Large dip artifacts in 1.5D internal multiple prediction and their mitigation

Kris Innanen and Pan Pan

ABSTRACT

In this short note we point out that large-dip artifacts noticeable in k g dependent integration limiting parameter ε. The results are largely consistent with those obtainable by post-prediction filtering, but the ε(k g ) approach is preferable in that it is tied to our interpretation of the origins of the artifacts.

View full article as PDF (4.53 Mb)