
TY  - JOUR
A1  - Hung, Barry 
A1  - Yang, Kunlun 
A1  - Zhou, Joe 
A1  - Long Xia, Qing 
T1  - Shallow Water Demultiple
JF  - ASEG Extended Abstracts
JO  - ASEG Extended Abstracts
Y1  - 2010
VL  - 2010
IS  - 1
SP  - 1
EP  - 4
KW  - 
UR  - https://doi.org/10.1071/ASEG2010AB076 
N2  - Multiples due to shallow water are observed in seismic data acquired in various places such as the Gippsland Basin of Australia. These short period multiple reflections often pose problems to the interpretation of geological structures. They are not easily handled by conventional surface-related multiple elimination (SRME) methods because the recorded primary waterbottom reflection, which is required by SRME, is often indistinct in shallow water situations due to the near offset gap. Hence, predictive deconvolution in the x-t or ?-p domain is frequently used for attenuating shallow water multiples. However, besides multiples, deconvolution also attenuates primary events that have a periodicity which is close to that of the water-layer. In this paper, we present a workflow that involves first attenuating short-period water-layer related multiples (WLRMs) ? a process that we term shallow water demultiple (SWD); and then suppressing other longperiod free surface multiples using conventional SRME. SWD is a wavefield-consistent method that first makes use of WLRMs in the data to reconstruct the missing water-bottom primary reflection and then uses the reflection for predicting shallow WLRMs. It is data driven and takes into account the spatial varying nature of subsurface structures. Since the WLRM model predicted by SWD has similar amplitude and phase as the input data, very short matching filters, which are not possible if deconvolution is used, can be utilised in the adaptive subtraction process. We demonstrate, through real-data examples, that our workflow provides an optimal multiple attenuation solution in shallow water environment in comparison with conventional methods such as ?-p deconvolution or SRME alone. 
ER  -

