Slant stacking based common conversion point stacking technique in suppressing multiples
Master of Science
On a large extent global seismology is working as a data driving subject. To process real data and then image the deep earth, we need to develop various imaging techniques. Among them, common conversion point (CCP) stacking is a powerful migration method in imaging the deep structures of the earth interior by using receiver function (RF) data. One critical assumption in CCP stacking is that the P to S conversion signals in the RF data are all coming from the direct P wave conversion phases at the velocity discontinuities. However, in real case the RFs computed contain other phases such as the Moho reverberations and other lithosphere discontinuity multiples, along with numerical noises due to the deconvolution instability and the approximation that the vertical component serving as the source function of the earthquake. Thus, in the imaging results there inevitably exist unfavorable fake structures and artifacts. Realizing this potential problem, we combine the widely used slant stacking technique in the CCP stacking and develop a robust algorithm to suppress these fake structures while conserving the real existing ones. We test this technique by using synthetic data. In the final migration result, at the depth range of 200 km to 1000 km there only exist signals due to the P to S conversion at 410 and 660 discontinuities, which are the only real structures in our earth model, compared with obvious fake signals between $200-300$ km from the traditional CCP imaging. We then apply it in the real data and compare to the traditional CCP imaging results, and the comparison indicates that our technique could dramatically suppress the imaging artifacts and highlight the globally existed discontinuities, along with other real structures induced by local effects.
seismic imaging; suppressing multiples