Sölvi Thrastarson

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Thrastarson

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Sölvi

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0000-0003-0931-6776

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Publications 1 - 10 of 22

Full Waveform Inversion Beneath the Central Andes: Insight Into the Dehydration of the Nazca Slab and Delamination of the Back-Arc Lithosphere
Gao, Yajian; Tilmann, Frederik; van Herwaarden, Dirk-Philip; et al. (2021)
Journal of Geophysical Research: Solid Earth
We present a new seismic tomography model for the crust and upper mantle beneath the Central Andes based on multi-scale full seismic waveform inversion, proceeding from long periods (40–80 s) over several steps down to 12–60 s. The spatial resolution and trade-offs among parameters are estimated through the multi-parameter point-spread functions. P- and S-wave velocity structures with spatial resolution of 30–40 km for the upper mantle and 20–25 km for the crust could be resolved in the central study region. In our study, the subducting Nazca slab is clearly imaged in the upper mantle, with dip-angle variations from the north to the south. Bands of low velocities in the crust and mantle wedge indicate intense crustal partial melting and hydration of the mantle wedge beneath the frontal volcanic arc, respectively, and they are linked to the vigorous dehydration from the subducting Nazca plate and intermediate depth seismicity within the slab. These low-velocity bands are interrupted at 19.8°–21°S, both in the crust and uppermost mantle, hinting at the lower extent of crustal partial melting and hydration of the mantle wedge. The variation of lithospheric high-velocity anomalies below the back-arc from north to south allows insight into the evolutionary foundering stages of the Central Andean margin. A high-velocity layer beneath the southern Altiplano suggests underthrusting of the leading edge of the Brazilian Shield. In contrast, a steeply westward dipping high-velocity block and low-velocity lithospheric uppermost mantle beneath the southern Puna plateau hint at the ongoing lithospheric delamination.
Accelerating numerical wave propagation by wavefield adapted meshes, Part II: Full-waveform inversion
Thrastarson, Sölvi; van Driel, Martin; Krischer, Lion; et al. (2020)
Geophysical Journal International
We present a novel full-waveform inversion (FWI) approach which can reduce the computational cost by up to an order of magnitude compared to conventional approaches, provided that variations in medium properties are sufficiently smooth. Our method is based on the usage of wavefield adapted meshes which accelerate the forward and adjoint wavefield simulations. By adapting the mesh to the expected complexity and smoothness of the wavefield, the number of elements needed to discretize the wave equation can be greatly reduced. This leads to spectral-element meshes which are optimally tailored to source locations and medium complexity. We demonstrate a workflow which opens up the possibility to use these meshes in FWI and show the computational advantages of the approach. We provide examples in 2-D and 3-D to illustrate the concept, describe how the new workflow deviates from the standard FWI workflow, and explain the additional steps in detail.
An illustrated guide to: Parsimonious multi-scale full-waveform inversion
Fichtner, Andreas; Thrastarson, Sölvi; van Herwaarden, Dirk-Philip; et al. (2024)
Earthquake Science
Having been a seemingly unreachable ideal for decades, 3-D full-waveform inversion applied to massive seismic datasets has become reality in recent years. Often achieving unprecedented resolution, it has provided new insight into the structure of the Earth, from the upper few metres of soil to the entire globe. Motivated by these successes, the technology is now being translated to medical ultrasound and non-destructive testing. Despite remarkable progress, the computational cost of full-waveform inversion continues to be a major concern. It limits the amount of data that can be exploited, and it largely inhibits quantitative and comprehensive uncertainty analyses. These notes complement a presentation on recent developments in full-waveform inversion that are intended to reduce computational cost and assimilate more data, thereby improving tomographic resolution. The suite of strategies includes flexible and user-friendly spectral-element simulations, the design of wavefield-adapted meshes that harness prior information on wavefield geometry, dynamic mini-batch optimisation that naturally takes advantage of data redundancies, and collaborative multi-scale updating to jointly constrain crustal and mantle structure.
LASIF: LArge-scale Seismic Inversion Framework, an updated version
Thrastarson, Sölvi; van Herwaarden, Dirk-Philip; Krischer, Lion; et al. (2021)
EarthArXiv
Recent methodological advances and increases in computational power have made it feasible to perform full-waveform inversions (FWI) of large domains while using more sources. This trend, along with the increasing availability of seismic data has led to an explosion of the data volumes that can, and should, be used within an inversion. Similar to machine learning problems, the incorporation of more data can result in more robust and higher quality models. In this contribution, we present the new version of LASIF, an open-source LArge-scale Seismic Inversion Framework, which helps to automate many of the historically labor-intensive tasks that were bottlenecks in earlier FWI workflows and prevented the use of the larger datasets. Among other things, the framework automates data selection, data acquisition from public web services, and data processing. It also defines an inversion project structure that organizes the data and documents the progress of the inversion. The code is open-source and available on Github. Features are available through a graphical user interface (GUI), a command-line interface (CLI), and an application programming interface (API). While we will show examples for use of LASIF with the Salvus wave equation solver, the API makes it possible to use the features of LASIF for any type of wave equation solver as long as the LASIF file formats are adhered to.
The EU Center of Excellence for Exascale in Solid Earth (ChEESE): Implementation, results, and roadmap for the second phase
Folch, Arnau; Abril, Claudia; Afanasiev, Michael; et al. (2023)
Future Generation Computer Systems
The EU Center of Excellence for Exascale in Solid Earth (ChEESE) develops exascale transition capabilities in the domain of Solid Earth, an area of geophysics rich in computational challenges embracing different approaches to exascale (capability, capacity, and urgent computing). The first implementation phase of the project (ChEESE-1P; 2018–2022) addressed scientific and technical computational challenges in seismology, tsunami science, volcanology, and magnetohydrodynamics, in order to understand the phenomena, anticipate the impact of natural disasters, and contribute to risk management. The project initiated the optimisation of 10 community flagship codes for the upcoming exascale systems and implemented 12 Pilot Demonstrators that combine the flagship codes with dedicated workflows in order to address the underlying capability and capacity computational challenges. Pilot Demonstrators reaching more mature Technology Readiness Levels (TRLs) were further enabled in operational service environments on critical aspects of geohazards such as long-term and short-term probabilistic hazard assessment, urgent computing, and early warning and probabilistic forecasting. Partnership and service co-design with members of the project Industry and User Board (IUB) leveraged the uptake of results across multiple research institutions, academia, industry, and public governance bodies (e.g. civil protection agencies). This article summarises the implementation strategy and the results from ChEESE-1P, outlining also the underpinning concepts and the roadmap for the on-going second project implementation phase (ChEESE-2P; 2023–2026).
First generation of a three-dimensional tomographic model for the uppermost mantle beneath the Zagros collision zone-constraints from full-waveform inversion
Masouminia, Neda; van Herwaarden, Dirk-Philip; Thrastarson, Sölvi; et al. (2025)
Acta Geophysica
We construct a three-dimensional model of seismic velocity structure beneath the Zagros collision zone by analyzing phase measurements of seismic waveform recordings from earthquakes. We used entire waveforms from 37 earthquakes and followed a multi-scale approach for periods between 20 and 80 s. As a starting model, we used the first generation of the Collaborative Seismic Earth Model, applied the adjoint method to compute model gradients, and utilized the Broyden-Fletcher-Goldfarb-Shanno (L-BFGS) optimization algorithm to reconstruct the uppermost mantle seismic velocity structure. The Zagros collision zone consists of the margin of the Arabian platform (the Zagros Fold-and-Thrust Belt) and the margin of the Eurasian plate (the Iranian microplates). The retrieved model reveals a strong shear wave velocity contrast at a depth of approximately 180 km along the Zagros mountain belt, and topography at the surface is a piece of evidence that the deformation of the transition zone stops along the Zagros. We interpret this as an interaction between the two continental lithospheres that end at this depth. We observe that the sub-crustal lithosphere of the studied region was constructed from relatively high shear velocity structures beneath Central Iran as well as the Lut block at 80-150 km depth and continuity of high-velocity structure throughout the margin of the Arabian lithosphere from 70- to 200-km depth. It explains continental collision caused earlier thickening during the convergence of the Arabian platform toward the northeast. This observation indicates that the lithosphere of Iranian microplates has a relatively warm structure. It also shows the non-uniform distribution of a sharp velocity contrast between this structure and the strong low-velocity structure underlying it, marking the lithosphere and asthenosphere boundary (LAB). Our results locate this boundary at approximately 119-km depth. On the other hand, we observed a thickened and cold lithosphere for the margin of the Arabian lithosphere.
Fiber-Optic Observation of Volcanic Tremor through Floating Ice Sheet Resonance
Fichtner, Andreas; Klaasen, Sara; Thrastarson, Sölvi; et al. (2022)
The Seismic Record
Entirely covered by the Vatnajökull ice cap, Grímsvötn is among Iceland’s largest and most hazardous volcanoes. Here we demonstrate that fiber-optic sensing technology deployed on a natural floating ice resonator can detect volcanic tremor at the level of few nanostrain/s, thereby enabling a new mode of subglacial volcano monitoring under harsh conditions. A 12.5 km long fiber-optic cable deployed on Grímsvötn in May 2021 revealed a high level of local earthquake activity, superimposed onto nearly monochromatic oscillations of the caldera. High data quality combined with dense spatial sampling identify these oscillations as flexural gravity wave resonance of the ice sheet that floats atop a subglacial lake. Although being affected by the ambient wavefield, the time–frequency characteristics of observed caldera resonance require the presence of an additional persistent driving force with temporal variations over several days, that is most plausibly explained in terms of low-frequency volcanic tremor. In addition to demonstrating the logistical feasibility of installing a large, high-quality fiber-optic sensing network in a sub arctic environment, our experiment shows that ice sheet resonance may act as a natural amplifier of otherwise undetectable (volcanic) signals. This suggests that similar resonators might be used in a targeted fashion to improve monitoring of ice-covered volcanic systems.
Evolutionary full-waveform inversion
van Herwaarden, Dirk-Philip; Afanasiev, Michael; Thrastarson, Sölvi; et al. (2021)
Geophysical Journal International
We present a new approach to full-waveform inversion (FWI) that enables the assimilation of data sets that expand over time without the need to reinvert all data. This evolutionary inversion rests on a reinterpretation of stochastic Limited-memory Broyden–Fletcher–Goldfarb–Shanno (L-BFGS), which randomly exploits redundancies to achieve convergence without ever considering the data set as a whole. Specifically for seismological applications, we consider a dynamic mini-batch stochastic L-BFGS, where the size of mini-batches adapts to the number of sources needed to approximate the complete gradient. As an illustration we present an evolutionary FWI for upper-mantle structure beneath Africa. Starting from a 1-D model and data recorded until 1995, we sequentially add contemporary data into an ongoing inversion, showing how (i) new events can be added without compromising convergence, (ii) a consistent measure of misfit can be maintained and (iii) the model evolves over times as a function of data coverage. Though applied retrospectively in this example, our method constitutes a possible approach to the continuous assimilation of seismic data volumes that often tend to grow exponentially.
Economical Full-Waveform Inversion
Thrastarson, Sölvi (2022)
Solving larger seismic inverse problems with smarter methods
Gebraad, Lars; van Herwaarden, Dirk-Philip; Thrastarson, Sölvi; et al. (2023)
Special Publications of the International Union of Geodesy and Geophysics ~ Applications of Data Assimilation and Inverse Problems in the Earth Sciences
The continuously increasing quantity and quality of seismic waveform data carry the potential to provide images of the Earth’s internal structure with unprecedented detail. Harnessing this rapidly growing wealth of information, however, constitutes a formidable challenge. While the emergence of faster supercomputers helps to accelerate existing algorithms, the daunting scaling properties of seismic inverse problems still demand the development of more efficient solutions. The diversity of seismic inverse problems – in terms of scientific scope, spatial scale, nature of the data, and available resources – precludes the existence of a silver bullet. Instead, efficiency derives from problem adaptation. Within this context, this chapter describes a collection of methods that are smart in the sense of exploiting specific properties of seismic inverse problems, thereby increasing computational efficiency and usable data volumes, sometimes by orders of magnitude. These methods improve different aspects of a seismic inverse problem, for instance, by harnessing data redundancies, adapting numerical simulation meshes to prior knowledge of wavefield geometry, or permitting long-distance moves through model space for Monte Carlo sampling.

Publications 1 - 10 of 22

Sölvi Thrastarson

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