The Role of Seismic and Slow Slip Events in Triggering the 2018 M 7.1 Anchorage Earthquake in the Southcentral Alaska Subduction Zone

The M 7.1 2018 Anchorage earthquake occurred in the bending part of the subducting North Pacific plate near the geometrical barrier formed by the underthrusting Yakutat terrane. We calculate the triggering potential related with stress redistribution from deformation sources including the M 9.2 1964 earthquake coseismic slip, postseismic deformation, slip from regional M > 5 earthquakes, and the cumulative slip of previously detected slow slip events over the past 55 years. We investigate the deeper shallow depth (20–60 km) seismicity response to these perturbations using an epidemic type aftershock sequence model to describe earthquake‐to‐earthquake interactions. The statistical forecast captures the triggered seismicity during the 1983 M 6+ aftershocks in Columbia Bay but performs poorly during the slow slip event period between 1992.0 and 2004.8 that presents a statistically significant rate change (β , Z > 2; M < 4.0). We find that stress effects from the 1964 postseismic source and the 12‐year‐long slow slip event (~M 7.8) contribute to the 2018 Anchorage earthquake occurrence and that slow slip events modulate the deeper shallow depth seismicity patterns in the region

The global aftershock zone

The aftershock zone of each large (M ≥ 7) earthquake extends throughout the shallows of planet Earth. Most aftershocks cluster near the mainshock rupture, but earthquakes send out shivers in the form of seismic waves, and these temporary distortions are large enough to trigger other earthquakes at global range. The aftershocks that happen at great distance from their mainshock are often superposed onto already seismically active regions, making them difficult to detect and understand. From a hazard perspective we are concerned that this dynamic process might encourage other high magnitude earthquakes, and wonder if a global alarm state is warranted after every large mainshock. From an earthquake process perspective we are curious about the physics of earthquake triggering across the magnitude spectrum. In this review we build upon past studies that examined the combined global response to mainshocks. Such compilations demonstrate significant rate increases during, and immediately after (~45 min) M N 7.0 mainshocks in all tectonic settings and ranges. However, it is difficult to find strong evidence for M N 5 rate increases during the passage of surface waves in combined global catalogs. On the other hand, recently published studies of individual large mainshocks associate M N 5 triggering at global range that is delayed by hours to days after surface wave arrivals. The longer the delay between mainshock and global aftershock, the more difficult it is to establish causation. To address these questions, we review the response to 260 M ≥ 7.0 shallow (Z ≤ 50 km) mainshocks in 21 global regions with local seismograph networks. In this way we can examine the detailed temporal and spatial response, or lack thereof, during passing seismic waves, and over the 24 h period after their passing. We see an array of responses that can involve immediate and widespread seismicity outbreaks, delayed and localized earthquake clusters, to no response at all. About 50% of the catalogs that we studied showed possible (localized delayed) remote triggering, and ~20% showed probable (instantaneous broadly distributed) remote triggering. However, in any given region, at most only about 2–3% of global mainshocks caused significant local earthquake rate increases. These rate increases are mostly composed of small magnitude events, and we do not find significant evidence of dynamically triggered M N 5 earthquakes. If we assume that the few observed M N 5 events are triggered, we find that they are not directly associated with surface wave passage, with first incidences being 9–10 h later. We note that mainshock magnitude, relative proximity, amplitude spectra, peak ground motion, and mainshock focal mechanisms are not reliable determining factors as to whether a mainshock will cause remote triggering. By elimination, azimuth, and polarization of surface waves with respect to receiver faults may be more important factors

An automatically generated high-resolution earthquake catalogue for the 2016–2017 Central Italy seismic sequence, including P and S phase arrival times

The 2016–2017 central Italy earthquake sequence began with the first main shock near the town of Amatrice on August 24 (Mw 6.0), and was followed by two subsequent large events near Visso on October 26 (Mw 5.9) and Norcia on October 30 (Mw 6.5), plus a cluster of four events with Mw > 5.0 within few hours on 18 January 2017. The affected area had been monitored before the sequence started by the permanent Italian National Seismic Network (RSNC), and was enhanced during the sequence by temporary stations deployed by the National Institute of Geophysics and Volcanology and the British Geological Survey. By the middle of September, there was a dense network of 155 stations, with a mean separation in the epicentral area of 6–10 km, comparable to the most likely earthquake depth range in the region. This network configuration was kept stable for an entire year, producing 2.5 TB of continuous waveform recordings. Here we describe how this data was used to develop a large and comprehensive earthquake catalogue using the Complete Automatic Seismic Processor (CASP) procedure. This procedure detected more than 450 000 events in the year following the first main shock, and determined their phase arrival times through an advanced picker engine (RSNI-Picker2), producing a set of about 7 million P- and 10 million S-wave arrival times. These were then used to locate the events using a non-linear location (NLL) algorithm, a 1-D velocity model calibrated for the area, and station corrections and then to compute their local magnitudes (ML). The procedure was validated by comparison of the derived data for phase picks and earthquake parameters with a handpicked reference catalogue (hereinafter referred to as ‘RefCat’). The automated procedure takes less than 12 hr on an Intel Core-i7 workstation to analyse the primary waveform data and to detect and locate 3000 events on the most seismically active day of the sequence. This proves the concept that the CASP algorithm can provide effectively real-time data for input into daily operational earthquake forecasts, The results show that there have been significant improvements compared to RefCat obtained in the same period using manual phase picks. The number of detected and located events is higher (from 84 401 to 450 000), the magnitude of completeness is lower (from ML 1.4 to 0.6), and also the number of phase picks is greater with an average number of 72 picked arrival for a ML = 1.4 compared with 30 phases for RefCat using manual phase picking. These propagate into formal uncertainties of ±0.9 km in epicentral location and ±1.5 km in depth for the enhanced catalogue for the vast majority of the events. Together, these provide a significant improvement in the resolution of fine structures such as local planar structures and clusters, in particular the identification of shallow events occurring in parts of the crust previously thought to be inactive. The lower completeness magnitude provides a rich data set for development and testing of analysis techniques of seismic sequences evolution, including real-time, operational monitoring of b-value, time-dependent hazard evaluation and aftershock forecasting

SISMIKO: emergency network deployment and data sharing for the 2016 central Italy seismic sequence

At 01:36 UTC (03:36 local time) on August 24th 2016, an earthquake Mw 6.0 struck an extensive sector of the central Apennines (coordinates: latitude 42.70° N, longitude 13.23° E, 8.0 km depth). The earthquake caused about 300 casualties and severe damage to the historical buildings and economic activity in an area located near the borders of the Umbria, Lazio, Abruzzo and Marche regions. The Istituto Nazionale di Geofisica e Vulcanologia (INGV) located in few minutes the hypocenter near Accumoli, a small town in the province of Rieti. In the hours after the quake, dozens of events were recorded by the National Seismic Network (Rete Sismica Nazionale, RSN) of the INGV, many of which had a ML > 3.0. The density and coverage of the RSN in the epicentral area meant the epicenter and magnitude of the main event and subsequent shocks that followed it in the early hours of the seismic sequence were well constrained. However, in order to better constrain the localizations of the aftershock hypocenters, especially the depths, a denser seismic monitoring network was needed. Just after the mainshock, SISMIKO, the coordinating body of the emergency seismic network at INGV, was activated in order to install a temporary seismic network integrated with the existing permanent network in the epicentral area. From August the 24th to the 30th, SISMIKO deployed eighteen seismic stations, generally six components (equipped with both velocimeter and accelerometer), with thirteen of the seismic station transmitting in real-time to the INGV seismic monitoring room in Rome. The design and geometry of the temporary network was decided in consolation with other groups who were deploying seismic stations in the region, namely EMERSITO (a group studying site-effects), and the emergency Italian strong motion network (RAN) managed by the National Civil Protection Department (DPC). Further 25 BB temporary seismic stations were deployed by colleagues of the British Geological Survey (BGS) and the School of Geosciences, University of Edinburgh in collaboration with INGV. All data acquired from SISMIKO stations, are quickly available at the European Integrated Data Archive (EIDA). The data acquired by the SISMIKO stations were included in the preliminary analysis that was performed by the Bollettino Sismico Italiano (BSI), the Centro Nazionale Terremoti (CNT) staff working in Ancona, and the INGV-MI, described below

Machine learning and earthquake forecasting—next steps

A new generation of earthquake catalogs developed through supervised machine-learning illuminates earthquake activity with unprecedented detail. Application of unsupervised machine learning to analyze the more complete expression of seismicity in these catalogs may be the fastest route to improving earthquake forecasting

Recent scientific advances in the understanding of induced seismicity from hydraulic fracturing of shales

The Secretary of State for Business, Energy & lndustrial Strategy has commissioned the British Geological Survey to write a short report about seismic activity associated with hydraulic fracturing (HF) of shales to extract hydrocarbons. The specific terms of reference are available at https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/fi le/1066525/BGS_Letter.pdf. These ask six questions related to recent scientific research on the hazard and risk from induced seismicity during hydraulic fracturing of shale rocks. Our report considers the scientific advances in this area since 2019 that have been published in peer reviewed scientific journals as well as other recent studies commissioned by regulatory authorities. The main conclusions of our report in relation to each of the questions in the terms of reference are as follows: Forecasting the occurrence of large earthquakes and their expected magnitude remains a scientific challenge for the geoscience community. This is the case for both tectonic and induced earthquakes. (Questions 1 and 2) Methods to estimate the maximum magnitudes of induced earthquakes based on operational parameters and observed seismicity have been tested using data from both Hydraulic Fracturing (HF) operations and data from other industries. These methods have shown some applicability to guide operational decisions using real-time data. However, they do not currently account for the possibility of events that occur after operations have stopped or earthquakes on faults that extend outside the stimulated volume whose magnitude is not controlled by operational parameters alone. (Questions 1 and 2) Probabilistic methods widely applied to model and forecast tectonic earthquake sequences show some promise when modified to incorporate information about HF operations and appear capable of providing informative forecasts of the observed earthquake patterns. Operators could make forecasts for operations in new wells using either generic parameters or ones calibrated for operations in adjacent wells. Further testing of these methods may allow them to be further developed for operational scenarios. (Questions 1 and 2) Enhanced seismicity monitoring and measurement based on machine learning (ML) has been shown to reveal previously undetected earthquakes and hidden faults, essential for both more reliable earthquake forecasts and characterisation of fault reactivation potential. This can compensate for both limited numbers of seismic stations and faults that remain unmapped even by 3D exploration seismic data. (Questions 1 and 2) Widely used probabilistic methods to assess hazards and risks for tectonic earthquakes can also be applied to induced seismicity. However, there are important differences between how tectonic and induced seismicity evolves in space and time. Recent studies have suggested possible solutions, but further work is needed to develop these models and incorporate them in risk assessments. (Questions 1 and 2) Traffic light systems remain a useful tool for the mitigation of risks from induced seismicity. New research shows how red-light thresholds can be chosen to reduce the probability of the scenario to be avoided to a required level. This research recommends that there should be sufficient space between the amber and red-light thresholds to ensure that operators have an opportunity to modify operations to mitigate risks. (Questions 1 and 2) Induced seismicity has been observed in other industries related to underground energy production both in the UK and elsewhere. In the absence of a seismic building code in the UK, consistent risk targets, i.e., scenarios to be avoided, could be considered for all energy related industries that present a risk of induced earthquakes. (Question 3) Recent research using high quality exploration data that is available for some parts of the UK reveals localised structural and stress heterogeneity that could influence fault reactivation. However, it is not possible to identify all faults that could host earthquakes with magnitudes of up to 3 prior to operations, even with the best available data. (Questions 4 and 5). Recent research from the USA demonstrates the importance of geomechanical modelling to identify faults that are most likely to rupture during operations. This information can be used to assess risks prior to and during operations. However, these models require accurate mapping of sub-surface faults, robust estimates of stress state, and knowledge of formation pore pressures and the mechanical properties of sub-surface rocks. While this information is available in areas with unconventional hydrocarbon potential such as the Bowland Basin, more data is needed from other basins to apply this more widely (Questions 4 and 5). Limited exploration data from other basins with unconventional hydrocarbon potential of the UK means that there are significant gaps in our knowledge of sub-surface structure of potential shale resources in these places. (Questions 4 and 5) The rates of HF-induced seismicity in other countries where shale gas production has been ongoing for many years are observed to vary widely. The limited number of HF operations in the UK means that it is difficult to make a valid comparison of the rates of occurrence of induced seismicity with elsewhere. This underlines the importance of knowledge exchange in monitoring and operational practices. (Question 6) Our review focusses on recently published geoscience related to induced seismicity caused by HF of shales. Ongoing and future research may bring new insights that may reduce uncertainties and improve mitigation of risks. We did not consider socio-economic research on perception of risks or the benefits of shale gas. Similarly, we do not consider technological advances in hydraulic fracturing

Testing earthquake links in Mexico from 1978 to the 2017 M = 8.1 Chiapas and M = 7.1 Puebla Shocks

The M = 8.1 Chiapas and the M = 7.1 Puebla earthquakes occurred in the bending part of the subducting Cocos plate 11 days and ~600 km apart, a range that puts them well outside the typical aftershock zone. We find this to be a relatively common occurrence in Mexico, with 14% of M > 7.0 earthquakes since 1900 striking more than 300 km apart and within a 2 week interval, not different from a randomized catalog. We calculate the triggering potential caused by crustal stress redistribution from large subduction earthquakes over the last 40 years. There is no evidence that static stress transfer or dynamic triggering from the 8 September Chiapas earthquake promoted the 19 September earthquake. Both recent earthquakes were promoted by past thrust events instead, including delayed afterslip from the 2012 M = 7.5 Oaxaca earthquake. A repeated pattern of shallow thrust events promoting deep intraslab earthquakes is observed over the past 40 years