analysis of Geological Susceptibility to Induced Seismicity in the Montney Formation, Canada

Machine Learning‐Based Analysis of Geological Susceptibility to Induced Seismicity in the Montney Formation, Canada

Hydraulic Fracturing‐Induced Seismicity

Statistical Modeling and Characterization of Induced Seismicity Within the Western Canada Sedimentary Basin

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