10 November 2020 at 10 AM Pacific
Featured Discussants: Andrew Curtis, University of Edinburgh and Kees Wapenaar, Delft University of Technology
Thank you to SmartSolo for sponsoring the Virtual
Characterization of a Magma Sill in the Mayotte Volcanic Zone Using Converted Waves
Presenting Author: Lise Retailleau, Université de Paris, Institut de Physique du Globe de Paris and Observatoire Volcanologique du Piton de la Fournaise, Institut de Physique du Globe de Paris
Authors: Lise Retailleau, Université de Paris, Institut de Physique du Globe de Paris, Observatoire Volcanologique du Piton de la Fournaise, Institut de Physique du Globe de Paris; Jean-Marie Saurel, Université de Paris, Institut de Physique du Globe de Paris; Jean Letort, Observatoire Midi Pyrénées, Université Paul Sabatier; Aude Lavayssière, Université de Paris, Institut de Physique du Globe de Paris; Claudio Satriano, Université de Paris, Institut de Physique du Globe de Paris; Wayne Crawford, Université de Paris, Institut de Physique du Globe de Paris; Jérome Vergne,Institut de Physique du Globe de Strasbourg, Université de Strasbourg; Arnaud Lemarchand; Université de Paris, Institut de Physique du Globe de Paris
The magmatic event and subsequent creation of a new volcanic edifice that occurred offshore from the Mayotte island in the North Mozambique channel (Indian Ocean) is unique in its emitted lava volume and duration since the Laki eruption in 1784.
The event was first noticed through the strong seismicity it generated. Indeed, multiple Volcano Tectonic (VT) earthquakes of magnitude superior to 4 were felt on the island during the first month of the crisis (May 2018). The seismic activity is still ongoing and regularly felt by the population of the Mayotte island.
Very long period events (VLP) have also been recorded. The 11 November 2018 VLP was recorded worldwide and highlighted the volcanic origin of the activity before a scientific cruise discovered the volcano in May 2019. On active volcanoes, VLP signals are often associated with fluid movement or fluid resonance in a structure of the volcanic system. Evidence of a reservoir above the main seismicity swarm has been proposed by recent Magneto-telluric and petrologic studies.
The signature of this structure also appears as multiple arrivals on recordings of VT earthquakes located beneath it. The P and S-waves propagating upward and crossing the layer undergo conversions and speed deceleration in the sill, generating the supplementary arrivals.
Combining arrival time analysis and wave modeling in teleseismic and regional settings, we characterize a possible sill and identify its geometry and main properties. The layered structure has a thickness of about 2km, topping at 20km depth.
Imaging Light Structures at Earth’s Core-mantle Boundary – In Heavy Detail
Presenting Author: Paula Koelemeijer, Royal Holloway University of London
Authors: Paula Koelemeijer, Royal Holloway University of London; Alex Robson, University of California, Berkeley; Harriet Lau, University of California, Berkeley; Barbara Romanowicz, University of California, Berkeley & College de France; Arwen Deuss, Utrecht University; Jeroen Ritsema, University of Michigan
Accurate estimates of density variations are essential for modeling mantle flow and to distinguish between a thermal or compositional origin of mantle heterogeneity. Particularly, constraining the density of the Large-Low-Velocity-Provinces (LLVPs) in the deep mantle is important as the properties and stability of these structures have major implications for the long term evolution of the mantle. However, resolving LLVP density via seismological observations is not straightforward. Body wave data are only indirectly sensitive to density, while the sensitivity of Earth’s normal modes to density is relatively small and also shows trade-offs with topography on the core-mantle boundary. Consequently, few models of lower mantle density exist, with the most recent studies based on specific normal modes (Koelemeijer et al., 2017) and tidal data (Lau et al., 2017) drawing opposite conclusions.
Here, I will review efforts from the last decades to constrain the nature of the LLVPs, focusing on density and CMB topography. Specifically, I will discuss how the spatial extent of any dense material may be restricted to smaller regions within the LLVPs. In addition, I will discuss our current knowledge of the large-scale CMB topography, which also holds clues as to what the LLVPs may be. Furthermore, I will demonstrate that including CMB topography reconciles recent density studies based on normal modes and Earth’s tides, while the presence of a dense layer is also able to explain both data types. Together, these results point towards primarily thermal LLVPs with deep, spatially confined dense material present at their base.
Imaging Stratified Structures Using Spectral and Temporal Autocorrelations of Earthquake-based Data: Applications to Antarctic Grounded and Floating Ice Caps
Presenting Author: Thanh-Son Phạm, The Australian National University
Authors: Thanh-Son Phạm, The Australian National University; Hrvoje Tkalčić, The Australian National University
The use of passive seismic data to study structures of the ice covers in some parts of the Earth has been limited. This is either due to the lack of over-ice seismic deployment or the inefficiency of existing seismic methodology in the presence of shallow but sharp stratifications often encountered in the icy environment or sedimentary basin. In this talk, we present a new class of single-component only analysis, the autocorrelation method, to image stratified ice structures beneath individual receivers. Instead of using continuous ambient noise records, we advocate the use of P-wave coda – the waveform records immediately following the P arrival at steep incidence – from distant earthquakes to obtain high-resolution images of the ice structures. The method is then demonstrated using seismic data from four major over-ice arrays in Antarctica in the last two decades. The stacked autocorrelogram in time domain over earthquakes is deployed to obtain distinct reflection signals from the ice-rock interface beneath grounded ice stations. Meanwhile, at stations deployed over a floating ice shelf, where a significant water layer must be included into the problem, the stacked autocorrelogram in the spectral domain, which is equivalent to the temporal autocorrelation via a Fourier transform, proves to be effective to obtain thickness of both ice and water layers. Because the autocorrelation method presented here requires single-component recordings only, it has great potential in cryoseismological studies, or imaging applications at places with limited logistical access, such as in space missions to icy planets, polar regions or in ocean-bottom deployments.
Imaging Yellowstone’s Crustal Magmatic System Using Ambient Noise Correlations
Presenting Author: Ross Maguire, Michigan State University, University of New Mexico
Authors: Ross Maguire, Michigan State University, University of New Mexico; Brandon Schmandt, University of New Mexico; Min Chen, Michigan State University; Chengxin Jiang, Australian National University; Justin Wilgus, University of New Mexico
Seismic tomography has provided key constraints on the geometry and melt fraction of Yellowstone’s magmatic system and can provide insight into where Yellowstone is in its volcanic life cycle. Recent tomography studies depict seismic wavespeed reductions consistent with a melt-poor, non-mobile, crustal magma reservoir with melt fractions of roughly 10% or less. However, the seismically determined melt fraction may be underestimated due to imperfect data coverage, inversion regularization and inaccurate forward modeling. Additionally, evidence from teleseismic body wave modeling hints that the melt fraction could be much higher than 10%. Here, we use 3D spectral element waveform modeling to illustrate that traditional surface wave tomography can dramatically underestimate the amplitude of seismic anomalies associated with a melt-rich reservoir, which could lead to misinterpretation of the volume and mobility of melt present in Yellowstone’s crustal reservoir. To overcome these limitations, we are developing a new model based on adjoint ambient noise tomography, which incorporates more realistic wave propagation physics compared with traditional inversion techniques. We present a new Vs model of Yellowstone’s crust and uppermost mantle which will serve as our starting point for an adjoint inversion. The model uses the most complete set of ambient noise cross-correlations assembled for the Yellowstone region thus far, including over 2000 distinct source-receiver pairs with exceptional signal-to-noise ratio. Key features of the model, such as the amplitude and geometry of the low wavespeed anomaly below the Yellowstone caldera, agree well with past studies based on body and surface wave tomography. Adjoint inversion of our ambient noise cross-correlation dataset will likely sharpen these features which should help improve our understanding of the melt fraction and distribution in Yellowstone’s magmatic system.
Matrix Approach Applied to Passive Seismic Data
Presenting Author: Rita Touma, ISTerre, Université Grenoble Alpes, Institut Langevin, ESPCI Paris, PSL University, CNRS
Authors: Rita Touma, ISTerre, Université Grenoble Alpes, Institut Langevin, ESPCI Paris, PSL University, CNRS; Thibaud Blondel, Institut Langevin, ESPCI Paris, PSL University, CNRS; Arnaud Derode, Institut Langevin, ESPCI Paris, PSL University, CNRS; Michel Campillo, ISTerre, Université Grenoble Alpes; Alexandre Aubry, Institut Langevin, ESPCI Paris, PSL University, CNRS
To understand fault systems, it is required to identify the structure of the crust and upper mantle. Seismic investigations have long been relying on active sources generating an incident wave-field from the Earth surface. The reflected wave-field is then recorded by sensors deployed at the surface. Nowadays, passive imaging has been adopted as an alternative of this source-receiver configuration by computing the correlations of ambient noise. This process allows to estimate the Green’s function between two receivers. We here present a passive imaging technique applied to data recorded along the Clark Branch of the San Jacinto Fault Zone (Ben-Zion et al., 2015). Inspired by previous works in optics and acoustics, we introduce a matrix approach of seismic imaging based on seismic noise cross correlations. Our method applies focusing operations at emission and reception (Blondel et al., 2018) allowing to project the reflection matrix recorded at the surface to depth (redatuming). Although seismic noise is dominated by surface waves, focusing operations allow to extract the body wave components that carry information about the reflectivity of in-depth structures. However, complex velocity distribution of the Earth’s crust results in phase distortions, referred to as aberrations in the imaging process. Phase distortions prevent the imaging of the true reflectivity of the subsurface leading to unphysical features and blurry images. To overcome these issues, we introduce a new operator: the so-called distortion matrix. It connects any virtual source induced by focusing at emission with the distorted part of the reflected wave-front in the spatial Fourier domain. A time-reversal analysis of the distortion matrix is applied to correct for high-order aberrations. A 3D image of the fault is retrieved with optimal resolution and contrast. The damage volume extends from the surface to the first few hundred meters. Strata layers located at depths on both sides of the fault were also identified.