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

Abstract

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.

Evolution of Short‐Term Seismic Hazard in Alberta, Canada, From Induced and Natural Earthquakes: 2011–2020

“…Considerable variations in the $$a$$‐ and $$b$$‐values from different seismic clusters in Alberta have been observed in other studies, including the statistical modeling and characterization of induced seismicity conducted by Kothari et al. (2020). For instance, Kothari et al.…”

“…Considerable variations in the 𝐴𝐴 𝐴𝐴 -and 𝐴𝐴 𝐴𝐴 -values from different seismic clusters in Alberta have been observed in other studies, including the statistical modeling and characterization of induced seismicity conducted by Kothari et al (2020). For instance, Kothari et al (2020) infer a 𝐴𝐴 𝐴𝐴 -value of 0.74 for the Rocky Mountain House cluster, whereas the Fox Creek area shows a 𝐴𝐴 𝐴𝐴 -value of 1.57. Another critical aspect is that, in cases like Fox Creek, we infer temporal changes in the annual 𝐴𝐴 𝐴𝐴 -values.…”

“…Considering multiple areas is important, particularly if the induced seismic source areas have different GR parameters, 𝐴𝐴 𝐴𝐴 -and 𝐴𝐴 𝐴𝐴 -values, as we identify in this study. Considerable variations in the 𝐴𝐴 𝐴𝐴 -and 𝐴𝐴 𝐴𝐴 -values from different seismic clusters in Alberta have been observed in other studies, including the statistical modeling and characterization of induced seismicity conducted by Kothari et al (2020). For instance, Kothari et al (2020) infer a 𝐴𝐴 𝐴𝐴 -value of 0.74 for the Rocky Mountain House cluster, whereas the Fox Creek area shows a 𝐴𝐴 𝐴𝐴 -value of 1.57.…”

“…For instance, Kothari et al. (2020) infer a $$b$$‐value of 0.74 for the Rocky Mountain House cluster, whereas the Fox Creek area shows a $$b$$‐value of 1.57. Another critical aspect is that, in cases like Fox Creek, we infer temporal changes in the annual $$b$$‐values.…”

An Adaptable Random Forest Model for the Declustering of Earthquake Catalogs

“…Physically speaking, classifying earthquakes in these two categories is not firmly accurate. However, isolating the background seismicity from the aftershocks, which we will refer to as catalog declustering, is crucial for a wide range of studies, such as the along‐fault monitoring of transient loading (Marsan, Prono, & Helmstetter, 2013; Marsan, Reverso, et al., 2013; Reverso et al., 2015) or fluid injections (Bachmann et al., 2011; Hainzl & Ogata, 2005; Kothari et al., 2020), and hazard assessments (Azak et al., 2018; Galina et al., 2019; Marzocchi & Taroni, 2014; Taroni & Akinci, 2021).…”