Improved inversion through use of the null space

Geophysics ◽  
1997 ◽  
Vol 62 (3) ◽  
pp. 869-883 ◽  
Author(s):  
Peter S. Rowbotham ◽  
R. Gerhard Pratt

Standard least‐squares traveltime inversion techniques tend to produce smoothed estimates of the velocity field. More complete results can be obtained by incorporating into the inversion scheme a priori information about the media to be imaged, derived from well logs, core data, and surface geology. A promising technique for achieving this involves projecting this information onto the null space model singular vectors of the inverse problem and including this projection with the non‐null space contribution in order to produce a solution. The method, demonstrated with both field and synthetic crosshole traveltime data acquired through layered, anisotropic media, successfully produces improved inversion solutions with lower traveltime residuals, layers that are more homogeneous, sharper interfaces, and better correlated anisotropy parameters than solutions obtained with standard techniques.

Geophysics ◽  
1999 ◽  
Vol 64 (4) ◽  
pp. 1116-1125 ◽  
Author(s):  
Gualtiero Böhm ◽  
Aldo L. Vesnaver

The possible nonuniqueness and inaccuracy of tomographic inversion solutions may be the result of an inadequate discretization of the model space with respect to the acquisition geometry and the velocity field sought. Void pixels and linearly dependent equations are introduced if the grid shape does not match the spatial distribution of rays, originating the well‐known null space. This is a common drawback when using regular pixels. By definition, the null space does not depend on the picked traveltimes, and so we cannot eliminate it by minimising the traveltime residuals. We show that the inversion quality can be improved by following a trial and error approach, that is, by adapting the pixels’ shape and distribution to the layer interfaces and velocity field. The resolution can be increased or decreased locally to search for an optimal grid, although this introduces a personal bias. On the other hand, we can so decide where, why, and which a priori information is introduced in the sought velocity field, which is hardly feasible by managing other stabilising tools such as damping factors and smoothing filters.


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