URTeC Activity

regnow

Top Leaderboard

page content

Data Analytics and Physics - Informed Models: The Next Generation Takes Shape

Monday, 20 July 2020, 3:25 p.m.–5:10 p.m.  |  Austin, Texas

short course image

Course Content

Speakers

3:25 Introductory Remarks
3:40 Hecto Klie, Chief Executive Officer and Lead Scientist, DeepCast
3:50 Cedric Fraces Gasmi, Director, Tenokonda Inc and Stanford University
4:00 Ruben Rodriguez Torrado, Founder and Chief Executive Officer, OriGen.ai
4:10 Rami M Younis, Associate Professor, McDougall School of Petroleum Engineering, Director, Future Reservoir Simulation Systems & Technology (FURSST) University of Tulsa
4:20 Moderated Panel
4:45 Audience Q&A


In recent years a substantial debate has developed between predictive machine learning models versus theoretically-correct physics models. Out of this debate has arisen a phenomena known as a physics-informed predictive model. A number of researchers in this field are claiming that this type of model seems to have adopted the best of both worlds. This panel will describe this kind of model, its benefits, typical pitfalls, and give examples of the latest case studies.

Domain experts are more important than ever as machine learning algorithms are being pushed to the limit, particularly for quantifying model uncertainty and risk assessment. Decisions can be made on the basis of a predictive model, but those decisions can be deeply flawed if data accuracy and physics representation aspects were not considered. We will discuss the key considerations in today’s decision-making environment, particularly in a situation where there is likely to be large-scale changes in ownership, and the new operators of fields will be under pressure to develop data-driven models that are both reliable and quickly modified. Tactics for data managing and feature engineering, as well as identifying key pitfalls in developing the algorithms, and deciding which algorithms to employ will be discussed.

Fee: Included with Registration


Speakers
icon

Hecto Klie
Chief Executive Officer and Lead Scientist, DeepCast

icon

Cedric Fraces Gasmi
Director, Tenokonda Inc and Stanford University

icon

Ruben Rodriguez Torrado
Founder and Chief Executive Officer, OriGen.ai

icon

Rami M Younis
Associate Professor, McDougall School of Petroleum Engineering, Director, Future Reservoir Simulation Systems & Technology (FURSST) University of Tulsa

Venue

Data Analytics and Physics - Informed Models: The Next Generation Takes Shape
Austin, TX
Austin, Texas
United States

Instructor

Alejandro Lerza
Alejandro Lerza Moderator Chevron, Argentina

leaderboard

three box footer