Geostatistical Analysis of Inverse Problem Variables: Application to Seismic Tomography

Abstract

In this article we present a geostatistical approach to the transmission tomographic inverse problem, which is based on consideration of the inverse problem variables (velocity and traveltime errors) as regionalized variables (R.V.). Their structural analysis provides us with a new method to study the geophysical anisotropy of the rock, an important source of a priori information in order to design the anisotropic corrections. The underlying idea is that the geophysical structure can be deduced from the spatial structure of the regionalized variables which result from solving the tomographic problem with an isotropic algorithm. Also, the application of the structural analysis technique to the anisotropic corrected velocity field allows us to characterize the reliability of these corrections (model quality analysis). Geostatistical formalism also provides us with different techniques (parametric and non-parametric) to estimate and even simulate the velocity in the areas where this field has been considered anomalous based on field studies and on geophysical and statistical criteria. The kriging acts as a low-pass smoothing filter for the anomalous model parameters (velocities), but is not a substitute for an adequate filtering of the outliers before the inversion. This methodology opens the possibility of considering the inverse problem variables as stochastic processes, an important feature in cases where the tomogram is to be used as a tool of assessment to quantify the rock heterogeneities.