SPE Online Education
QRI Expert Hour -- Using Advanced Analytics, Computational Algorithms, and AI to Automate Geological Target Identification (and Other Geological Workflows)
Includes a Live Event on 04/24/2019 at 10:00 AM (EDT)
The rise of advanced analytics in oil & gas has resulted in great efficiency gains especially in the area of automated field/reservoir diagnostics. However, the solution space is still labor-intensive, mired in subjective geologic interpretations and hindered by the lack of interdisciplinary data integration. In this webinar, a QRI expert presents a robust framework that fully streamlines opportunity identification, as well as a platform that automates geologic/engineering workflows. The technology uses a series of computational and data-driven algorithms to solve the various sub-problems encountered in the process of identifying field development opportunities.
Computational Geoscientist and Lead, Application Development at QRI
With a bachelor's in computer science and a master's in geology, Wassim Benhallam uses his interdisciplinary skills to develop fast, automated, and data-driven solutions that incorporate geological and engineering data to prescribe how to maximize oil production. Since joining QRI, he has had the opportunity to deploy these technologies to identify workovers/recompletion opportunities and new drill locations in various oil fields in the Middle East, California, and Mexico. Mr. Benhallam also uses his quantitative background to develop cloud-based virtual assistant applications leveraging the latest machine learning (NLU) models and web technology to assist engineers and geoscientists in querying subsurface data, investigating reservoir problems, and extracting insights. During his graduate studies, he conducted multi-scale point pattern analysis of channel-belt sand bodies from the Straight Cliffs Formation in Utah and developed photorealistic outcrop models using DEM reconstruction from large LiDAR point clouds that can be used as quantitative inputs into reservoir models.
Content for this webinar is provided by QRI. By registering, your contact information will be shared with the sponsor.