Steven Zobell in his article published by Forbes magazine in March of 2018 estimates that in 2018 enterprises will invest $1.3 trillion USD in Digital Transformation projects to “improve efficiencies, increase customer value and create new monetization opportunities”. In the same research, Steven analyses the reasons why 70% of these initiatives will not reach the objectives. AVGeo specialists were involved in digital workflow improvement projects in 2018 and would like to share our experiences and see if the predictions of Steve Zobell were correct.
In this presentation, I've discussed human cognitive learning while working with different sets of Big Data in Petroleum Exploration workflows. An effective reduction in the volumes of Big Data without information loss, AI in seismic interpretation and spatial analytics, and a visual aggregation of the single-threaded evaluations into a comprehensive multithreaded business decision are required for delivery of successful exploration programs
There is a renewed interest in exploration for oil and gas in deep and shallow waters of South Atlantic. The hopes are high especially with recent exploration success offshore Guyana and Mauritania. Delineation of the basins and mapping the extents of the pursued plays are two out of several critical components of the comprehensive geologic analysis and are fundamental to exploration success. During the last decade, deepwater drilling in South Atlantic proved multiple assumptions of the earlier geologic models of continent-ocean transition inadequate.
The purpose of this study is to provide a pore pressure prediction from seismic data targeting unconventional gas plays (i.e., the Qusaiba Member hot shale and the underlying Sarah Formation). The area of interest (AOI) located in NW Saudi Arabia, and is covered by 1,600 km2 of 3D pre-stack time migrated (PSTM) data. The resulting pore pressure maps for the Qusaiba Member hot shale and Sarah Formation highlight potential drilling hazards. Importantly, areas of higher pore pressure may ultimately represent potential areas of higher gas production (i.e., sweet spots).