%0 Journal Article
%T Optimal Parameter Updating in Assisted History Matching Using Streamlines as a Guide Mise ¨¤ jour optimale des param¨¨tres dans un processus de calage d¡¯historique en s¡¯aidant des lignes de courants
%A Kazemi A.
%A Stephen K.D.
%J Oil & Gas Science and Technology
%D 2013
%I Institut Fran?ais du P¨¦trole
%R 10.2516/ogst/2012071
%X It is becoming more and more common to use assisted history matching methods to find different combinations of reservoir simulation models that agree with production data. Models with a large number of cells contain millions of unknown parameters and selecting the correct property values can be difficult. In practice, not all are important but finding which parts of the reservoir require updating is a challenge. In this work, we investigate methods of history matching by focusing on sub-sets of the full array model parameters and we use streamlines to help us choose where the model requires change. We identify localities in the reservoir that affect particular wells and we update reservoir properties (net:gross and permeability) within. We control changes using the pilot point method combined with a Neighbourhood Algorithm. We apply these approaches to the Nelson field (North Sea, UK) where uncertainty of the shale distribution controls predictions. The field is divided into localities based on the performance of the worst well predictions. We history match to improve production rates. The localities that require change are sufficiently separate that we can modify them one at a time. We also compare our result with a more ad hoc approach where the whole area around the well is modified. We find that, for the wells of interest, the streamline guided approach gives a 70% improvement in the history match from our starting model and around 40% reduction of misfit in prediction. This improvement is twice that of modifying the properties all around the well. L¡¯utilisation de m¨¦thodes de calage d¡¯historique assist¨¦ est de plus en plus fr¨¦quente pour d¨¦terminer diff¨¦rentes combinaisons de mod¨¨les de r¨¦servoir reproduisant les donn¨¦es de production. Les mod¨¨les comprenant un grand nombre de cellules contiennent des millions de param¨¨tres inconnus, et leur attribuer des valeurs appropri¨¦es peut s¡¯av¨¦rer difficile. En pratique, tous les param¨¨tres n¡¯ont pas la m¨ºme importance, et identifier les zones du r¨¦servoir o¨´ les param¨¨tres doivent ¨ºtre mis ¨¤ jour est un d¨¦fi. Dans cette ¨¦tude, nous ¨¦tudions les m¨¦thodes de calage d¡¯historique en nous concentrant sur les sous-ensembles des param¨¨tres du mod¨¨le, et nous utilisons les lignes de courant pour choisir les zones du mod¨¨le qui doivent ¨ºtre modifi¨¦es. Nous identifions les r¨¦gions du r¨¦servoir affectant des puits particuliers et nous y ajustons les propri¨¦t¨¦s du r¨¦servoir (fraction de roche r¨¦servoir et perm¨¦abilit¨¦). Les changements sont r¨¦alis¨¦s ¨¤ partir de la m¨¦thode des points pilotes associ¨¦e ¨¤ un algorithme d¡¯o
%U http://dx.doi.org/10.2516/ogst/2012071