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Near‐surface layer traveltime inversion: a synthetic example 1
Author(s) -
Bloor Robert
Publication year - 1996
Publication title -
geophysical prospecting
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.735
H-Index - 79
eISSN - 1365-2478
pISSN - 0016-8025
DOI - 10.1111/j.1365-2478.1996.tb00146.x
Subject(s) - geophone , surface (topology) , geology , inversion (geology) , geodetic datum , surface layer , geometry , linearization , geodesy , point (geometry) , layer (electronics) , geophysics , mathematics , physics , nonlinear system , seismology , materials science , quantum mechanics , composite material , tectonics
The near‐surface layer is modelled as a constant‐velocity layer with varying thickness. The base of the layer is described by a B‐spline curve. The optimum model is calculated by minimizing, with respect to the model parameters, the difference between traveltimes predicted by the model and those observed in the data. Once a model has been produced, corrections that are dependent on the raypath geometry through the near‐surface layer can be calculated. The effect of the near‐surface layer is normally considered to be consistent at each shot or geophone station for all traveltimes arriving at that location (the surface‐consistent approximation). This assumption linearizes the problem, allowing timeshifts to be calculated and the traveltimes corrected to a chosen datum, representing static corrections. The single correction at each point is an averaged correction, based on an assumption that is particularly inaccurate in the presence of lateral variations of velocity or thickness of the surface layer, in the presence of large surface layer velocities or in the presence of a thick surface layer. The method presented considers the non‐linear relationship between data and model explicitly, hence the correction that is dependent on the raypath. Linearization removes this dependence and reduces the problem to a surface‐consistent approximation. The method is applied to synthetic data calculated from a model with surface layer variations. Comparisons are made between the corrected data resulting from the method described here and the conventional surface‐consistent approach. From these results it becomes apparent that the near‐surface layer inversion method presented here can reproduce accurate models and correct for near‐surface layer effects in cases where conventional methods encounter difficulties. Additionally the method can be readily extended to 3D.