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IMSCCS
2007
IEEE

Ensemble Subsurface Modeling Using Grid Computing Technology

8 years 11 months ago
Ensemble Subsurface Modeling Using Grid Computing Technology
Ensemble Kalman Filter (EnKF) uses a randomized ensemble of subsurface models for error and uncertainty estimation. However, the complexity of geological models and the requirement of a large number of simulation runs make routine applications extremely difficult due to expensive computation cost. Grid computing technologies provide a cost-efficient way to combine geographically distributed computing resources to solve large-scale data and computation intensive problems. Hence, we design and implement a grid-enabled EnKF solution to ill-posed model inversion problems for subsurface modeling. It has been integrated into the ResGrid, a problem solving environment aimed at managing distributed computing resources and conducting subsurface-related modeling studies. Two synthetic cases in reservoir studies indicate that the enhanced ResGrid efficiently performs EnKF inversions to obtain accurate, uncertainty-ware predictions on reservoir production. This grid-enabled EnKF solution is also ...
Xin Li, Zhou Lei, Christopher D. White, Gabrielle
Added 03 Jun 2010
Updated 03 Jun 2010
Type Conference
Year 2007
Where IMSCCS
Authors Xin Li, Zhou Lei, Christopher D. White, Gabrielle Allen
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