A framework to integrate history matching and geostatistical modeling using genetic algorithm and direct search methods (Record no. 169129)
[ view plain ]
| 000 -LEADER | |
|---|---|
| fixed length control field | 02154nab a2200217 4500 |
| 008 - CÓDIGOS DE INFORMACIÓN DE LONGITUD FIJA - INFORMACIÓN GENERAL | |
| Campo de control de longitud fija | 260224s2008 xxu |
| 245 00 - TITULO | |
| Título | A framework to integrate history matching and geostatistical modeling using genetic algorithm and direct search methods |
| 260 ## - PUBLICACION, DISTRIBUCION, ETC | |
| Lugar de publicación, distribución, etc. | |
| Nombre de publicador, distribuidor, etc. | |
| Fecha de publicación, distribución, etc. | Dic. 2008 |
| 270 ## - FECHA DE CARGA | |
| Fecha de carga | 24/02/2009 ; 24/02/2009 |
| 300 ## - DESCRIPCION FISICA | |
| Otra extensión | 8 p. ; 34-42 |
| 520 ## - RESUMEN, ETC | |
| Resumen | Transcripción del resúmen publicado por el autor: History matching is an inverse problem where the reservoir model is modified in order to reproduce field observed data. Traditional history matching processes are executed separately from the geological and geostatistical modeling stage due to the complexity of each area. Changes made directly on the reservoir properties generally yield inconsistent geological models. This work presents a framework to integrate geostatistical modeling and history matching process, where geostatistical images are treated as matching parameters. The traditional optimization methods normally applied in history matching generally use gradient information. The treatment of geostatistical images as matching parameters is difficult for these methods due to the strong non-linearities in the solution space. Therefore, another objective of this work is to investigate the application of two optimization methods: genetic algorithm and direct search method in the proposed framework. In order to accelerate the optimization process, two additional techniques are used: upscaling and distributed computing. Results are presented showing the viability of the genetic algorithm in the type of problem addressed in this work and also that direct search method can be used with some restriction. Finally, the benefits of distributed computing and the consistence of the upscaling process are shown. |
| 581 ## - ESTADO DE COLECCIÓN | |
| Estado de colección | 1-4 |
| 773 0# - CORRECCIÓN | |
| Título | Journal of Petroleum Science & Engineering |
| Partes relacionadas | 63 |
| 942 ## - DESC. DE MATERIAL | |
| Tipo de item KOHA | Artículo de Revista |
| 100 1# - RESPONSABLE PERSONAL | |
| Apellido, Nombre | Maschio, Célio |
| 9 (RLIN) | 24259 |
| 100 1# - RESPONSABLE PERSONAL | |
| Apellido, Nombre | Campane Vidal, Alexandre |
| 9 (RLIN) | 40398 |
| 100 1# - RESPONSABLE PERSONAL | |
| Apellido, Nombre | Schiozer, Denis José |
| 9 (RLIN) | 37526 |
| 650 #0 - MATERIA | |
| Término tópico | Simulación de reservorios |
| 9 (RLIN) | 1795 |
| 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 | 200043920 | 200043920 | 05/03/2026 | Artículo de Revista |
