Estimating Facies Fields by Use of the Ensemble Kalman Filter and Distance Functions--Applied to Shallow-Marine Environments (Record no. 187601)

MARC details
000 -LEADER
fixed length control field 03028nab a2200217 4500
008 - CÓDIGOS DE INFORMACIÓN DE LONGITUD FIJA - INFORMACIÓN GENERAL
Campo de control de longitud fija 260224s2013 xxu ing
041 ## - IDIOMA
Idioma Inglés
245 00 - TITULO
Título Estimating Facies Fields by Use of the Ensemble Kalman Filter and Distance Functions--Applied to Shallow-Marine Environments
260 ## - PUBLICACION, DISTRIBUCION, ETC
Lugar de publicación, distribución, etc.
Nombre de publicador, distribuidor, etc.
Fecha de publicación, distribución, etc. feb. 2013
270 ## - FECHA DE CARGA
Fecha de carga 16/04/2013 ; 16/04/2013
300 ## - DESCRIPCION FISICA
Otra extensión 12 p. ; 146-158
520 ## - RESUMEN, ETC
Resumen Transcripción del resumen del autor: The ensemble Kalman filter (EnKF) is one of the most promising tools for assisted history matching of reservoir models, but challenges remain for applications on complex geological structures (facies fields). In this paper, we propose a method that uses distance functions to estimate such fields. The definition of a distance function is "the shortest distance between a given position in the field and the boundary separating facies types." The idea behind this approach is that distances have smooth properties, and the distribution of the ensemble in a given gridblock is without multimodality and in better agreement with the EnKF Gaussianity assumptions. The distances are then updated by use of the EnKF and converted to petrophysical parameters when the reservoir simulator is run to the next assimilation time. The approach is flexible and simple and possesses several advantages compared with other existing methods: The input items for the method are facies realizations that can be generated with any preferred geostatistical tool; we ensure that the updated fields always are facies realizations; we ensure the conditioning of the correct facies types at the well location, both initially and during the assimilation steps; and the method does not involve complex modifications of the standard EnKF equations. The approach presented here is based on an extension of previous work performed by the authors. The novelty of the extension is summarized by the following: Any number of specified facies types can be estimated; one distance function is used for each facies type--at each gridblock, the facies type that corresponds to the distance function with maximal value is selected; there are no restrictions on the structure of the facies field to be estimated; and the methodology is extended to update variations in the petrophysical parameters within each facies type. The first of these extensions is considered the most important because the flexibility regarding the number of facies types is necessary for every real industrial application. We demonstrate the methodology on a field with shallow-marine-environment characteristics. The conclusions from the example are that the history match is improved, uncertainty is reduced, and the method always returns facies realizations with geological authenticity.
581 ## - ESTADO DE COLECCIÓN
Estado de colección 1
773 0# - CORRECCIÓN
Título SPE Journal
Partes relacionadas 18
942 ## - DESC. DE MATERIAL
Tipo de item KOHA Artículo de Revista
100 1# - RESPONSABLE PERSONAL
Apellido, Nombre Lorentzen, Rolf J.
9 (RLIN) 19735
100 1# - RESPONSABLE PERSONAL
Apellido, Nombre Naevdal, Geir
9 (RLIN) 52467
100 1# - RESPONSABLE PERSONAL
Apellido, Nombre Shafieirad, Ali
9 (RLIN) 52468
Holdings
Biblioteca propietaria Biblioteca actual Fecha de adquisición Inventario Total de préstamos Inventario Fecha de carga Tipo de item KOHA
Biblioteca Alejandro Angel Bulgheroni Biblioteca Alejandro Angel Bulgheroni 06/03/2026 200059734   200059734 06/03/2026 Artículo de Revista


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