Localization of Ensemble-Based Control-Setting Updates for Production Optimization (Record no. 187478)
[ view plain ]
| 000 -LEADER | |
|---|---|
| fixed length control field | 01940nab a2200205 4500 |
| 008 - CÓDIGOS DE INFORMACIÓN DE LONGITUD FIJA - INFORMACIÓN GENERAL | |
| Campo de control de longitud fija | 260224s2012 xxu ing |
| 041 ## - IDIOMA | |
| Idioma | Inglés |
| 245 00 - TITULO | |
| Título | Localization of Ensemble-Based Control-Setting Updates for Production Optimization |
| 260 ## - PUBLICACION, DISTRIBUCION, ETC | |
| Lugar de publicación, distribución, etc. | |
| Nombre de publicador, distribuidor, etc. | |
| Fecha de publicación, distribución, etc. | mar. 2012 |
| 270 ## - FECHA DE CARGA | |
| Fecha de carga | 05/12/2012 ; 05/12/2012 |
| 300 ## - DESCRIPCION FISICA | |
| Otra extensión | 14 p. ; 122-136 |
| 520 ## - RESUMEN, ETC | |
| Resumen | Transcripción del resumen del autor In the ensemble-based approach to production optimization (EnOpt), a steepest-ascent direction is computed from an ensemble of controls to iteratively improve a set of control settings. The method was shown to work well in maximizing field net present value (NPV) with an ensemble size of 104 on the Brugge SPE comparative test case for closed-loop optimization that had 84 controllable completion intervals (and 3,360 control variables), but performance of the method with smaller ensemble size or on larger problems might be difficult. Without regularization, the cross-covariance between control variables and the objective function is often likely to be dominated by spurious correlations. Because the update to the control variables is proportional to the covariance, spurious correlations will result in poor control settings. We propose a localization method that updates the control setting to optimize the field production while reconciling information from each individual well. The proposed localization method reduces the effect of spurious correlations for improved performance. The Brugge test case is used as an example to show that with covariance localization, greater efficiency could be achieved through the use of a smaller ensemble, or that for a given ensemble size, the optimization results can be improved. |
| 581 ## - ESTADO DE COLECCIÓN | |
| Estado de colección | 1 |
| 773 0# - CORRECCIÓN | |
| Título | SPE Journal |
| Partes relacionadas | 17 |
| 942 ## - DESC. DE MATERIAL | |
| Tipo de item KOHA | Artículo de Revista |
| 100 1# - RESPONSABLE PERSONAL | |
| Apellido, Nombre | Chen, Yan |
| 9 (RLIN) | 42191 |
| 100 1# - RESPONSABLE PERSONAL | |
| Apellido, Nombre | Oliver, Dean S. |
| 9 (RLIN) | 42192 |
| 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 | 200059595 | 200059595 | 06/03/2026 | Artículo de Revista |
