38 research outputs found
Scaling full seismic waveform inversions
The main goal of this research study is to scale full seismic waveform inversions using the adjoint-state method to the data volumes that are nowadays available in seismology. Practical issues hinder the routine application of this, to a certain extent theoretically well understood, method. To a large part this comes down to outdated or flat out missing tools and ways to automate the highly iterative procedure in a reliable way.
This thesis tackles these issues in three successive stages. It first introduces a modern and properly designed data processing framework sitting at the very core of all the consecutive developments. The ObsPy toolkit is a Python library providing a bridge for seismology into the scientific Python ecosystem and bestowing seismologists with effortless I/O and a powerful signal processing library, amongst other things.
The following chapter deals with a framework designed to handle the specific data management and organization issues arising in full seismic waveform inversions, the Large-scale Seismic Inversion Framework. It has been created to orchestrate the various pieces of data accruing in the course of an iterative waveform inversion.
Then, the Adaptable Seismic Data Format, a new, self-describing, and scalable data format for seismology is introduced along with the rationale why it is needed for full waveform inversions in particular and seismology in general.
Finally, these developments are put into service to construct a novel full seismic waveform inversion model for elastic subsurface structure beneath the North American continent and the Northern Atlantic well into Europe. The spectral element method is used for the forward and adjoint simulations coupled with windowed time-frequency phase misfit measurements. Later iterations use 72 events, all happening after the USArray project has commenced, resulting in approximately 150`000 three components recordings that are inverted for. 20 L-BFGS iterations yield a model that can produce complete seismograms at a period range between 30 and 120 seconds while comparing favorably to observed data
Scaling full seismic waveform inversions
The main goal of this research study is to scale full seismic waveform inversions using the adjoint-state method to the data volumes that are nowadays available in seismology. Practical issues hinder the routine application of this, to a certain extent theoretically well understood, method. To a large part this comes down to outdated or flat out missing tools and ways to automate the highly iterative procedure in a reliable way.
This thesis tackles these issues in three successive stages. It first introduces a modern and properly designed data processing framework sitting at the very core of all the consecutive developments. The ObsPy toolkit is a Python library providing a bridge for seismology into the scientific Python ecosystem and bestowing seismologists with effortless I/O and a powerful signal processing library, amongst other things.
The following chapter deals with a framework designed to handle the specific data management and organization issues arising in full seismic waveform inversions, the Large-scale Seismic Inversion Framework. It has been created to orchestrate the various pieces of data accruing in the course of an iterative waveform inversion.
Then, the Adaptable Seismic Data Format, a new, self-describing, and scalable data format for seismology is introduced along with the rationale why it is needed for full waveform inversions in particular and seismology in general.
Finally, these developments are put into service to construct a novel full seismic waveform inversion model for elastic subsurface structure beneath the North American continent and the Northern Atlantic well into Europe. The spectral element method is used for the forward and adjoint simulations coupled with windowed time-frequency phase misfit measurements. Later iterations use 72 events, all happening after the USArray project has commenced, resulting in approximately 150`000 three components recordings that are inverted for. 20 L-BFGS iterations yield a model that can produce complete seismograms at a period range between 30 and 120 seconds while comparing favorably to observed data
VERCE delivers a productive e-Science environment for seismology research
The VERCE project has pioneered an e-Infrastructure to support researchers
using established simulation codes on high-performance computers in conjunction
with multiple sources of observational data. This is accessed and organised via
the VERCE science gateway that makes it convenient for seismologists to use
these resources from any location via the Internet. Their data handling is made
flexible and scalable by two Python libraries, ObsPy and dispel4py and by data
services delivered by ORFEUS and EUDAT. Provenance driven tools enable rapid
exploration of results and of the relationships between data, which accelerates
understanding and method improvement. These powerful facilities are integrated
and draw on many other e-Infrastructures. This paper presents the motivation
for building such systems, it reviews how solid-Earth scientists can make
significant research progress using them and explains the architecture and
mechanisms that make their construction and operation achievable. We conclude
with a summary of the achievements to date and identify the crucial steps
needed to extend the capabilities for seismologists, for solid-Earth scientists
and for similar disciplines.Comment: 14 pages, 3 figures. Pre-publication version of paper accepted and
published at the IEEE eScience 2015 conference in Munich with substantial
additions, particularly in the analysis of issue
The EU Center of Excellence for Exascale in Solid Earth (ChEESE): Implementation, results, and roadmap for the second phase
publishedVersio
mtspec Python wrappers 0.3.2
mtspec is a Python wrapper for the Multitaper Spectrum Estimation Library by Germán Prieto. The relevant publication is
Prieto, G. A., R. L. Parker, F. L. Vernon. (2009), A Fortran 90 library for multitaper spectrum analysis, Computers and Geosciences, 35, pp. 1701-1710. doi:10.1016/ j.cageo.2008.06.007
It enables you to calculate Slepian windows, perform multitaper spectral estimations with various options, calculate Wigner-Ville time-frequency distributions, and construct coherence spectra with multitapers.
It currently wraps version 3.1 of the library
pyflex: 0.1.4
<p><em>Released Sep 30th 2015</em></p>
<ul>
<li>Minor change to adapt tests to the latest ObsPy version.</li>
<li>Dropped official support for Python 2.6. It still works with it for now but I don't plan on further supporting it.</li>
</ul
Accelerating numerical wave-propagation using wavefield adapted meshes, Part I: Forward and adjoint modelling
ISSN:0956-540XISSN:1365-246