Machine Learning (ML) is a field of Artificial Intelligence that has experienced rapid growth in the last ten years across diverse industries, including communications, financial services, security, transportation, and others. Applications of ML have produced dramatic results, enabling new opportunities and business models. Driving the adoption of ML are the volume and velocity of information, the application of deep learning techniques, and economic computing power. Applied to geoscience, these data-driven approaches are complementary tools for physical-based modeling, simulation, and inversion. ML facilitates an understanding of complex relationships among a large and diverse set of variables, valuable for generating and validating models and answering scientific questions. ML can enable fast high-quality decisions in the Oil & Gas industry, an essential component for viability given the industry’s long-term outlook. Geoscience datasets are among the largest volumes of data in the industry. The data has a wide spectrum of properties with scales varying over many orders of magnitude
This workshop will discuss the challenges, opportunities, and trends related to the adoption of Machine Learning in geoscience research and industrial workflows. Professionals from academia, Oil & Gas, and technology companies will present applications and case studies, promote discussion, and propose practical solutions to take greater advantage of Machine Learning methods.