Quantifying and predicting naturally fractured reservoir behavior with continuous fracture models (Record no. 171185)

MARC details
000 -LEADER
fixed length control field 01890nab a2200205 4500
008 - CÓDIGOS DE INFORMACIÓN DE LONGITUD FIJA - INFORMACIÓN GENERAL
Campo de control de longitud fija 260224s2009 xxu
245 00 - TITULO
Título Quantifying and predicting naturally fractured reservoir behavior with continuous fracture models
260 ## - PUBLICACION, DISTRIBUCION, ETC
Lugar de publicación, distribución, etc.
Nombre de publicador, distribuidor, etc.
Fecha de publicación, distribución, etc. nov. 2009
270 ## - FECHA DE CARGA
Fecha de carga 17/06/2010 ; 17/06/2010
300 ## - DESCRIPCION FISICA
Otra extensión 12 p. ; 1597-1608
520 ## - RESUMEN, ETC
Resumen Transcripción del resumen del autor. This article describes the workflow used in continuous fracture modeling (CFM) and its successful application to several projects. Our CFM workflow consists of four basic steps: (1) interpreting key seismic horizons and generating prestack and poststack seismic attributes; (2) using these attributes along with log and core data to build seismically constrained geocellular models of lithology, porosity, water saturation, etc.; (3) combining the derived geocellular models with prestack and poststack seismic attributes and additional geomechanical models to derive high-resolution three-dimensional (3-D) fracture models; and (4) validating the 3-D fracture models in a dynamic reservoir simulator by testing their ability to match well performance. Our CFM workflow uses a neural network approach to integrate all of the available static and dynamic data. This results in a model that is better able to identify fractured areas and quantify their impact on well and reservoir flow behavior. This technique has been successfully applied in numerous sandstone and carbonate reservoirs to both understand reservoir behavior and determine where to drill additional wells. Three field case studies are used to illustrate the capabilities of the CFM approach.
581 ## - ESTADO DE COLECCIÓN
Estado de colección 11
773 0# - CORRECCIÓN
Título AAPG Bulletin
Partes relacionadas 93
942 ## - DESC. DE MATERIAL
Tipo de item KOHA Artículo de Revista
100 1# - RESPONSABLE PERSONAL
Apellido, Nombre Wingard, Jeff
9 (RLIN) 42971
100 1# - RESPONSABLE PERSONAL
Apellido, Nombre Zellou, Abdel
9 (RLIN) 42972
100 1# - RESPONSABLE PERSONAL
Apellido, Nombre Jenkins, Creties
9 (RLIN) 42973
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 05/03/2026 200046043   200046043 05/03/2026 Artículo de Revista


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