Improving automatic first-arrival picking by supervirtual interferometry: examples from Saudi Arabia

Abstract

The objective of this study is to test the feasibility of using the supervirtual seismic interferometry method for improving automatic picking of first arrivals in petroleum seismic data. Fundamentally, interferometry is a mathematical technique used to position virtual sources at the location of actual receivers to gain the power of additional signals utilizing the physics of wavefield reciprocity and time reversal. Supervirtual interferometry extends the technique to far source-receiver offsets having very low signal-to-noise ratios. The benefits gained in more accurate first-arrival picking are significant, especially when near-surface velocity variations are severe and can have a detrimental impact on accurately mapping subtle structures. The supervirtual workflow consists of the following: windowing around first arrivals, cross-correlation, source stacking, convolution, and receiver stacking. The workflow is tested on a 2-D synthetic seismic data. In addition, the workflow has been tested on a 2-D petroleum seismic data from Saudi Arabia with considerable attenuation of first arrivals with offset. Results show that the workflow greatly improves first arrivals at all offsets, particularly at far offsets. Furthermore, testing the effect of a localized continuous random-noise source (e.g., due to machines) on the method’s performance show that such noise does not affect the method’s performance, which might be due to extensive trace mixing by the cross-correlation and convolution operations.