An iterative ensemble Kalman filter for reservoir engineering applications
نویسندگان
چکیده
منابع مشابه
SPE 109808 An Iterative Ensemble Kalman Filter for Data Assimilation
The ensemble Kalman filter (EnKF) is a subject of intensive investigation for use as a reservoir management tool. For strongly nonlinear problems, however, EnKF can fail to achieve an acceptable data match at certain times in the assimilation process. Here, we provide iterative EnKF procedures to remedy this deficiency and explore the validity of these iterative methods compared to standard EnK...
متن کاملReal - Time Reservoir Model Updating Using Ensemble Kalman Filter
This paper was selected for presentation by an SPE Program Committee following review of information contained in a proposal submitted by the author(s). Contents of the paper, as presented, have not been reviewed by the Society of Petroleum Engineers and are subject to correction by the author(s). The material, as presented, does not necessarily reflect any position of the Society of Petroleum ...
متن کاملNear-Well Reservoir Monitoring Through Ensemble Kalman Filter
In the management of reservoirs it is an important issue to utilize the available data in order to make accurate forecasts. In this paper a novel approach for frequent updating of the near-well reservoir model as new measurements becomes available is presented. The main focus of this approach is to have an updated model usable for forecasting. These forecasts should have initial values that are...
متن کاملReservoir Multiscale Data Assimilation Using the Ensemble Kalman Filter
In this paper we propose a way to integrate data at different spatial scales using the ensemble Kalman filter (EnKF), such that the finest scale data is sequentially estimated, subject to the available data at the coarse scale (s), as an additional constraint. Relationship between various scales has been modeled via upscaling techniques. The proposed coarse-scale EnKF algorithm is recursive and...
متن کاملControlling balance in an ensemble Kalman filter
We present a method to control unbalanced fast dynamics in an ensemble Kalman filter by introducing a weak constraint on the imbalance in a spatially sparse observational network. We show that the balance constraint produces significantly more balanced analyses than ensemble Kalman filters without balance constraints and than filters implementing incremental analysis updates (IAU). Furthermore,...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Computational Geosciences
سال: 2008
ISSN: 1420-0597,1573-1499
DOI: 10.1007/s10596-008-9087-9