Application of Grid-enabled technologies for solving optimization problems in data-driven reservoir studies

Authors:
Manish Parashar;Hector Klie;Umit Catalyurek;Tahsin Kurc;Wolfgang Bangerth;Vincent Matossian;Joel Saltz;Mary F. Wheeler
Affiliations:
TASSL, Department of Electrical and Computer Engineering, Rutgers, The State University of New Jersey, NJ, USA;CSM, ICES, The University of Texas at Austin, TX, USA;Department of Biomedical Informatics, The Ohio State University, OH, USA;Department of Biomedical Informatics, The Ohio State University, OH, USA;CSM, ICES, The University of Texas at Austin, TX, USA and Institute for Geophysics, The University of Texas at Austin, TX, USA;TASSL, Department of Electrical and Computer Engineering, Rutgers, The State University of New Jersey, NJ, USA;Department of Biomedical Informatics, The Ohio State University, OH, USA;CSM, ICES, The University of Texas at Austin, TX, USA
Venue:
Future Generation Computer Systems
Year:
2005

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Abstract

This paper presents the use of numerical simulations coupled with optimization techniques in oil reservoir modeling and production optimization. We describe three main components of an autonomic oil production management framework. The framework implements a dynamic, data-driven approach and enables Grid-based large scale optimization formulations in reservoir modeling.