History Matching and Uncertainty Characterization Using Ensemble-based Methods

History Matching and Uncertainty Characterization
  • Engels
  • Paperback
  • 9783659107283
  • april 2012
  • 264 pagina's
Alle productspecificaties

Samenvatting

In the last decade, ensemble-based methods have been widely investigated and applied for data assimilation of flow problems associated with atmospheric physics and petroleum reservoir history matching. Among these methods, the ensemble Kalman filter (EnKF) is the most popular one for history-matching applications. The main advantages of EnKF are computational efficiency and easy implementation. Moreover, because EnKF generates multiple history-matched models, EnKF can provide a measure of the uncertainty in reservoir performance predictions. However, because of the inherent assumptions of linearity and Gaussianity and the use of limited ensemble sizes, EnKF does not always provide an acceptable history-match and does not provide an accurate characterization of uncertainty. In this work, we investigate the use of ensemble-based methods, with emphasis on the EnKF, and propose modifications that allow us to obtain a better history match and a more accurate characterization of the uncertainty in reservoir description and reservoir performance predictions.

Productspecificaties

Inhoud

Taal
Engels
Bindwijze
Paperback
Verschijningsdatum
2012-01-01
Aantal pagina's
264 pagina's
Illustraties
Nee

EAN

EAN
9783659107283

Overige kenmerken

Extra groot lettertype
Nee
Oorspronkelijke releasedatum
2012-04-27
Subtitel
Using Ensemble-based Methods
Thema Subject Code
RB

Je vindt dit artikel in

Categorieën
Taal
Engels
Studieboek of algemeen
Algemene boeken
Onderwerp
Aardwetenschappen
Boek, ebook of luisterboek?
Boek
Nog geen reviews
Bindwijze: Paperback
97 99
2 - 3 weken Tooltip
Verkoop door bol.com
  • Gratis verzending
  • 30 dagen bedenktijd en gratis retourneren
  • Ophalen bij een bol.com afhaalpunt mogelijk
  • Dag en nacht klantenservice