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Webinars

Introduction to Uncertainty Quantification and Predictive Modeling for the Oil & Gas Industry

On Demand

Uncertainty and variability runs through the very core of engineering activities in the oil & gas industry. Whether it is making a billion-dollar decision from very limited field data, having to design ultra-reliable equipment that performs optimally in extreme conditions, or introducing more efficient processes, experts in the oil & gas field must understand the sources of these uncertainties, be able to compute them, and find ways to reduce them and make decisions in their presence.

This webinar is an introduction to Uncertainty Quantification and predictive modeling techniques for reservoir engineers, drilling engineers, equipment design teams, simulation engineers and data scientists in the oil & gas industry who want to find ways to reduce time, improve design robustness, or make better decisions from the data they have. The webinar includes a software demonstration for a case study that quantifies the uncertainty for a CFD example.

Key Learning Objectives:

  • Understand what Uncertainty Quantification is and why it is important
  • Learn how Uncertainty Quantification and predictive modeling methods can applied to challenges in the Oil and Gas industry
  • See first-hand the process of quantifying uncertainties for a CFD simulation
    • Presented by Dr. Mark Andrews, SmartUQ UQ Technology Steward
    He is responsible for advising SmartUQ on the industry’s uncertainty quantification needs and challenges. Dr. Andrews is SmartUQ’s principal investigator for the Probabilistic Secondary Flow and Heat Transfer Model project as part of the Probabilistic Analysis Consortium for Engines (PACE). Prior to working at SmartUQ, Dr. Andrews spent 15 years at Caterpillar where he worked as a Senior Research Engineer, Engineering Specialist in Corporate Reliability, and Senior Engineering Specialist in Virtual Product Development. He has a Ph.D. and M.S. in Mechanical Engineering from the New Mexico State University, as well as a BS in Mechanical Engineering from the University of New Mexico.

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