Understanding Complex Subsurface Features from 3D-2D Mega Merge Seismic Data

Seismic surveys are critical for the investigation of subsurface geological formations, and the process of acquiring new surveys involves considerable planning, resources and huge costs. This study reuses legacy seismic surveys collected in the state of Kuwait, which includes thirteen vintages of 3D surveys, as well as three vintage 2D surveys from 1997, 1998, and 2005 where 3D data is not available. These surveys encompass both onshore and offshore areas and were conducted by various companies to provide geological insights of the subsurface. In a previous study, all the interpretation was done on individual surveys and when we merge interpretation and create maps of various properties then we always see the survey boundaries. In the case of 2D data the interpretation becomes very cumbersome, and interpretation of regional faults and acoustic properties cannot be determined efficiently. So, in this study we have created 3D data from 2D data combining geostatistical and machine Learning to get more accurate picture of the subsurface. Then in this study we merge the 3D data generated from 2D with the existing 3D surveys to create a Mega-Merge 3D dataset for the whole of Kuwait including both onshore and offshore.