Earthquake energy dissipation in a fracture mechanics framework.

Earthquakes are rupture-like processes that propagate along tectonic faults and cause seismic waves. The propagation speed and final area of the rupture, which determine an earthquake's potential impact, are directly related to the nature and quantity of the energy dissipation involved in the rupture process. Here, we present the challenges associated with defining and measuring the energy dissipation in laboratory and natural earthquakes across many scales. We discuss the importance and implications of distinguishing between energy dissipation that occurs close to and far behind the rupture tip, and we identify open scientific questions related to a consistent modeling framework for earthquake physics that extends beyond classical Linear Elastic Fracture Mechanics.

High resolution seafloor thermometry for internal wave and upwelling monitoring using Distributed Acoustic Sensing.

Temperature is an essential oceanographic variable (EOV) that still today remains coarsely resolved below the surface and near the seafloor. Here, we gather evidence to confirm that Distributed Acoustic Sensing (DAS) technology can convert tens of kilometer-long seafloor fiber-optic telecommunication cables into dense arrays of temperature anomaly sensors having millikelvin (mK) sensitivity, thus allowing to monitor oceanic processes such as internal waves and upwelling with unprecedented detail. Notably, we report high-resolution observations of highly coherent near-inertial and super-inertial internal waves in the NW Mediterranean sea, offshore of Toulon, France, having spatial extents of a few kilometers and producing maximum thermal anomalies of more than 5 K at maximum absolute rates of more than 1 K/h. We validate our observations with in-situ oceanographic sensors and an alternative optical fiber sensing technology. Currently, DAS only provides temperature changes estimates, however practical solutions are outlined to obtain continuous absolute temperature measurements with DAS at the seafloor. Our observations grant key advantages to DAS over established temperature sensors, showing its transformative potential for the description of seafloor temperature fluctuations over an extended range of spatial and temporal scales, as well as for the understanding of the evolution of the ocean in a broad sense (e.g. physical and ecological). Diverse ocean-oriented fields could benefit from the potential applications of this fast-developing technology.

Laboratory earthquakes decipher control and stability of rupture speeds.

Earthquakes are destructive natural hazards with damage capacity dictated by rupture speeds. Traditional dynamic rupture models predict that earthquake ruptures gradually accelerate to the Rayleigh wave speed with some of them further jumping to stable supershear speeds above the Eshelby speed (~[Formula: see text] times S wave speed). However, the 2018 Mw 7.5 Palu earthquake, among several others, significantly challenges such a viewpoint. Here we generate spontaneous shear ruptures on laboratory faults to confirm that ruptures can indeed attain steady subRayleigh or supershear propagation speeds immediately following nucleation. A self-similar analysis of dynamic rupture confirms our observation, leading to a simple model where the rupture speed is uniquely dependent on a driving load. Our results reproduce and explain a number of enigmatic field observations on earthquake speeds, including the existence of stable subEshelby supershear ruptures, early onset of supershear ruptures, and the correlation between the rupture speed and the driving load.

Magnitude estimation and ground motion prediction to harness fiber optic distributed acoustic sensing for earthquake early warning.

Earthquake early warning (EEW) systems provide seconds to tens of seconds of warning time before potentially-damaging ground motions are felt. For optimal warning times, seismic sensors should be installed as close as possible to expected earthquake sources. However, while the most hazardous earthquakes on Earth occur underwater, most seismological stations are located on-land; precious seconds may go by before these earthquakes are detected. In this work, we harness available optical fiber infrastructure for EEW using the novel approach of distributed acoustic sensing (DAS). DAS strain measurements of earthquakes from different regions are converted to ground motions using a real-time slant-stack approach, magnitudes are estimated using a theoretical earthquake source model, and ground shaking intensities are predicted via ground motion prediction equations. The results demonstrate the potential of DAS-based EEW and the significant time-gains that can be achieved compared to the use of standard sensors, in particular for offshore earthquakes.

A Self-Supervised Deep Learning Approach for Blind Denoising and Waveform Coherence Enhancement in Distributed Acoustic Sensing Data.

Fiber-optic distributed acoustic sensing (DAS) is an emerging technology for vibration measurements with numerous applications in seismic signal analysis, including microseismicity detection, ambient noise tomography, earthquake source characterization, and active source seismology. Using laser-pulse techniques, DAS turns (commercial) fiber-optic cables into seismic arrays with a spatial sampling density of the order of meters and a time sampling rate up to one thousand Hertz. The versatility of DAS enables dense instrumentation of traditionally inaccessible domains, such as urban, glaciated, and submarine environments. This in turn opens up novel applications such as traffic density monitoring and maritime vessel tracking. However, these new environments also introduce new challenges in handling various types of recorded noise, impeding the application of traditional data analysis workflows. In order to tackle the challenges posed by noise, new denoising techniques need to be explored that are tailored to DAS. In this work, we propose a Deep Learning approach that leverages the spatial density of DAS measurements to remove spatially incoherent noise with unknown characteristics. This approach is entirely self-supervised, so no noise-free ground truth is required, and it makes no assumptions regarding the noise characteristics other than that it is spatio-temporally incoherent. We apply our approach to both synthetic and real-world DAS data to demonstrate its excellent performance, even when the signals of interest are well below the noise level. Our proposed methods can be readily incorporated into conventional data processing workflows to facilitate subsequent seismological analyses.

Integrated rupture mechanics for slow slip events and earthquakes.

Slow slip events occur worldwide and could trigger devastating earthquakes, yet it is still debated whether their moment-duration scaling is linear or cubic and a fundamental model unifying slow and fast earthquakes is still lacking. Here, we show that the rupture propagation of simulated slow and fast earthquakes can be predicted by a newly-developed three-dimensional theory of dynamic fracture mechanics accounting for finite rupture width, an essential ingredient missing in previous theories. The complete spectrum of rupture speeds is controlled by the ratio of fracture energy to energy release rate. Shear stress heterogeneity can produce a cubic scaling on a single fault while effective normal stress variability produces a linear scaling on a population of faults, which reconciles the debated scaling relations. This model provides a new framework to explain how slow slip might lead to earthquakes and opens new avenues for seismic hazard assessment integrating seismological, laboratory and theoretical developments.

Bridging time scales of faulting: From coseismic to postseismic slip of the Mw 6.0 2014 South Napa, California earthquake.

Transient fault slip spans time scales from tens of seconds of earthquake rupture to years of aseismic afterslip. So far, seismic and geodetic recordings of these two phenomena have primarily been studied separately and mostly with a focus on kinematic aspects, which limits our physical understanding of the interplay between seismic and aseismic slip. Here, we use a Bayesian dynamic source inversion method, based on laboratory-derived friction laws, to constrain fault stress and friction properties by joint quantitative modeling of coseismic and postseismic observations. Analysis of the well-recorded 2014 South Napa, California earthquake shows how the stressing and frictional conditions on the fault govern the spatial separation between shallow coseismic and postseismic slip, the progression of afterslip driving deep off-fault aftershocks, and the oblique ribbon-like rupture shape. Such inferences of stress and frictional rheology can advance our understanding of earthquake physics and pave the way for self-consistent cross-scale seismic hazard assessment.

Instantaneous tracking of earthquake growth with elastogravity signals.

Rapid and reliable estimation of large earthquake magnitude (above 8) is key to mitigating the risks associated with strong shaking and tsunamis1. Standard early warning systems based on seismic waves fail to rapidly estimate the size of such large earthquakes2-5. Geodesy-based approaches provide better estimations, but are also subject to large uncertainties and latency associated with the slowness of seismic waves. Recently discovered speed-of-light prompt elastogravity signals (PEGS) have raised hopes that these limitations may be overcome6,7, but have not been tested for operational early warning. Here we show that PEGS can be used in real time to track earthquake growth instantaneously after the event reaches a certain magnitude. We develop a deep learning model that leverages the information carried by PEGS recorded by regional broadband seismometers in Japan before the arrival of seismic waves. After training on a database of synthetic waveforms augmented with empirical noise, we show that the algorithm can instantaneously track an earthquake source time function on real data. Our model unlocks 'true real-time' access to the rupture evolution of large earthquakes using a portion of seismograms that is routinely treated as noise, and can be immediately transformative for tsunami early warning.

Interevent-time distribution and aftershock frequency in non-stationary induced seismicity.

The initial footprint of an earthquake can be extended considerably by triggering of clustered aftershocks. Such earthquake-earthquake interactions have been studied extensively for data-rich, stationary natural seismicity. Induced seismicity, however, is intrinsically inhomogeneous in time and space and may have a limited catalog of events; this may hamper the distinction between human-induced background events and triggered aftershocks. Here we introduce a novel Gamma Accelerated-Failure-Time model for efficiently analyzing interevent-time distributions in such cases. It addresses the spatiotemporal variation and quantifies, per event, the probability of each event to have been triggered. Distentangling the obscuring aftershocks from the background events is a crucial step to better understand the causal relationship between operational parameters and non-stationary induced seismicity. Applied to the Groningen gas field in the North of the Netherlands, our model elucidates geological and operational drivers of seismicity and has been used to test for aftershock triggering. We find that the hazard rate in Groningen is indeed enhanced after each event and conclude that aftershock triggering cannot be ignored. In particular we find that the non-stationary interevent-time distribution is well described by our Gamma model. This model suggests that 27.0(± 8.5)% of the recorded events in the Groningen field can be attributed to triggering.

Dynamic viability of the 2016 Mw 7.8 Kaikoura earthquake cascade on weak crustal faults.

We present a dynamic rupture model of the 2016 Mw 7.8 Kaikoura earthquake to unravel the event's riddles in a physics-based manner and provide insight on the mechanical viability of competing hypotheses proposed to explain them. Our model reproduces key characteristics of the event and constraints puzzling features inferred from high-quality observations including a large gap separating surface rupture traces, the possibility of significant slip on the subduction interface, the non-rupture of the Hope fault, and slow apparent rupture speed. We show that the observed rupture cascade is dynamically consistent with regional stress estimates and a crustal fault network geometry inferred from seismic and geodetic data. We propose that the complex fault system operates at low apparent friction thanks to the combined effects of overpressurized fluids, low dynamic friction and stress concentrations induced by deep fault creep.

Observations and modeling of the elastogravity signals preceding direct seismic waves.

After an earthquake, the earliest deformation signals are not expected to be carried by the fastest (P) elastic waves but by the speed-of-light changes of the gravitational field. However, these perturbations are weak and, so far, their detection has not been accurate enough to fully understand their origins and to use them for a highly valuable rapid estimate of the earthquake magnitude. We show that gravity perturbations are particularly well observed with broadband seismometers at distances between 1000 and 2000 kilometers from the source of the 2011, moment magnitude 9.1, Tohoku earthquake. We can accurately model them by a new formalism, taking into account both the gravity changes and the gravity-induced motion. These prompt elastogravity signals open the window for minute time-scale magnitude determination for great earthquakes.

Induced seismicity provides insight into why earthquake ruptures stop.

Injection-induced earthquakes pose a serious seismic hazard but also offer an opportunity to gain insight into earthquake physics. Currently used models relating the maximum magnitude of injection-induced earthquakes to injection parameters do not incorporate rupture physics. We develop theoretical estimates, validated by simulations, of the size of ruptures induced by localized pore-pressure perturbations and propagating on prestressed faults. Our model accounts for ruptures growing beyond the perturbed area and distinguishes self-arrested from runaway ruptures. We develop a theoretical scaling relation between the largest magnitude of self-arrested earthquakes and the injected volume and find it consistent with observed maximum magnitudes of injection-induced earthquakes over a broad range of injected volumes, suggesting that, although runaway ruptures are possible, most injection-induced events so far have been self-arrested ruptures.

Localized seismic deformation in the upper mantle revealed by dense seismic arrays.

Seismicity along continental transform faults is usually confined to the upper half of the crust, but the Newport-Inglewood fault (NIF), a major fault traversing the Los Angeles basin, is seismically active down to the upper mantle. We use seismic array analysis to illuminate the seismogenic root of the NIF beneath Long Beach, California, and identify seismicity in an actively deforming localized zone penetrating the lithospheric mantle. Deep earthquakes, which are spatially correlated with geochemical evidence of a fluid pathway from the mantle, as well as with a sharp vertical offset in the lithosphere-asthenosphere boundary, exhibit narrow size distribution and weak temporal clustering. We attribute these characteristics to a transition from strong to weak interaction regimes in a system of seismic asperities embedded in a ductile fault zone matrix.

Prompt gravity signal induced by the 2011 Tohoku-Oki earthquake.

Transient gravity changes are expected to occur at all distances during an earthquake rupture, even before the arrival of seismic waves. Here we report on the search of such a prompt gravity signal in data recorded by a superconducting gravimeter and broadband seismometers during the 2011 Mw 9.0 Tohoku-Oki earthquake. During the earthquake rupture, a signal exceeding the background noise is observed with a statistical significance higher than 99% and an amplitude of a fraction of µGal, consistent in sign and order of magnitude with theoretical predictions from a first-order model. While prompt gravity signal detection with state-of-the-art gravimeters and seismometers is challenged by background seismic noise, its robust detection with gravity gradiometers under development could open new directions in earthquake seismology, and overcome fundamental limitations of current earthquake early-warning systems imposed by the propagation speed of seismic waves.

Near-trench slip potential of megaquakes evaluated from fault properties and conditions.

Near-trench slip during large megathrust earthquakes (megaquakes) is an important factor in the generation of destructive tsunamis. We proposed a new approach to assessing the near-trench slip potential quantitatively by integrating laboratory-derived properties of fault materials and simulations of fault weakening and rupture propagation. Although the permeability of the sandy Nankai Trough materials are higher than that of the clayey materials from the Japan Trench, dynamic weakening by thermally pressurized fluid is greater at the Nankai Trough owing to higher friction, although initially overpressured fluid at the Nankai Trough restrains the fault weakening. Dynamic rupture simulations reproduced the large slip near the trench observed in the 2011 Tohoku-oki earthquake and predicted the possibility of a large slip of over 30 m for the impending megaquake at the Nankai Trough. Our integrative approach is applicable globally to subduction zones as a novel tool for the prediction of extreme tsunami-producing near-trench slip.

Frictional velocity-weakening in landslides on Earth and on other planetary bodies.

One of the ultimate goals in landslide hazard assessment is to predict maximum landslide extension and velocity. Despite much work, the physical processes governing energy dissipation during these natural granular flows remain uncertain. Field observations show that large landslides travel over unexpectedly long distances, suggesting low dissipation. Numerical simulations of landslides require a small friction coefficient to reproduce the extension of their deposits. Here, based on analytical and numerical solutions for granular flows constrained by remote-sensing observations, we develop a consistent method to estimate the effective friction coefficient of landslides. This method uses a constant basal friction coefficient that reproduces the first-order landslide properties. We show that friction decreases with increasing volume or, more fundamentally, with increasing sliding velocity. Inspired by frictional weakening mechanisms thought to operate during earthquakes, we propose an empirical velocity-weakening friction law under a unifying phenomenological framework applicable to small and large landslides observed on Earth and beyond.

The 2011 magnitude 9.0 Tohoku-Oki earthquake: mosaicking the megathrust from seconds to centuries.

Geophysical observations from the 2011 moment magnitude (M(w)) 9.0 Tohoku-Oki, Japan earthquake allow exploration of a rare large event along a subduction megathrust. Models for this event indicate that the distribution of coseismic fault slip exceeded 50 meters in places. Sources of high-frequency seismic waves delineate the edges of the deepest portions of coseismic slip and do not simply correlate with the locations of peak slip. Relative to the M(w) 8.8 2010 Maule, Chile earthquake, the Tohoku-Oki earthquake was deficient in high-frequency seismic radiation--a difference that we attribute to its relatively shallow depth. Estimates of total fault slip and surface secular strain accumulation on millennial time scales suggest the need to consider the potential for a future large earthquake just south of this event.