Co-Authors: Zhiming James Wu, Jing Wu, Frederico Xavier de Melo, Clement Kostov, all from Schlumberger

We consider methods that predict internal multiples by combining events in the data through convolutions and correlations. It is well established that such methods predict traveltimes of internal multiples accurately. However, the use of correlations in the prediction leads to amplitudes of the predicted internal multiples that contain systematic errors related to scattering or absorptive losses.
Building on previous analysis of prediction of internal multiples in absorptive media (Wu and Weglein, 2014), we present a modified method for prediction of boundary-related internal multiples (Verschuur, 2006; Wu et al., 2011) that uses models of attenuation in the subsurface. 

Taking the attenuation factors into account improves the amplitudes of the predicted internal multiples, making the task of adaptive subtraction easier. We’ll discuss various scenarios depending on availability of attenuation models that extend to the acquisition surface, or alternatively, cover only some part of the subsurface.
We illustrate our method with synthetic and 2D marine field data, as in Melo et al. (SEG 2018).

Speaker Biography: James Wu, Schlumberger
James Wu has been working as a Geophysical Software Developer since 1999, with Western Geophysical and then Schlumberger. James’s applications expertise ranges from signal enhancement and noise suppression to various domain transformations, as well as surface and internal multiples prediction and attenuation. James is also involved in providing technical support for the software.
James received Physics BS and MSc degrees from Suzhou University in 1990.  He came to the U.S. in 1995 and obtained a Computer Science MSc degree from University of North Texas in 1998. In 1997, James qualified to be a PhD candidate in Physics at Toulouse Graduate School, University of North Texas.