Data-Adaptive Inversion of the Oklahoma EMAP Dataset.

Abstract

The Oklahoma EMAP dataset was analyzed using a two-dimensional inversion algorithm which includes static shifts as free parameters. Model misfit was minimized while simultaneously minimizing the resistivity roughness norm and the static shift L2 norm. The tradeoff parameters between the model misfit and these two norms were determined to minimize the Akaike's Bayesian Information Criterion (ABIC).