Seismic attenuation imaging with causality

Abstract

Seismic data enable imaging of the Earth, not only of velocity and density but also of attenuation contrasts. Unfortunately, the Born approximation of the constant-density visco-acoustic wave equation, which can serve as a forward modelling operator related to seismic migration, exhibits an ambiguity when attenuation is included. Different scattering models involving velocity and attenuation perturbations may provide nearly identical data. This result was obtained earlier for scatterers that did not contain a correction term for causality. Such a term leads to dispersion when considering a range of frequencies. We demonstrate that with this term, linearized inversion or iterative migration will almost, but not fully, remove the ambiguity. We also investigate if attenuation imaging suffers from the same ambiguity when using non-linear or full waveform inversion. A numerical experiment shows that non-linear inversion with causality convergences to the true model, whereas without causality, a substantial difference with the true model remains even after a very large number of iterations. For both linearized and non-linear inversion, the initial update in a gradient-based optimization scheme that minimizes the difference between modelled and observed data is still affected by the ambiguity and does not provide a good result. This first update corresponds to a classic migration operation. In our numerical experiments, the reconstructed model started to approximate the true model only after a large number of iterations.