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Dynamic Datasets Using Forward Modeling to Reduce Uncertainty and Improve Recovery

Abstract

Geoscience instructors create training material from a variety of sources. Interpretation projects are frequently derived from real field data and pressed into service for a variety of classes.

Unfortunately, real field data may not align with the specific teaching objectives for students at a particular level; it may be too complex, too large, or lack critical data elements. It is very rare that a single dataset would contain all of the elements for training classes that span a full spectrum of subsurface disciplines.