- Copyright: © 2007 This is an Open Access article: verbatim copying and redistribution of this article are permitted in all media for any purpose, provided this notice is preserved along with the article's original URL.
We investigate the influence of uncorrelated high frequency Gaussian noise on the accuracy and reliability of first-break arrival time picks. Using a reliable automatic picking algorithm based on the Akaike information criterion (AIC) and systematically noise contaminated synthetic data, allows us to develop a characteristic relation between the mis-pick (i.e., the error in the picked arrival time) and the signal-to-noise (S/N) ratio for a specific waveform. For typical near-surface crosshole georadar survey setups, we further study the impact of such noise-related picking errors on tomographically reconstructed velocity images. Using synthetic and field data examples, results of tomographic inversions illustrate that significant velocity distortions can be introduced by noise-related mis-picking. In addition, we show that, under favorable conditions, it is possible to correct the noise-related picking errors prior to inversion.