The use of capacitance-resistance models for rapid estimation of waterflood performance and optimization (Record no. 171141)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 02251nab a2200205 4500 |
| 008 - CÓDIGOS DE INFORMACIÓN DE LONGITUD FIJA - INFORMACIÓN GENERAL | |
| Campo de control de longitud fija | 260224s2009 xxu |
| 245 00 - TITULO | |
| Título | The use of capacitance-resistance models for rapid estimation of waterflood performance and optimization |
| 260 ## - PUBLICACION, DISTRIBUCION, ETC | |
| Lugar de publicación, distribución, etc. | |
| Nombre de publicador, distribuidor, etc. | |
| Fecha de publicación, distribución, etc. | dic. 2009 |
| 270 ## - FECHA DE CARGA | |
| Fecha de carga | 17/06/2010 ; 16/06/2010 |
| 300 ## - DESCRIPCION FISICA | |
| Otra extensión | 12 p. ; 227-238 |
| 520 ## - RESUMEN, ETC | |
| Resumen | Transcripción del resumen del autor. The capacitance–resistance model (CRM) offers the promise of rapid evaluation of waterflood performance. This semianalytical modeling approach is a generalized nonlinear multivariate regression technique that is rooted in signal processing. Put simply, a rate variation at an injector introduces a signal, with the corresponding response felt at one or more producers. CRM uses production and injection rate data and bottomhole pressure, if available, to calibrate the model against a specific reservoir. Thereafter, the model is used for predictions. We focused on three different control volumes for CRMs: the volume of the entire field, the drainage volume of each producer, and a drainage volume between each injector/producer pair. Unlike the numerical simulation approach, the CRMs use only production/injection data to predict performance, which provides simplicity and speed of calculation. Once the CRM is calibrated with historical production/injection data, we use an optimization technique to maximize the amount of oil produced by reallocating water injection rates. To verify CRM predictions, the models were tested against numerical flow-simulation results. Two case studies showed that the CRMs are able to successfully history match, and maximize the amount of oil produced by just reallocating water injection. This study introduces analytical solutions to the fundamental differential equations of the capacitance model based on superposition in time. In so doing, this approach adds flexibility, simplicity, and computational speed to the work presented previously. |
| 581 ## - ESTADO DE COLECCIÓN | |
| Estado de colección | 3-4 |
| 773 0# - CORRECCIÓN | |
| Título | Journal of Petroleum Science & Engineering |
| Partes relacionadas | 69 |
| 942 ## - DESC. DE MATERIAL | |
| Tipo de item KOHA | Artículo de Revista |
| 100 1# - RESPONSABLE PERSONAL | |
| Apellido, Nombre | Sayarpour, M. |
| 9 (RLIN) | 42909 |
| 100 1# - RESPONSABLE PERSONAL | |
| Apellido, Nombre | Zuluaga, E. |
| 9 (RLIN) | 25060 |
| 100 1# - RESPONSABLE PERSONAL | |
| Apellido, Nombre | Kabir, C.S. |
| 9 (RLIN) | 15994 |
| 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 | 200045999 | 200045999 | 05/03/2026 | Artículo de Revista |
