Propagating Interval Uncertainties In Supervised Pattern Recognition For Reservoir Characterization
Philippe Nivlet and Frédérique Fournier and Jean-Jacques Royer. ( 2001 )
in: Journal of Petroleum Technology, 54:6 (1-4)
Abstract
Characterizing reservoir quality, identifying the main rock types, and predicting their spatial variations are a challenge. Supervised pattern-recognition methods are used as discriminant analysis of these parameters. However, the uncertainties of the measurement arrays are not considered, which may cause misinterpretations. A methodology was developed that is an extension of the standard parametric approach to discriminant analysis. The resulting reservoir-quality model is less precise but more realistic by taking into account all data and associated uncertainties.
Download / Links
- HAL
- DOI: 10.2523/71327-MS
BibTeX Reference
@article{nivlet:hal-04055731,
abstract = {Characterizing reservoir quality, identifying the main rock types, and predicting their spatial variations are a challenge. Supervised pattern-recognition methods are used as discriminant analysis of these parameters. However, the uncertainties of the measurement arrays are not considered, which may cause misinterpretations. A methodology was developed that is an extension of the standard parametric approach to discriminant analysis. The resulting reservoir-quality model is less precise but more realistic by taking into account all data and associated uncertainties.},
author = {Nivlet, Philippe and Fournier, Fr{\'e}d{\'e}rique and Royer, Jean-Jacques},
doi = {10.2523/71327-MS},
hal_id = {hal-04055731},
hal_version = {v1},
journal = {{Journal of Petroleum Technology}},
number = {6},
pages = {1-4},
publisher = {{Society of Petroleum Engineers of Aime}},
title = {{Propagating Interval Uncertainties In Supervised Pattern Recognition For Reservoir Characterization}},
url = {https://hal.univ-lorraine.fr/hal-04055731},
volume = {54},
year = {2001}
}
