Improving optimum-offset data for near-surface reflection surveying using a multi-parameter stacking scheme

Shallow reflection data processing is a challenging task mainly because of the high level of coherent/non-coherent noise in the data. Non-reflective coherent events are not easy to attenuate and might be present on final image, leading to misinterpretation. Moreover, quite often the noise and reflection energy share the same signal properties that makes it difficult to separate them using frequency-based filters. In general, nearsurface seismic reflections are stronger in a specific portion of the field record that is conventionally called the optimum window. To enhance the reflections, one solution is to mute the record outside the optimum window where the effect of source-generated noise as well as direct and surface waves are more pronounce. Noise muting might increase signal-to-noise ratio and improves processing; however, it is problematic when a very large portion of data is contaminated with strong noise and the optimum window becomes very narrow. This leads to difficult data processing and smeared images. In this work, we propose to enhance data quality not only within the optimum window, but in the whole field record by interpolation and extrapolation of reflections. To accomplish this, we use a processing workflow based on the stacking parameters of the common-reflection-surface method, which is a powerful seismic processing technique for data enhancement. Data applications on a synthetic data as well as a shallow field data set show promising results.