1887

Abstract

This article describes a nonlinear differential semblance approach to waveform inversion. Nonlinear differential semblance optimization combines the ability of full waveform inversion to account for nonlinear physical effects, such as multiple reflections, with the tendency of differential semblance migration velocity analysis to avoid local minima. It borrows the gather-flattening concept from migration velocity analysis, and updates the velocity by flattening primaries-only gathers obtained via nonlinear inversion. We describe the underlying idea and formulation of this algorithm, and present a layered 2D acoustic inversion excercise for which standard full waveform inversion fails, whereas nonlinear differential semblance succeeds in constructing a kinematically correct model and fitting the data rather precisely.

Loading

Article metrics loading...

/content/papers/10.3997/2214-4609.20131208
2013-06-10
2021-10-19
Loading full text...

Full text loading...

http://instance.metastore.ingenta.com/content/papers/10.3997/2214-4609.20131208
Loading
This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error