Enhancing Imaging in Low Signal-to-Noise Environments Using Advanced CRS Techniques

Summary Obtaining high quality amplitude preserved images for quantitative analysis is a challenging task in areas of low data quality. Low signal-to-noise ratio can be the result of several factors, such as near-surface acquisition conditions, gaps in data acquisition, high ambient noise, etc. A key step in overcoming this problem is to have a tool for interpolation and regularisation of data in low S/N data. In this paper, we will show the effect of using an advanced Common Reflection Surface (CRS) technique to solve this problem. We will show the improvement achieved with CRS on a sample 3D dataset from onshore Morocco. This improvement allows us to accurately image the structure and perform a quantitative interpretation.