DATA VOLUME VS MODEL RESOLUTION IN NEAR-SURFACE MODELING USING FULL WAVEFORM INVERSION

Detecting near surface artifacts (within the first few meters) using seismic imaging methods has been often challenging. Key complications include lack of coherent reflections, along with insufficient data volume because of random noise, clipped amplitudes or incomplete data. Here I showed how the resolution of the models significantly vary with the decreasing data volume. This paper presents two experiments with an approach of establishing a relation between model resolution achieved and the fraction of data volume used for the modeling. The experiments demonstrated the best case scenarios assuming a simple velocity model with two different acquisitions representing 24 channel and 48 channel datasets. Results suggest that the fraction of data volume, especially the loss of near offset data has significant effect on the model resolution although there are still some frequencies available.