As recently as 2015, it was common in the scientific literature to find assertions that the risk of triggering a damaging earthquake by hydraulic fracturing (HF) — an industrial process where pressurized fluids are used to create or open fractures within rock layers — could be treated as negligible. However, that viewpoint has changed dramatically. It is now clear that the hazard from induced seismicity (including HF) exceeds the natural hazard in low-to-moderate seismicity environments. As such, to mitigate risk to vulnerable and critical infrastructure, it is important to address the likelihood and triggering mechanisms of HF-induced earthquakes. Although it is sometimes claimed that HF-induced earthquakes can be accurately predicted, avoided or controlled, critical knowledge gaps still remain. In this Review, we discuss six fundamental issues surrounding induced seismicity, focusing specifically on HF-induced events, including: the triggering mechanisms of HF seismicity; the relationship between tectonic environment and HF seismicity; the similarities and differences between induced and natural events; the damage potential associated with HF-induced seismicity; whether HF-induced events can be predicted; and the relative hazards of HF-induced and natural seismic events. We finish by outlining future research directions that are required to minimize the uncertainty and hazard that surround induced seismicity.
Hydraulic fracturing can trigger earthquakes large enough (generally, magnitude >4) to cause potentially damaging ground motions, with actual damage depending on the intensity of motions and the vulnerability of nearby infrastructure.
The triggering of anomalous events (M >2) requires a source of stress perturbation, a pre-existing, critically stressed fault with sufficient surface area to host a felt event and a coupling mechanism that connects the source to the fault, either directly or indirectly.
Induced earthquakes are similar to their natural counterparts with respect to source characteristics, magnitude–frequency characteristics and ground motions.
The hazard from earthquakes induced by hydraulic fracturing might greatly exceed the natural earthquake hazard in regions of low to moderate seismicity, which is consequential for the seismic safety of nearby (<10 km) infrastructure.
Potentially damaging induced events cannot be confidently predicted in advance of operations. Current risk-mitigation strategies, such as traffic light protocols, have not yet proved reliable. Further development of hazard forecasting and mitigation approaches is a critical future area of research.
Induced seismicity — defined as earthquakes associated with human activity — has been a topic of active research for many decades1,2,3,4,5,6,7,8,9. Induced seismicity can be caused by a range of human activities, including deep underground mining and injection (or withdrawal) of fluids in the subsurface10 (Table 1). In the central USA, the rate of induced earthquakes with a magnitude >3 (greater than the felt threshold) has increased tenfold over the past decade11; in western Canada, the rate has increased by a factor of 3 (refs12,13) (magnitude (M) is typically reported on either the moment magnitude (M) or local magnitude (ML) scales). In the central USA, increased seismic activity has been primarily linked to large-volume saltwater disposal (SWD)14, whereas in western Canada, it is typically associated with the industrial process of hydraulic fracturing (HF) along horizontal wellbores12.
Hydraulic fracturing, or ‘fracking’, is a wellbore-completion method that is used to improve the recovery of hydrocarbons from unconventional oil and gas reservoirs (such as low-permeability rocks)15. Injection of high-pressure fluids, usually a water–sand slurry, is used to create an open fracture network that enhances fluid flow within porous but otherwise impermeable strata10. Since its inception in 1947, HF has been employed at more than 1.8 million wells in North America, with the first reported HF-induced earthquake in Love County, Oklahoma in 1979 (M 1.9)16. Technological advances, beginning around 2009, facilitated the widespread application of massive, multistage HF along horizontal wellbores17.
International attention to HF-related seismicity increased in response to a series of small earthquakes triggered in 2011 by fracking of the Preese Hall 1 exploration well near Blackpool, UK18,19. Since 2011, HF-triggered earthquakes of increasing magnitudes, up to ML 5.7, have been documented at many locations around the world20 (Fig. 1; Table 2). The largest HF-triggered events, which occurred in China, caused economic losses, injuries and fatalities, leading to heightened concern surrounding HF-triggered seismicity20,21. In addition, the events in China indicate that we should not focus solely on the probability of events occurring (the hazard) but also on the risks associated with these events (the consequences)22.
It is important to note, however, that there are large parts of western Canada, North Dakota and Pennsylvania where induced seismicity has not been observed, even though HF operations are widespread12,23. In fact, statistical studies12 indicate that, averaged over western Canada as a whole, only ~0.3% of horizontally drilled HF wells are associated with events of M ≥3, although this value varies widely within the region24. Nevertheless, the increase in frequency (and magnitude) of seismic events associated with HF over the past decade indicates that it is important to consider the hazards and risks associated with these events, even if they only originate from a small percentage of HF wells.
In this Review, we provide an overview of the current state of knowledge of HF-triggered seismicity. We discuss the available literature surrounding six fundamental issues that have important ramifications for the assessment and mitigation of hazards associated with the use of HF technology: how HF triggers seismicity; the relationship between the tectonic environment and HF-triggered seismicity; the differences between HF-triggered and natural earthquakes; the damage potential of HF earthquakes; the predictability of HF earthquakes; and the relative hazards of HF-triggered versus natural seismicity. Our Review is primarily focused on HF-triggered seismicity, but other forms of injection-triggered seismicity (such as enhanced geothermal stimulation (EGS) and SWD) are also discussed to illustrate common themes (Table 1).
Determining how HF triggers earthquakes is important, as it represents the starting point for understanding the physical processes that control HF seismicity. By design, HF is intended to create new fractures and/or open existing fractures to enhance the permeability of the reservoir and, thus, enable economic flow rates15. The fracturing process is commonly associated with seismic events M <0, referred to as operationally induced microseismicity10. Microseismic events close to hydraulic fractures, which provide a useful proxy for the stimulated part of the reservoir25,26, are considered a normal part of HF. However, activation of pre-existing fault systems during HF could lead to larger and potentially damaging earthquakes. In this section, we examine the triggering mechanisms of HF-induced earthquakes and discuss the conditions that are required to explain larger events (M >2) triggered by HF, which often occur at a substantial distance (approximately 2 km) from the well27,28,29.
Necessary conditions for triggering felt events
A small fraction of HF-induced earthquakes might be large enough (generally, M >2) to generate ground motions that people feel (known as felt induced events). Researchers studying induced seismicity widely acknowledge that certain conditions are required for the generation of felt induced events, including: a source of stress perturbation, a pre-existing critically stressed fault with sufficient surface area to host a felt event and a coupling mechanism that directly or indirectly connects the source to the fault10.
The concept of a critically stressed fault implies that it is in a state of incipient failure and, therefore, subject to activation in response to a perturbation that is small relative to ambient stresses30. It is often treated as a binary concept (a fault either is or is not critically stressed), although, in practice, the stress change required to reactivate a fault will depend on the in situ stress field and the orientation of the fault31,32. As a result, a discrete reactivation threshold is difficult to determine. Nevertheless, in some cases, induced seismicity has been postulated to result from very small stress perturbations (<1 MPa)28,29,33,34.
Fault reactivation by pore-pressure effects
Reactivation of a fault is often evaluated with respect to the Mohr–Coulomb threshold, where slip will occur if the shear stress τ exceeds the criterion:
where σ′n is the effective normal stress (σ′n = σn − P, where σ′n is the normal stress and P is the pore pressure), ϕ is the coefficient of friction and C is the fault cohesion. We use the sign convention that positive σn corresponds with an increase in the compressive force acting on a surface. It is apparent that slip might be triggered by a reduction of the normal stress, an increase in the pore pressure, a change in the coefficient of friction and/or loss of fault cohesion35.
Since the Denver earthquakes in the mid 1960s1 and subsequent studies at Rangely, Colorado2, it has been well established that a reduction in effective normal stress on a fault due to increasing pore pressure is an important seismogenic mechanism (Fig. 2). In the case of HF, direct injection of pressurized fluids into a fault zone represents a conceptually simple causative mechanism for triggering seismicity36,37. For example, microseismic observations tracked the direct intersection (and subsequent activation) of a pre-existing fault by HF in western Canada36.
However, hydraulic fractures typically do not extend more than a few hundred metres from the treatment well38 and the low matrix permeability of most unconventional plays inhibits transfer of elevated pore pressures beyond the stimulated zone12. It has been proposed that high-permeability pathways (for example, fracture corridors) within low-permeability rocks could represent a mechanism by which elevated pore pressures are rapidly transferred to larger distances27,39,40. Analysis of the time delays between injection and seismicity can be used to characterize the permeability of such features41,42,43,44 and determine the cases for which increased pore pressure might be the triggering mechanism.
Fault reactivation by poroelastic effects
In cases where there appears to be no direct hydraulic connection to the well, some studies have invoked poroelastic effects to explain fault reactivation28,29. An increase in pore pressure causes an expansion of the rock frame, which pushes outwards on the surrounding rocks (and vice versa), perturbing the surrounding stress field45 (Fig. 2). Because the resulting stress field is transferred through the rock frame, it is not constrained by the low permeability of the pore space. For SWD operations, poroelastic coupling has been invoked to explain induced seismicity at a distance of >40 km (ref.34). Similarly, tensile opening of hydraulic fractures is thought to cause deformation in the surrounding rock that appears to control the location of induced events. The potential role of poroelastic effects in event triggering is typically evaluated by comparing numerical models of stress changes caused by injection with the locations of induced seismicity29,37,46.
Fault reactivation by aseismic slip
Fault activation by fluid injection is a complex process that depends on the interplay between fluid pressurization and friction47. Direct measurements of the offset on a pre-existing fault in south-eastern France, following an increase in pore pressure, demonstrate that slip can occur at slip speeds of only ~0.01 mm s−1, accompanied by minor brittle failure within the damage zone around the fault48. Measurements of the frictional parameters of rocks that characterize unconventional plays49 show that high clay mineral content, total organic content or both increase the probability of slow slip due to velocity-strengthening effects50.
Aseismic slip provides another potential triggering mechanism for induced dynamic rupture. In this scenario, pressurization of the faulted region due to HF causes slow slip (creep) on frictionally stable parts of the fault system near the stimulated zone. As aseismic slip accumulates, it progressively loads other parts of the fault system that are frictionally unstable, leading (in some cases) to dynamic rupture51. Numerical simulations suggest that the creep front can outpace pore-pressure diffusion, ultimately leading to earthquake nucleation outside the region of increased pore pressure48,52. There is also evidence that the presence of injected fluids and/or aseismic creep might prolong the duration of induced seismicity (typically, for days to weeks), giving rise to swarm-like behaviour, as well as enhanced susceptibility to remote triggering53.
The Mohr–Coulomb failure criteria (Eq. 1) suggest that there are several mechanisms by which HF can trigger seismicity. Although the direct impact of elevated pore pressure is generally limited to the stimulated part of a reservoir close (on the order of hundreds of metres) to the injection well, mechanisms such as poroelastic coupling and aseismic creep could extend the range of influence of HF. Such effects have been used to explain seismicity that has been triggered above51 and below28,54,55,56 the target formation, as well as to distances of ~1–2 km laterally from the well27,28,44. It is important to recognize that the triggering mechanisms, distance over which events can be triggered and the probability of induced seismicity occurring is likely to depend on the local and regional tectonic and geological structure of the region.
Some unconventional HF plays, such as the Duvernay57, Montney58 and Exshaw56 plays in the Western Canada Sedimentary Basin (WCSB), the SCOOP (South Central Oklahoma Oil Province) and the STACK (Sooner Trend (oil field), Anadarko (basin), Canadian and Kingfisher (counties)) plays in Oklahoma59 and the Sichuan Basin, China20,21, have produced high levels of seismicity. However, the lack of induced seismicity associated with several other unconventional HF plays, such as the Barnett (Texas), Marcellus (centred on Pennsylvania) and Bakken (North Dakota and Saskatchewan) shale gas plays, demonstrates that the relationship between HF and induced seismicity is likely to be influenced by the tectonic setting23. For example, in the Bowland Shale (UK), only three wells have been stimulated by HF; yet, these have produced events with magnitudes of M = 2.3, 1.5 and 2.9 (refs18,60). Considering the paucity of HF operations in the Bowland Shale, the occurrence of these events suggests a high susceptibility to induced seismicity.
The areas that have a high susceptibility to induced seismicity occur within a wide range of different tectonic environments. For example, areas of high susceptibility within the WCSB, such as the Duvernay and the Montney plays, are located in the Late Cretaceous–Paleocene foreland of the Canadian Rocky Mountain thrust belt, which developed in a continental sedimentary platform setting61. The Lower Paleozoic Sichuan Basin in China has a very complex tectonic history, coupled to the development of four orogenic belts62. The Bowland Basin (UK) represents an Early Carboniferous basin that experienced several phases of extension and intrabasinal tectonics, including basin inversion in the Late Carboniferous63.
The rate of induced seismicity in different environments can be directly compared by using quantitative measures, such as the seismogenic index, Σ (ref.31), which relates the number of events of a given magnitude to the injection volume. The original definition of the seismogenic index was developed for EGS applications involving injection into one well, but adapted definitions have been proposed for multiwell HF operations57,64. Previous studies have shown that Σ values vary by ~10 orders of magnitude across a selection of sites (both unconventional gas and geothermal sites), demonstrating clear variations in the susceptibility of a region to induced seismicity. The rate of seismicity in different tectonic environments can also be examined by comparing the per-well likelihood of triggering events. In the WCSB, the per-well probability of triggering events with M ≥3 ranges from ~0.1% for the Cardium Formation to ~5% for the Duvernay Formation65. However, for formations where no triggered seismicity has yet been observed, there is no accepted methodology to forecast the likelihood of an event.
Multiple mechanisms have been proposed to explain the variation observed in the susceptibility to induced seismicity across different tectonic settings. For example, HF-induced seismicity might be expected to correlate with formations that are overpressured (pore pressures greater than hydrostatic), as elevated pore pressure will reduce the effective normal stress, bringing faults closer to the Mohr–Coulomb threshold66. Alternatively, the relative abundance of pre-existing faults can be used to explain the observed distribution of induced seismicity: the edges of Paleozoic reef complexes in the WCSB have been used as a proxy for the presence of basement faulting, explaining an apparent correlation between induced seismicity and the edges of the Swan Hills carbonate platform67.
In addition, application of machine-learning algorithms to documented instances of triggered seismicity in the WCSB found that a selection of features, including the proximity to the basement, in situ stress, proximity to fossil-reef margins, lithium concentration and rate of natural seismicity, were among the strongest predictor variables for the presence of induced seismicity68. Such algorithms might be promising but are still in learning modes, with their utility to accurately forecast risk yet to be established. Indeed, a series of felt events triggered by HF near Red Deer, Alberta, including an event of M 4.4, occurred in March 2019 in an area that was previously mapped by machine-learning algorithms as having a relatively low seismogenic-activation potential68.
Comparison with tectonic earthquakes
Regardless of whether induced events occur in regions that have a high seismogenic-activation potential or not, it is important to compare HF earthquakes and tectonic earthquakes to determine whether a specific event is natural or induced and if triggered earthquakes have the same damage potential as their natural counterparts. A commonly employed approach to distinguish natural from induced events uses a series of questions about the temporal and spatial relationship between events and industrial activities, and about the expected pressure perturbations69,70. In cases that return a higher number of ‘yes’ answers, there is a higher likelihood that the events were induced. This approach was updated in 2019 by weighting questions according to their relative importance, and by including a term that describes the quality of evidence used to perform the assessment71.
Alternatively, a suite of assessment schemes has been proposed to assess whether seismic events are induced or natural. The first assessment scheme compares observed seismicity with seismicity simulated from physics-based models that include the effects of depletion-induced subsurface stress perturbations, where the null hypothesis posits that seismicity occurs at a regional background rate72. The second scheme uses statistical correlations between industrial activities and parameters that describe the seismic-event population, such as the event frequency, magnitude distribution, spatial distribution and interevent times73. The third scheme uses source mechanisms as a discriminator, as some industrial activities, such as collapse events during mining, might produce characteristic source mechanisms that differ from those of earthquakes74.
In addition, it has been suggested that, in Oklahoma and California, changes in the background rate, aftershock productivity and interevent distances, as documented through epidemic-type aftershock sequence (ETAS) models75, can distinguish fluid-induced seismicity from natural seismicity76. The ETAS model has also been applied to identify induced events in the Sichuan Basin, China77. Using a similar method, several distinguishing statistical characteristics of seismicity induced by fluid injection were identified in California78, which included higher background rates, faster temporal decay sequences and different spatial-clustering properties.
In some cases, it has been straightforward to compile compelling evidence that events were likely induced by HF27,28,56,79,80. However, in specific cases, it has been challenging to make an unambiguous assessment, with debate continuing within both the academic literature and the public sphere81. Often, the association can be generic rather than specific; for example, statistical analysis of the spatio-temporal correlation between HF and seismicity, relative to that expected by random chance, was used to infer that more than half of the observed seismicity in the WCSB (with M ≥3) was related to HF12. However, in the WCSB, it is not feasible to determine the relationship between natural and induced events for every well and every earthquake.
Some case studies indicate that, unlike natural events, low-magnitude microseismicity (M <0) associated with HF propagation might exhibit non-double-couple components82,83,84. Larger HF-triggered events (M >3), however, typically have dominantly double-couple focal mechanisms that are consistent with regional stress fields18,20,55,60,85,86. Moreover, the radiated spectra and stress drop associated with large HF events appears to be similar to that observed in shallow natural earthquakes87,88,89. In addition, ground motions generated by induced events are comparable to those resulting from shallow tectonic events of the same magnitude and hypocentral distance90,91,92. In summary, once triggered, M >2 HF earthquakes appear to be very similar to their natural counterparts, which reinforces the interpretation that HF triggers earthquakes by reactivation of pre-existing tectonic structures.
Some differences in the stress drop and, in turn, ground motion resulting from natural and induced earthquakes are likely to occur owing to variations in the focal depth of the events (induced events, on average, occur at shallower depths)90. However, the focal depths of both natural and induced events are often poorly constrained by regional seismograph networks; high-density local arrays are needed to provide definitive solutions. For example, a single M 4.1 earthquake in Alberta, Canada, was identified to have occurred at ~3-km depth (above the treatment formation)86 and at ~5-km depth (below the treatment formation)93 by different studies. In this single example, the shallower depth estimate could be considered as the most reliable, as a dense local network, calibrated by ground-truth events, was used to estimate the depth, whereas the deeper estimate was based on more limited station data. Moving forward, a new method has been developed, based on the velocity information from co-located, multicomponent seismic data94, to provide better depth constraints in the future.
Damage potential of HF earthquakes
Despite the clear evidence that earthquakes associated with industrial processes (HF, EGS, SWD) can produce seismic events that are M >3 and have similar source characteristics to natural events, the potential of induced seismicity to cause damage to local or critical infrastructure has only recently been considered. Therefore, in this section, we address the potential of HF to trigger damaging earthquakes, a topic that is especially important in developing regions with a high density of vulnerable infrastructure.
Distribution of event magnitudes
Induced events, like their natural counterparts, generally follow the well-known Gutenberg–Richter relation95, where the number of earthquakes for a given time period (N(M)) decreases exponentially as magnitude (M) increases57,60,96. The Gutenberg–Richter (1944) relation is characterized by a rate parameter (‘a-value’) and the decay slope (‘b-value’):
Therefore, the expected number of large events can be predicted, in a general sense, from the observed or modelled number of small events if the b-value is known60. For a typical b-value of 1, the event rate decreases by a factor of 10 for every increase of 1 magnitude unit. HF-driven microseismicity (M <0), which occurs near the injection point as a direct response to pore-pressure perturbation, is often observed to have a b-value of ~2 (refs36,84,97), indicating an unusually sharp drop in event frequency with increasing magnitude. By contrast, injection-triggered sequences that include larger events (M ≥3) typically have b-values of ~1, similar to that observed for natural earthquakes57,96,98.
If there are no physical constraints on the maximum size of event that can be triggered, the basic statistics of HF-triggered seismicity can, at least in theory, be used to assess the likelihood of earthquakes of potentially damaging magnitudes96. From 2010 through 2018, there were ~20,000 horizontally drilled HF wells in western Canada. Given the basin-wide average incidence rate of wells with M >3 events (0.3%)12, we would expect to have seen approximately six HF-triggered events of M ≥4, with the expected value of the largest event being M ~4.7 (assuming a Gutenberg–Richter relation with b ~1). In fact, in western Canada, seven HF-triggered events of M >4 were observed between 2010 and 2018, with a largest magnitude of M 4.6 (ref.65). More broadly, we could expect that, as the number of HF wells grows, the maximum magnitude of HF-triggered events would gradually rise globally. Consistent with predictions, the largest reported magnitudes for HF-triggered events has increased globally from M 2.3 in 2011 (ref.18) to ML 3.8 in 2012 (ref.79), M 4.6 in 2015 (ref.12) and ML 5.7 in 2018 (ref.20).
The largest HF-triggered event to date (ML 5.7, M 5.3) occurred in the Sichuan Basin in China, causing injury to 17 people, large-scale landslides, collapse of nine houses and extensive damage to 390 houses20, highlighting that HF-triggered events can be damaging. However, the scale of the damage that could be caused by HF-triggered events depends on a range of factors, including the magnitude of the event, its proximity to population or critical infrastructure, the intensity of the ground motions it generates and the vulnerability of the local infrastructure.
Ground motions and damage potential
It is now well documented that injection-induced earthquakes might produce high-amplitude ground motions that could damage nearby infrastructure13,20,99,100,101. Documented damage caused by HF-induced seismicity ranges from superficial damage of vulnerable unreinforced masonry structures (M 3.4)102 to major and/or widespread damage of buildings (M 4.9–5.8)20,101,103. The ground motion expected from induced events was initially estimated on the basis of instrumental ground-motion data from shallow earthquakes in California104. However, since 2015, the amount of quantitative information on induced ground motions has grown dramatically, enriched by instrumental records from events in Oklahoma105,106 and western Canada107,108,109,110. The growth of instrumental data has enabled development of ground-motion models directly from induced-event databases106,110, and these models will continue to improve in the future.
The U.S. Geological Survey (USGS) ‘Did You Feel It’ reporting system also contains a wealth of information about ground motion resulting from induced seismic events, with more than 100,000 felt reports from induced events in Oklahoma alone. Felt reports provide a rich database of human observations and have been used to examine the damage potential of induced events. Early results indicated that the felt intensities of induced events are the same as those for natural events at short distances (<10 km), but that induced events tend to have lower intensities at larger distances111. As a result, it was inferred that induced events have lower stress drop on average than do natural events, where stress drop controls the strength of high-frequency ground motion. Instrumental ground-motion data have been used to show that stress drop scales with focal depth90, so, on average, induced earthquakes might be expected to have a relatively low stress drop, owing to their shallow depths (compared with natural events). Alternatively, it has been proposed that apparent differences in the stress drop of induced events (mostly in central North America) and natural events (mostly in eastern North America) might be explained by differences in their focal mechanism88. The effects of stress drop and distance counteract at short distances, which can explain the similar felt intensities near the epicentre for induced events (with lower stress drop) and natural events (with higher stress drop) in a given region.
In addition, ruptures in relatively stable intraplate regions, such as central and eastern North America, tend to be characterized by higher stress drops in comparison with active interplate regions, such as California112. As a result, it has been suggested that ground motions might have larger amplitudes (by a factor of 1.5) for ruptures on immature faults in comparison with mature faults113. Consequently, the higher stress drop that is observed in central and eastern North America, owing to the stable tectonic setting of the region, has been suggested to offset the focal depth effect, which explains why ground motions for induced intraplate events in central and eastern North America are observed to be similar to those of natural California events of the same magnitude and distance91.
Direct comparison of the damage potential of natural and induced earthquakes (M >3.5), using compiled ground-motion and felt-intensity data, is shown in Fig. 3, with the peak ground motions used as an instrumental measure of damage potential. The peak ground velocity (PGV) is an effective damage metric, with PGV = 1–2 cm s−1 being the threshold for cosmetic damage to buildings and infrastructure114,115. In addition, compiled felt-intensity data (Modified Mercalli Intensity, MMI) were also used as a damage metric, where MMI = 2 is the felt threshold, MMI = 6 is considered the threshold for minor damage and MMI = 7–8 is the threshold for major damage, depending on the structural vulnerability116. The felt intensities from induced seismicity can then be compared with models for peak ground motions (PGV and peak ground acceleration (PGA)), which were converted into MMI using empirical relationships92.
Generally, ground motions and felt intensities from natural earthquakes in California104, SWD-induced earthquakes in Oklahoma106 and HF-induced earthquakes in western Canada110 plot in the same amplitude range, for a specified magnitude and distance, despite differences in the dominant triggering mechanism92. Moreover, the consistency between the observations and model predictions indicate that these published models can be used to estimate the event magnitude that is required to cause cosmetic and/or major damage at different epicentral distances. The minimum magnitude that can cause damage in the epicentral region is inferred to be M ~4.0, depending on the vulnerability of the infrastructure. Events of M ≥4.5 are inferred to have substantial damage potential at distances <5 km (ref.92).
Hazard forecasting and risk mitigation
As induced earthquakes with M >4 have the potential to cause damage to local infrastructure, it is not surprising that the hazards and risks associated with HF operations have received a large amount of attention. The hazard refers to the likelihood of large, and potentially damaging, events or ground motions, whereas the risk refers to the probability of undesirable consequences (such as damage) and, therefore, requires knowledge of the vulnerability of proximal infrastructure. For HF hazard assessment and risk mitigation, it is important to determine whether critical aspects of HF seismicity can either be predicted in advance of operations or controlled during operations, thus, preventing undesirable outcomes. In this section, we review the efficacy of such strategies.
Since the existence of pre-existing, critically stressed faults is a prerequisite for HF-triggered events, it should be theoretically possible to prevent induced seismicity by mandating a setback (or respect distance) between HF and such faults117. However, in practice, it is difficult to detect faults prior to reactivation, especially if they are strike-slip in nature. In several cases, no clear correlation has been found between faults that are detected by geophysical surveys before injection began and the structures on which seismicity occurred60,118,119. As an example, an investigation of a prolific sequence of induced events in the Horn River Basin, Canada, which included events as large as ML 3.6, concluded that all but one of the induced events occurred on previously unknown faults or fractures79. By contrast, the dozen pre-existing faults mapped by 2D and 3D seismic imaging were not (with one exception) associated with the induced events79. Seismogenic faults are often identified after they have been illuminated by an earthquake sequence119,120 and, therefore, it appears as though the hazard from HF-induced seismicity cannot be reliably controlled by avoiding known pre-existing faults.
Traffic light protocols
As induced seismicity cannot be confidently mitigated using respect distances to known fault structures, other mitigation approaches are required. The most common approach for risk mitigation is a traffic light protocol (TLP)114, whereby operators are required to take predefined actions: reducing injection for an amber light or stopping injection for a red light. The thresholds used in TLPs are usually defined by event magnitude, although ground-motion thresholds have also been used114,121. The exact threshold that is used varies substantially between different regions. For example, in Alberta and British Columbia (WCSB), the TLP red-light threshold is generally ML = 4 in sparsely populated regions, but ML = 3 in some areas where events are likely to be widely felt. In the UK, the red-light threshold is only ML = 0.5 (ref.60) (Fig. 4). Such vast differences in the TLP thresholds (by a factor of over 1,000 in terms of seismic moment) reflect that the risks associated with seismic hazards vary with population density and other factors.
TLPs are conceptually simple and can be operated with minimal input data: all that is required is the magnitude of the largest event. In regions where monitoring is only provided by sparse, regional networks, smaller events cannot be detected and hypocentral uncertainties are usually large. Therefore, the magnitude of the largest event is the easiest parameter to constrain. However, some implicit assumptions and limitations of TLPs must be questioned. Crucially, TLPs are, by nature, retroactive: action is taken after an event has occurred. In addition, TLPs are based on the premise that halting injection will stop seismicity and prevent large events from occurring. In many cases, however, the largest events occur after injection has ceased and induced seismicity can persist for days to weeks122. Therefore, the red-light threshold must be set to a level that considers the possible distribution of trailing events – including those of larger magnitude. Unfortunately, there is no accepted methodology, at present, to constrain the trailing-event distribution.
In addition, another implicit premise of a TLP is that larger events are preceded by smaller, precursory events that will activate the various warning levels (green to amber to red) in time to take mitigative action. However, analysis of events induced by waste-water injection in the central USA96 revealed that the largest event during a sequence occurs randomly and, therefore, is not necessarily preceded by smaller events. Precursory events (2 < M < 4) occurred prior to an M 4.6 event in 2015 near Fort St. John, Canada58, and for an M 4.1 event in 2016 near Fox Creek, Canada51. By contrast, in 2019, an HF-triggered event of M 4.4 near Red Deer, Canada, had no precursors of M >2. Likewise, an M 4.6 HF-triggered event in November 2018 near Fort St. John had no M >2 precursors. Moreover, in spite of an immediate suspension order, the M 4.6 Fort St. John event was shortly followed by M 3.5 and M 4.0 events109.
For HF-triggered seismicity in the Sichuan Basin, China, it appears that numerous 2 < M < 4 events occurred prior to the occurrence of the larger magnitude (ML 5.3 and 5.7) events20,21. It is not possible to know, however, whether ceasing injection at an earlier point in time could have prevented the larger seismic events in the Sichuan Basin, or whether processes such as stress transfer between events would have continued to produce seismicity123. Moreover, owing to the small sample size, we cannot adequately assess whether small-magnitude precursors will precede all large-magnitude HF events. Complications also arise from the possibility that the likelihood of precursory events depends on the nature of the triggering process124. In summary, there is much to learn regarding the capabilities and limitations of real-time forecasting and TLPs for risk mitigation.
Forecasting the maximum expected magnitude
The retrospective nature of TLPs has motivated development of other approaches to mitigate the hazard from HF-triggered seismicity. Alternative approaches are typically based on model forecasts, with both physical and statistical models used to estimate the expected event magnitudes.
Physical models typically require population of a large model space and a number of free parameters need to be defined125. As such, they are challenging to apply in real time to HF, where each of the multiple frack stages might only last for a few hours. Statistical models use the temporal evolution of induced seismicity to define a small number of parameters that can be used to extrapolate the temporal data and produce a projection of the event population. The projection generated includes a forecast for the magnitude of the largest event, MMAX. Because of their ease and simplicity of operation, such statistical models have been widely applied31,43,60,64,96,126,127,128.
Various empirical relationships have been used to characterize the maximum rupture dimensions (and, thus, event size), as well as the cumulative seismic moment, ΣMO, of induced earthquakes. For example, in 2011, it was hypothesized that the maximum rupture dimensions of an induced event are constrained by the dimensions of the stimulated volume, as defined by the spatial extent of microseismicity126. However, recent observations of induced seismicity reveal that ruptures can extend ~2 km beyond the stimulated zone28,119 and, therefore, that the maximum rupture dimensions of induced event cannot always be constrained by the spatial extent of microseimicity.
Alternatively, a linear scaling relationship between the cumulative injection volume, ΔV, and the cumulative seismic moment, of the form ΣMO = 2µΔV, where µ is the shear modulus, has also been proposed129. However, the scaling relationship between ΔV and ΣMO has limited predictive power64, since it provides only an upper bound to the expected magnitude. In addition, although most HF-triggered events fall well below the upper bound, some events in the WCSB have exceeded this limit12,130. In addition, the bound was also exceeded by EGS at Pohang, which produced an M 5.5 event when the limit predicted by the scaling relationship was only MMAX = 3.7 (ref.131) (Fig. 5). To address the discrepancies between observations and the values of MMAX predicted by the volume-based models, several variations of the scaling relationships have been proposed. The variations introduced include additional parameters, such as seismic efficiency127, seismogenic index31 or the use of geomechanical models for fracture propagation that allow an unbounded runaway earthquake132.
All volume-based and moment-based models are applied in similar ways: the scaling relationship between ΔV and ΣMO is characterized at an early stage during injection and then extrapolated to calculate the total expected seismic moment budget. When combined with the b-value, scaling relationships can be used to determine the expected value (with uncertainty) of MMAX. Aftershock-type event rate decay terms can also be added to model the trailing seismicity after injection has ceased133,134, and recent studies have attempted to take volume and moment-based models a step further by proposing a method to evaluate the risk posed by the expected seismicity135. Models in this vein have also linked event occurrence to preoperational loss models, allowing real-time evaluation of the evolving risk22.
Forecast methods based on the observed scaling relationship between injection volumes and seismicity have been used to guide operational decisions to mitigate induced seismicity in geothermal sites128 and HF plays60. However, the scaling relationship between ΔV and ΣMO often changes during injection, potentially owing to hydraulic fractures impinging on a larger fault60, and, thus, the predictive ability of scaling relationships is limited. Therefore, it is clear that hazard mitigation, via the use of forecasting models to control the magnitude of the largest possible event, is in its infancy.
Furthermore, observations of large events that occur after simulation has been completed136,137, or do not appear to fit the Gutenberg–Richter scaling of smaller-magnitude events130, challenge the premise that MMAX can be controlled by controlling the volume of injected material. When considering HF operations, some of the largest events are outliers on the magnitude–frequency distribution130. Such high-magnitude outliers have been linked130 with the concept of characteristic earthquakes138, wherein most events represent rupture on small patches of a larger fault, but that rupture of the entire fault plane occurs episodically. In instances where the entire fault plane ruptures, events that are larger than would be expected based on power-law scaling are produced.
In HF operations, high-magnitude outliers might also arise owing to runaway rupture, where large events are generated by triggering the release of tectonic strain on faults outside the stimulated region132,139. Figure 5 shows a compilation of injection-induced seismicity data, including the Pohang 2017 earthquake and the Fort St. John 2018 earthquake. Five seismic events in the compiled data have been determined to meet the criteria for runaway rupture. However, it remains unclear how (or if) the concept of runaway rupture can be incorporated into models that are used to forecast induced seismicity.
In future, highly sensitive monitoring and response set-ups might be able to identify fault activation prior to a mainshock, with the potential to cease operations before runaway ruptures are initiated140. For example, determining the precise location of microseismicity could be used to reveal reactivation of planar structures near the stimulated region. However, it remains necessary to consider well-known complexities that are associated with fault activation in active tectonic environments, such as the possibility that foreshocks might occur on different faults than the mainshock.
Seismic hazards from HF earthquakes
Although we cannot predict the location, timing and magnitude of natural or induced events with precision, we can assess their likelihoods. For this reason, seismic-hazard assessment is performed probabilistically rather than deterministically. A probabilistic seismic hazard analysis (PSHA) uses the spatial distribution of events, their magnitude–frequency distribution (the Gutenberg–Richter relation) and ground-motion models to calculate the likelihood of exceeding different amplitude levels of ground motion at a site141,142,143,144. For example, building codes typically require all infrastructure to be able to withstand ground motions with an annual exceedance probability of 2% in 50 years (or 1/2,500 per annum), although for critical infrastructure, such as extreme-consequence dams, this threshold is raised to an exceedance probability of no more than 1/10,000 per annum142,145,146.
Assessing the hazards of induced seismicity
The methods used to assess hazards associated with induced seismicity follow a similar structure to those used for natural earthquakes, but with one key difference. For natural seismicity, activity is assumed to be relatively stationary in space and time, such that its spatial distribution and magnitude–frequency distribution can be derived from an historical earthquake catalogue. For injection-induced seismicity, however, activity is dependent on the location and activation potential of industrial activities, which are non-stationary.
PSHAs for induced seismicity are commonly conducted as year-by-year hindcast exercises, in which the hazard is assessed under the implicit assumption that the patterns and rates of induced events will mimic those of the preceding year99,147,148. Such hindcasts are useful for demonstrating the impact of induced seismicity on estimated hazard. However, hindcasts can only be used as forecasts if the induced seismicity patterns are stable in time – a situation that is unlikely, given the nature of oil and gas operations. PSHAs aimed at forecasting seismic hazards in advance of conducting operations must consider the likelihood of triggering damaging seismicity in the future, as well as the expected magnitude–frequency distribution of potential events13,24. Unfortunately, the likelihood and magnitude–frequency distribution of future events will depend on the susceptibility of the target formation and the injection parameters in a complex way that is not yet well understood10,14,57,67,149. As a result, large uncertainties in hazard forecasts are to be expected13,150.
Hazard models that include the influence of injection rates, which have mostly been developed in conjunction with SWD hazards, could potentially reduce the uncertainties associated with such models43,151. For HF seismicity, the seismic productivity in the Duvernay play of Fox Creek, Alberta, has been shown to scale linearly with injection volume, which enables the Gutenberg–Richter relation to be modulated by operational parameters. Future developments in hazard modelling are likely to focus on developing reliable algorithms to incorporate operational parameters into site-specific or region-specific PSHAs.
Relative hazards of natural versus induced seismicity
Regardless of whether it is hindcast or forecast, the hazard associated with induced seismicity can greatly exceed the pre-existing natural hazard, particularly in regions of low-to-moderate seismicity13,99,100,147,150. The increased hazard associated with HF (or SWD) raises pressing socio-economic questions concerning how the heightened hazard might be managed, mitigated or avoided. Several approaches have been suggested, which consider the perceived hazard, risk and consequences, as well as the societal acceptance of industrial activity that could cause induced seismicity, sometimes in a risk-matrix framework152. In general, owing to the lack of specific industrial regulations and practices153, several very different approaches have been used to deal with the hazards associated with induced seismicity.
As discussed previously, the most common regulatory approach to manage hazards from induced seismicity has been to implement a TLP. However, the largest events cannot necessarily be predicted from the observed seismicity and might occur without notable precursors. In addition, the largest event can occur after injection ceases28,122, sometimes during mitigation efforts103. Therefore, although TLPs can be a useful operational measure to limit the number of trailing events and invoke mitigation after the amber condition is activated, they might not reduce the likelihood of initiating a large induced earthquake. A case in point is a damaging M 5.5 earthquake that was triggered by hydraulic stimulation of the Pohang geothermal field in South Korea, despite a traffic light system that was in place with a magnitude threshold of 2.0 (later raised to 2.5)101.
For HF operations in proximity to critical infrastructure, such as major dams or nuclear power plants, a combination of hazard avoidance and mitigation is required to achieve stringent, mandated safety standards13. For example, such a strategy could involve the presence of a minimum setback distance, such as 5 km, to remove the possibility of large events occurring directly beneath critical facilities. The setback distance could then be combined with regional seismic monitoring in the surrounding area, with a plan to reduce operations if the rate rises above a preset threshold. The occurrence of damaging (M ≥5) earthquakes triggered by HF in China has brought the need to develop improved hazard-mitigation tools, and to avoid hazards in situations where they are unacceptable, into sharper focus20.
Summary and future perspectives
Our Review has considered six fundamental questions associated with the generation, damage potential and prediction of induced seismicity. In general, we have focused on seismicity generated by HF, although evidence from SWD and EGS processes were considered, where relevant. Here, we summarize the key conclusions of this Review, focusing on each of the six fundamental issues, and provide a forward-looking perspective to outline how induced-seismicity prediction and risk mitigation can be improved in the future.
Certain conditions are considered necessary for an earthquake to be triggered: a source of stress perturbation, a pre-existing, critically stressed fault, a large enough surface area on the fault to host a felt event and a coupling mechanism that connects the source to the fault. The coupling mechanism can represent a direct connection between the injected fluids and the fault (such as elevated pore pressure) or an indirect connection (loading by poroelastic stress transfer or stress transfer by aseismic slip). Induced seismic events typically occur within ~2 km of HF operations, with a mechanism-dependent time lag that varies from minutes to years (typically, days to weeks). Further work is encouraged to try and identify how the triggering mechanisms, and the distance over which events can be triggered, is controlled by geological and tectonic factors.
Multiple factors are believed to influence the susceptibility of a region to HF-induced seismicity, including the degree of faulting/fracturing, fracture-network connectivity, state of stress, overpressure and proximity to basement. Regional and local variations in such parameters might explain the order-of-magnitude variability in the seismogenic index, a quantitative measure of the rate of induced seismicity. Future progress in understanding the relationship between tectonic environment and induced seismicity is required and can be achieved by quantifying susceptibility in a wide range of settings, and identifying the physical factors and mechanisms that relate to the observed differences in susceptibility.
Although differences are observed in the spatio-temporal clustering properties of induced and tectonic events (as identified by ETAS modelling) and the average depth of induced and natural events, once triggered, individual induced events appear to share the same source and ground-motion characteristics as their natural counterparts. The similarity between natural and induced events supports the premise that triggered events represent reactivation of pre-existing tectonic structures. Comparative studies of induced versus natural events of similar magnitudes, depths and focal mechanisms in the same tectonic setting could provide further insights into their similarities or differences. However, such conditions are rarely met in regions of sparse natural seismicity.
The clearest documented case of damaging earthquakes triggered by HF are the M ~5.0 to 5.5 events in the Sichuan Basin, China, which caused injuries, fatalities and millions of dollars in structural damage. The damage potential of triggered seismicity is dependent on the magnitude of the event, its proximity to population and/or infrastructure, the intensity of resulting ground motion and the vulnerability of the local infrastructure. Generally, we can consider M 4.0 events as the smallest events that can cause notable damage (near the epicentre). To advance knowledge of the damage potential of triggered earthquakes, engineering studies of how structures respond to strong, short-duration ground motions are needed.
At present, it is not possible to confidently forecast the occurrence, or the maximum size, of an HF-triggered event. However, statistical methods can assess the likelihood and expected magnitude distribution of events, at least in a regional sense, and such assessments are useful inputs to probabilistic seismic-hazard analyses. Current statistical hazard-assessment methods carry very large (orders of magnitude) uncertainties. Nevertheless, dense real-time monitoring and imaging of HF operations (for example, using microseismicity) represents a promising new method for tracking the seismic risk during operations.
The hazard from HF-triggered seismicity exceeds the natural hazard in low-to-moderate-seismicity environments (such as Alberta and eastern British Columbia). Detailed monitoring and response protocols, including (but not limited to) TLPs, are a first step towards mitigation in these regions. However, at present, such retrospective strategies are not sufficient to protect critical or vulnerable infrastructure that have unacceptable failure consequences. Further development of real-time hazard forecasting and mitigation strategies is required, so that mitigation approaches can be verified and applied to future HF operations.
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The authors receive financial support for their research programmes from the Natural Sciences and Engineering Research Council of Canada. We thank James Verdon for constructive discussions that contributed to the manuscript and Minhee Choi for assistance in preparing the final manuscript.
The authors declare no competing interests.
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- Operationally induced microseismicity
Weak seismicity that is expected to occur during operations such as hydraulic fracturing or development of an engineered geothermal system.
- Unconventional plays
Oil and gas resources whose porosity, permeability, fluid-trapping mechanism or other characteristics differ from conventional hydrocarbon reservoirs.
A process in which permanent plastic deformation occurs owing to various microscale or atomic-scale mechanisms.
- Failure criteria
A mathematical model defining stress conditions under which failure might occur, such as the Mohr–Coulomb failure criteria.
- Epidemic-type aftershock sequence (ETAS) models
Cascading point processes derived from Omori’s law that can be used to simulate the temporal patterns of earthquake sequences in a given region.
Seismicity of magnitude less than 0.
A mathematical model for an earthquake-source mechanism, consisting of two orthogonal force couples. The mechanism is typically parameterized using the strike and dip of the fault plane, as well as the rake (slip vector).
- Stress drop
The co-seismic reduction in shear stress acting on a fault (the difference between the shear stress on the fault before an earthquake and the shear stress after an earthquake).
The effects of earthquake ground motion on the natural or built environment.
The point on the surface vertically above an earthquake’s focus.
- Peak ground acceleration
Maximum instantaneous amplitude of the absolute value of the acceleration of the ground.
- Seismic moment
A measure of the size of an earthquake based on the product of the rupture area, the average amount of slip and the force that was required to overcome fault friction.
- Runaway rupture
The initiation of larger-magnitude earthquakes that extend past the stimulated region. These events primarily release tectonic strain on faults outside the stimulated region.
Earthquakes that precede the largest earthquake in a sequence.
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Atkinson, G.M., Eaton, D.W. & Igonin, N. Developments in understanding seismicity triggered by hydraulic fracturing. Nat Rev Earth Environ 1, 264–277 (2020). https://doi.org/10.1038/s43017-020-0049-7
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