The evolution of fluid injection-induced seismicity, generally characterized through the number of events or their seismic moment, depends on, among other factors, the injected fluid volume. Migration of seismicity is observed during those sequences and might be caused by a range of mechanisms: fluid pressure diffusion, fluid-induced aseismic slip propagating along a stimulated fault, interactions between earthquakes. Recent theoretical and observational developments underline the important effect on seismicity migration of structural parameters, like fault criticality, or injection parameters, like flow rate or pressurization rate. Here, we analyze two well-studied injection-induced seismic sequences at the Soultz-sous-Fôret and Basel geothermal sites, and find that the evolution of the seismicity front distance primarily depends on the injected fluid volume. Based on a fracture mechanics model, we develop new equations relating seismicity migration to injected fluid volume and frictional and structural properties of the fault. We find that the propagation of a fluid-induced aseismic slip front along the stimulated fault, triggering seismicity, explains well the observations made on the two sequences. This model allows us to constrain parameters describing the seismicity front evolution and explains the diversity of migration patterns observed in injection-induced and natural earthquake swarms.

We introduce the Ensemble Earthquake Early Warning System (E3WS), a set of Machine Learning algorithms designed to detect, locate and estimate the magnitude of an earthquake using 3 seconds of P waves recorded by a single station. The system is made of 6 Ensemble Machine Learning algorithms trained on attributes computed from ground acceleration time series in the temporal, spectral and cepstral domains. The training set comprises datasets from Peru, Chile, Japan, and the STEAD global dataset. E3WS consists of three sequential stages: detection, P-phase picking and source characterization. The latter involves magnitude, epicentral distance, depth and back-azimuth estimation. E3WS achieves an overall success rate in the discrimination between earthquakes and noise of 99.9%, with no false positive (noise mis-classified as earthquakes) and very few false negatives (earthquakes mis-classified as noise). All false negatives correspond to M ≤ 4.3 earthquakes, which are unlikely to cause any damage. For P-phase picking, the Mean Absolute Error is 0.14 s, small enough for earthquake early warning purposes. For source characterization, the E3WS estimates are virtually unbiased, have better accuracy for magnitude estimation than existing single-station algorithms, and slightly better accuracy for earthquake location. By updating estimates every second, the approach gives time-dependent magnitude estimates that follow the earthquake source time function. E3WS gives faster estimates than present alert systems relying on multiple stations, providing additional valuable seconds for potential protective actions.

A document by Gabriela Arias Mendez. Click on the document to view its contents.

A document by Asaf Inbal. Click on the document to view its contents.

Tsunami wave observations far from the coast remain challenging due to the logistics and cost of deploying and operating offshore instrumentation on a long-term basis with sufficient spatial coverage and density. Distributed Acoustic Sensing (DAS) on submarine fiber optic cables now enables real-time seafloor strain observations over distances exceeding 100 km at a relatively low cost. Here, we evaluate the potential contribution of DAS to tsunami warning by assessing theoretically the sensitivity required by a DAS instrument to record tsunami waves. Our analysis includes signals due to two effects induced by the hydrostatic pressure perturbations arising from tsunami waves: the Poisson’s effect of the submarine cable and the compliance effect of the seafloor. It also includes the effect of seafloor shear stresses and temperature transients induced by the horizontal fluid flow associated with tsunami waves. The analysis is supported by fully coupled 3-D physics-based simulations of earthquake rupture, seismo-acoustic waves and tsunami wave propagation. The strains from seismo-acoustic waves and static deformation near the earthquake source are orders of magnitude larger than the tsunami strain signal. We illustrate a data processing procedure to discern the tsunami signal. With enhanced low-frequency sensitivity on DAS interrogators (strain sensitivity ≈ 2×10−10 at mHz frequencies), we find that, on seafloor cables located above or near the earthquake source area, tsunamis are expected to be observable with a sufficient signal-to-noise ratio within a few minutes of the earthquake onset. These encouraging results pave the way towards faster tsunami warning enabled by seafloor DAS.

Back-projection (BP) is a cornerstone method for imaging earthquake ruptures, particularly effective at teleseismic distances for deciphering large earthquake kinematics. Its superior resolution is attributed to the ability to resolve high-frequency (>1 Hz) seismic signals, where waveforms immediately following the first coherent arrivals are composed of waves scattered by small-scale seismic velocity heterogeneities. This scattering leads to waveform incoherence between neighboring stations, a phenomenon not captured by synthetic tests of BP using Green’s functions (GF) derived from oversimplified 1D or smooth 3D velocity models. Addressing this gap, we introduce a novel approach to generate synthetic Incoherent Green’s Functions (IGF) that include scattered waves, accurately mimicking the observed inter-station waveform coherence decay spatially and temporally. Our methodology employs a waveform simulator that adheres to ray theory for the travel times of scattered waves, aggregating them as incident plane waves to simulate the high-frequency scattered wavefield across a seismic array. Contrary to conventional views that scattered waves degrade BP imaging quality by reducing array coherence, our synthetic tests reveal that IGFs are indispensable for accurately imaging extensive ruptures. Specifically, the rapid decay of IGF coherence prevents early rupture segments from overshadowing subsequent ones, a critical flaw when using coherent GFs. By leveraging IGFs, we delve into previously unexplored aspects of BP imaging’s resolvability, sensitivity, fidelity, and uncertainty. Our investigation not only highlights and explains the commonly observed “tailing” and “shadowing” artefacts but also proposes a robust framework for identifying different rupture stages and quantifying their uncertainties, thereby significantly enhancing BP imaging accuracy.

Fluid-filled cracks sustain a slow guided wave (Krauklis wave or crack wave) whose resonant frequencies are widely used for interpreting long period (LP) and very long period (VLP) seismic signals at active volcanoes. Significant efforts have been made to model this process using analytical developments along an infinite crack or numerical methods on simple crack geometries. In this work, we develop an efficient hybrid numerical method for computing resonant frequencies of complex-shaped fluid-filled cracks and networks of cracks and apply it to explain the ratio of spectral peaks in the VLP signals from the Fani Maoré submarine volcano that formed in Mayotte in 2018. By coupling triangular boundary elements and the finite volume method, we successfully handle complex geometries and achieve computational efficiency by discretizing solely the crack surfaces. The resonant frequencies are directly determined through eigenvalue analysis. After proper verification, we systematically analyze the resonant frequencies of rectangular and elliptical cracks, quantifying the effect of aspect ratio and crack stiffness ratio. We then discuss theoretically the contribution of fluid viscosity and seismic radiation to energy dissipation. Finally, we obtain a crack geometry that successfully explains the characteristic ratio between the first two modes of the VLP seismic signals from the Fani Maoré submarine volcano in Mayotte. Our work not only reveals rich eigenmodes in complex-shaped cracks but also contributes to illuminating the subsurface plumbing system of active volcanoes. The developed model is readily applicable to crack wave resonances in other geological settings, such as glacier hydrology and hydrocarbon reservoirs.

A document by Julián Peláez Quiñones. Click on the document to view its contents.

Underwater fiber optic cables commonly traverse a variety of seafloor conditions, which leads to an uneven mechanical coupling between the cable and the ocean bottom. On rough seafloor bathymetry, some cable portions might be suspended and thus susceptible to Vortex-Induced Vibrations (VIV) driven by deep ocean currents. Here, we examine the potential of Distributed Acoustic Sensing (DAS) to monitor deep-sea currents along suspended sections of underwater telecom fiber optic cables undergoing VIV. Oscillations of a seafloor fiber optic cable located in southern France are recorded by DAS along cable sections presumably hanging. Their characteristic frequencies are lower than 1 Hz, at different ocean depths, and have an amplitude-dependency consistent with the driving mechanism being VIV. Based on a theoretical proportionality between current speed and VIV frequencies, we derive ocean current speed time series at 2390 m depth from the vortex shedding frequencies recorded by DAS. The DAS-derived current speed time series is in agreement with recordings by a current meter located 3.75 km away from the hanging cable section (similar dominant period, high correlation after time shift). The DAS-derived current speed time series displays features, such as characteristic periods and spectral decay, associated with the generation of internal gravity waves and weak oceanic turbulence in the Mediterranean Sea. The results demonstrate the potential of DAS along hanging segments of fiber optic cables to monitor a wide range of oceanography processes, at depths barely studied with current instrumentation.

Distributed Acoustic Sensing (DAS) enables data acquisition for underwater Earth Science with unprecedented spatial resolution. Submarine fibre optic cables traverse sea bottom features that can lead to suspended or decoupled cable portions, and are exposed to the ocean dynamics and to high rates of marine erosion or sediment deposition, which may induce temporal variations of the cable’s mechanical coupling to the ocean floor. Although these spatio-temporal fluctuations of the mechanical coupling affect the quality of the data recorded by DAS, and determine whether a cable section is useful or not for geophysical purposes, the detection of unsuitable cable portions has not been investigated in detail. Here, we report on DAS observations of two distinct vibration regimes of seafloor fibre optic cables: a high-frequency (> 2 Hz) regime we associate to cable segments pinned between seafloor features, and a low-frequency (< 1 Hz) regime we associate to suspended cable sections. While the low-frequency oscillations are driven by deep ocean currents, the high-frequency oscillations are triggered by the passage of earthquake seismic waves. Using Proper Orthogonal Decomposition, we demonstrate that high-frequency oscillations excite normal modes comparable to those of a finite 1D wave propagation structure. We further identify trapped waves propagating along cable portions featuring high-frequency oscillations. Their wave speed is consistent with that of longitudinal waves propagating across the steel armouring of the cable. The DAS data on cable sections featuring such cable waves are dominated by highly monochromatic noise. Our results suggest that the spatio-temporal evolution of the mechanical coupling between fibre optic cables exposed to the ocean dynamics and the seafloor can be monitored through the combined analysis of the two vibration regimes presented here, which provides a DAS-based method to identify underwater cable sections unsuitable for the analysis of seismic waves.

De Novellis et al. (2020, hereafter DN20) studied the effect of mass extraction from a quarry on the occurrence of the Mw 4.9 Le Teil, France, earthquake of November 11 2019. This topic was also the focus of the report of the French working group mandated by CNRS INSU (“Groupe de Travail Teil” of Institut National des Sciences de l’Univers du Centre National de la Recherche Scientifique; Delouis et al, 2019). Despite using similar data and methods, these two independent research efforts reached contrasting conclusions. While both concluded the earthquake was possibly a triggered event (i.e. its initiation was possibly promoted by the quarry activity but its further rupture growth was primarily enabled by natural pre-existing stresses), DN20 deemed realistic the hypothesis that the earthquake was an induced event (i.e. both the earthquake initiation and its further growth, up to its final size, were caused by the quarry activity). This distinction is critical for our understanding of future anthropogenic hazards in the region and in similar settings elsewhere, and may have significant social, economical and legal repercussions. Here, we show that a severe error in the calculations carried by DN20 undermines their conclusion.

While the notion that injecting fluids into the subsurface can reactivate faults by reducing frictional resistance is well established, the ensuing evolution of slip is still poorly understood. What controls whether the induced slip remains stable and confined to the fluid-affected zone or accelerates into a runaway earthquake? Are there observable indicators of the propensity to earthquakes before they happen? Here, we investigate these questions by modeling a unique fluid-injection experiment on a natural fault with laboratory-derived friction laws. We show that a range of fault models with diverging stability with sustained injection reproduce the slip measured during pressurization. Upon depressurization, however, the most unstable scenario departs from the observations, suggesting that the fault is relatively stable. The models could be further distinguished with optimized depressurization tests or spatially distributed monitoring. Our findings indicate that avoiding injection near low-residual-friction faults and depressurizing upon slip acceleration could help prevent large-scale earthquakes.