Distributed parameter and state estimation in petroleum reservoirs

被引:8
|
作者
Oliver, Dean S. [1 ]
Zhang, Yanfen [3 ]
Phale, Hemant A. [2 ]
Chen, Yan [3 ]
机构
[1] Uni Ctr Integrated Petr Res, N-5007 Bergen, Norway
[2] Univ Oklahoma, Norman, OK 73019 USA
[3] Chevron Energy Technol Co, Houston, TX 77002 USA
关键词
History matching; Data assimilation; Constrained EnKF; Petroleum reservoir; Regularization of Kalman gain; ENSEMBLE KALMAN FILTER; DATA ASSIMILATION; SIMULATION;
D O I
10.1016/j.compfluid.2010.10.003
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
In this paper, we describe some of the key elements of the data assimilation problem for multiphase flow in petroleum reservoirs that make the problem distinctly different from data assimilation problems in weather or oceanography. Most importantly, the reservoir is often initially in a state of static equilibrium, the number of model parameters may be greater than the number of state variables, and the evolution of some of the state variables proceed monotonically from the initial state (low water saturation) to a final state (high water saturation). As a result of the differences, data assimilation is sometimes applied with a focus on estimation of model parameters. (C) 2010 Elsevier Ltd. All rights reserved.
引用
收藏
页码:70 / 77
页数:8
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