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Seismic waveform simulation for models with fluctuating interfaces

Authors
  • Rao, Ying1, 2
  • Wang, Yanghua2
  • 1 China University of Petroleum (Beijing), State Key Laboratory of Petroleum Resources and Prospecting, Beijing, 102249, China , Beijing (China)
  • 2 Imperial College London, Centre for Reservoir Geophysics, Department of Earth Science and Engineering, London, SW7 2BP, UK , London (United Kingdom)
Type
Published Article
Journal
Scientific Reports
Publisher
Springer Nature
Publication Date
Feb 15, 2018
Volume
8
Issue
1
Identifiers
DOI: 10.1038/s41598-018-20992-z
Source
Springer Nature
License
Green

Abstract

The contrast of elastic properties across a subsurface interface imposes a dominant influence on the seismic wavefield, which includes transmitted and reflected waves from the interface. Therefore, for an accurate waveform simulation, it is necessary to have an accurate representation of the subsurface interfaces within the numerical model. Accordingly, body-fitted gridding is used to partition subsurface models so that the grids coincide well with both the irregular surface and fluctuating interfaces of the Earth. However, non-rectangular meshes inevitably exist across fluctuating interfaces. This non-orthogonality degrades the accuracy of the waveform simulation when using a conventional finite-difference method. Here, we find that a summation-by-parts (SBP) finite-difference method can be used for models with non-rectangular meshes across fluctuating interfaces, and can achieve desirable simulation accuracy. The acute angle of non-rectangular meshes can be relaxed to as low as 47°. The cell size rate of change between neighbouring grids can be relaxed to as much as 30%. Because the non-orthogonality of grids has a much smaller impact on the waveform simulation accuracy, the model discretisation can be relatively flexible for fitting fluctuating boundaries within any complex problem. Consequently, seismic waveform inversion can explicitly include fluctuating interfaces within a subsurface velocity model.

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