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Earthquake hazard and risk analysis for natural and induced seismicity: towards objective assessments in the face of uncertainty
Abstract and Figures
The fundamental objective of earthquake engineering is to protect lives and livelihoods through the reduction of seismic risk. Directly or indirectly, this generally requires quantification of the risk, for which quantification of the seismic hazard is required as a basic input. Over the last several decades, the practice of seismic hazard analysis has evolved enormously, firstly with the introduction of a rational framework for handling the apparent randomness in earthquake processes, which also enabled risk assessments to consider both the severity and likelihood of earthquake effects. The next major evolutionary step was the identification of epistemic uncertainties related to incomplete knowledge, and the formulation of frameworks for both their quantification and their incorporation into hazard assessments. Despite these advances in the practice of seismic hazard analysis, it is not uncommon for the acceptance of seismic hazard estimates to be hindered by invalid comparisons, resistance to new information that challenges prevailing views, and attachment to previous estimates of the hazard. The challenge of achieving impartial acceptance of seismic hazard and risk estimates becomes even more acute in the case of earthquakes attributed to human activities. A more rational evaluation of seismic hazard and risk due to induced earthquakes may be facilitated by adopting, with appropriate adaptations, the advances in risk quantification and risk mitigation developed for natural seismicity. While such practices may provide an impartial starting point for decision making regarding risk mitigation measures, the most promising avenue to achieve broad societal acceptance of the risks associated with induced earthquakes is through effective regulation, which needs to be transparent, independent, and informed by risk considerations based on both sound seismological science and reliable earthquake engineering.
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... The risk perception implications of Mmax for induced earthquakes is a serious point because in many cases of energy projects being closed down due to induced earthquakes, the cited justification has usually not been based mainly on the size of the earthquakes that did occur but rather speculation and concern about the largest earthquakes that might occur (Bommer, 2022). Induced seismicity at the Groningen gas field in the Netherlands and seismicity caused by hydraulic fracturing for shale gas in the UK represent two demonstrative cases. ...
... The assumed SI and/or SEFF distributions are used with a planned injection volume to estimate Mmax values. However, where a priori estimated distributions of SI and/or SEFF are excessively broad due to a lack of relevant data to provide empirical constraint, the resulting seismic hazard assessments may be so poorly constrained as to have little practical utility (e.g., Silva et al. 2021;Bommer 2022). In situations where the prior levels of constraint for recurrence rate and Mmax parameters are so broad as to be uninformative, then probabilistic approaches are not helpful. ...
... TLSs typically define a yellow-light threshold, at which operations are adjusted (e.g., reduced injection rates or pressures) to mitigate seismicity, and a red-light threshold, at which operations are terminated. TLS thresholds can be defined with respect to earthquake magnitudes or ground motion levels, although for several practical reasons, it is generally advantageous to define thresholds in terms of magnitudes, even if this are inferred from shaking levels (Bommer et al. 2006;Ader et al. 2020;Verdon and Bommer 2021a;Bommer 2022). ...
... The methods may be used on their own, or they may be used together to provide complementary information for decision making. In modern times, the probabilistic approach has more or less prevailed, with very few exceptions [Bommer 2022]. ...
... In a generic sense, risk can be defined as the possibility of such consequences occurring at a given location due to potential future earthquakes. In a more formal probabilistic framework, seismic risk is quantified by both the severity of a given metric of loss and the annual frequency or probability of that level of loss being exceeded (Bommer 2022). More details about how PSHRA is implemented in practice can be found in section 4.7. ...
... Such reasons include: to take into account the advancement in knowledge, methods and data (for instance, the discovery of new active faults [e.g. see examples in Bommer (2022)]); to overcome deficiencies in previous models, such as inappropriate probabilistic approaches or insufficient consideration of epistemic uncertainty; to update seismic building codes; and, particularly for site-specific studies, the design or periodic safety assessment of infrastructure (e.g. USNRC 2018). ...
When new seismic hazard estimates are published it is natural to compare them to existing results for the same location. This type of comparison routinely indicates differences amongst hazard estimates obtained with the various models. The question that then arises is whether these differences are scientifically significant, given the large epistemic uncertainties inherent in all seismic hazard estimates, or practically important, given the use of hazard models as inputs to risk and engineering calculations. A difference that exceeds a given threshold could mean that building codes may need updating, risk models for insurance purposes may need to be revised, or emergency management procedures revisited. In the current literature there is little guidance on what constitutes a significant or important difference, which can lead to lengthy discussions amongst hazard modellers, end users and stakeholders. This study reviews proposals in the literature on this topic and examines how applicable these proposals are, using, for illustration purposes, several sites and various seismic hazard models for each site, including the two European Seismic Hazard Models of 2013 and 2020. The implications of differences in hazard for risk and engineering purposes are also examined to understand how important such differences are for potential end users of seismic hazard models. Based on this, we discuss the relevance of such methods to determine the scientific significance and practical importance of differences between seismic hazard estimates and identify some open questions. We conclude that there is no universal criterion for assessing differences between seismic hazard results and that the recommended approach depends on the context. Finally, we highlight where additional work is required on this topic and that we encourage further discussion of this topic.
... Seismic source characterisation involves identifying and defining all possible rupture scenarios that could produce ground shaking within the model coverage area. Using fault characteristics, observed seismicity and geo-tectonic setting, a rupture scenario is mainly characterised by earthquake magnitudes and their epicentral locations, in addition to its likelihood of occurrence (Bommer 2022). This section discusses the steps taken to characterise earthquake sources within and around Uganda. ...
Uganda lies between the eastern and western arms of the East African Rift System, the largest seismically active rift above sea level. With increasing population, urbanisation and rapid construction, seismic risk in the country is escalating fast and is compounded by the high vulnerability of the building stock and inadequate disaster prevention and mitigation strategies. Hence, there is an urgent need to assess Uganda’s resilience against seismic risks. This paper presents a Monte-Carlo based probabilistic seismic hazard model for Uganda, as the first step towards the development of a seismic risk and resilience assessment framework for the country. In addition to fault segment data, earthquake catalogues are compiled for the period between 1900 and 2022 to estimate recurrence parameters for source zones in the area of interest. Area source zones incorporating focal mechanisms are used to stochastically model a national hazard framework for Uganda. A logic tree approach is applied to implement four ground motion prediction equations for both stable continental and active shallow crust geologies. Mean hazard curves, uniform hazard spectra, earthquake disaggregation and spectral pseudo-accelerations for major Ugandan cities are derived in addition to hazard maps for the country. The findings are largely consistent with previous regional studies and confirm that western Uganda is exposed to the highest level of seismicity. The model presented herein can be used to kick-start the update and continuous improvement of Uganda Seismic Design Code and the National Policy for Disaster Preparedness and Management.
... Recently, deterministic and probabilistic seismic hazard analyses ((DSHA and PSHA, respectively) have been widely used. Both hazard analyses have two basic elements, namely, the source earthquake model and the ground motions owing to the source earthquake model (Bommer, 2022). PSHA better accounts for uncertainty. ...
A comprehensive database that has been used to develop ground motion models for induced earthquakes in the Groningen gas field is provided in a freely accessible online repository. The database includes more than 8500 processed ground motion recordings from 87 earthquakes of local magnitude M L between 1.8 and 3.6, obtained from a large network of surface accelerographs and borehole geophones placed at 50 m depth intervals to a depth of 200 m. The 5%-damped pseudo-acceleration spectra and Fourier amplitude spectra of the records are also provided. Measured shear-wave velocity (V S ) profiles, obtained primarily from seismic Cone Penetration Tests (CPTs), are provided for 80 of the ∼100 recording stations. A model representing the regional dynamic soil properties is presented for the entire gas field plus a 5 km onshore buffer zone, specifying lithology, V S , and damping for all layers above the reference baserock horizon located at about 800 m depth. Transfer functions and frequency-dependent amplification factors from the reference rock horizon to the surface for the locations of the recording stations are also included. The database provides a valuable resource for further refinement of induced seismic hazard and risk modeling in Groningen as well as for generic research in site response of thick, soft soil deposits and the characteristics of ground motions from small-magnitude, shallow-focus induced earthquakes.
We present an overview of induced seismicity due to subsurface engineering in the Netherlands. Our overview includes events induced by gas extraction, underground gas storage, geothermal heat extraction, salt solution mining and post-mining water ingress. Compared to natural seis-micity, induced events are usually small (magnitudes ≤ 4.0). However, due to the soft topsoils in combination with shallow hypocentres, in the Netherlands events exceeding magnitude 1.5-2.0 may be felt by the public. These events can potentially damage houses and infrastructure, and undermine public acceptance. Felt events were induced by gas production in the north of the Netherlands and by post-mining water ingress in the southeast. Notorious examples are the earthquakes induced by gas production from the large Groningen gas field with magnitudes up to 3.6. Here, extensive non-structural damage incurred and public support was revoked. As a consequence, production will be terminated in 2022 leaving approximately 800 billion cubic metres of gas unexploited. The magnitudes of the events observed at underground gas storage, geothermal heat production and salt solution mining projects have so far been very limited (magnitudes ≤ 1.7). However, in the future larger events cannot be excluded. Projector industry specific risk governance protocols, extensive gathering of subsurface data and adequate seismic monitoring are therefore essential to allow sustainable use of the Dutch subsurface now and over the decades to come.
We introduce the cumulative-distribution-based area metric (AM)—also known as stochastic AM—as a scoring metric for earthquake ground-motion models (GMMs). The AM quantitatively informs the user of the degree to which observed or test data fit with a given model, providing a rankable absolute measure of misfit. The AM considers underlying data distributions and model uncertainties without any assumption of form. We apply this metric, along with existing testing methods, to four GMMs in order to test their performance using earthquake ground-motion data from the Preston New Road (United Kingdom) induced seismicity sequences in 2018 and 2019. An advantage of the proposed approach is its applicability to sparse datasets. We, therefore, focus on the ranking of models for discrete ranges of magnitude and distance, some of which have few data points. The variable performance of models in different ranges of the data reveals the importance of considering alternative models. We extend the ranking of GMMs through analysis of intermodel variations of the candidate models over different ranges of magnitude and distance using the AM. We find the intermodel AM can be a useful tool for selection of models for the logic-tree framework in seismic-hazard analysis. Overall, the AM is shown to be efficient and robust in the process of selection and ranking of GMMs for various applications, particularly for sparse and small-sized datasets.
Induced earthquakes caused by hydraulic fracturing are a growing concern, with risks that are often managed by traffic light protocols (TLPs). Here, we apply a risk‐informed strategy for choosing TLP red‐light thresholds. We utilize a combination of probabilistic maximum magnitudes, formation depth, site amplification, ground motion relationships, felt/damaging shaking tolerances, and population information to simulate the spatial distribution of nuisance and damage impacts. We apply this approach to many of the prominent North American shale plays that have caused earthquakes: the Horn River Basin, the Duvernay Formation, the Montney Formation, the Utica Shale, the Marcellus Shale, the SCOOP & STACK play in Oklahoma, the Eagle Ford Formation, and the Delaware Basin. We find that induced earthquake impacts are spatially heterogeneous, depending most strongly on population density. These spatial heterogeneities vary on different length scales, depending on if they are related to nuisance (longer range, 100s kms) or damage (shorter range, 10s kms). Because of this variability, we suggest an approach that sets red‐light magnitudes based on tolerances to nuisance and damage risks (varying between Mw 2.0–5.0). Comparison of the results between North American shale plays where TLPs have been enacted suggests that nuisance risks have been an influencing factor in determining red‐light thresholds. Our method provides quantitative guidelines for traffic light protocols designed in a risk‐informed manner that retains the implementational simplicity of magnitude‐based thresholds. In addition, our results provide a benchmark for jurisdictional nuisance tolerances that future TLPs could be guided by.
We evaluate the seismic performance of modern seismically designed wood light-frame (WLF) buildings, considering regional seismic hazard characteristics that influence ground motion duration and frequency content and, thus, seismic risk. Results show that WLF building response correlates strongly with ground motion spectral shape but weakly with duration. Due to the flatter spectral shape of ground motions from subduction events, WLF buildings at sites affected by these earthquakes may experience double the economic losses for a given intensity of shaking, and collapse capacities may be reduced by up to 50%, compared to those at sites affected by crustal earthquakes. These differences could motivate significant increases in design values at sites affected by subduction earthquakes to achieve the uniform risk targets of the American Society of Civil Engineers (ASCE) 7 standard.
Monitoring small magnitude induced seismicity requires a dense network of seismic stations and high-quality recordings in order to precisely determine events' hypocentral parameters and mechanisms. However, microseismicity (e.g. swarm activity) can also occur in an area where a dense network is unavailable and recordings are limited to a few seismic stations at the surface. In this case, using advanced event detection techniques such as template matching can help to detect small magnitude shallow seismic events and give insights about the ongoing process at the subsurface giving rise to microseismicity. In this paper, we study shallow microseismic events caused by hydrofracking of the PNR-2 well near Blackpool, UK, in 2019 using recordings of a seismic network which was not designed to detect and locate such small events. By utilizing a sparse network of surface stations, small seismic events are detected using template matching technique. In addition, we apply a full-waveform moment tensor inversion to study the focal mechanisms of larger events (M L > 1) and used the double-difference location technique for events with high-quality and similar waveforms to obtain accurate relative locations. During the stimulation period, temporal changes in event detection rate were in agreement with injection times. Focal mechanisms of the events with high-quality recordings at multiple stations indicate a strike-slip mechanism, while a cross-section of 34 relocated events matches the dip angle of the active fault.
The backbone approach to constructing a ground-motion logic tree for probabilistic seismic hazard analysis (PSHA) can address shortcomings in the traditional approach of populating the branches with multiple existing, or potentially modified, ground-motion models (GMMs) by rendering more transparent the relationship between branch weights and the resulting distribution of predicted accelerations. To capture epistemic uncertainty in a tractable manner, there are benefits in building the logic tree through the application of successive adjustments for differences in source, path, and site characteristics between the host region of the selected backbone GMM and the target region for which the PSHA is being conducted. The implementation of this approach is facilitated by selecting a backbone GMM that is amenable to such host-to-target adjustments for individual source, path, and site characteristics. The NGA-West2 GMM of Chiou and Youngs (CY14) has been identified as a highly adaptable model for crustal seismicity that is well suited to such adjustments. Rather than using generic source, path, and site characteristics assumed appropriate for the host region, the final suite of adjusted GMMs for the target region will be better constrained if the host-region parameters are defined specifically on the basis of their compatibility with the CY14 backbone GMM. To this end, making use of a recently developed crustal shear-wave velocity profile consistent with CY14, we present an inversion of the model to estimate the key source and path parameters, namely the stress parameter and the anelastic attenuation. With these outputs, the effort in constructing a ground-motion logic tree for any PSHA dealing with crustal seismicity can be focused primarily on the estimation of the target-region characteristics and their associated uncertainties. The inversion procedure can also be adapted for any application in which different constraints might be relevant.
Seismic hazard and risk analyses underpin the loadings prescribed by engineering design codes, the decisions by asset owners to retrofit structures, the pricing of insurance policies, and many other activities. This is a comprehensive overview of the principles and procedures behind seismic hazard and risk analysis. It enables readers to understand best practises and future research directions. Early chapters cover the essential elements and concepts of seismic hazard and risk analysis, while later chapters shift focus to more advanced topics. Each chapter includes worked examples and problem sets for which full solutions are provided online. Appendices provide relevant background in probability and statistics. Computer codes are also available online to help replicate specific calculations and demonstrate the implementation of various methods. This is a valuable reference for upper level students and practitioners in civil engineering, and earth scientists interested in engineering seismology.
