Sensitivity evaluation of a seismic interpolation algorithm

Abstract

Sparse seismic acquisition is a new trend in seismic exploration, as it costs much less than conventional methods. To maintain the initial resolution of the seismic image, we propose several ways to sample data irregularly but periodically. These were tested by decimating the synthetic data, then interpolating, imaging and inversion. At every processing step, we quantified the effect of interpolation by comparing the results with those from the fully sampled data. Once the numerical test suggested the best decimation scheme, we were able to proceed to test the real dataset. This test confirmed that sparse acquisition using 60% of the available data is feasible.

To maintain the initial resolution of the seismic image from seismic sparse acquisition, we propose several ways to sample data irregularly but periodically. At every processing step, we quantified the effect of interpolation by comparing the results with those from the fully sampled data. The result shows that using 60% of the available data is feasible.

• FWI
• imaging
• interpolation
• seismic processing
• sparse acquisition

Acknowledgements

This research was funded by the Vietnam National Foundation for Science and Technology Development (NAFOSTED) under grant number 105.04–2015.12 and the National Science and Technology Research Program under grant number KC 09.01/16-20.