Least-squares extended imaging with surface-related multiples

TitleLeast-squares extended imaging with surface-related multiples
Publication TypeReport
Year of Publication2015
AuthorsRajiv Kumar, Ning Tu, Tristan van Leeuwen, Felix J. Herrmann
Document NumberTR-EOAS-2015-1
Month01
InstitutionUBC
Keywordsimage gathers, surface-related multiples
Abstract

Common image gathers are used in building velocity models, inverting for anisotropy parameters, and analyzing reservoir attributes. Typically, only primary reflections are used to form image gathers as multiples can cause artifacts that interfere with the events of interest. However, it has been shown that multiples can actually provide extra illumination of the subsurface, especially for delineating the near-surface features. In this paper, we aim to form common image gathers directly from the data with surface related multiples by applying concepts that have been used to successfully deal with surface-related multiples in imaging. We achieve this by effectively inverting an extended migration operator. This results in extended images with better near-surface illumination that are free of artifacts that can hamper velocity analysis. In addition, being able to generate extended images directly from the total data avoids the need for (time-consuming) pre-processing. Synthetic examples on a layered model show that the proposed formulation is promising.

URLhttps://slim.gatech.edu/Publications/Public/TechReport/2015/kumar2015EAGElse/kumar2015EAGElse.html
Citation Keykumar2015EAGElse