DocumentCode :
2267318
Title :
Ensemble Subsurface Modeling Using Grid Computing Technology
Author :
Xin Li ; Zhou Lei ; White, C.D. ; Allen, G. ; Guan Qin ; Tsai, F.T.-C.
Author_Institution :
Louisiana State Univ., Baton Rouge
fYear :
2007
fDate :
13-15 Aug. 2007
Firstpage :
235
Lastpage :
244
Abstract :
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 being applied for data assimilation of large-scale groundwater hydrology nonlinear models. The ResGrid with EnKF solution is open-source and available for downloading.
Keywords :
Kalman filters; grid computing; modelling; ResGrid; distributed computing; ensemble Kalman filter; ensemble subsurface modeling; grid computing; model inversion; Computational efficiency; Computational modeling; Distributed computing; Estimation error; Geology; Grid computing; Large-scale systems; Problem-solving; Reservoirs; Uncertainty;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer and Computational Sciences, 2007. IMSCCS 2007. Second International Multi-Symposiums on
Conference_Location :
Iowa City, IA
Print_ISBN :
978-0-7695-3039-0
Type :
conf
DOI :
10.1109/IMSCCS.2007.98
Filename :
4392607
Link To Document :
بازگشت