Towards Dynamic Data-Driven Optimization of Oil Well Placement

The adequate location of wells in oil and environmental applications has a significant economical impact on reservoir management. However, the determination of optimal well locations is both challenging and computationally expensive. The overall goal of this research is to use the emerging Grid infrastructure to realize an autonomic dynamic data-driven self-optimizing reservoir framework. In this paper, we present the use of distributed data to dynamically drive the optimization of well placement in an oil reservoir.

• Type: Conference
• Year: 2005
• Where: ICCS
• Authors: Manish Parashar, Vincent Matossian, Wolfgang Bangerth, Hector Klie, Benjamin Rutt, Tahsin M. Kurç, Ümit V. Çatalyürek, Joel H. Saltz, Mary F. Wheeler
• Keywords: Data-driven Self-optimizing Reservoir, ICCS 2005, Reservoir Management, Significant Economical Impact