SPE London YP section is excited to invite you to a virtual technical talk on ‘Deep learning based workflows for an automated evergreen subsurface model building’.
In recent years, we have seen great achievements accomplished by artificial intelligence (AI) and machine learning(ML), in various areas. Driven by the advances in the GPU technology, cloud computing, and the rapidly increasing data volumes within the geoscience applications, the energy industry has recognised and embraced the tremendous potential of AI/ML. Early research and development utilising these algorithms for geoscience applications have shown encouraging and promising results.
In this webinar, we will discuss a variety of highly successful geoscience applications that leverage AI/ML algorithms to improve efficiency, accuracy, and to automate workflows, and to explore a new way of extracting values from geoscience data. Specifically, we will focus on the automated evergreen subsurface model building workflow utilising seismic, wellbore and other geophysical data for deriving 3D subsurface models. A case study result will be discussed.
Dr Aria Abubakar is currently the Head of Data Science & Scientific Advisor for Digital Subsurface Solutions at Schlumberger based in Houston, Texas, USA. He received an MSc in electrical engineering and a PhD in computational sciences, from Delft University of Technology in Delft, The Netherlands. He was the 2020 SEG-AAPG Distinguish Lecturer and the 2014 SEG North America Honorary Lecturer. He holds over 50 patents/patent applications, and has published five book and book chapters, over 100 peer-reviewed scientific articles, over 250 peer-reviewed conference papers, and over 50 conference abstracts.