Application of Cross Correlation for Global Velocity Quality Control in Seismic Imaging

The seismic processing geophysicist of today is faced with increasing challenges for finding hydrocarbons. Amidst many, one major challenge is building an accurate velocity model truly representative of the subsurface geology. Accurate estimate of the subsurface velocity field is important for repositioning of recorded seismic data in their true geologic positions in the subsurface during imaging of the data and for a high quality stacking of seismic data. Most imaging geophysicists rely greatly on visual inspection of the flatness of CMP gathers, amongst several other automated methods, for quality-checking built seismic velocity models. In most cases, these visual QC of seismic gathers is localized, and a number of seismic gathers could be missed out if the survey is large, leading to poor velocity and hence poor final image of the subsurface in most areas of the survey. In this paper, we propose that cross correlation of the near and far angle stacks provides a global quality-checking of the velocity model thereby allowing for an overall better quality image of the subsurface