Constraining Martian Regolith and Vortex Parameters From Combined Seismic and Meteorological Measurements

The InSight mission landed on Mars in November 2018 and has since observed multiple convective vortices with both the high performance barometer and the low-noise seismometer SEIS that has unprecedented sensitivity. Here, we present a new method that uses the simultaneous pressure and seismic measurements of convective vortices to place constraints on the elastic properties of the Martian subsurface and the Martian vortex properties, while also allowing a reconstruction of the convective vortex trajectories. From data filtered in the (0.02–0.3 Hz) frequency band, we estimate that the mean value of η (η = E/[1 − ν2], where E is the Young's modulus and ν is the Poisson's ratio) of the Martian ground in the region around SEIS is 239 ± 140 MPa. In addition, we suggest that the previously reported paucity of vortex seismic observations to the west of InSight may be due to the fact that the ground is harder to the west than to the east, consistent with geomorphological surface interpretations

Autocorrelation of the Ground Vibrations Recorded by the SEIS‐InSight Seismometer on Mars

Since early February 2019, the SEIS (Seismic Experiment for Interior Structure) seismometer deployed at the surface of Mars in the framework of the InSight mission has been continuously recording the ground motion at Elysium Planitia. In this study, we take advantage of this exceptional data set to put constraints on the crustal properties of Mars using seismic interferometry (SI). To carry out this task, we first examine the continuous records from the very broadband seismometer. Several deterministic sources of environmental noise are identified and specific preprocessing strategies are presented to mitigate their influence. Applying the principles of SI to the single-station configuration of InSight, we compute, for each Sol and each hour of the martian day, the diagonal elements of the time-domain correlation tensor of random ambient vibrations recorded by SEIS. A similar computation is performed on the diffuse waveforms generated by more than a hundred Marsquakes. A careful signal- to-noise ratio analysis and an inter-comparison between the two datasets suggest that the results from SI are most reliable in a narrow frequency band around 2.4 Hz, where an amplification of both ambient vibrations and seismic events is observed. The average autocorrelation functions (ACFs) contain well identifiable seismic arrivals, that are very consistent between the two datasets. Interpreting the vertical and horizontal ACFs as, respectively, the P- and S- seismic reflectivity below InSight, we propose a simple stratified velocity model of the crust, which is mostly compatible with previous results from receiver function analysis. Our results are discussed and compared to recent works from the literature

Detection, analysis, and removal of glitches from InSight's seismic data from Mars

The instrument package SEIS (Seismic Experiment for Internal Structure) with the three very broadband and three short‐period seismic sensors is installed on the surface on Mars as part of NASA's InSight Discovery mission. When compared to terrestrial installations, SEIS is deployed in a very harsh wind and temperature environment that leads to inevitable degradation of the quality of the recorded data. One ubiquitous artifact in the raw data is an abundance of transient one‐sided pulses often accompanied by high‐frequency spikes. These pulses, which we term “glitches”, can be modeled as the response of the instrument to a step in acceleration, while the spikes can be modeled as the response to a simultaneous step in displacement. We attribute the glitches primarily to SEIS‐internal stress relaxations caused by the large temperature variations to which the instrument is exposed during a Martian day. Only a small fraction of glitches correspond to a motion of the SEIS package as a whole caused by minuscule tilts of either the instrument or the ground. In this study, we focus on the analysis of the glitch+spike phenomenon and present how these signals can be automatically detected and removed from SEIS's raw data. As glitches affect many standard seismological analysis methods such as receiver functions, spectral decomposition and source inversions, we anticipate that studies of the Martian seismicity as well as studies of Mars' internal structure should benefit from deglitched seismic data.Centre National d'Etudes Spatiales (CNES)Swiss SpaceOffice (SSO)Agence Nationale de la RechercheDLR German Space AgencyInSight PSP progra

Constraints on the shallow elastic and anelastic structure of Mars from InSight seismic data

Mars’s seismic activity and noise have been monitored since January 2019 by the seismometer of the InSight (Interior Exploration using Seismic Investigations, Geodesy and Heat Transport) lander. At night, Mars is extremely quiet; seismic noise is about 500 times lower than Earth’s microseismic noise at periods between 4 s and 30 s. The recorded seismic noise increases during the day due to ground deformations induced by convective atmospheric vortices and ground-transferred wind-generated lander noise. Here we constrain properties of the crust beneath InSight, using signals from atmospheric vortices and from the hammering of InSight’s Heat Flow and Physical Properties (HP3) instrument, as well as the three largest Marsquakes detected as of September 2019. From receiver function analysis, we infer that the uppermost 8–11 km of the crust is highly altered and/ or fractured. We measure the crustal diffusivity and intrinsic attenuation using multiscattering analysis and find that seismic attenuation is about three times larger than on the Moon, which suggests that the crust contains small amounts of volatiles

Seismic Interferometry applied to the data of the SEIS seismometer aboard the NASA Discovery InSight mission : Crustal structure and monitoring

Le sismomètre SEIS (Seismic Experiment for Interior Structure) a été déposé à la surface de la planète Mars le 19 décembre 2018 dans le cadre de la mission NASA Discovery InSight (Interior Exploration using Seismic Investigations, Geodesy and Heat Transport). Ses objectifs sont d'explorer la structure interne et l'activité sismique de Mars.Dans cette thèse nous analysons les données transmisent par SEIS sous le prisme de l'interférométrie sismique. Cette technique tire parti des propriétés des champs diffus tels que la coda sismique ou le bruit ambiant pour reconstruire la réponse impulsionnelle du milieu par corrélation d'enregistrements sismiques. L'exceptionnelle sensibilité du sismomètre SEIS rend possible l'étude des caractéristiques du bruit ambiant martien, qui nous étaient inconnues jusqu'alors.En comparant des fonctions d'auto-corrélations de bruit et de coda d'événements sismiques martiens nous avons identifié deux régions du spectre où s'observe le bruit microsismique martien.Une amplification locale du sol autour de 2.4 Hz présente une structure spectrale que nous avons pu relier à la structure crustale de Mars. La réponse en réflexion reconstruite par auto-corrélation a permis de détecter deux interfaces crustales, à ~9 et ~24 km de profondeur, cohérentes avec les fonctions récepteur.Nous montrons également que les composantes horizontales du sismomètre contiennent la signature d'une variation saisonnière des vitesses sismiques dans leurs spectres à hautes fréquences (> 5 Hz). Ces variations, observées également dans la coda de multiplets sismiques hautes fréquences, ont pu être reliées à une réponse thermo-élastique de la subsurface sous l'effet des changements saisonnier du forçage thermique solaire. Cette observation fournie une opportunité de sonder les paramètres thermiques et élastiques de la subsurface martienne jusqu'à plus de 20 mètres de profondeur.The Seismic Experiment for Interior Structure (SEIS) seismometer was deposited on the surface of Mars on December 19, 2018 as part of the NASA Discovery InSight (Interior Exploration using Seismic Investigations, Geodesy and Heat Transport) mission. Its objectives are to explore the internal structure and seismic activity of Mars.In this thesis we analyze the data transmitted by SEIS in the light of seismic interferometry. This technique takes advantage of the properties of diffuse fields such as seismic coda or ambient noise to recover the impulse response of the medium by correlation of seismic records.The exceptional sensitivity of the SEIS seismometer makes it possible to study the characteristics of the Martian ambient noise, which were unknown to us until now.By comparing autocorrelation functions of seismic ambient noise and Marsquake coda we have identified two regions of the spectrum where Martian microseismic noise is observed.A local ground amplification around 2.4 Hz presents a spectral structure that we were able to link to the crustal structure of Mars. The reflection response reconstructed by auto-correlation allowed us to detect two crustal interfaces, at ~9 and ~24 km depth, consistent with receiver functions analysis.We also show that the horizontal components of the seismometer contain the signature of a seasonal variation of seismic velocities in their high frequency spectra (> 5 Hz).These variations, also observed in the coda of high frequency seismic multiplets, could be related to a thermo-elastic response of the subsurface under the effect of seasonal changes in solar thermal forcing.This observation provides an opportunity to probe the thermal and elastic parameters of the Martian subsurface to a depth of over 20 meters

Bayesian evidential learning : an alternative to hydrogeophysical coupled inversion

Deterministic geophysical inversion suffers from a lack of realism because of the regularization, while stochastic inversion allowing for uncertainty quantification is computationally expensive. In this contribution, we propose to use Bayesian Evidential Learning as an alternative to hydrogeophysical coupled inversion. We demonstrate the ability of the approach to successfully predict a hydrogeological target from time-lapse ERT data in the context of a heat injection and storage experiment