Solving larger seismic inverse problems with smarter methods
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Date
2023-06-20
Publication Type
Book Chapter
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Abstract
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.
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Publication status
published
Book title
Applications of Data Assimilation and Inverse Problems in the Earth Sciences
Volume
5
Pages / Article No.
239 - 251
Publisher
Cambridge University Press
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Subject
Earth structure; High-performance computing; Inverse theory; Numerical simulation; Seismic tomography; Seismology; Uncertainty quantification; Wave propagation
Organisational unit
03971 - Fichtner, Andreas / Fichtner, Andreas
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Is part of: 10.1017/9781009180412