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Reduced Order / Physics (lumped parameter) Models for Coupling Processes at Various Time/Length Scales, Preserving the Key Nonlinear Features of Physical Systems

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Course Credit: 0.15 CEU, 1.5 PDH

Reduced-physics models are a computationally efficient bridge between full physics-based models (i.e., reservoir models) and completely data-driven models (i.e., machine learning-based proxies). They can play a useful role in supporting rapid decision making in field-scale enhanced oil recovery projects (e.g., water flooding), as well as feasibility evaluation of energy transition related subsurface operations (e.g., geological CO2 sequestration).

In this webinar, Ram Ratnakar begins with a short summary of how reduced-physics models are used in other porous media applications. Next, webinar speaker, Larry Lake from the University of Texas, presents an overview of Capacitance Resistance Modeling (CRM) and discusses its application for optimization of waterflooding projects. Finally, Srikanta Mishra (Battelle) discusses the derivation and application of reduced-physics models for pressure buildup and plume migration during CO2 sequestration by combining full-physics simulations with first principles.

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 1 chapter
  1 downloadable resource

Course Chapters

  • 1Reduced Order / Physics (lumped parameter) Models for Coupling Processes at Various Time/Length Scales, Preserving the Key Nonlinear Features of Physical Systems - Chapter 1
    Media Type: Video

Credits

Earn credits by completing this course0.15 CEU credit1.5 PDH credits

Speakers

Larry Lake
Ram Ratnakar
Srikanta Mishra