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Dynamic Datasets Using Forward Modeling to Reduce Uncertainty and Improve Recovery

Chip Corbett1, Nejma Djabelkhir1, Theresa Hartman1, Geoff Mills2, Jennie Graham2, Margaret Leathard3, Stephen McHugo3 and Horacio Trajtenberg4

1Schlumberger, 5599 San Felipe St., Ste. 100, Houston, Texas 77056
2WesternGeco, 3750 Briar Park Dr., Houston, Texas 77042
3Schlumberger House, Buckingham Gate, Gatwick, West Sussex RH6 0HZ, United Kingdom
4Schlumberger Italiana Spa, Torree Beta 5th Floor, Via dell'Unione Europea 4, 20097 San Donato Milano, Italy

September 21, 2015 Monday 2:25 P.M. GCAGS, Houston, Texas

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.

AAPG Datapages/Search and Discovery Article #90219 © 2015 GCAGS, Houston, Texas, September 20-22, 2015