Ocean bottom nodes (OBN) data are successfully being used in the deep water environment to acquire time-lapse surveys due to their low 4D noise level. In order to better recognize the benefits of using such data, we built an acoustic model based on a deep water subsalt field from the Gulf of Mexico. Synthetic base and monitor data were generated using a realistic acquisition geometry and laterally variable, random water velocity layer. Our OBN time-lapse processing study investigates solutions to understand and mitigate the sources of 4D noise introduced during the modeling phase. We applied a similar processing workflow to the up- and down-going wavefields, and observed an uplift in the 3D subsalt images generated using the up-going data. This particular synthetic example shows similar 4D noise values in the extra salt area on both up-and down-going images, but improved values subsalt on images generated using up-going compared to the down-going wavefields.
Presentation Date: Wednesday, October 19, 2016
Start Time: 3:35:00 PM
Location: 146
Presentation Type: ORAL
