Julian Chenin


Geophysical Data Scientist

Julian Chenin is passionate leader and geoscientist who is now quantitatively optimizing machine learning algorithms for various geoscience applications at Bluware. He recently completed his MSc in Geophysics at the University of Oklahoma where his thesis work used unsupervised machine learning techniques to better image gas in the subsurface. Julian serves on the AAPG Sustainable Development Committee, the GEO2021 Young Professionals Committee (YPC), and as the incoming alternate USA member of the World Petroleum Council’s YPC for the 2021 – 2023 cycle.

Sessions With Julian Chenin

Wednesday, 9 March

  • 02:00pm - 02:30pm (CST) / 09/mar/2022 08:00 pm - 09/mar/2022 08:30 pm

    Bluware | Interactive Deep Learning for Enhanced Petroleum System Characterization on Microsoft AzureTM

    Presentation Digitalization/AI/Machine Learning/Robotics/Cybersecurity Start-ups

    Detailed geomodelling within high-resolution, 3D and 2D seismic data is a time-consuming and arduous process. Supported by cloud compute capabilities, recent advances in deep learning practices are accelerating the speed at which geologic features can be mapped. Bluware will showcase an interactive deep learning methodology using advanced data streaming capabilities running natively on Azure. Geoscientists can now use these solutions with established play analysis procedures to generate accurate models in a fraction of the time it takes using traditional interpretation methods. This tool is flexible for E&P, windfarm installations, carbon sequestration, and geothermal opportunities. We will also highlight the value that The Open Group OSDUTM Data Platform is providing through multi-vendor integrations on Azure.