Tinti, Elisa

Accurate assessment of the rate and state friction parameters of rocks is essential for producing realistic earthquake rupture scenarios and, in turn, for seismic hazard analysis. Those parameters can be directly measured on samples, or indirectly based on inversion of coseismic or postseismic slip evolution. However, both direct and indirect approaches require assumptions that might bias the results. Aiming to reduce the potential sources of bias, we take advantage of a downscaled analog model reproducing megathrust earthquakes. We couple the simulated annealing algorithm with quasi-dynamic numerical models to retrieve rate and state parameters reproducing the recurrence time, rupture duration and slip of the analog model, in the ensemble. Then, we focus on how the asperity size and the neighboring segments’ properties control the seismic cycle characteristics and the corresponding variability of rate and state parameters. We identify a tradeoff between (a-b) of the asperity and (a-b) of neighboring creeping segments, with multiple parameter combinations that allow mimicking the analog model behavior. Tuning of rate and state parameters is required to fit laboratory experiments with different asperity lengths. Poorly constrained frictional properties of neighboring segments are responsible for uncertainties of (a-b) of the asperity in the order of per mille. Roughly one order of magnitude larger uncertainties derive from asperity size. Those results provide a glimpse of the variability that rate and state friction estimates might have when used as a constraint to model fault slip behavior in nature.

Large seismogenic faults consist of approximately meter-thick fault cores surrounded by hundreds-of-meters-thick damage zones. Earthquakes are generated by rupture propagation and slip within fault cores and dissipate the stored elastic strain energy in fracture and frictional processes in the fault zone and in radiated seismic waves. Understanding this energy partitioning is fundamental in earthquake mechanics to explain fault dynamic weakening and causative rupture processes operating over different spatial and temporal scales. The energy dissipated in the earthquake rupture propagation along a fault is called fracture energy or breakdown work. Here we review fracture energy estimates from seismological, modeling, geological, and experimental studies and show that fracture energy scales with fault slip. We conclude that although material-dependent constant fracture energies are important at the microscale for fracturing grains of the fault zone, they are negligible with respect to the macroscale processes governing rupture propagation on natural faults.

Although rheological heterogeneities are invoked to explain differences in fault-slip be- havior, case studies where an interdisciplinary approach is adopted to capture their specific roles are still rare. In this work, we integrated geophysical, geological, and laboratory data to explain how rheological heterogeneities influence the earthquake activity at the roots of the seismogenic zone. During the 2016–2017 Central Italy sequence, following the major earthquakes, we observed a deepening of seismicity within the basement associated with a transient stress change. Part of this seismicity was organized in clusters of events, with similar sizes and waveforms. The structural study of exhumed basement rocks highlighted a heterogeneous fabric made of strong, quartz-rich lenses (up to 200 m) surrounded by a weak, interconnected phyllosilicate-rich matrix. Laboratory experiments simulating the main shock–induced increase in loading rate showed that the matrix lithology experienced an ac- celerating and self-decelerating aseismic creep, whereas the lens lithology showed dynamic instabilities. Our results suggest that the post–main shock loading rate increases favored accelerated creep within the matrix, which promoted, as a consequence, seismic instabilities within the lenses in the form of clustered seismicity. Our findings emphasize the strong con- nection between seismicity and the structural and frictional properties of the seismogenic zone.

Analysis of seismicity can illuminate active fault zone structures but also deformation within large volumes of the seismogenic zone. For the Mw 6.5 2016-2017 Central Italy seismic sequence, seismicity not only localizes along the major structures hosting the mainshocks (on-fault seismicity), but also occurs within volumes of Triassic Evaporites, TE, composed of alternated anhydrites and dolostones. These volumes of distributed microseismicity show a different frequency-magnitude distribution than on-fault seismicity. We interpret that, during the sequence, shear strain-rate increase, and fluid overpressure promoted widespread ductile deformation within TE that light-up with distributed microseismicity. This interpretation is supported by field and laboratory observations showing that TE background ductile deformation is complex and dominated by distributed failure and folding of the anhydrites associated with boudinage hydro-fracturing and faulting of dolostones. Our results indicate that ductile crustal deformation can cause distributed microseismicity, which obeys to different scaling laws than on-fault seismicity occurring on structures characterized by elasto-frictional stick-slip behaviour.

Earthquake forecasting and prediction have long and in some cases sordid histories but recent work has rekindled interest based on advances in early warning, hazard assessment for induced seismicity and successful prediction of laboratory earthquakes. In the lab, frictional stick-slip events provide an analog for earthquakes and the seismic cycle. Labquakes are ideal targets for machine learning (ML) because they can be produced in long sequences under controlled conditions. Recent works show that ML can predict several aspects of labquakes using fault zone acoustic emissions. Here, we generalize these results and explore deep learning (DL) methods for labquake prediction and autoregressive (AR) forecasting. DL improves existing ML methods of labquake prediction. AR methods allow forecasting at future horizons via iterative predictions. We demonstrate that DL models based on Long-Short Term Memory (LSTM) and Convolution Neural Networks predict labquakes under several conditions, and that fault zone stress can be predicted with fidelity, confirming that acoustic energy is a fingerprint of fault zone stress. We predict also time to start of failure (TTsF) and time to the end of Failure (TTeF) for labquakes. Interestingly, TTeF is successfully predicted in all seismic cycles, while the TTsF prediction varies with the amount of preseismic fault creep. We report AR methods to forecast the evolution of fault stress using three sequence modeling frameworks: LSTM, Temporal Convolution Network and Transformer Network. AR forecasting is distinct from existing predictive models, which predict only a target variable at a specific time. The results for forecasting beyond a single seismic cycle are limited but encouraging. Our ML/DL models outperform the state-of-the-art and our autoregressive model represents a novel framework that could enhance current methods of earthquake forecasting.

Crustal seismicity is in general confined within the seismogenic layer, which is bounded at depth by processes related to the brittle-ductile transition (BDT) and in the shallow region by fault zone consolidation state and mineralogy. In the past 10-15 years, high resolution seismological and geodetic data have shown that faulting within and around the traditional seismogenic zone occurs in a large variety of slip modes. Frictional and structural heterogeneities have been invoked to explain such differences in fault slip mode and behaviour. However, an integrated and comprehensive picture remains extremely challenging because of difficulties to properly characterize fault rocks at seismogenic depths. Thus, the central-northern Apennines provide a unique opportunity because of the integration of deep-borehole stratigraphy and seismic reflection profiles with high resolution seismological data and outcrop studies. These works show that seismic sequences are limited within the sedimentary cover (depth < 9-10 km), suggesting that the underlaying basement plays a key-role in dictating the lower boundary of the seismogenic zone. Here we integrate structural data on exhumed outcrops of basement rocks with laboratory friction data to shed light on the mechanics of the Apenninic basement. Structural data highlight heterogeneous and pervasive deformation where foliated and phyllosilicate-rich rocks surround more competent quartz-rich lenses up to hundreds of meters in thickness. Phyllosilicate horizons deform predominantly by folding and foliation-parallel frictional sliding whereas quartz-rich lenses are characterized by brittle signatures represented by extensive fracturing and minor faulting. Laboratory experiments revealed that quartz-rich lithologies have relatively high friction, μ ≈ 0.51, velocity-strengthening to neutral behaviour, and elevated healing rates. On the contrary, phyllosilicate-rich (muscovite and chlorite) lithologies show low friction, 0.23 < μ < 0.31, a marked velocity strengthening behaviour that increases with increasing sliding velocity and negligible rates of frictional healing. Our integrated approach suggests that in the Apenninic basement deformation occurs along shear zones distributed on thickness up-to several kilometres, where the frictionally stable, foliated, and phyllosilicate-rich horizons favour aseismic deformation and therefore confine the depth of major earthquake ruptures and the seismogenic zone.

Fault stability is inherently linked to the frictional and healing properties of fault rocks and associated fabrics. Their complex interaction controls how the stored elastic energy is dissipated, that is, through creep or seismic motion. In this work, we focus on the relevance of fault fabrics in controlling the reactivation and slip behavior of dolomite-anhydrite analog faults. We designed a set of laboratory experiments where we first develop fault rocks characterized by different grain size reduction and localization at normal stresses of σN = 15, 35, 60, and 100 MPa and second, we reload and reactivate these fault rocks at the frictional stability transition, achieved at σN = 35 MPa by reducing the machine stiffness. If normal stress is lowered this way, reactivation occurs with relatively large stress drops and large peak-slip velocities. Subsequent unstable behavior produces slow stick-slip events with low stress drop and with either asymmetric or Gaussian slip velocity function depending on the inherited fault fabric. If normal stress is raised, deformation is accommodated within angular cataclasites promoting stable slip. The integration of microstructural data (showing brittle reworking of preexisting textures) with mechanical data (documenting restrengthening and dilation upon reactivation) suggests that frictional and chemically assisted healing, which is common in natural faults during the interseismic phase, can be a relevant process in developing large instabilities. We also conclude that fault rock heterogeneity (fault fabric) modulates the slip velocity function and thus the dynamics of repeating stick-slip cycles.

Moment tensor inversions of broadband velocity data are usually managed by adopting Green's functions for 1D layered seismic wave speed models. This assumption can impact on source parameter estimates in regions with complex 3D heterogeneous structures and discontinuities in rock properties. In this work, we present a new centroid moment tensor (CMT) catalog for the Amatrice-Visso-Norcia (AVN) seismic sequence based on a recently generated 3D wave speed model for the Italian lithosphere. Forward synthetic seismograms and Fréchet derivatives for CMT-3D inversions of 159 earthquakes with Mw ≥ 3.0 are simulated using a spectral-element method (SEM) code. By comparing the retrieved solutions with those from time domain moment tensor (TDMT) catalog, obtained with a 1D wave speed model calibrated for Central Apennines (Italy), we observe a remarkable degree of consistency in terms of source geometry, kinematics, and magnitude. Significant differences are found in centroid depths, which are more accurately estimated using the 3D model. Finally, we present a newly designed parameter, τ, to better quantify and compare a-posteriori the reliability of the obtained MT solutions. τ measures the goodness of fit between observed and synthetic seismograms accounting for differences in amplitude, arrival time, percentage of fitted seconds, and the usual L2-norm estimate. The CMT-3D solutions represent the first Italian CMT catalog based on a full-waveform 3D wave speed model. They provide reliable source parameters with potential implications for the structures activated during the sequence. The developed approach can be readily applied to more complex Italian regions where 1D models are underperforming and not representative of the area.

The topography is the only ingredient of the kinematic finite fault inversion that is explicitly known. Nevertheless, such analyses commonly assume Green's functions for a 1D layered geological model with flat surface topography. Minimization of the complexity is needed to reduce the computational cost of the inversions in realistic conditions but such assumptions can significantly impact the retrieved source parameters. In particular, the lack of management of approximations and uncertainties could lead to overconfident and biased interpretations of the kinematic results. The increasing computational power available in the coming exascale era provides the opportunity to include the topography at a high resolution and low cost. We have modified the non-negative least-square inversion method of Dreger et al. [2005] for taking into account Green’s functions generated by SPECFEM3D including explicitly significant topography. We applied this new procedure to retrieve the kinematic rupture history of the 30 October 2016 Norcia earthquake (Mw 6.5), by inverting strong motion and high-rate global positioning system datasets. The considered complex fault geometry consists of a main normal fault striking N155°, dipping 47° and belonging to the Mt. Vettore‐Mt. Bove fault system (VBFS), and a secondary fault plane striking N210° and dipping 36° to the NW. The choice is supported by seismological data, geological constraints, and observed surface breakages, but also by inferences from dynamic simulations. We have inverted for slip and rake distribution on the faults while allowing a Bayesian exploration of all the remaining parameters (i.e., rupture velocity, rise time).

During the 2016–2017 Central Italy earthquake sequence, a series of moderate to large earthquakes M > 5 occurred near the Amatrice and Norcia towns. These events are recorded on a dense seismic network, providing relevant observational evidence of complex earthquakes in time and space. In this work, we used this substantial data set to study the ground-motion characteristics of the Norcia earthquake M6.5 on October 30, 2016, through a broadband ground-motion simulation. Three-component broadband seismograms are generated to cover the entire frequency band of engineering interest. Low and high frequencies are computed considering the heterogeneous slip rupture model of Scognamiglio et al. (2018) [1]. High frequencies are calculated using a stochastic approach including P, SV, and SH waves, while low frequencies are obtained through a forward simulation of the kinematic model at the various stations. To predict earthquake-induced ground motions in the area, we adopted region-specific attenuation and source scaling parameters derived by Malagnini et al. (2011) [2]. Ground-motion parameters, including peak ground acceleration (PGA), peak ground velocity (PGV) and spectral amplitudes, are calculated at the selected sites adopting physics-based parameters to understand better the earthquake fault rupture, the wave propagation, and their impacts on the seismic hazard assessment in the region. We showed that combining the fault rupture history over the entire frequency spectrum of engineering interest, the attenuation characteristics of the seismic wave propagation, and the properly defined site responses can improve the prediction of ground motions and time histories, especially in near seismic sources.